A Water-Energy Assessment at Basin Scale | Charlotte Newiadomsky

UNIVERSITY OF APPLIED SCIENCES COLOGNE INSTITUTE FOR TECHNOLOGY AND RESOURCE MANAGEMENT IN THE TROPICS AND SUBTROPICS

A WATER-ENERGY ASSESSMENT AT BASIN SCALE

Master Thesis handed in by Dipl.-Ing. (FH) Charlotte Newiadomsky September 2011

UNIVERSITY OF APPLIED SCIENCES COLOGNE INSTITUTE FOR TECHNOLOGY AND RESOURCE MANAGEMENT IN THE TROPICS AND SUBTROPICS

Master Thesis handed in by

Dipl.-Ing. (FH) Charlotte Newiadomsky Matr.-No.: 11072572

TOPIC: A WATER-ENERGY ASSESSMENT AT BASIN SCALE

Supervisor:

Prof. Dr. Lars Ribbe (FH Köln – ITT)

Co-Supervisor:

Dr. Helmut Lehn (KIT – ITAS)

Date of submission:

15.09.2011

PROJECT HAS BEEN REALIZED IN: THE CONTEXT OF CLIMATE ADAPTATION STRATEGY FOR THE METROPOLITAN REGION OF SANTIAGO DE CHILE AND A REGIONAL LEARNING NETWORK IN MEGA-CITIES OF LATIN AMERICA

ITT IN COOPERATION WITH HELMHOLTZ ASSOCIATION AND LATIN AMERICAN PARTNERS METROPOLITAN REGION OF SANTIAGO DE CHILE

WITH THE HELP OF: CENTER FOR NATURAL RESOURCES AND DEVELOPMENT (CNRD)

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Declaration Name: Charlotte Newiadomsky Matri.-Nr.: 11072572

I declare hereby on oath that this Master Thesis in hand has been made independently and without the help of any other than acknowledged. The thoughts taken directly or indirectly from external sources are made recognizable as such.

This thesis was not presented to any other examination authority either in the same or similar form.

Cologne, ________________ Signature: ______________

I do further agree to a later publication of this Master Thesis, may it be in parts or entirely within the ITT publications or within the scope of the ITT’s public relations.

Signature: __________________

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Acknowledgement The research which led to the present master thesis was accomplished under the umbrella of the Institute for Technology and Resources management in the Tropics and Subtropics (ITT) at the Cologne University of Applied Sciences, Germany and the Karlsruhe Institute for Technology (KIT), respectively the Institute for Technology Assessment and Systems Analysis (ITAS), Germany. In particular, I would like to thank Prof. Dr. Lars Ribbe and Dr. Helmut Lehn for their support and help during the time of the master thesis and appreciate their critical and helpful recommendations. Many thanks also to James McPhee, Ximena Vargas and Marcelo Olivares of the University of Chile and Joachim Vogdt from Ingeniería Alemana S.A. for their help on Chilean side during my stay in Santiago. Furthermore I would like to thank also the General Water Directorate of Chile (DGA) which supported me with most of the data I needed for my thesis work, specifically Andrea Osses Vargas, Reinaldo Fuentealba, José Luis Larroucau and Eduardo Santibañez. Additional material has been provided by the Nacional Energy Comission of Chile (CNE), the Nacional Irrigation Commission (CNR), the Superintendence of Health Services (SISS), the Society of the Maipo Channels as well as Chilectra and the Municipal Department of Water and Sewerage (SMAPA). Without the financial support of the CNRD-Scholarship it wouldn’t be possible for me to do my field research in Chile for 4 months, in order to gather the needed data for this thesis. Finally, I would like to thank all the people, who reviewed this thesis and my whole family in supporting me during my studies and the phase of my master thesis.

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Table of Content List of Figures ........................................................................................................................ vi List of Tables ........................................................................................................................viii Acronyms and Abbreviations ................................................................................................ix Symbols.................................................................................................................................. x Abstract .................................................................................................................................xi Zusammenfassung ................................................................................................................xii Resumen .............................................................................................................................. xiii 1. Introduction ..................................................................................................................... 1 2. Background ...................................................................................................................... 3 2.1. Introduction ............................................................................................................ 3 2.2. Definitions of Energy .............................................................................................. 3 2.3. Energy Potential ..................................................................................................... 4 2.4. Significance of the Water-Energy Nexus ................................................................ 5 2.4.1. Water Demand of the Energy Sector ......................................................... 6 2.4.2. Energy Demand of the Water Sector ......................................................... 7 2.4.3. Energy Potential on Water Basis ................................................................ 8 2.4.4. Water Potential on Energy Basis ................................................................ 9 3. Research Study Region Chile ......................................................................................... 11 3.1. Water sector ......................................................................................................... 12 3.2. Energy Sector ........................................................................................................ 14 3.3. Review of Water-Energy Nexus Applications ....................................................... 17 3.3.1. Introduction .............................................................................................. 17 3.3.2. State of the Art ......................................................................................... 17 3.3.3. Deficiencies ............................................................................................... 18 4. Research Problem.......................................................................................................... 19 5. Objective ........................................................................................................................ 21 6. Methodology ................................................................................................................. 22 6.1. Required Data ....................................................................................................... 23

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6.2. Literature Research .............................................................................................. 25 6.3. Research Conditions ............................................................................................. 25 6.4. Justification of the research area ......................................................................... 26 7. General Introduction to Energy Potential Modelling .................................................... 27 7.1. Energy Potential Calculations ............................................................................... 27 7.2. Modelling Energy Potential .................................................................................. 28 8. Modelling Energy Potential – Model Set up and Inputs ............................................... 29 8.1. Determine the Hydrological Network .................................................................. 29 8.1.1. Network and Catchment Model ............................................................... 30 8.1.2. List of Data Inputs ..................................................................................... 30 8.1.3. Water and Energy Users ........................................................................... 31 8.1.4. Channel System ........................................................................................ 33 9. Maipo Watershed Analysis ............................................................................................ 36 9.1. Introduction to the Study Area............................................................................. 36 9.2. Watershed Description ......................................................................................... 36 9.2.1. Location and General Description ............................................................ 36 9.2.2. Water Uses ............................................................................................... 41 9.3. Reported Water Data ........................................................................................... 44 9.3.1. Energy Uses .............................................................................................. 50 9.4. Reported Energy Data .......................................................................................... 50 9.5. Water-Energy Balance .......................................................................................... 53 9.5.1. Water Demand of the Energy Sector ....................................................... 53 9.5.2. Energy Demand of the Water Sector ....................................................... 54 9.5.3. Energy Potential on Water Basis .............................................................. 56 9.5.4. Water Potential on Energy Basis .............................................................. 57 9.6. Conclusions ........................................................................................................... 57 10. Central Valley Analysis................................................................................................... 59 10.1. Energy potential of irrigation channels ................................................................ 61 10.2. Technical Possibilities for hydropower energy generation .................................. 66 10.3. Interpretation of Results ...................................................................................... 69 11. Discussion and Recommendations ................................................................................ 70 11.1. Water-Energy Balance .......................................................................................... 70

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11.2. Technical Possibilities for hydropower energy generation .................................. 71 11.3. Possibility of integration of “Energy Users” in Mike Basin................................... 72 12. References ........................................................................................................................ I 13. Annex ............................................................................................................................. VII Annex 1: List of Institutions and Contact Persons in Chile ............................................ VII Annex 2: Energy Laws Chile .......................................................................................... VIII Annex 3: Water Rights Chile ............................................................................................ X

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List of Figures

List of Figures Fig. 1: Water-Energy Nexus ................................................................................................... 5 Fig. 2: Map of Chile .............................................................................................................. 11 Fig. 3: Supply of Primary Energy 2007 ................................................................................. 14 Fig. 4: Development of net hydroelectric power generation in Chile from 1980 - 2006 .... 15 Fig. 5: Overview of distribution of installed capacities in Chile in 2008 ............................. 16 Fig. 6: Overview of methodological approach..................................................................... 22 Fig. 7: River Network as Basis for the Mike Basin model derived from Digital Elevation Model................................................................................................................................... 29 Fig. 8: Basic Set Up of the Mike Basin Model for the Maipo Watershed ............................ 30 Fig. 9: Location of the Maipo Watershed ............................................................................ 37 Fig. 10: Location of the 56 municipalities in nine provinces located in the Maipo Watershed ........................................................................................................................... 37 Fig. 11: Number of inhabitant of the biggest cities in the Maipo Watershed .................... 38 Fig. 12: Climate Diagram Santiago de Chile, Quinta Normal Station .................................. 40 Fig. 13: Percentage of irrigation technique according to the irrigation area...................... 44 Fig. 14: Average Monthly Precipitation (blue) and Flow Rate (black) 2006 - 2010 recorded at Rio Mapocho Rinconada de Maipu ................................................................................. 44 Fig. 15: Average Monthly Precipitation (blue) and Flow Rate (black) 2006 - 2010 recorded at Rio Angostura en Valdivia de Paine................................................................................. 45 Fig. 16: Flow Rate 2006 - 2010 recorded at Estero Alhue en Quilamuta ............................ 45 Fig. 17: Flow Rate 2006 - 2010 recorded at Rio Maipo en el Manzano .............................. 45 Fig. 18: Flow Rate 2006 - 2010 recorded at Rio Mapocho en los Almendros ..................... 46 Fig. 19: Precipitation 2006 - 2010 recorded at Barrera Loncha .......................................... 46 Fig. 20: Precipitation 2006 - 2010 recorded at Carmen de las Rosas.................................. 46 Fig. 21: Precipitation 2006 - 2010 recorded at El Vergel ..................................................... 47 Fig. 22: Precipitation 2006 - 2010 recorded at Fundo Marruecos ...................................... 47 Fig. 23: Precipitation 2006 - 2010 recorded at Ibacache Alto ............................................. 47 Fig. 24: Precipitation 2006 - 2010 recorded at Laguna Aculeo ........................................... 48 Fig. 25: Precipitation 2006 - 2010 recorded at Los Guindos ............................................... 48 Fig. 26: Precipitation 2006 - 2010 recorded at Los Panguiles ............................................. 48 Fig. 27: Precipitation 2006 - 2010 recorded at Mallarauco................................................. 49 Fig. 28: Precipitation 2006 - 2010 recorded at Melipilla ..................................................... 49 Fig. 29: Precipitation 2006 - 2010 recorded at Villa Alhue.................................................. 49 Fig. 30: Distribution of Electricity Demand in 2007............................................................. 50 Fig. 31: Evolution of Electricity Generation with Hydropower Plants from 1996 - 2011.... 53 Fig. 32: Monthly energy consumption of wastewater treatment plants in 2010 ............... 54 Fig. 33: Overview of Channels in the Maipo Watershed ..................................................... 59 Fig. 34: Investigation area Central Valley ............................................................................ 60 Fig. 35: Height Profile Channel D Caperana (31.32 MW) .................................................... 64 Fig. 36: Height Profile Channel El Paico (93.19 MW) .......................................................... 64 Fig. 37: Height Profile Channel Lonquen Isla (14.44 MW) .................................................. 64 Fig. 38: Height Profile Channel San Antonio de Naltahua (40.83 MW) .............................. 65 Fig. 39: Height Profile Channel San Jose Alto (18.45 MW).................................................. 65 Fig. 40: Height Profile Channel San Miguel (18.12 MW) ..................................................... 65

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List of Figures Fig. 41: Application of the different turbines according to height and water flow ............ 67 Fig. 42: Application areas of the different turbines according to the net head and water flow (x-axis: water flow, y-axis: net head)........................................................................... 67 Fig. 43: Distribution of channel characteristics according to Fig. 42 .................................. 68 Fig. 44: Distribution of channel characteristics with maximum slopes according to Fig. 42 ............................................................................................................................................. 68

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List of Tables

List of Tables Tab. 1: Overview of the different forms of energy ............................................................... 3 Tab. 2: Water Demand in Power Generation Technologies.................................................. 6 Tab. 3: Water Demand according to Fuel Sources ................................................................ 7 Tab. 4: Energy Demand in Water Production........................................................................ 7 Tab. 5: Energy Potential on Water Basis ............................................................................... 8 Tab. 6: Water Potential on Energy Basis ............................................................................... 9 Tab. 7: Distribution of the water service providers............................................................. 13 Tab. 8: Main required data for modelling and analysis....................................................... 24 Tab. 9: Data Inputs............................................................................................................... 31 Tab. 10: Water users described in the model ..................................................................... 31 Tab. 11: Electricity users and producers considered .......................................................... 32 Tab. 12: Channel Properties in the Central Valley............................................................... 33 Tab. 13: Mean Monthly Water Use of Wastewater Treatment Plants operating in the Maipo Basin ......................................................................................................................... 41 Tab. 14: Irrigation areas in the provinces of the Metropolitan Region 2006/2007 ............ 43 Tab. 15: Characteristics of Hydropower Plants operating in the Maipo Basin ................... 51 Tab. 16: Mean Monthly Energy Use of Wastewater Treatment Plants operating in the Maipo Basin ......................................................................................................................... 55 Tab. 17: Installed Capacity in MW of the principal hydroelectric power plants in the Metropolitan Region ........................................................................................................... 56 Tab. 18: Calculated Energy Potential of irrigation channels in the research area within the Central Valley....................................................................................................................... 62 Tab. 19: Advantages and disadvantages of hydropower turbines for small hydropower (< 100 kW) ........................................................................................................................... 66

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Acronyms and Abbreviations

Acronyms and Abbreviations BMU

CDEC-SIC

CNE CNR CONAMA DEM DGA DHI DOH ENSO ESSBIO ESVAL ET GIS GTZ IEA IFRI INE IPCC ITAS KIT LGSE Ltda. MB n/a OECD RM SCM SIC SING SISS SMAPA T TU Wien USAID

Federal Ministry of the Environment, Nature Conservation and Nuclear Safety (Bundesministerium für Umwelt, Naturschutz und Reaktorsicherheit, Germany) Center for Economic Load Dispatch of the Central Interconnected System (Centro de Despacho Económico de Carga del Sistema Interconectado Central) National Energy Commission (Comisión Nacional de Energía) National Irrigation Commission (Comisión Nacional de Riego) National Environmental Commission (Comisión Nacional del Medio Ambiente) Digital Elevation Model General Directorate of Water (Dirección General de Aguas) Danish Hydraulic Institute Directorate of Waterworks (Dirreción de Obras Hidráulicas) El Niño-Southern Oscillation Sanitary Company Bio-Bío (Empresa de Servicios Sanitarios del Bio-Bío) Health Company Valparaíso (Empresa Sanitaria de Valparaíso) Evapotranspiration Geographic Information System German Agency for Technical Cooperation (Deutsche Gesellschaft für Technische Zusammenarbeit) International Energy Agency International Food Policy Research Institute National Institute of Statistics, Chile (Instituto Nacional de Estadisticas) Intergovernmental Panel on Climate Change Institute for Technology Assessment and Systems Analysis Karlsruhe Institute of Technology General Law of Electricity Services (Ley General de Servicios Eléctricos) Limited (Limitada) Mike Basin not available Organisation for Economic Co-operation and Development Metropolitan Region (Región Metropolitana) Society of the Maipo River Channels (Sociedad Canal de Maipo) Central Interconnected System (Sistema Interconectado Central) Northern Interconnected System (Sistema Interconectado del Norte Grande) Superintendence of Health Services (Superintendencia de Servicios Sanitarios) Municipal Department of Water and Sewerage (Servicio Municipal de Agua Potable y Alcantarillado) Temperature Technical University of Vienna (Technische Universität Wien) United States Agency for International Development

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Symbols

Symbols Δh E e0 g h ha J kW m m3 MW P Q r ρ s W yr

Height difference Energy Efficiency coefficient of the power plant ranging from 0 to 1 Gravitational force 9.81 m/s2 Height Hectare Joule Kilo Watt Meter Cubic meter Mega Watt Power Volume of liquid moved per time unit Flow rate Water density Second Watt year

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Abstract

Abstract Energy and water are interlinked at multiple scales, although they are conventionally managed in isolation. Following this, synergies between these two resources are not recognized properly. The generic term for all interactions between water and energy is “Water-Energy Nexus”. It shows the relationship between how much water is used to generate and transmit energy, and how much energy it takes to collect, clean, move, store and dispose water. The Maipo River Basin, which is located in Central Chile, is a semi-arid region with temporary water scarcity and the biggest demand of electricity in the country. Since high amounts of water are used for irrigation purposes and a high demand of energy exists especially in the capital city Santiago, it is important to find out the linkages between these two resources. Hence, this master thesis has the main objective to examine the “Water-Energy Nexus” by investigating the Water-Energy Balance in the Maipo Watershed, in order to calculate the hydropower energy potential of a small area with irrigation channels within the basin. The Balance of Water and Energy are accomplished with the modelling programs ArcGIS and Mike Basin, the hydropower energy potential is calculated by Microsoft Excel by taking data partly from the model. The obtained results of the energy potential are used to identify adequate technologies for energy generation in irrigation channels.

Keywords: Chile, Water-Energy Nexus, Maipo River Basin, energy potential, Water-Energy Balance

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Zusammenfassung

Zusammenfassung Energie und Wasser sind auf mehreren Ebenen miteinander verknüpft, obwohl sie üblicherweise isoliert betrachtet werden. Folglich werden Synergien zwischen diesen beiden Ressourcen nicht erkannt. Der Oberbegriff für alle Zusammenhänge zwischen Wasser und Energie lautet "Wasser-Energie-Nexus". Er zeigt die Beziehung zwischen der benötigten Menge Wasser um Energie zu erzeugen und zu übertragen, und wie viel Energie es braucht, um Wasser zu sammeln, zu säubern, zu bewegen, zu lagern und zu entsorgen. Das Flusseinzugsgebiet des Maipo, welches sich in Zentral-Chile befindet, ist eine semiaride Region mit temporärer Wasserknappheit und der größten Nachfrage nach Strom im ganzen Land. Da hohe Mengen Wasser für die Bewässerung gebraucht werden und eine hohe Nachfrage von Energie speziell in der Hauptstadt Santiago existiert, ist es wichtig die Verknüpfungen zwischen diesen beiden Ressourcen herauszufinden. Da das Hauptziel dieser Masterarbeit die Untersuchung des "Wasser-Energie Nexus" ist, wurde die WasserEnergie-Bilanz im Studiengebiet untersucht, um daraufhin das Energiepotential der Wasserkraft

in

einem

kleinen

Bereich

des

Untersuchungsgebietes

mit

Bewässerungskanälen zu berechnen. Die Wasser-Energie Bilanz ist durch Modellierungen mit den Programmen ArcGIS und Mike Basin veranschaulicht worden, das Wasserkraftenergiepotenzial ist mit Microsoft Excel berechnet, indem die benötigten Daten teilweise aus dem Modell genommen sind. Die erhaltenen Ergebnisse werden verwendet,

um

geeignete

Technologien

für

die

Energieerzeugung

in

Bewässerungskanälen zu identifizieren.

Schlüsselwörter: Chile, Wasser-Energie Nexus, Flusseinzugsgebiet Maipo, Energiepotential, Wasser-Energie-Bilanz

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Resumen

Resumen Energía y agua se unen a múltiples niveles, a pesar de que suelen ser considerados de forma aislada. En consecuencia, las sinergias entre estos dos recursos no son detectados. El término genérico para todas las correlaciones entre la energía y el agua es "aguaenergía nexo". Se muestra la relación entre la cantidad de agua necesaria para producir energía y la transferencia y la cantidad de energía que se necesita para recoger, limpiar, mover, almacenar y eliminar el agua.

La cuenca del río Maipo, que se encuentra en el centro de Chile, es una región semi-árida con escasez de agua temporales y la mayor demanda de electricidad en todo el país. Debido a que grandes cantidades de agua utilizada para riego y una alta demanda de energía existe, especialmente en la capital Santiago, es importante que los vínculos entre estos dos recursos para averiguarlo. Dado que el objetivo principal de esta tesis, la investigación del "agua-energía nexo" es el equilibrio agua-energía fue examinado en el área de estudio a fin de calcular entonces el potencial energético de la energía hidroeléctrica en una pequeña zona del área de estudio con los canales de riego. El Balance de Agua y Energía se llevan a cabo con el modelado de los programas de ArcGIS y Mike Basin, el potencial de energía hidroeléctrica se calcula Microsoft Excel, tomando los atos de parte del modelo. Los resultados obtenidos se utilizan para identificar las tecnologías adecuadas para la producción de energía en los canales de riego.

Palabras clave: Chile, el agua, el agua-energía nexo, cuenca del río Maipo, el potencial energético, equilibrio de energía y agua

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Introduction

1. Introduction Water and energy are essential resources in many activities within the domestic environment. This includes washing, cleaning, cooking and drinking. The industry depends on water and energy for cooling, cleaning or chemical processes among others. Agriculture needs water for irrigation, while this is only possible with energy for pumping and distribution. On the one hand all purposes having to do with water can not be accomplished without energy, which is necessary for pumping, moving and treating the water for households, industry and agriculture. On the other hand energy can not be generated without water for cooling or impelling turbines (not taken into account are the possibilities to generate electricity with other renewable energy systems, such as solar or wind power). As a result, one resource is interlinked in many cases with the other one. This is called “Water-Energy Nexus”. Climate change plays an important role within the nexus: Higher global temperatures will increase the possibility of droughts or floods, which in turn reduces the quality, quantity and accessibility of water resources (Intergovernmental Panel on Climate Change (IPCC) 2007). This will lead to higher energy use to treat low quality water or to pump water from greater depth (U.S. Department of Energy 2007). In turn, increased energy use will cause bigger greenhouse gas emissions. A vicious circle can be observed, if countries depending on hydroelectricity have to turn to energy sources affecting higher emissions and thus, influence the climate change (Thirlwell et al. 2007). That’s why energy and water must be managed together to maintain reliable energy and water supplies. The purpose of the master thesis research is to investigate the “Water-Energy Nexus” in the Maipo River Basin in Central Chile and to deduce an energy balance. Furthermore, the energy potential of the irrigation channels in the Central Valley will be calculated with the help of a model in Mike Basin, as far as it is possible. Afterwards, recommendations to the use of hydropower plants within the irrigation channels are made, taking into account the economic feasibility. At the end, the possibility of the implementation of a new energy node into Mike Basin is discussed.

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Introduction After a short description of the global situation of water and energy, intersections of both resources are analysed leading to a detailed description of the Water-Energy Nexus in chapter two. Chapter three describes the situation of the Water-Energy Nexus in Chile, while chapter four explains the need for research and the explicit research questions of the thesis. The aims of the thesis are described in chapter five. In chapter six the methodologies used in data retrieval and analysis and the data sources are described. Chapter seven and eight give an introduction to the general calculation and modelling of energy potentials in Mike Basin. The following chapter nine deals with the research area of the Maipo Watershed in Central Chile in more detail, while chapter ten analyses specifically the study region with irrigation channels in the Central Valley of the Maipo Watershed. At the end, in chapter eleven, the results obtained in chapters nine and ten are discussed and recommendations are made.

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Background

2. Background 2.1. Introduction

In this chapter, the context of the study – the water-energy nexus – is presented. At first, the different definitions of energy are described, in order to distinguish between primary, secondary and end user energy (chapter 2.2). In chapter 2.3 the term “energy potential” is briefly described in order to provide information about the physical background. Following this, the term “water-energy nexus” is briefly explained and described with the help of examples, always being aware of the different kinds of energy (primary energy, secondary energy, gross power or net power)(chapter 2.4).

2.2. Definitions of Energy

Firstly it has to be defined, what kind of energy is looked at in this thesis. Several forms of energy are available: Primary energy, secondary energy and end user energy. The differences and definitions of each energy form are described in Tab. 1.

Form of Energy

Primary Energy

Secondary Energy

End User Energy

Tab. 1: Overview of the different forms of energy Definition

Examples Energy, which is available through natural energy sources like coal, gas or wind. - Fossil Fuels: coal, lignite, turf, Primary energy can not be used directly by natural gas, crude oil the end user without conversion or - Nuclear Energy transformation into other forms of energy - Renewable Energies: Solar energy, (e.g. electricity). biomass, wind energy, hydropower, Primary energy is used in energy statistics geothermal energy and in the field of energetics. Energy, which is available after conversion - electricity or transformation of primary energy. The - refined fuels transformation and conversion of primary - synthetic fuels (hydrogen fuel) energy into secondary energy causes high - heated water losses. Energy, which is available for the end user after deduction of losses from transport and conversion / transformation. Source: Own compilation after Hamhaber (2010)

According to Tab. 1, water energy is a primary energy, which can not be used directly by the end user. For this purpose the primary energy of water has to be transformed into

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Background secondary energy, causing high losses due to the efficiencies of the electricity generators. For the purpose of the energy balance within the research area and the energy potential of the irrigation channels, it is looked at the primary energy. This is not taking into account the electricity generation and transport losses.

2.3. Energy Potential

Two parameters are essential for using hydropower: the available amount of water and the usable gradient to let the potential energy of water free. For further understanding the meaning of “potential” will be described according to Nischler et al. (2011).

1. Theoretical Potential: The theoretical potential is used for potential energy of all water bodies within the research area without taking into account technical and economical limitations. This kind of potential represents the conceivable upper limit. i. Potential of Rainfall: Use of the total potential energy of the rainfall. ii. Surface runoff potential: Only the effective rainfall runoff is used in the potential calculation. Input is the average rainfall during a certain period of time (month, year). iii. Drain line potential: Takes into account the theoretically available potential along the river. The long-term average runoff values and the drop heights along the river are used within the calculation of the drain line potential.

2. Technical Development Potential: This refers to the technical usable potential, taking into account the overall efficiency of the energy conversion chain, including the water-flow losses and the ecological, infrastructural, legal and organizational framework.

3. Technical and Economical Development Potential: Part of technical potential, which can be used economically worthwhile after taking into account economic conditions.

Depending on the kind of potential, additional data like precipitation, water flow or gradients alongside the rivers is necessary. This additional data could be e.g. information

4

Background about the watershed, river flows, efficiency of hydropower plants, location of already existing hydropower plants and their production data or evaporation.

2.4. Significance of the Water-Energy Nexus

The USAID Global Environment Center in Washington D.C. recognized in 2001 that energy and water have much in common and that “Together, water and energy are also closely connected, based on two fundamental truths: Energy is Required to Make Use of Water (…) Water is Needed to Make Use of Energy” (Hurdus 2001, p.1). However, the World Economic Forum states that the International Food Policy Research Institute (IFRI) expects a 30 % increase in demand for water by 2030, while the International Energy Agency (IEA) forecasts an increasing energy demand of 40 % by 2030 (World Economic Forum 2011). As it can be seen in Fig. 1, intersections between water and energy occur in nearly all situations of life. The blue arrows show water flows, while the red ones show energy flows. Missing in this figure is the agricultural use of water and energy, which is the biggest water user in the watershed.

Fig. 1: Water-Energy Nexus (Source: National Conference of State Legislatures 2009)

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Background 2.4.1. Water Demand of the Energy Sector

Looking at the water demand in energy production, it can be seen in Fig. 1 that water is necessary for cooling the electricity power plants, which is either evaporated and released into the atmosphere or cooled down to be used in a circular cooling system. Furthermore, water is also needed for the production of fuels. According to the Pace Energy and Climate Center (2000) 98 % of the water used in power plants is returned to its source. Due to unequal use of units, several very different amounts of water use can be found in literature. The most often used unit in literature is kWh, which defines the produced electricity that is transmitted and distributed to the communities and households. In Tab. 2, some data about how much water is needed for different power plants is shown. Units used are L / 1,000 kWh, signalizing secondary energy, or gallons / day, not saying something about how much electricity has been generated. Tab. 3 shows the water demand according to the fuel source.

Tab. 2: Water Demand in Power Generation Technologies Power Generation Amount of water needed Technologies (depending on plant size) 1 Biodiesel 180,900 – 969,000 L / 1,000 kWh Biomass

3

PV

2 – 438 L /1,000 kWh 1 - 530 L / 1,000 kWh 3 - 2.5 – 98.4 L / 1,000 kWh 1 - 14,200 – 28,400 L / 1,000 kWh 2 - 185 billion gallons / day 1 - 1,680 L / 1,000 kWh 2 - 187 billion gallons / day 1 260 L / 1,000 kWh 1 - 38L / 1,000 kWh 3 - 2.3 – 85.9 L / 1,000 kWh 1 - 31,000 – 74,900 L / 1,000 kWh 2 - 185 billion gallons per day 3 - 3,900 – 120 L / 1,000 kWh 3 1.9 – 800 L / 1,000 kWh

Solar Thermal

2,970 – 3,500 L / 1,000 kWh

Coal-fired Power Plant Fossil-fuel thermoelectric Geothermal Hydroelectric Natural Gas Nuclear Power Plant

1

3

Wind 230 L / 1,000 kWh 1 2 3 Sources: (Jones 2008), (Pace Energy and Climate Center 2000), (Fthenakis & Kim 2010)

6

Background Tab. 3: Water Demand according to Fuel Sources Fuel Source Amount of water needed - 180,000 L / electricity for one day in Biodiesel 1000 homes - 180,900 – 969,000 L / 1,000 kWh Coal 530 – 2,100 L / 1,000 kWh Fuel ethanol

32,400 – 375,900 L / 1,000 kWh

Hydrogen

1,850 – 3,100 L / 1,000 kWh

Liquid natural gas

1,875 L / 1,000 kWh

Natural Gas

38L / 1,000 kWh electricity

Oil shale Petroleum/oil-electric sector Solar Thermal

260 – 640 L / 1,000 kWh

Synfuel: Coal gasification

144 - 340 L / 1,000 kWh

Synfuel: Fisher-Tropsch

530 – 2,100 L / 1,000 kWh

Tar sands

15,500 – 31,200 L / 1,000 kWh 2,970 – 3,500 L / 1,000 kWh

190 - 490 L / 1,000 kWh Source: (Jones 2008)

2.4.2. Energy Demand of the Water Sector

Looking at the energy demand in water production, it can be seen in Tab. 4 that energy is necessary for water treatment, distribution, pumping and for mining fuels. Furthermore energy is necessary for desalinating brackish or sea water. Globally around 7 % of the total world consumption of energy is used for delivering water (Hoffman 2009). In the following table some data about how much end user energy is needed for different water purposes is shown.

Tab. 4: Energy Demand in Water Production Purpose Amount of electricity needed 3

Desalination multi-stage flash distillation

23-27 (kWh/m )

Desalination Reverse Osmosis

4.7-5.7 (kWh/m )

3

Distribution Recycled Water Treatment and Distribution for Non-potable Uses Supply and Conveyance

700 - 1,200 (kWh / Million gallons)

Treatment

100 - 1,500 (kWh / Million gallons)

Wastewater Collection and Treatment

400 - 1,200 (kWh / Million gallons) 0 - 16,000 (kWh / Million gallons) 1,100 - 4,600 (kWh / Million gallons)

Wastewater Discharge 0 – 400 (kWh / Million gallons) Sources: (Hoffman 2009; U.S. Department of Energy 2007)

7

Background How much energy is necessary for these actions depends on several purposes. It is possible that groundwater needs only minimal energy amounts for purification, while surface waters generally require more treatment, due to several possibilities of pollution from outside the water. Energy amounts for distribution and collection can vary, depending on system size, topography or age of channels, as older systems need more energy (U.S. Department of Energy 2007). Furthermore, several other dependencies have to be taken into account, when calculating the energy needed e.g. the size of the treatment plant or the pipes for distribution. For pumping purposes it is crucial to know the quantity of pumped water and from which depth or to up to which height the water has to be pumped.

2.4.3. Energy Potential on Water Basis

A high energy potential based on water is available. In Tab. 5 an overview of the most important technologies is listed.

Tab. 5: Energy Potential on Water Basis Potential Energy Generation Existing Technology Examples (secondary energy) Bremerhaven, Germany, Dynamic tidal power > 8 GW 1,000 MW Large conventional hydropower > 14,000 MW (Itaipú Dam) Hoover Dam, USA, 2,080 MW Low power hydropower

100 kW – 1 MW

Microhydropower

5 - 100 kW

Picohydropower

< 5 kW

Pumped-storage hydroelectric power stations

< 2,820 MW (Kannagawa Hydropower Plant, Japan)

-

Run-Of the River Hydroelectricity Plant

< 4,800 MW (Jinping-II Hydropower Station, China)

Small hydropower

1 – 30 MW

-

Kithamba, Kenya, 1.1 kW Thimba, Kenya, 2.2 kW Smith Mountain Dam, USA, 656 MW Dinorwig Power Station, United Kingdom, 1,728 MW East Toba/Montrose Hydro Project, British Columbia, Canada, 196 MW Satluj Jal Vldyut Nigam Ltd, Satluj River, Shimla, India, 1,500 MW

-

Rance Tidal Power Station, France, 240 MW Tidal power 1 – 240 MW Strangford Lough SeaGlen, United Kingdom, 1.2 MW Sources: (Dixon 2007; Global Energy Observatory 2011; Ramboll 2006; The Ashden Awards 2011; UN Water 2009)

8

Background Such waterpower conversion technologies convert the kinetic energy of the water into electricity. According to Dixon (2007), these technologies can be divided into three main classes:

1. Technologies using channels or constructed waterways (e.g. dams or run-of-theriver power plants) 2. Conversion technologies converting energy from tidal streams 3. Technologies using natural currents (e.g. Pico hydropower)

Energy derived from wave energy, tidal energy, ocean current energy, salinity gradient and thermal gradient energy is called ocean energy (Dixon 2007).

2.4.4. Water Potential on Energy Basis

As it can be seen in 2.4.2, Desalination needs energy. Furthermore it produces energy as well as potable water due to the technology used. The biggest plants can be found in countries dealing with water scarcity and droughts (e.g. Saudi Arabia or United Arab Emirates). Some examples of desalination plants can be seen in Tab. 6.

Plant

Tab. 6: Water Potential on Energy Basis Gained End User Energy energy / day needed / day (secondary energy)

Desalination multi-stage flash distillation Desalination Reverse Osmosis

4.7-5.7 (kWh/m )

Jebel Ali M, United Arab Emirates

n/a

Capacity of water 3 (m /day)

3

23-27 (kWh/m ) 3

2,000 MW

600,000

Ashkelon, Israel

56 MW

80 MW

330,000

Sulaibiya, Kuwait

n/a

n/a

300,000

Perth, Australia

66 kW

507 MWh

123,300

Shuaiba III, Saudi Arabia n/a 900 MW 880,000 Sources: (Hoffman 2009; Pacific Institute 2005; Pacific Institute 2006; Sauvet-Goichon 2006; Zawya Projects 2011)

Depending on the size, the amount of water desalinated and the kind of treating the sea water, different data can be obtained for energy gain, energy use and the gain of potable

9

Background water. Further technologies to gain potable water as product, while producing electricity are e.g. ocean thermal energy conversion systems, which produce mainly electricity. Potable water can be gained by diverting the electrical output into a desalination facility (Ocean Thermal Energy Corporation 2011).

10

Research Study Region Chile

3. Research Study Region Chile The Republic of Chile is a country situated in the west of Latin America, lying between the Andes and the South Pacific Ocean. It borders Bolivia, Argentina and Peru and is part of the so called “Ring of Fire”, where large numbers of earth-quakes and volcanic eruptions occur (see Fig. 2) (Central Intelligence Agency USA 2011). Chile has a total area of 756,102 km2, on which a population of 16,888,760 people lives (estimation from July 2011), while 89% is urban population (2010). In 2010 there was a growth rate of 0.856% and an average age of 31.7 years (Central Intelligence Agency USA 2011). An estimation of 2005 comprises that 18.2% of the population has to live below the poverty line and the unemployment rate in 2009 was about 9.6%. The Gini Fig. 2: Map of Chile (Source: Central Intelligence Agency USA 2011)

index of the distribution of the family income was about 54.9 in 2003, which indicates social inequalities within the population (Central Intelligence Agency USA 2011).

The country is distributed into 15 regions, numerated with Roman numerals with the exception of the region of the capital city Santiago de Chile, which is numerated with RM (Región Metropolitana). In terms of administration there are 50 provinces under the direction of governors, who are appointed by the president of Chile (Botschaft der Republik Chile in Deutschland 2011). Quantity and distribution of water resources in Chile are determined by its mountainous topography and three climate zones. While there is desert with an arid climate in the north, in the central regions a Mediterranean and temperate climate can be found and a cool and damp climate prevails in the south (Food and Agriculture Organization of the United Nations 2010; www.climate-zone.com 2004).

11

Research Study Region Chile 3.1. Water sector

In Chile, precipitation occurs unevenly in time and space from the north to the south and from the west to the east. It varies from nearly no precipitation in the Atacama desert (Región II) to up to nearly 3,000 mm in region XI in the south, so that the mean rainfall is 1,522 mm in Chile (Food and Agriculture Organization of the United Nations 2010). In total there is an annual volume of 1,152 km3 of precipitation, of which 884 km3 are runoff and 268 km3 evaporate into the atmosphere. Chile shares water resources in the far north of the country between the latitudes of 18° and 27° with Argentina, Peru and Bolivia and additionally between the latitudes of 40° and 55° in the south with Argentina. The cordillera of the Andes is the division of the main watersheds between the countries Chile and Argentina.

In the northern part of Chile flows only a very low water quantity between 0,06 and 0,25 km3/year, while in the south of Chile there is an inflow of 38 km3/year and an outflow of 3,15 km3/year (Food and Agriculture Organization of the United Nations 2010). Nearly two million hectares of land are irrigated areas in Chile. Around 75% of this irrigated land is supplied by private channels, which were built before 1920, whereas the rest is supplied with water from state projects built after 1920 (Bauer 1998).

Water supply and sanitation in Chile is accomplished with high levels of access and service quality, which is based on the fact that all urban water companies are privately owned or operated. In 2007 99.8% of the urban areas had access to water supply and 95.2% to sanitation (Superintendencia de Servicios Sanitarios 2009, p.60)1. 58 entities provide the water supply and sanitation services in the urban areas of Chile. To avoid monopolization, the providers are classified into three categories according to the percentage of the population supplied and served: Bigger companies, medium sized companies and small companies. No person or society is allowed to possess more than 49% of the companies within one category (Superintendencia de Servicios Sanitarios 2009). The current distribution can be seen in Tab. 7.

1

The Superintendencia de Servicios Sanitarios (SISS) records only the urban water customers in Chile.

12

Research Study Region Chile Tab. 7: Distribution of the water service providers Number of Total category share Category Criterion companies of population Supplies and serves more than Bigger companies 2 50.4% 15% of the total population Medium sized Supplies and serves between 4 6 34.2% companies and 15% of the total population Supplies and serves less than Small companies 50 15.4% 4% of the total population Source: (Superintendencia de Servicios Sanitarios 2009, p.31)

The largest companies, serving 62.6% of the total urban water customers, are: •

Aguas Andinas, which serves the capital city Santiago,

•

Empresa de Servicios Sanitarios del Bio-Bío (ESSBIO), serving the sixth and eighth region near Concepción and

•

Empresa Sanitaria de Valparaíso (ESVAL), serving the region of Valpaíso.

In rural areas the water supply services are provided by local water cooperatives or water committees, whereas most isolated housings have insufficient water connections (Cariola & Alegria 2004).

13

Research Study Region Chile 3.2. Energy Sector

As it can be seen in Fig. 3, 73% of the primary energy supply is covered through fossil fuels, while only about 8% are covered by hydropower and 19% by fuelwood and other today’s used renewable energy sources. Furthermore Chile is dependent on imports of fossil fuels such as natural gas from Argentina.

Fig. 3: Supply of Primary Energy 2007 (Deutsche Gesellschaft für Technische Zusammenarbeit 2010)

In history hydropower has been Chile’s single largest power source. There is an overall capacity of 4 million kW available, producing 15.6 million kWh of electricity per year. The hydropower potential in Chile is estimated at 23,800 MWh, which equals to 128,000 GWh /yr. Only about 10 % of this potential has been used in 2003 (TU Braunschweig 2004). The fast flowing rivers coming from the Andes are the basis for the hydropower plants in Chile. At the end of the 1980’s, great efforts have been made to expand the hydropower potential of the country in order to supply not only ¾ of the Chilean electricity demand with the already existing hydropower plants, but to provide 100% of the demanded electricity (TU Braunschweig 2004). However, periodically occurring droughts, like from 1997 to 1999, shortened the hydropower production, leading to deficits or even blackouts of electricity.

14

Research Study Region Chile

Hydroelectric Power Generation, 1980 - 2006 30,00

Billion KWh

25,00 20,00 15,00 10,00 5,00

20 06

20 04

20 02

20 00

19 98

19 96

19 94

19 92

19 90

19 88

19 86

19 84

19 82

19 80

0,00

Year

Fig. 4: Development of net hydroelectric power generation in Chile from 1980 - 2006 (Energy Information Administration 2008)

In order to become less dependent on hydropower, in the 1990’s the Chilean government decided to diversify its energy mix (Clough 2008) and to create four separate power grids (TU Braunschweig 2004):

The Central Interconnected System (SIC), serving the central part of Chile, the Northern Interconnected System (SING), serving the northern parts and the Aysén and Magallanes systems, serving the southern parts of the country (see Fig. 5) (Capurro 2010). As these systems are autonomous, long distances between them make the integration difficult. Fig. 5 shows how much electricity has been generated in % and total numbers by each of the four electric systems as well as how much of the generated electricity has been produced by renewable or conventional energy resources.

15

Research Study Region Chile

Fig. 5: Overview of distribution of installed capacities in Chile in 2008 (Comisión Nacional de Energía Chile 2010)

Starting with the import of natural gas from Argentina the systems SIC and SING transformed by introducing the latest technology, which created important business opportunities for foreign companies. In Chile, there are 36 electrical distribution companies, 31 generator companies and five transportation companies, which supplied a national demand of 42,633 GWh in 2002 (Capurro 2010). The participation of “NonConventional Renewable Energies”2 (Molina C. et al. 2010; Deutsche Gesellschaft für Technische Zusammenarbeit 2010) in the electricity market is quite small, but has risen in the last few years. Often not taken into account with the electricity generation is the quantity of water needed for cooling or fuel production purposes.

2

“Non Conventional Renewable Energies” (NCRE): Encompasses all renewable energy sources, except large hydropower plants (wind, solar, photovoltaic, geothermal and mini hydropower plants) (Molina C. et al. 2010; Deutsche Gesellschaft für Technische Zusammenarbeit 2010)

16

Research Study Region Chile 3.3. Review of Water-Energy Nexus Applications 3.3.1. Introduction

As described above, the correlations between water and energy are an essential and significant part of water and energy management strategies, as it provides information for further decisions in order to improve water and energy supply. The investigations made at governmental level often lack the application, as these are often made only on theoretical base in order to obtain a result to the research question. Most approaches rely on only one part of the nexus or are linked to each other but not investigated with taking into account all intersections or possibilities. This chapter describes the state of the art in coherence with the Water-Energy Nexus in Chile and depicts the deficiencies.

3.3.2. State of the Art

The National Energy Commission (CNE) and the National Irrigation Commission (CNR) developed in 2007 with the help of an engineering company a preliminary survey of the energy potential of hydroelectric plants in association with canals and dams located between the Region III (Atacama) and Region IX (la Araucanía), where more than 97% of the irrigated areas of Chile are concentrated. The investigation was focused on identification of possible project sites to generate more than 2 MW of power, although sites with lower potential have been identified (Procivil Ingeniería Ltda. 2007). Regarding the results for the Metropolitan Region, nine sites have been identified with an installable potential of 24.2 MW. In only three cases an installable potential of over 2 MW has been found, while the other sites lie below 2 MW. Two of these sites are located in the Central Valley, while the rest can be found at the foot of the Andes or the coastal mountains. One site with an installable potential of over 2 MW is situated in the Central Valley, using the declination of the irrigation channel “Mallarauco” (see Procivil Ingeniería Ltda. 2007, p.23). Based on personal communication with Mr. Orlando Peralta from the Society of the Maipo Canal (Sociedad del Canal de Maipo - SCM), many hydroelectric power plants have been constructed in ancient years at the rivers Maipo and Mapocho and are now out of service because of the non-rentability. This non-rentability is grounded in producing less

17

Research Study Region Chile than 2 MW of energy at the hydroelectric power plants. Taking into account the occurring costs for such a plant, these plants are not rentable for further generation of electricity. Furthermore there are many active plants at the river Maipo, producing around 2 MW or more, while at the river Mapocho no active plants are known. According to information from Mr. Gabriel Zamorano of the Superintendence of Health Services (Superintendencia de Servicios Sanitarios – SISS) there are discussions between the main water producer in the region (Aguas Andinas) with an energy producer within the project “Alto Maipo”. One problem of this project concerning the water-energy nexus is the use of water from Aguas Andinas for power generating purposes. Aguas Andinas uses the reservoir “El Yeso” for supplying their clients with potable water during the dry summer months, when less water is available. Water from this reservoir is released until it reaches the treatment plant further down the mountains. The energy producer would like to use this water at the release point in order to generate additional electricity, while Aguas Andinas refuses to let the energy producer work and gain money indirectly with the water, of which Aguas Andinas owns the rights.

3.3.3. Deficiencies

Missing in all these before mentioned studies is the specific reflection on how much energy potential is available in the canals used for irrigation. The reflection is only concerned about the profitability of a project in order to gain at least 2 MW of energy. Even in the irrigation channel “Mallarauco” it is more important to produce as much energy as possible. This thinking makes sense as long as the interconnections between energy and water are not taken into account. Furthermore there are missing investigations of the hydroelectric potential below 2 MW as well as the dependencies of the hydroelectric power generation to the water availability and climate change. As climate change influences the water availability by less occurring precipitation and longer drought periods, less energy can be converted due to the decreased flow rate.

18

Research Problem

4. Research Problem The previous discussion made clear that: •

Approaches to generate energy over 2 MW have been investigated roughly and are described in studies of the government

•

Approaches of generating energy within irrigation channels are often not taken into account, as energy generation would be often lower than 2 MW, which is not taken as rentable

•

Discrepancies between water and energy producers, caused by the actual water law

•

Dependency on water and energy production are not considered caused by lacking knowledge of the nexus

The Maipo Watershed, located in central Chile, was chosen as overall case study region. It is a big sized watershed (around 15,000 km²) in a semi-arid environment with relatively strong human impacts regarding water use and contamination stemming from settlements, irrigation, industry and mining. Data on water discharges, water use, water treatment, energy use and energy generation is available, permitting to model the basin in a rough way. To model the channel system in more detail, an irrigation area located in the second section of the Maipo River, the Central Valley, of the watershed was chosen.

The overall aim of this master thesis is the assessment of an energy balance related to hydropower and the analysis of the Water-Energy Nexus. From this overall goal, more specific goals can be determined. The analysis of how much water and energy are supplied and demanded in the study area belongs to the specific objectives of the arising research questions mentioned in chapter 5. Furthermore, the calculation of the hydropower energy potential of irrigation channels in the Central Valley based on a previously compounded model of the basin, with the help of GIS-based programs, is another specific goal. The obtained results will then be used for the creation of recommendations on what kind of technologies for energy generation in irrigation channels could be used.

19

Research Problem

I. To analyse the available water quantities in the study area within the watershed by researching II. To analyse the available energy quantities in the study area within the watershed by researching III. To carry out energy potential calculations to evaluate the amount of energy that could be used in the irrigation channels IV. To give recommendations on the improvement of energy potential calculations within Mike Basin

20

Objective

5. Objective The objective of this research is to do first an analysis of how much water and energy is demanded and supplied in the study area and then classify the channel system according to the lengths, the slopes as well as the aquifer system of each channel. Hence, the research will attempt in assessing the energy potential related to hydropower. Additionally, the nexus between water and energy shall be explored as well as indicators for the implementation of the results into reports about the state of the basin shall be identified. For this reason, it is important to define the specific objectives in connection with the arising research questions:

I. To analyse the available water quantities in the study area within the watershed by researching •

how much precipitation is obtained per year / month?

•

how much water is evapotranspirated per year / month?

•

how much snowmelt can be obtained during the summer season?

II. To analyse the available energy quantities in the study area within the watershed by researching •

how much water is available for energy generation?

•

how much electricity can be or is generated per year / month?

•

how much electricity is transmitted to the customers per year / month?

III. To carry out energy potential calculations to evaluate the amount of energy that could be used in the irrigation channels and determine •

what kind of hydropower stations can be used?

•

losses associated with each kind of hydropower station.

IV. To give recommendations on the improvement of energy potential calculations within Mike Basin and determine •

what kind of data is necessary for the calculations?

•

necessary, but actually missing functions for the calculations.

21

Methodology

6. Methodology Based on the objectives, the following methodological approach in Fig. 6 has been developed: The first step is the development of a conceptual model approach for the whole Maipo Basin, which is able to calculate the energy potential in irrigation channels for monthly time steps (chapter 7). In the second step the spatiotemporal analysis considers available data on precipitation, flow rate, gradients, channel dimensions, rural, municipal and industrial water extractions and discharges as well as the energy supply and demand. This data is used for the modelling of energy and water supply and demand in the Maipo Basin (chapter 8).

1

Develop Conceptual Model for Hydroelectric Energy Potential in Irrigation Channels Methods to estimate energy potential per channel reach considering: • Flow rate • Dimensions (height, width) • Gradient

2

Spatio-temporal Modelling of Energy and Water Supply and Demand in the Maipo Basin Mike Basin Setup Results

3

Maipo Watershed Analysis Extractions and return flow from rivers and wells, demand of energy for distribution and pumping

5

4

Analysis of Water-Energy Nexus Hydroelectric Energy Production, Energy Supply and Demand Water Supply and Demand Water-Energy Balance Maipo Basin

Central Valley Analysis Energy Potential of irrigation channels Possible turbine application

6

Water-Energy Assessment (Discussion and Recommendations) Recommendations on technology used for hydropower energy generation in irrigation channels Possibilities for the implementation of an “Energy User” node in Mike Basin

Fig. 6: Overview of methodological approach (Source: Own compilation)

22

Methodology In step four follows the analysis of the Maipo Watershed, including extractions and return flows from rivers and wells as well the energy demand for distribution, pumping and treating the water (chapter 9). Afterwards, the fourth step is the analysis of the Water-Energy Nexus. The result shows the energy demand for water purposes (irrigation, distribution etc.) as well as the water demand for energy purposes (cooling, production etc.). At the end a water-energy balance of the Maipo watershed is established (Chapter 9). Based on the information acquired in the first two steps (compare Fig. 6), the potential of hydroelectric power in the irrigation channels of the Central Valley is modelled in space and time in the fifth step. For this purpose a GIS-based network model (Mike Basin) is used, which allows to model the transport of water within the system. The energy potential of irrigation channels is modelled based on measured inputs from gauging stations, discharges and withdrawals from ungauged basins by consulting the distributed water rights. The energy potential is determined by the combination of river and channel flows with gradients and dimensions of the channels. Calculations follow in general the formula P = rho*Q*g*h, whereas P is the energy potential, rho is the specific density of water with 999,975 kg/m³, Q is the flow rate, g is the gravitational field with the strength of 9.81 m/s2 and h is the gradient. The result is the gross energy potential, not taking into account which kind of hydropower energy conversion technologies could be used, so that efficiency parameters are neglected in this approach (Chapter 10). Subsequently, recommendations on technologies for hydropower energy generation in irrigation channels are established and possibilities for the implementation of “Energy User” nodes in Mike Basin are presented (Chapter 11).

6.1. Required Data

The data comes from a wide range of sources and documents. The information provided by the Ministries of Chile and the National Institute of Statistics form the basis for the model, such as the watershed area, water flows or energy data. It should be noted that absolute accuracy is not possible for the purpose of this thesis, since e.g. water flows are available for the natural river reaches, but not for the irrigation channel system itself and that not all channel dimensions are available for the energy potential calculations as there

23

Methodology is no cadastre available including all built channels in the Central Valley. For a more specific result many more months would have been required for data sampling and gathering.

Tab. 8: Main required data for modelling and analysis Water

Energy

Chile

Watershed Boundaries Digital Elevation Model (DEM) Location of basin, rivers and irrigation channels Mass flows water (monthly) Hydrological data (monthly) Water use Water supply

Energy use Energy supply Currently used hydropower stations

Natural conditions

Source: Author

Table Tab. 8 shows a list of the required data for modelling and the analysis. Those relating to water are data about the watershed boundaries, the location of the basin, the rivers and the irrigation channels, the digital elevation model, the measured hydrological data and water flow data as well as the water use and supply. Data about the watershed itself have been acquired by the CNR, while mass flow data and hydrological data were available from KIT-ITAS and the General Directorate of Water (DGA). The digital elevation model has been obtained online from Earth Explorer. Information about the water and energy demand and supply has been achieved from local authorities, such as the INE (Chilean National Institute of Statistics), the CNR, Aguas Andinas, SMAPA or Chilectra. Concerning the irrigation channels, interviews with key informants and literature research were done on regional level of the Metropolitan Region. The availability of the channel data was limited. They were obtained partly from the DGA-MOP, the CNR, the Society of the Maipo River Channels (Sociedad Canal del Maipo – SCM) and the Irrigator Association of the Maipo River (Asociación de Canalistas de Maipo). Background information to Chile and the study region were retrieved through literature research.

24

Methodology 6.2. Literature Research

An extensive literature research has been carried out as preparation for the background information about the research area, the creation of the model and the analysis of this thesis. Primary and secondary data were used. Most of the literature was published either by national organisations and institutions or international ones.

The considered topics taken into account: •

Policy in Chile’s energy sector

•

Water Law of Chile

•

Maipo River Basin

•

Hydropower

•

Energy Potential Calculations of Hydropower

6.3. Research Conditions

The time period for the meteorological data, fluviometrical data and water level data of wells cover years from 2006 until 2011 as far as they were already available. Channel dimensions, like height, slope or width, are needed for the calculation of the energy potential in irrigation channels. As there is no complete and official cadastre of channels available showing the needed parameters, only those channels are taken into account of the analysis, which have sufficient data sets for the calculation of the energy potential. For all other channels with insufficient data sets, the energy potential can just be roughly calculated depending on the estimation of water amounts flowing through the channel for irrigation purposes, which is defined by the distributed water rights.

25

Methodology 6.4. Justification of the research area

The reason why the Central Valley of the Maipo Watershed was chosen for the research is the ongoing research of the Karlsruhe Institute for Technology in Santiago de Chile and the surrounding regions. Furthermore the Central Valley is the main region of agricultural production thus, needing high amounts of water for irrigation during the summer season. During the last hundred years many irrigation channels have been built, without taking into account the possibility of generating energy by hydropower within these channels.

26

General Introduction to Energy Potential Modelling

7. General Introduction to Energy Potential Modelling 7.1. Energy Potential Calculations

There are several possibilities in calculating energy, depending on what type of energy is looked at. In general terms, the amount of energy (E) equals the mathematical product of the mass (m) of an object, the height (h) this object drops and the gravitational field of strength (g): E = mgh

(1)

In order to calculate the energy potential of water over time, the power is related to the mass flow rate: E m = gh t t

(2)

By replacing P for E⁄t and express m⁄t into the rate of fluid flow Q (volume of liquid moved per time unit) and the water density ρ, following expression is valid:

Pgross = ρQghgross

[ J s or W]

(3)

A simpler formula for the energy potential of hydroelectric power plants is:

P = ρ Qg∆he0

[ J s or W]

(4)

With P = Power in W, Δh = height difference in m, Q = flow rate in m3/s, g = gravitational force 9.81 m/s2, ρ = water density 1,000 kg/m3 and e0 = efficiency coefficient of the power plant ranging from 0 to 1. Depending on the size of the power plant the efficiency coefficient ranges between 0.7 and 0.8, signifying 70 – 80% of efficiency of the complete power plant (including efficiencies of turbines, of the gear units, generators and transformers). The calculated power P equals the gross output of which the used power of the plant itself has to be deducted (Harvey 2009, p.5). In order to calculate the net power, which is the power reaching the consumer, following equation is true (Harvey 2009, p.5):

Pnet = e0 ρQghgross

[W]

Pnet = e0 1000 Q 9.8 hgross

[W]

Pnet = e0Q 9.8 hgross

(5)

[kW]

27

General Introduction to Energy Potential Modelling 7.2. Modelling Energy Potential

In order to model the energy potential of natural river systems in a GIS-based form, only few approaches are described in literature. Nischler et al. (2011), Schröder (2009) and Anderer et al. (2010) describe the calculation and modelling of hydropower energy potential based on GIS. The first step of modelling is the development of four main layers, including one for a digital elevation model, one for water flow, one layer for the river network and the last one for the water balance, each calculated within a raster. To achieve the hydropower potential of each raster cell, it is necessary to model the drop height of each cell into direction of water flow, based on the digital elevation model. After calculation of the energy potential with ΔE = m·g·Δh the result can be shown in an additional layer, showing the energy potential of each raster cell. The main objective of the model is to predict energy potentials of natural river systems for gauged catchments, in order to show possible sites for electricity generation with the help of hydropower plants. Nischler et al. (2011) achieved an energy potential analysis of natural river systems in Italy, France, Spain and Portugal, taking into account natural peculiarities. The simulation is limited by not basing on data of evapotranspiration and provides only annual estimates.

During this thesis work, the energy potential calculations of the irrigation channels have not been done with Mike Basin, as not all necessary data for the “Hydropower” node was available. That is why the energy potential within irrigation channels has been calculated on basis of height profiles from the channels (derived from ArcGIS) and the flow rates of water according to the water rights of the users. The efficiency coefficient described in Formulas (4) and (5) has not been taken into account for the calculations of the energy potential. Chapter 11 shows technologies, which could be used in the irrigation channels taking into account the water flows.

28

Modelling Energy Potential – Model Set up and Inputs

8. Modelling Energy Potential – Model Set up and Inputs 8.1. Determine the Hydrological Network

The stream network has been defined on the basis of the watershed topography in a first step. Afterwards, sub-watersheds were delineated, involving the following steps and data: 1. Based on the DEM (30 x 30 m resolution), the river network (Comisión Nacional de Energía Chile 2010) was copied onto the DEM to create a modified one, using the Mike Basin extension (Version 2009.0 DHI 2009); 2. In order to prevent discontinuities in the flow direction calculation, the DEM has to be cleaned up of gaps by using the ArcToolbox from the ArcCatalog with the commands “Is Null”, “Focal Statistics” and “Con”; 3. Determination of flow direction (with Mike Basin command “Process DEM”); 4. River flow and hydrological network were calculated and digitized using the command “Trace River” from Mike Basin (compare result in Fig. 7).

Fig. 7: River Network as Basis for the Mike Basin model derived from Digital Elevation Model (own compilation after data from Dirección General de Aguas 2011)

29

Modelling Energy Potential – Model Set up and Inputs 8.1.1. Network and Catchment Model

The network model is based on the hydrological network, where river nodes were placed at confluences, meteorological stations, fluviometrical stations and discharge stations. At catchment nodes according to the DEM the subcatchments are delineated. Water users are added at abstraction points, summarizing the smaller municipalities to one water user. Industrial water users were added separately to the municipal water users, resulting in ten water user nodes for municipalities and 5 for wastewater treatment plants. The resulting set up of the model including nodes, water users and catchments is shown in Fig. 8.

Fig. 8: Basic Set Up of the Mike Basin Model for the Maipo Watershed (Source: Own compilation)

8.1.2. List of Data Inputs

The data for the model input are derived from studies of the Maipo watershed and the water rights cadastre of the channels. The water data has been deduced by the gauging stations at the main rivers in the watershed. The energy data has been collected at the electricity generating companies or from electricity studies of the Maipo watershed.

30

Modelling Energy Potential – Model Set up and Inputs In particular they are shown in Tab. 9:

Tab. 9: Data Inputs Data

Availability

Time series of measured discharge

Monthly data 2006 - 2010

Time series of precipitation

Monthly data 2006 - 2010

Time series of static levels of wells

Monthly data 2000 - 2010

Data of water abstraction channels

Data according to the water rights

Data of energy generation

Daily data 1996 - 2011

Data of energy demand

Monthly data Source: Author

Within the Mike Basin interface it is possible to directly insert data in formats of shapefiles and related attribute tables with the extension “Temporal Analyst”. The original time series were prepared beforehand in Excel and converted into the data format dfs0 used by Mike Basin Temporal Analyst.

8.1.3. Water and Energy Users

In order to describe the water – energy balance of the Maipo Basin, all major water users abstracting from and recharging to the rivers were located and time series of water use associated. Furthermore, all major energy users and generators were located and balances of energy supply and demand were associated. As it was not possible to add “energy user nodes”, time series data of energy use and generation could not be associated to the model. Summarised in Tab. 10 water users considered in the model are shown, while Tab. 11 lists all electricity users considered for the water-energy balance.

Tab. 10: Water users described in the model Name

Type

Remarks

Aguas Andinas - Pomaire

Industry

48,821.07 l/s treated water

Aguas Andinas - Buin Poniente, Maipo

Industry

242,246.09 l/s treated water

Aguas Andinas - Melipilla

Industry

457,238 l/s treated water

31

Modelling Energy Potential – Model Set up and Inputs

Name

Type

Remarks

Aguas Andinas - El Monte, El Aguas Andinas Paico, Lo Chacón

Industry

124,678.33 l/s treated water

Aguas Andinas - Valdivia de Paine

Industry

68,620.17 l/s treated water

Aguas Andinas – El Trebal

Industry

8,454,882.58 l/s treated water

Aguas Andinas – La Farfana

Industry

18,142,519.3 l/s treated water

Aguas Andinas - San José de Maipo

Industry

300,002.33 l/s treated water

Industry

191,586.25 l/s treated water

Industry

1,290,379.68 l/s treated water

Aguas Andinas - Curacaví

Industry

92,812.33 l/s treated water

Aguas Andinas - Til Til

Industry

18,236.17 l/s treated water

A.P. Melipilla Norte - Villa Galilea

Industry

7,483.83 l/s treated water

Aguas Manquehue - Los Trapenses

Industry

90,992.60 l/s treated water

Gran Santiago

Municipality

4,668,473 inhabitants

Talagante

Municipality

217,449 inhabitants

Melipilla

Municipality

141,165 inhabitants

Buin

Municipality

63,419 inhabitants

Paine

Municipality

50,028 inhabitants

El Monte

Municipality

26,459 inhabitants

Padre Hurtado

Municipality

45,529 inhabitants

Peñalolén

Municipality

200,000 inhabitants

Pomaire

Municipality

10,000 inhabitants

Puente Alto

Municipality

515,400 inhabitants

Aguas Andinas - Paine, Buin Oriente, Linderos, Alto Jahuel Aguas Andinas - Talagante, Padre hurtado, Calera Tango, Malloco, Peñaflor

Sources: (Instituto Nacional de Estadísticas 2007; Comision Nacional de Riego 2009)

Several smaller municipalities and irrigation areas were summarised where plausible, when they were connected to the same wastewater treatment plants.

Tab. 11: Electricity users and producers considered Name

Type

Remark

Alfalfal

Producer

178 MW of capacity

Caemsa

Producer

3,2 MW of capacity

32

Modelling Energy Potential – Model Set up and Inputs

Name

Type

Remark

Eyzaguirre

Producer

1,5 MW of capacity

Florida

Producer

28,5 MW of capacity

Los Bajos

Producer

5,1 MW of capacity

Los Morros

Producer

3,1 MW of capacity

Maitenes

Producer

30,8 MW of capacity

Puntilla

Producer

22 MW of capacity

Queltehues

Producer

49 MW of capacity

Volcán

Producer

13 MW of capacity

Source: Author

8.1.4. Channel System

In order to calculate the energy potential within the channels, it is necessary to know the flow rate of water within each channel as well as the slope (derived from the DEM in Mike Basin). The flow rate is estimated on basis of given water rights until November 2000 of the DGA.

Tab. 12: Channel Properties in the Central Valley Mean Slope Flow Rate Channel Name 3 [m] [m /s] Aguilino Arenal o Villita Bustamante Carampangue Carmen Alto Chacon Chacra del Loa Poniente Chico Chinihue Concreto D 1 Chico D 1 Grande D 1 Huiticalan D 1 Mercedano D 1 Vinculano D 2 Arenal o Villita D 2 Doce D 2 Grande

0.0008 0.0016 0.006 -0.0262 0.011 -0.0064 0.0103 -0.0577 0.002 0.0571 -0.3249 -0.2986 0.0093 -0.0156 -0.0017 0.0114 0.0152 0.1308

4.55 0.67 3.62 16.40 0.55 1.06 13.32 5.74 10.40 3.50 2.17 1.04 0.30 0.48 0.42 0.70 2.00 0.41

33

Modelling Energy Potential – Model Set up and Inputs

Channel Name D 2 Tranque D 2 Vinculano D 3 Challacura D 3 Huiticalan D 3 Naltahua D 4 San Antonio de Naltahua D 5 San Antonio de Naltahua D 6 Naltahua D 7 Naltahua D 7 San Antonio de Naltahua D 8 San Antonio de Naltahua D 9 San Antonio de Naltahua D Camposano Quinta D Caperana D Carampangue D El Monte D El Triunfador D La Cantera D La Islita D Las Pircas D Santa Filomena Quinta D Sitios El Triunfador D Sta Adriana D Tronco Huelemu D Valdiviano Quinta Diez y Nueve El Paico El Vergel Grande Huiticalan La Playa Las Manresas Lo Aguirre Lo Valdes Chancho Lonquen Isla Los Chanchos Mercedano Naltahua Rosario San Antonio de Naltahua San Jose Alto San Jose Dos San Miguel SD 2 A Vinculano SD 2 C Tranque

Mean Slope [m]

Flow Rate 3 [m /s]

-0.0237 0.0235 0.0055 -0.0372 -0.0233 -0.0186 -0.0268 -0.5502 -0.1221 -0.0626 -0.031 -0.1773 0.0063 0.0188 0.0053 0.0002 -0.0268 0.0101 -0.0089 -0.0135 -0.0045 -0.0303 -0.0036 -0.0046 0.001 -0.1303 0.002 0.0006 -0.1413 -0.01 -0.0655 0.0149 -0.009 0.0036 -0.0376 -0.0149 -0.02 0.0017 -0.1111 -0.0314 0.0017 -0.0146 -0.0009 0.0277 0.0109

0.38 0.17 0.80 2.70 7.66 11.82 12.20 0.30 0.20 1.94 9.50 0.40 86.90 45.59 38.69 7.54 0.80 17.50 51.21 26.50 9.92 0.06 6.69 0.15 36.55 1.75 37.45 1.71 1.15 1.50 0.70 3.45 31.15 13.97 39.61 6.03 5.80 2.70 5.30 17.93 8.46 3.51 12.36 0.20 6.86

34

Modelling Energy Potential – Model Set up and Inputs

Channel Name SD 3A Naltahua SD 3B Naltahua SD 3E Naltahua SD 3L Naltahua SD 4A San Antonio Naltahua SD 4B Dos San Antonio de Naltahua SD 5A San Antonio de Naltahua SD 7A Naltahua SD 7B Naltahua SD 8A San Antonio de Naltahua SD 9A San Antonio de Naltahua SD El Pueblo SD Eucaliptus Silverio Trebulco Treinta y Tres Vinculano Source: Author

Mean Slope [m]

Flow Rate 3 [m /s]

0.0062 -0.0206 -0.1085 -0.025 -0.087 0.0123 0.0198 -0.1314 -0.09 -0.0903 -0.0729 -0.0058 -0.0022 -0.0089 0.0136 -0.2574 0.0479

0.40 0.20 0.05 4.50 2.28 4.10 2.97 0.40 1.30 0.20 0.20 15.05 6.33 9.00 1.76 0.77 7.08

35

Maipo Watershed Analysis

9. Maipo Watershed Analysis In this chapter, the Maipo watershed is being analyzed regarding those factors which are important in order to be able to model the spatial-temporal energy potential. The aim is to establish time series for the water and energy flows as described in chapter 6 related to river reaches, water users and sub-watersheds.

9.1. Introduction to the Study Area

The Maipo watershed represents a typical watershed in central Chile, which can be classified as “heavily modified watershed” as large parts of the watershed area are amended by land uses and water infrastructure. During the summer months available water is used at least once, as the availability of water is depending on snow melts in the Andes during spring time and precipitation, occurring mainly in the winter months. Large quantities of water are transferred in channels from the main rivers Maipo and Mapocho to the agricultural production sites.

9.2. Watershed Description 9.2.1. Location and General Description

The Maipo River Basin is located in the central regions of Chile, bordering in the north the Aconcagua Basin, in the south the Cachapoal Basin, in the east the Andes and in the west the coastal region of the Pacific Ocean (see Fig. 9) (Cai et al. 2006, p.7). It covers 100% of the Región Metropolitana and small parts of the regions Valparaíso (Región V) and Libertador Bernardo O’Higgins (Región VI) between the latitudes of 32°55’-34°15’ south and the longitudes of 69°55’-71°33’ west (Dirección General de Aguas 2004). Within its area, there are nine provinces and 56 municipalities (compare Fig. 10 for political boundaries) with a total population of 6,331,156.00, of which 96.8 % are urban population (Comision Nacional de Riego 2009). The major cities are Santiago, Talagante and Melipilla (see Fig. 11).

36

Maipo Watershed Analysis The main rivers are the Río Maipo and the Río Mapocho, which both start in the glacier zones in the Andes and cross the Metropolitan Region from east to west, until they exchange the flow before entering the sea.

Fig. 9: Location of the Maipo Watershed (Gobierno de Chile Ministerio de Obras Publicas Dirección General de Aguas 2006)

Fig. 10: Location of the 56 municipalities in nine provinces located in the Maipo Watershed (Source of Data: Comision Nacional de Riego 2009)

37

Maipo Watershed Analysis Depending on the literature several sizes of the watershed are mentioned. The area is approximately 15,000 km2 large. According to the DGA (2004) the watershed has a size of 15,304 km2, while the Castor y Polux Ltda. (2011) and M.W. Rosegrant et al. (2000, p.2) state 15,380 km2. Consistent with the INE (2010) 15,303 km2 is the size of the Maipo Basin, while the International Food Policy Research Institute IFPRI (Cai et al. 2006, p.7) mentions 15,549 km2.

Fig. 11: Number of inhabitant of the biggest cities in the Maipo Watershed (Source of Data: Comision Nacional de Riego 2009)

The Río Maipo is 250 km long and has a total declination of 5,000 m (Bartosch 2007, p.22). It represents the main water source of the Región Metropolitana as well as of the province of San Antonio lying in the V. Región Valparaíso. The river supplies 70% of the potable water demand and around 90% of the demand for irrigation (Dirección General de Aguas 2004). Several tributaries join the Río Maipo on its course. At first there are three big tributaries flowing into the Maipo in the Cordillera of the Andes, namely Río Volcán, Río Yeso and Río Colorado. The rivers Volcán and Yeso discharge into the Maipo at San Gabriel (1,250 m), while the river Colorado joins shortly afterwards. At the border from the Andes and the

38

Maipo Watershed Analysis Central Basin the river reaches the gauging station El Manzano, which is one of the most important stations of the DGA. All water quantities coming from this station represent the total water supply from the Andes, as all bigger tributaries already discharged into the Río Maipo. Leaving the Andes behind and entering the Central Basin, the Río Maipo receives the Río Clarillo. At the Cordillera de la Costa the river Maipo meets the Río Angostura, maintaining water from the Rancagua watershed. The Mapocho joins the Maipo finally in Valle Angosto near El Monte. Further east discharges the Estero Puangue into the Río Maipo. The source of this tributary lies in the Cordillera de la Costa and is characterized by leading water only during the winter months, when concentrated precipitation occurs (Bartosch 2007; CONAMA Nacional 2007, p.3).

The Río Mapocho is the second largest river in the research area. It is 110 km long and most of its water comes from snow melts in summer (Dirección General de Aguas 2004), while in winter most of the water derives from precipitation. After 50 km the river reaches the capital city Santiago. This tributary receives most of the wastewater of the region, coming from households or the industry (Dirección General de Aguas 2004), which in turn leads to a decreasing water quality during its way through the city. Several smaller tributaries discharge into the Río Mapocho, too. These are mainly Río San Francisco, Estero Arrayán and Estero Lampa. Like for the Maipo watershed, the size of the Mapocho watershed is varying between 1,005 km2 (Cai et al. 2006, p.10) to 4,230 km2 (Instituto Nacional de Estadísticas 2010, p.63). The river passes the gauging stations at Rinconada de Maipo and Los Almendros, which are as important as the gauging station for the Río Maipo at El Manzano.

From April to October, representing the wettest and coldest time during the year, around 76 to 100% (years 2004 and 2006) of the annual rainfall precipitates, while during the summer time from November to March there is only 24 to 0 % (years 2004 and 2006) precipitation of the annual rainfall (Rubio 2008) in the Maipo watershed (compare Fig. 12). Additionally to this amount of water, there is the water amount resulting from snow melts in the Andes during the summer time.

39

Maipo Watershed Analysis

30.0

180 160 140 120 100 80 60 40 20 0

T in °C

25.0 20.0 15.0 10.0 5.0 December

November

October

September

Month

August

July

June

May

April

March

February

January

0.0

mm

T mean Precipitation ET [mm]

Quinta Normal Station

Fig. 12: Climate Diagram Santiago de Chile, Quinta Normal Station T mean = average monthly temperature, ET = Evapotranspiration (Source of Data: Meza 2003, p.4; World Meteorological Organization 2011)s

Hence, the Maipo River Basin comprises agriculture, industry and services, high amounts of water and electricity are needed daily. Consistent with Neary & Garcia-Chevesich (2008), the occurring effects of the El Niño-Southern Oscillation (ENSO) led especially in 2008 to an ample drought, which affected not only the agricultural production, but also the electricity generation. Water shortages and high costs of pumping groundwater for irrigation were the biggest problem in the agricultural sector, while the low levels of the hydroelectric reservoirs caused a hydroelectric energy shortage. According to Cai et al. (2001), the basin “is a prime example of a ‘mature water economy’ (see Randall 1981) with growing water shortages and increasing competition for scarce water resources across sectors”, due to its fast growing industry and high amount of population. Nevertheless more than 90 % of the agricultural land depends on irrigation from surface flows. As it can be seen, water scarcity is a big problem in this basin, but at the same time there is a high demand of energy. 50% of the power of the Metropolitan Region of Santiago is provided with hydropower (Banzhaf et al. 2011, p.11), although hydropower generation in the basin is only carried out on run-off-the river power stations (Cai et al. 2001). The rest of the demanded energy has to be supplied by fossil fuels. The high electricity demand is caused by energy intensive procedures for treating the waste water, pumping groundwater for irrigation purposes, drinking water distribution services, for transportation or domestic and industrial needs (Banzhaf et al. 2011).

40

Maipo Watershed Analysis 9.2.2. Water Uses

In 2009, 779,251,000 m3 of potable water have been produced, while only 69.44% of it has been consumed in the same year. Most water is used for irrigation purposes the watershed accounting for 74 % of the total consumption in 2007 (Bartosch 2007), while the drinking water supply accounts for 18.5 m3/s (Simon 2009, p.84). The most important drinking water reservoir is situated in the Andes, called Embalse El Yeso, used for the purpose of supplying the capital city Santiago with drinking water. The El Yeso reservoir has a capacity of 250,000,000 m3 (Instituto Nacional de Estadísticas 2010). Depending on the demand of drinking water, water is abstracted from the reservoirs, although most of it is abstracted during the summer months in order to secure the drinking water supply of the city. The detailed time series is not available and could not be incorporated in the river basin model. Smaller cities are mostly supplied by surface water from the Maipo River (Simon 2009). An overview of the spatial distribution of water uses of the river system can be seen in Fig. 8. Water demand of the total industrial sector was 508,550 m3 in the year 2000 (Bartosch 2007). The Industrial water users of wastewater treatment plants are shown in Tab. 13. It shows the number of inhabitants, who are connected to each wastewater treatment plant, as well as the used technology and the mean monthly water use.

Tab. 13: Mean Monthly Water Use of Wastewater Treatment Plants operating in the Maipo Basin Communities Population Mean monthly Company Technology 3 Connected Served water use [m /s] 5,624,630 Stabilisation Aguas Andinas Pomaire 18.57 (total) Ponds Buin Poniente, Activated Aguas Andinas 91.13 Maipo Sludge Sequential Aguas Andinas Melipilla Batch 175.38 Reactor El Monte, El Sequential Aguas Andinas Paico, Lo Batch 52.38 Chacón Reactor Preliminary Valdivia de treatment Aguas Andinas 26.16 Paine and disinfection Activated Aguas Andinas Gran Santiago 3,538.46 Sludge El

41

Maipo Watershed Analysis

Company

Aguas Andinas Aguas Andinas

Aguas Andinas

Aguas Andinas

Aguas Andinas

Aguas Andinas A.P. Melipilla Norte Aguas Manquehue Aguas Santiago BCC EMAPAL ESSA Huertos Familiares Santiago Poniente SELAR S.A. SEPRA SERVICOMUNAL SERVILAMPA

Communities Connected

Gran Santiago San José de Maipo Paine, Buin Oriente, Linderos, Alto Jahuel Talagante, Padre hurtado, Calera Tango, Malloco, Peñaflor

Population Served

Technology Trebal Activated Sludge La Farfana Activated Sludge

8,500.90 16.33

Activated Sludge

74.98

Activated Sludge

491.51

Sequential Batch Reactor Sequential Til Til Batch Reactor Activated Villa Galilea 12,627 Sludge Activated Los Trapenses 34,336 Sludge Activated Colina 11,956 Sludge Santa Luz Activated Santo Tomas 1,018 Sludge Lomas de Lo Activated 1,864 Aguirre Sludge Aerated Quilicura n.a. lagoons Alto El Activated 858 Manzano Sludge Activated Pudahuel 16,267 Sludge Activated Lampa 5,890 Sludge Larapinta Ciudad de los Activated 10,380 Valles Sludge Stabilisation Colina 74,056 Ponds Activated Lampa 20,249 Sludge n/a = not available Curacaví

Mean monthly 3 water use [m /s]

34.75

6.93 7.49 37.80 n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a

Source: (Superintendencia de Servicios Sanitarios - Gobierno de Chile 2011)

42

Maipo Watershed Analysis Most water demand is produced by the agricultural sector for irrigation. According to Tab. 11 the Melipilla province has most of the irrigated areas. In comparison to that the provinces of Santiago and Chacabuco are quite small (Instituto Nacional de Estadísticas 2007). In total there are 810,137.35 ha of agricultural land use, of which 16.88 % are irrigated. During the agricultural year 2006/2007 irrigation by gravitation has been accomplished for 66.47 % of the irrigated area, while 2.78 % have been irrigated through mechanical irrigation and finally 30.75 % by micro irrigation (Instituto Nacional de Estadísticas 2007).

Tab. 14: Irrigation areas in the provinces of the Metropolitan Region 2006/2007 Province

Irrigated area in ha

Santiago

6,004.80

Chacabuco

7,628.84

Cordillera

17,051.60

Maipo

32,798.27

Melipilla

52,592.18

Talagante

20,656.65

Total

136,732.34

Source: (Instituto Nacional de Estadísticas 2007)

The efficiency of irrigation is 20 – 60 %, depending on the used technique. Gravitational irrigation has an efficiency of 35 %, mechanical irrigation of 70 % and micro irrigation of 85% (Bartosch 2007, p.57). As already mentioned before, the gravitational irrigation is used for the largest parts, although it has the lowest efficiencies of all. Best irrigation technology is the micro irrigation, working with micro sprinkling or drip tapes. A percental overview about the irrigation techniques in relation to the irrigated area is shown in Fig. 13. According to Bartosch (2007), 20,000 m3 of water are necessary for the irrigation of one hectare, which would mean that 2,734,646,800 m3 have to be supplied each year for the Maipo watershed for irrigation. This results in a water demand of 227,887,233.33 m3 per month and 7,596,241.11 m3 per day, not taking into account the crop fluctuation during the year.

43

Maipo Watershed Analysis

Micro Irrigation 30.75%

Mechanical Irrigation 2.78%

Gravitation 66.47%

Fig. 13: Percentage of irrigation technique according to the irrigation area (Source of Data: Instituto Nacional de Estadísticas 2007)

Actual data about the water demand of the mining sector is unknown, but Bartosch (2007, p.62) writes of 300 l/s in 1998, which would lead to an annual demand of 9.5 million m3.

9.3. Reported Water Data

For the modelling and the calculation of the energy potential, flow rates and the monthly mean precipitations are important (compare chapter 7). The following Fig. 14 to Fig. 29 show the flow rates and precipitations between the years 2006 to 2010 at the shown gauging stations.

Fig. 14: Average Monthly Precipitation (blue) and Flow Rate (black) 2006 - 2010 recorded at Rio Mapocho Rinconada de Maipu (Dirección General de Aguas 2011)

44

Maipo Watershed Analysis

Fig. 15: Average Monthly Precipitation (blue) and Flow Rate (black) 2006 - 2010 recorded at Rio Angostura en Valdivia de Paine (Dirección General de Aguas 2011)

Fig. 16: Flow Rate 2006 - 2010 recorded at Estero Alhue en Quilamuta (Dirección General de Aguas 2011)

Fig. 17: Flow Rate 2006 - 2010 recorded at Rio Maipo en el Manzano (Dirección General de Aguas 2011)

45

Maipo Watershed Analysis

Fig. 18: Flow Rate 2006 - 2010 recorded at Rio Mapocho en los Almendros (Dirección General de Aguas 2011)

Fig. 19: Precipitation 2006 - 2010 recorded at Barrera Loncha (Dirección General de Aguas 2011)

Fig. 20: Precipitation 2006 - 2010 recorded at Carmen de las Rosas (Dirección General de Aguas 2011)

46

Maipo Watershed Analysis

Fig. 21: Precipitation 2006 - 2010 recorded at El Vergel (Dirección General de Aguas 2011)

Fig. 22: Precipitation 2006 - 2010 recorded at Fundo Marruecos (Dirección General de Aguas 2011)

Fig. 23: Precipitation 2006 - 2010 recorded at Ibacache Alto (Dirección General de Aguas 2011)

47

Maipo Watershed Analysis

Fig. 24: Precipitation 2006 - 2010 recorded at Laguna Aculeo (Dirección General de Aguas 2011)

Fig. 25: Precipitation 2006 - 2010 recorded at Los Guindos (Dirección General de Aguas 2011)

Fig. 26: Precipitation 2006 - 2010 recorded at Los Panguiles (Dirección General de Aguas 2011)

48

Maipo Watershed Analysis

Fig. 27: Precipitation 2006 - 2010 recorded at Mallarauco (Dirección General de Aguas 2011)

Fig. 28: Precipitation 2006 - 2010 recorded at Melipilla (Dirección General de Aguas 2011)

Fig. 29: Precipitation 2006 - 2010 recorded at Villa Alhue (Dirección General de Aguas 2011)

49

Maipo Watershed Analysis 9.3.1. Energy Uses

The total consume of electricity accounted in 2007 for 17,000 GWh. Dominant electricity user within the watershed is the Industry accounting for 30 % of the total consumption, while the residential and commercial sector need 26 % and 22 %, followed by the mining sector with 7 % and the agricultural sector with only 2 % (Instituto Nacional de Estadísticas 2008).

Distribution of Electrity Demand in 2007 (17,000 GWh) Others 13% Industry Agriculture 2%

Industry 30%

Residential Comercial Mining

Mining 7%

Agriculture

Comercial 22%

Others Residential 26%

Fig. 30: Distribution of Electricity Demand in 2007 Source: (Instituto Nacional de Estadísticas 2008)

9.4. Reported Energy Data

From 1996 onwards daily data about the electricity generation from the five most important hydropower plants are documented. El Niño-Oscillations as well as droughts can be seen in the evolution from 1996 to 2011, like in 2002 and 2003, where the total electricity generation was all the year long below 1,500 MWh or less. In comparison to that, the year 2010 is a “normal” year. Fluctuations in electricity generation only occur due to the seasonal variability of the water level caused by snow melts and precipitation. An overview about the characteristics of the hydropower plants is shown in Tab. 15, while in Fig. 31 the evolution of electricity generation from 1996 to today can be seen.

50

Maipo Watershed Analysis Tab. 15: Characteristics of Hydropower Plants operating in the Maipo Basin Electricity Generation2010 Name of Hydropower Plant Technology (in MWh) Alfalfal Run of the river 845,500 Florida Run of the river 118,661 Maitenes Run of the river 129,722 Queltehues Run of the river 357,686 Volcan Run of the river 107,659 (Source: Ministerio de Energía 2011)

Energy Generation Maipo 1997 8.000

7.000

7.000

3.000

01.10.97

01.11.97

01.12.97

01.11.99

01.12.99

Energy Generation Maipo 1999

Energy Generation Maipo 1998 8.000

8.000

7.000

7.000

Energy Generation / MWh

6.000 5.000 4.000 3.000 2.000 1.000 0

6.000 5.000 4.000 3.000 2.000 1.000

Tim e / daily

01.09.99

01.08.99

01.07.99

01.06.99

01.05.99

01.04.99

01.03.99

01.01.99

01.12.98

01.11.98

01.10.98

01.09.98

01.08.98

01.07.98

01.06.98

01.05.98

01.04.98

01.03.98

01.02.98

01.01.98

0 01.02.99

Energy Generation / MWh

01.09.97

Tim a / daily

Tim e / daily

Tim e / daily

Energy Generation Maipo 2000

Energy Generation 2001 8.000

7.000

7.000 Energy Generation / MWh

8.000

6.000 5.000 4.000 3.000 2.000 1.000 0

6.000 5.000 4.000 3.000 2.000 1.000

Tim e / daily

01 .0 1. 01 01 .0 2. 01 01 .0 3. 01 01 .0 4. 01 01 .0 5. 01 01 .0 6. 01 01 .0 7. 01 01 .0 8. 01 01 .0 9. 01 01 .1 0. 01 01 .1 1. 01 01 .1 2. 01

01.12.00

01.11.00

01.10.00

01.09.00

01.08.00

01.07.00

01.06.00

01.05.00

01.04.00

01.03.00

01.02.00

0

01.01.00

Energy Generation / MWh

01.10.99

01.01.97

01.12.96

01.11.96

01.10.96

01.09.96

01.08.96

01.07.96

01.06.96

01.05.96

01.04.96

01.03.96

0 01.02.96

1.000

0

01.08.97

2.000

1.000

01.07.97

2.000

4.000

01.06.97

3.000

5.000

01.05.97

4.000

6.000

01.04.97

5.000

01.03.97

6.000

01.02.97

Energy Generation MWh

8.000

01.01.96

Energy Generation MWh

Energy Generation Maipo 1996

Tim e / daily

51

Tim e / daily

5.000

4.000

3.000

2.000

1.000

0

Tim e / daily

Energy Generation Maipo 2008

8.000

6.000

5.000

4.000

3.000

2.000

1.000

0 0

Tim e / daily

Energy Generation Maipo 2009

8.000

7.000

6.000

5.000

4.000

3.000

2.000

1.000

0

Tim e / daily

52

01.09.05

01.08.05

01.07.05

01.12.05

1.000

01.12.07

2.000

01.12.09

3.000

01.11.05

4.000

01.11.07

5.000

01.11.09

6.000

01.10.05

Energy Generation Maipo 2007

01.10.07

Tim e / daily

01.10.09

01.09.07

7.000

01.09.09

6.000

01.08.07

8.000

7.000

01.07.07

Energy Generation Maipo 2006

01.08.09

Tim e / daily

01.07.09

0 01.06.05

1.000

01.06.07

Tim e / daily

01.06.09

2.000

01.05.05

3.000

01.04.05

4.000

01.05.07

5.000

01.04.07

6.000

01.05.09

8.000

01.04.09

Energy Generation Maipo 2004

01.03.05

01.12.03

01.11.03

01.10.03

01.09.03

01.08.03

01.07.03

01.06.03

01.05.03

01.04.03

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01.02.03

0

01.02.05

1.000

01.03.07

2.000

01.02.07

Energy Generation 2002

01.03.09

3.000

01.01.03

4.000

Energy Generation / MWh

5.000

01.01.05

7.000

Energy Generation / MWh

01.12.02

01.11.02

01.10.02

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01.08.02

01.07.02

01.06.02

01.05.02

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Energy Generation / MWh 6.000

01.01.07

8.000

Energy Generation / MWh

01.12.04

01.11.04

01.10.04

01.09.04

01.08.04

01.07.04

01.06.04

01.05.04

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01.02.04

01.01.04

Energy Generation / MWh

7.000

01.02.09

7.000

Energy Generation / MWh

01.12.06

01.11.06

01.10.06

01.09.06

01.08.06

01.07.06

01.06.06

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Energy Generation / MWh 8.000

01.01.09

01.12.08

01.11.08

01.10.08

01.09.08

01.08.08

01.07.08

01.06.08

01.05.08

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01.02.08

01.01.08

Energy Generation / MWh

Maipo Watershed Analysis

Energy Generation Maipo 2003

8.000

7.000

6.000

5.000

4.000

3.000

2.000

1.000 0

Tim e / daily

Energy Generation Maipo 2005

8.000

7.000

6.000

5.000

4.000

3.000

2.000

1.000 0

Maipo Watershed Analysis

Energy Generation Maipo 2011

2.000 1.000

Tim e / daily

01.12.11

01.11.11

01.10.11

01.09.11

0

01.12.10

01.11.10

01.10.10

01.09.10

01.08.10

01.07.10

01.06.10

01.05.10

01.04.10

01.03.10

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0

3.000

01.08.11

1.000

4.000

01.07.11

2.000

5.000

01.06.11

3.000

6.000

01.05.11

4.000

7.000

01.04.11

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01.03.11

6.000

8.000

01.02.11

7.000

01.01.11

Energy Generation / MWh

8.000

01.01.10

Energy Generation / MWh

Energy Generation Maipo 2010

Tim e / daily

Fig. 31: Evolution of Electricity Generation with Hydropower Plants from 1996 - 2011 (Source of Data: Ministerio de Energía 2011)

9.5. Water-Energy Balance 9.5.1. Water Demand of the Energy Sector

In the year 2000, the industrial sector in Santiago had a daily water demand of 508,550 m3, equalling 183 million m3 of water per year. Between 1997 and 2005 an increase of water demand of 1000 l/s has been observed, which is an increase of 20% since 1997 (Bartosch 2007). It turned out that data sampling from electricity generating companies is difficult, as most big companies own their own wells to cover their water demand for cooling. This cooling often is done by circulating water amounts, so that the amount of water for cooling has to be changed or refilled after a certain time. Two thermoelectric power plants generating electricity are located in the Maipo watershed (Sociedad Eléctrica Santiago S.A. 2008):

•

Thermoelectric Central Renca in Renca Owner: Sociedad Eléctrica Santiago S.A. In operation since 1962 with a potential of 100 MW Turbine works with Diesel Premium - Vapor

•

Combined-Cycle Central Nueva Renca in Santiago Owner: Sociedad Eléctrica Santiago S.A. In operation since 1998 with a potential of 379 MW Turbine works with Natural Gas

53

Maipo Watershed Analysis All other electricity generating power plants are hydroelectric run-of-the-river power plants, using water for electricity generation.

9.5.2. Energy Demand of the Water Sector

The water sector needs mainly electricity in order to treat the wastewater or pump subterranean water to the surface. Irrigation is mostly done by channels, leading the water to its final destination by gravitational forces. In total 136,732.34 ha have to be irrigated with water during the year, of which 90,890.12 ha are irrigated by gravitation, 3,799.83 ha are irrigated by bigger mechanics like traditional sprinkling and 42,042.39 ha are irrigated by micro irrigation done with micro sprinkling (4,761.07 ha) or drip tape (37,281.32 ha) (Instituto Nacional de Estadísticas 2007). According to data from Chilectra (2011), the mean energy consumption of treatment plants is 8,508 MWh. An overview of the energy demand of the wastewater treatment plants within the watershed is shown in Tab. 16, while Fig. 32 shows the monthly energy

12,000 10,000 8,000 6,000 4,000 2,000

Dec-10

Nov-10

Oct-10

Sep-10

Aug-10

Jul-10

Jun-10

May-10

Apr-10

Mar-10

Feb-10

0 Jan-10

Wastewater Treatment Plant [MWh]

consumption of wastewater treatment plants.

Month

Fig. 32: Monthly energy consumption of wastewater treatment plants in 2010 (Source of Data: Chilectra 2011)

54

Maipo Watershed Analysis Tab. 16: Mean Monthly Energy Use of Wastewater Treatment Plants operating in the Maipo Basin Communities Population Mean monthly energy use Company Technology Connected Served [kWh] 5,624,630 Stabilisation Aguas Andinas Pomaire 14,484.33 (total) Ponds Buin Poniente, Activated Aguas Andinas 123,084.75 Maipo Sludge Sequential Aguas Andinas Melipilla 161,298.67 Batch Reactor El Monte, El Sequential Aguas Andinas 61,128.50 Paico, Lo Chacón Batch Reactor Preliminary Aguas Andinas Valdivia de Paine treatment and 2,433.25 disinfection Activated Aguas Andinas Gran Santiago Sludge El 2,154,974.91 Trebal Activated Aguas Andinas Gran Santiago Sludge La 6,052,346.18 Farfana San José de Activated Aguas Andinas 26,320.50 Maipo Sludge Paine, Buin Activated Aguas Andinas Oriente, Linderos, 104,850 Sludge Alto Jahuel Talagante, Padre hurtado, Calera Activated Aguas Andinas 314,570 Tango, Malloco, Sludge Peñaflor Sequential Aguas Andinas Curacaví 63,804.25 Batch Reactor Sequential Aguas Andinas Til Til 12,367.58 Batch Reactor A.P. Melipilla Activated Villa Galilea 12,627 8,798.92 Norte Sludge Aguas Activated Los Trapenses 34,336 33,206.13 Manquehue Sludge Activated Aguas Santiago Colina 11,956 Sludge Santa n/a Luz Activated BCC Santo Tomas 1,018 n/a Sludge Lomas de Lo Activated EMAPAL 1,864 n/a Aguirre Sludge Aerated ESSA Quilicura n.a. n/a lagoons Huertos Activated Alto El Manzano 858 n/a Familiares Sludge Santiago Activated Pudahuel 16,267 n/a Poniente Sludge Activated SELAR S.A. Lampa 5,890 Sludge n/a Larapinta Ciudad de los Activated SEPRA 10,380 n/a Valles Sludge SERVICOMUNAL Colina 74,056 Stabilisation n/a

55

Maipo Watershed Analysis

Company

SERVILAMPA

Communities Connected Lampa

Population Served

Technology

Mean monthly energy use [kWh]

Ponds Activated 20,249 Sludge n/a = not available

n/a

Source: (Superintendencia de Servicios Sanitarios - Gobierno de Chile 2011)

9.5.3. Energy Potential on Water Basis

Half of the electricity generation within the Maipo Watershed is derived from large as well as small hydropower plants. Small hydropower plants are classified as “NonConventional Renewable Energy” within the Chilean electrical system. It differs from large hydropower plants by having an installed capacity of less than 20 MW. In Tab. 17 a list of the principal hydroelectric power plants of the Metropolitan Region is presented. All power plants use the run of the river technology, meaning the height difference of water flow from the tributaries of the river Maipo.

Tab. 17: Installed Capacity in MW of the principal hydroelectric power plants in the Metropolitan Region Name Hydroelectric Power Plant

Turbine Type

Caemsa Francis Eyzaguirre Ossberger Crossflow Los Bajos Francis Los Morros Francis Volcán Pelton Non-Conventional Renewable Energy Alfalfal Pelton Florida Francis Maitenes Francis Puntilla Francis Queltehues Pelton Conventional Renewable Energy Total Hydroelectric Capacity Source: (CDEC-SIC 2011, pp.31–32)

Capacity

Total

3,2 1,5 5,1 3,1 13 26 178 28,5 30,8 22 49 308 334

The largest mini hydropower plant of the Metropolitan Region, called “Volcán”, is located in the commune San José de Maipo and belongs to the company AES GENER S.A. (CDECSIC 2011). The second half of the electricity generation is supplied by coal power plants (19%), natural gas (19%), fuel oil / diesel (10%) and biomass (2%) (CDEC-SIC 2011).

56

Maipo Watershed Analysis 9.5.4. Water Potential on Energy Basis

As it has been mentioned in chapter 2.4.4, desalination plants are the technology for producing energy and water at once. These plants are not used for electricity generation in the watershed, as most of the produced electricity is gained from the rivers as well as from fossil fuels.

9.6. Conclusions

Water availability and demand in the Maipo Watershed is characterised through seasonal variability. The runoff in the rivers Maipo and Mapocho are determined by snowmelt with peaks from October to November. Furthermore smaller peaks of runoff can be observed during winter, when precipitation is high. High water demands occur during the summer months from October to March in order to supply agricultural plants. The highest water deficit is usually observed in January, when snowmelt declines and irrigation demand is at maximum. The hydrological cycle of the watershed is amended by human intervention, such as distributing the water from the main rivers to the irrigation areas by channel systems, which in turn leads to a reduced flow in the main rivers.

The hydropower energy supply is highly dependent on the water availability, which in turn is dependent on the seasonal variability. The main electricity production by hydropower peaks from December to February, while less is produced during the winter months. It can be concluded, that during the winter and spring months, when most water precipitates or melts, the reservoirs of the hydropower plants are filled. During the drought season in summer, water has to be released from the reservoirs in the watershed in order to provide the municipalities, industry and agriculture with enough water. The electricity production is situated directly at the water releasing point, so that the highest head can be used. High electricity demands occur during the winter months from April to September for heating purposes. Electricity deficits are avoided by electricity generation with gas, coal, oil or other fossil fuels.

57

Maipo Watershed Analysis Since the energy potential of the irrigation channels is not taken into account for energy conversion in a large extent, a special study was designed to quantify the potentials in the main irrigation area of the Maipo watershed, the Central Valley, which is presented in the following chapter.

58

Central Valley Analysis

10. Central Valley Analysis In order to quantify the energy potential of irrigation channels a special study was designed in the area of the Central Valley, one of the major irrigated areas of the Maipo watershed.

The Central Valley lies between the Andes and the Cordillera de la Costa. The analyzed area of the Central Valley lies within the Maipo watershed in Central Chile within the Metropolitan Region. Biggest parts of this region are used for agricultural cultivation and following this needs great amounts of water for irrigation purposes. Channels have been built in order to provide even the furthest areas of the rivers Maipo and Mapocho with potable water. This area is ideal to study the calculation and modelling of the energy potential of irrigation channels, as a high amount of irrigation channels can be found there (see Fig. 33).

Fig. 33: Overview of Channels in the Maipo Watershed (own compilation after data from Comisión Nacional de Energía Chile 2010)

59

Central Valley Analysis The settlements within this region are connected to local wastewater treatment plants in order to purify their wastewater and to afterwards discharge it again into the main streams nearby.

The area of investigation is marked red in Fig. 34. The study area is signified by a high amount of sold water rights (marked with brown dots) within the channel system area. The major municipalities Buin, Maipo, Melipilla, Paine, Peñalolén and Pomaire are surrounding the area, so that it can be concluded that the study area is used only for irrigation purposes for agricultural activities, as no bigger municipality is situated directly within it.

Fig. 34: Investigation area Central Valley (own compilation after data from Comisión Nacional de Energía Chile 2010)

60

Central Valley Analysis 10.1.

Energy potential of irrigation channels

In order to find out the water flows within each channel, data from the sold water rights and the location of the channels were compared. Water right owners have been assigned to the nearest channel, if no other possibility of water removal is traceable. In cases, where the water right owner could not be assigned to a channel without doubts, the distance to each channel beneath has been measured with the measuring tool of ArcGIS. The channel with the lowest distance has been taken as water removal site.

After the compilation of water rights to each channel, the water flows of each channel are summed up in order to calculate the hydropower energy potential of each channel. As the real slopes of each channel are not available, all channel height profiles are derived from the model in order to calculate the height differences every 70 meters. Based on these height differences, the hydropower energy potential is calculated with

Pgross = ρQghgross

[ J s or W]

(see 3)

with Pgross as the hydropower energy potential ρ as the water density (1,000 kg/m3) Q as the flow rate g as gravitational force 9.81 m/s2 and hgross as the height difference.

The energy potential of the irrigation channels in the research area within the Central Valley varies between 86.72 W and 284.98 MW, depending on the amount of water rights at each channel. According to the calculations, the highest energy potentials can be derived from the channels “El Paico” (93.19 MW), “San Antonio de Naltahua” (40.83 MW), “D Camperana” (31.32 MW), “San Jose Alto” (18.45 MW), “San Miguel” (18.12 MW) and “Lonquen Isla” (14.44 MW) (compare Tab. 18). As the real slopes of each channel are not available, they were derived from the DEM in the model.

61

Central Valley Analysis Tab. 18: Calculated Energy Potential of irrigation channels in the research area within the Central Valley Flow Rate Name Channel in W in kW in MW 3 [m /s] Aguilino 4.55 4,039,093.18 4,039.09 4.04 Arenal o Villita 0.67 28,285.61 28.29 0.03 Bustamante 3.62 266,522.54 266.52 0.27 Carampangue 16.40 511,401.97 511.40 0.51 Carmen Alto 0.55 1,844,302.23 1,844.30 1.84 Chacon 1.06 150,174.50 150.17 0.15 Chacra del Loa Poniente 13.32 453,761.86 453.76 0.45 Chico 5.74 2,846,006.20 2,846.01 2.85 Chinihue 10.40 2,653,878.90 2,653.88 2.65 Concreto 3.50 175,623.52 175.62 0.18 D 1 Chico 2.17 92,782.00 92.78 0.09 D 1 Grande 1.04 51,587.42 51.59 0.05 D 1 Huiticalan 0.30 51,674.37 51.67 0.05 D 1 Mercedano 0.48 11,224.37 11.22 0.01 D 1 Vinculano 0.42 26,782.54 26.78 0.03 D 2 Arenal o Villita 0.70 11,235.10 11.24 0.01 D 2 Doce 2.00 22,474.71 22.47 0.02 D 2 Grande 0.41 3,140.46 3.14 0.00 D 2 Tranque 0.38 5,834.01 5.83 0.01 D 2 Vinculano 0.17 7,128.08 7.13 0.01 D 3 Challacura 0.80 73,527.14 73.53 0.07 D 3 Huiticalan 2.70 34,925.76 34.93 0.03 D 3 Naltahua 7.66 1,284,409.08 1,284.41 1.28 D 4 San Antonio de Naltahua 11.82 787,920.38 787.92 0.79 D 5 San Antonio de Naltahua 12.20 465,646.76 465.65 0.47 D 6 Naltahua 0.30 7,980.83 7.98 0.01 D 7 Naltahua 0.20 3,032.86 3.03 0.00 D 7 San Antonio de Naltahua 1.94 43,387.20 43.39 0.04 D 8 San Antonio de Naltahua 9.50 217,833.99 217.83 0.22 D 9 San Antonio de Naltahua 0.40 17,034.08 17.03 0.02 D Camposano Quinta 86.90 5,293,359.95 5,293.36 5.29 D Caperana 45.59 31,317,776.61 31,317.78 31.32 D Carampangue 38.69 6,204,675.64 6,204.68 6.20 D El Monte 7.54 1,134,275.29 1,134.28 1.13 D El Triunfador 0.80 1,716,962.68 1,716.96 1.72 D La Cantera 17.50 1,487,495.20 1,487.50 1.49 D La Islita 51.21 5,305,671.92 5,305.67 5.31 D Las Pircas 26.50 1,981,401.24 1,981.40 1.98 D Santa Filomena Quinta 9.92 813,895.68 813.90 0.81 D Sitios El Triunfador 0.06 1,830.37 1.83 0.00 D Sta Adriana 6.69 403,094.37 403.09 0.40 D Tronco Huelemu 0.15 36,967.46 36.97 0.04 D Valdiviano Quinta 36.55 5,517,667.17 5,517.67 5.52 Diez y Nueve 1.75 347,213.70 347.21 0.35 El Paico 37.45 93,189,650.12 93,189.65 93.19 El Vergel 1.71 103,094.35 103.09 0.10 Grande 1.15 136,998.18 137.00 0.14 Huiticalan 1.50 86,968.59 86.97 0.09

62

Central Valley Analysis Flow Rate 3 [m /s] La Playa 0.70 Las Manresas 3.45 Lo Aguirre 31.15 Lo Valdes Chancho 13.97 Lonquen Isla 39.61 Los Chanchos 6.03 Mercedano 5.80 Naltahua 2.70 Rosario 5.30 San Antonio de Naltahua 17.93 San Jose Alto 8.46 San Jose Dos 3.51 San Miguel 12.36 SD 2 A Vinculano 0.20 SD 2 C Tranque 6.86 SD 3A Naltahua 0.40 SD 3B Naltahua 0.20 SD 3E Naltahua 0.05 SD 3L Naltahua 4.50 SD 4A San Antonio Naltahua 2.28 SD 4B Dos San Antonio de Naltahua 4.10 SD 5A San Antonio de Naltahua 2.97 SD 7A Naltahua 0.40 SD 7B Naltahua 1.30 SD 8A San Antonio de Naltahua 0.20 SD 9A San Antonio de Naltahua 0.20 SD El Pueblo 15.05 SD Eucaliptus 6.33 Silverio 9.00 Trebulco 1.76 Treinta y Tres 0.77 Vinculano 7.08 Name Channel

Total

in W 7,921.77 403,409.52 5,241,700.59 709,026.16 14,444,970.17 430,110.92 216,502.58 2,310,265.01 3,376,617.79 40,831,518.88 18,451,777.96 363,589.43 18,122,785.52 3,329.12 328,077.65 16,941.48 4,346.42 199.09 74,825.78 38,775.08 150,044.44 53,936.01 4,530.26 86.72 6,652.55 3,637.74 845,197.20 627,691.93 286,968.99 266,312.33 180,493.59 5,911,138.28

in kW 7.92 403.41 5,241.70 709.03 14,444.97 430.11 216.50 2,310.27 3,376.62 40,831.52 18,451.78 363.59 18,122.79 3.33 328.08 16.94 4.35 0.20 74.83 38.78 150.04 53.94 4.53 0.09 6.65 3.64 845.20 627.69 286.97 266.31 180.49 5,911.14

in MW 0.01 0.40 5.24 0.71 14.44 0.43 0.22 2.31 3.38 40.83 18.45 0.36 18.12 0.00 0.33 0.02 0.00 0.00 0.07 0.04 0.15 0.05 0.00 0.00 0.01 0.00 0.85 0.63 0.29 0.27 0.18 5.91

701.68 284,980,991.12 284,980.99 284.98 Red colour marks the channels with the highest calculated energy potentials Source: Author

Sites for possible hydropower plants can be seen in the height profiles for each channel, high inclinations signify potential sites for hydropower plants and high energy potential. The following figures (Fig. 35- Fig. 40) show examples of height profiles from those channels with the highest calculated energy potentials.

63

47 5. 0 9 98 08 8. 95 7 14 07 31 97 18 .98 50 67 22 .56 64 86 27 .35 25 59 31 .71 94 81 37 .70 57 08 42 .53 00 27 46 .90 53 74 51 .57 32 93 56 .47 38 16 61 .54 38 33 65 .00 78 17 .8 70 27 12 1 75 .7 21 96 78 .49 89 95 82 .40 41 16 .6 86 47 27 3 90 .3 24 36 .0 19 1

Height [m]

Length [m]

Fig. 37: Height Profile Channel Lonquen Isla (14.44 MW)

64

Length [m]

Fig. 36: Height Profile Channel El Paico (93.19 MW)

Height Difference Channel Lonquen Isla

25

20

15

10

5

0

19648

18821

17963

17016

16124

15273

14441

13602

12793

11781

10846

9789

8885

7868

6931

6130

5253

4333

3398

2513

1603

800.6

0

Height [m] 24 2. 0 9 53 017 8. 7 1 85 923 0. 3 4 11 930 83 8 . 14 725 98 3 18 .74 05 13 . 20 705 71 5 23 .415 57 1 26 .560 24 3 . 29 994 16 2 . 32 101 17 8 35 .179 47 8 38 .69 78 38 .2 42 079 08 45 .72 08 2 . 47 088 34 6 50 .198 14 3 53 .875 03 4 . 55 033 88 8 .6 52 7

Height [m]

Central Valley Analysis

Height Profile D Caperana

30

25 20

15

10 5

0

Length [m]

Fig. 35: Height Profile Channel D Caperana (31.32 MW) Height Profile El Paico

35

30

25

20

15

10

5

0

Central Valley Analysis

Height Profile San Antonio de Naltahua 35

Height [m]

30 25 20 15 10 5 17034

17767

18597

37651

39349

16287

35810

15523

14788

13974

13106

12256

11444

10550

9727

8756

7936

7039

6134

5149

4290

3497

2569

1703

794.2

0

0

Length [m]

Fig. 38: Height Profile Channel San Antonio de Naltahua (40.83 MW)

33894

32117

30451

28770

27010

25390

23616

22013

20241

18428

16667

14815

12925

11267

9339

7350

5393

3536

1704

20 18 16 14 12 10 8 6 4 2 0 0

Height [m]

Height Profile San Jose Alto

Length [m]

Fig. 39: Height Profile Channel San Jose Alto (18.45 MW)

Height Profile San Miguel 30

20 15 10 5

Length [m]

Fig. 40: Height Profile Channel San Miguel (18.12 MW)

65

15417

14712

13967

13250

12491

11861

11154

10490

9716

8959

8281

7650

7035

6394

5732

4989

4345

3586

2789

2116

1406

717

0 0

Height [m]

25

Central Valley Analysis 10.2.

Technical Possibilities for hydropower energy generation

According to the results of the energy potential in chapter 10, it can be concluded, that mainly mini-hydropower plants should be used for the energy conversion in irrigation channels. This conclusion is based on the fact, that the amounts of water led through the channels is varying during the year, depending on the occurring precipitations in winter and snow melts in summer. Several turbines are available for energy conversion from hydropower, as there are e.g. Pelton turbines, Kaplan turbines or Francis turbines, which are used mainly for large hydropower plants generating more than 2 MW. The following table gives an overview of the most often used turbines and explains their advantages and disadvantages (Tab. 19).

Tab. 19: Advantages and disadvantages of hydropower turbines for small hydropower (< 100 kW) Max. Efficiency Turbine Type Advantages Disadvantages % Efficiencies between 70Crossflow Turbine Specific speed of 40-200 80% are lower than those (Michell-Bánki or 85 obtained by varying only of Pelton, Francis and Ossberger Turbine) the width. Turgo. Manufacturing standard A relatively low efficiency Francis Turbine 95 available from various at partial loads. manufacturers Bulb and tube types offer High velocities of Kaplan Turbine 95 advantages when applied overspeeding to existing dams Requires multiple Erosion damages are easily Pelton Turbine 92 injectors to cope with repaired large volumes Application range similar Large axial loads s / Turgo Turbine 90 to the multi-injector Pelton bearings. Turbine (own compilation after Centro de Demonstración y Capacitación en Tecnologías Apropiadas 2008)

Pelton and Turgo turbines are mainly used for huge height differences and small water flows, while Kaplan, Helix and Archimedes' screw is used for small height differences and high water flows. River turbines are used, if no height difference can be observed. Medium height differences and water flows are used by crossflow turbines, Francis turbines, pumps used as turbines and Pelton turbines with multiple injectors. An overview about the usage of each turbine is shown in Fig. 41.

66

Central Valley Analysis H (m)

-Pelton -Turgo

Physical altitude (or static)

0 Dynamic Altitude

Big altitudes and small water flows

-Crossflow -Francis turbine -Pumps like turbines -Pelton with multiple injectors

Medium altitudes and medium water flows

-Kaplan -Helix -Archmedes‘ Screw

Small altitudes and big water flows

-River turbines

„zero altitude“ Q (m3/s)

Fig. 41: Application of the different turbines according to height and water flow (Centro de Demonstración y Capacitación en Tecnologías Apropiadas 2008, p.4)

Fig. 42 shows the areas of application according to the net head and water flow of the most important turbines used for energy conversion from hydropower. As it can be seen, the minimum net head has to be at least 3 m in order to be able to use either the Bánki Turbine or the Kaplan Turbine. Which one to choose is depending on the flow rate available, with which the turbine has to work with. According to the results of the flow rate and the mean slopes (over the whole channel), no turbine could be used for energy conversion, as all correlations between the mean slope and the flow rate are below the minimum net head of 3 m, although (compare Fig. 42 and Fig. 43).

Fig. 42: Application areas of the different turbines according to the net head and water flow (x-axis: water flow, y-axis: net head) (Centro de Demonstración y Capacitación en Tecnologías Apropiadas 2008, p.22)

67

Central Valley Analysis

Distribution of channel characteristics mean slope 1

Mean Slope [m]

0,1

0,01

0,001

0,0001 0,01

0,10

1,00

10,00

100,00

Flow Rate [m3/s]

Fig. 43: Distribution of channel characteristics according to Fig. 42 (Source: Own compilation)

That’s why it has to be looked at the maximum slopes of each channel, as these places would be the sites for hydroelectric power generation. In Fig. 44 the new distribution of the channel characteristics based on the maximum slopes has been developed. The red line marks the minimum slope for using any kind of turbine mentioned in Fig. 42.

Distribution of channel characteristics maximum slope 100.00

Max Slope [m]

10.00 1.00 0.10 0.01 0.00 0.01

0.10

1.00

10.00

100.00

Flow Rate [m3/s]

Fig. 44: Distribution of channel characteristics with maximum slopes according to Fig. 42 (Source: Own compilation)

As it can be seen, several sites of the channels are within the range for the application of turbines. Those channels, having a flow rate between 1 and 9 m3/s and a maximum slope

68

Central Valley Analysis between 11 and 100 m could use a Bánki or Kaplan Turbine for electricity generation. Those channels with a flow rate around 10 m3/s and a maximum slope around 10 m could either use the Kaplan or the Francis Turbine. Channels with flow rates over 50 m3/s and less than 7 m of slope can’t use any turbine anymore, as this is outside of the range of the turbines. Another possibility in order to generate electricity with the channels would be the installation of water vortex power plants. The problem of this power plant is that the channels would have to be changed in their construction in order to implement it.

10.3.

Interpretation of Results

The study presented above determined, that the energy potential of the 81 irrigation channels in the study area is in total 284.98 MW. This value results from the given water rights in the Central Valley, taking into account an area of a high density of water rights owners (see Fig. 34). As most of the channels only have a low slope, it does not make sense to install any hydropower turbine, as the combination of water flow and slope would not lie within the operating area of them. One possibility to implement hydropower turbines would be to artificially increase the slope by splitting up a part of the channel and return the water amounts into the same channel further down (diversion plant). This kind of plant is used in the channel “Mallarauco”, which is situated near the Cordillera de la Costa further north of the study area in the Central Valley. Water vortex power plants seem to be an alternative to the conventional turbines, although the channel has to be modified. Probably the costs for modifying the channel in order to construct this kind of power plant would be higher than what could be earned in form of energy, so that the project would not be economically. It is assumed, that in the other irrigation areas in the Maipo Watershed it is possible to gather a similar energy potential. This assumption is based on the fact that the other irrigation sectors of the rivers Maipo and Mapocho show a high channel distribution pattern with similar slopes. A region which is significantly different from the conditions of the research area in the Central Valley is the upper section of the Mapocho watershed since there is no close irrigation channel system available.

69

Discussion and Recommendations

11. Discussion and Recommendations 11.1.

Water-Energy Balance

It is not possible to describe the Water-Energy Balance completely for the Maipo Watershed. Data about the water demand for the energy sector is not available, although there are only two electrical power plants located within the watershed, not working as hydroelectric power plants. It is recommended to investigate the water demand for the energy sector not only based on the power plants located within the watershed, but also for the energy “imported” from other regions of Chile into the Metropolitan Region transported by the SIC-System. The electricity mix of the Chilean electricity market should be analysed in a more precise way than it was possible during this study.

The energy demand of the water sector can be narrowed to three main energy users: Wastewater treatment plants, irrigation and production of potable water. Most irrigation is done with the help of gravitational forces without the need of pumps for the distribution. In contrast to superficial irrigation, water use of subterranean aquifers needs energy, respectively electricity, for pumping water from the well up to where it is needed. Depending on the used pump and the height difference between the water level in the well and the place of destination, energy demand can be high or low. The production of potable water is, like the treatment of wastewater, often associated with the use of chemical, physical or biological procedures, which need energy in order to be performed. As the specific use of energy for pumping water is not yet investigated, it is recommended to look at the main users of subterranean water in order to create a cadastre of energy use for pumping. Furthermore, continuous daily monitoring of the wells is recommended. The available monitoring data from the water levels of the wells is deficient and proper time series could not be produced for the model in Mike Basin, as no pattern of seasonal dependency could be observed. Moreover, some wells have been emptied within a short time without any remark, why the water level fell so fast.

70

Discussion and Recommendations The investigation of the energy potential on water basis has been completed successfully. The huge amount of hydropower plants in the watershed shows that the electricity generation with water is exhausted at the superficial river reaches. Locations with big height differences are used for hydropower plants, as long as it is possible to construct one at this point. In contrast, the energy potentials of irrigation channels are not yet exhausted. Reason for this is possibly the low energy potential, lying below the technical limits of hydropower turbines used for electricity generation. However, it is recommended to investigate the energy potentials of irrigation channels with respect to the construction of split channels in order to increase the net head. The energy potentials should rise and it would be possible to generate electricity. Furthermore, a cost-benefit analysis for these modifications of the irrigation channels should be created. It could happen that a construction like described before is economically not viable due to the amount of electricity produced and the incurred costs for construction and maintenance.

The water potential on energy basis is not available in the study area, as most of the water comes from the superficial river reaches. The region managed to cope with the changes of the water amounts by using natural as well as artificial reservoirs. Desalination plants are not used for water production, respectively water treatment of sea water, because most of the water users are located far inside the country. Desalination plants could be a solution for the future, when climate change will lead to less occurring precipitation and the glaciers in the Andes are melting away. Without this natural filling up of the rivers, reservoirs, the groundwater level and the wells it could become problematic to meet the needs of water demand. It is recommended to develop a model to look at the future climate change impacts in order to start investigating into technologies like desalination plants in order to be able to supply the demand in the future.

11.2.

Technical Possibilities for hydropower energy generation

According to the results of the energy potential and the implementation of hydropower turbines in chapter 10, it can be concluded that in most cases it is not possible to convert the energy potential of the channel into electricity. Very often this is caused by the low

71

Discussion and Recommendations gradients of the channels, so that electricity generation would only be possible by customisation of the channels in order to increase artificially the gradients. Economically not worthwhile is the construction of diversion plants or water vortex power plants in comparison to the possible amount of generated electricity in most of the irrigation channels. They have to be modified heavily in order to operate these power plants. This could cause financial problems, caused by the construction costs for modifying the channel and the implementation of the turbines. Further costs arise for maintenance and energy storage devices, as long as there is no grid connection available or useful. Additionally, costs for irrigation come to pass, when the channel has to be drained in order to work on the construction of the before mentioned power plants.

Direct measurements of the water flows within the channels are recommended, since the data used for this thesis is based only on the distributed water rights. These data is based on the water flow, which is allowed to be taken out of the channel without taking into account the water demand over the year. Furthermore, data of the channel dimensions like height, width and water level variation should be investigated, as it was difficult to gather all necessary data without directly knowing from the beginning, which person from which institution is capable to hand out these data.

11.3.

Possibility of integration of “Energy Users” in Mike Basin

Based on personal information from DHI it is already possible to calculate the energy potential with the help of Mike Basin and Mike 11. Irrigation channels can be modelled with Mike 11, including the channel dimensions and slopes. The channels would not be treated like traced rivers, but as channels, if all necessary data like heights, widths and slopes are available. In order to calculate the energy potentials within the channels, it is possible to use the node “Hydropower” (Danish Hydraulic Institute 2010, pp.25–31). The so-called “Power Demand Time Series” is necessary for the calculations of the energy potential. To create this time series, four items have to be included into it: 1. Target power demand: Can be power in MW (or equivalent) or discharge (water flow) in m3/s.

72

Discussion and Recommendations 2. Installed capacity: Only necessary, if “use surplus capacity” is checked and should be investigated. Furthermore it can be power in MW (or equivalent) or discharge (water flow) in m3/s. 3. Surplus capacity: Fraction between 0 and 1 without using dimensions. 4. Minimum head for operation of turbines: If the difference between reservoir level and tail water level (head) is below this value, the turbines are not working, as no water will be routed to them. Furthermore, parameters like target power, tail water level, machine efficiency and the installed capacity have to be specified for the hydropower scheme, as well as so-called “Operation Rules” to add time series (e.g. Power Demand Time Series) (Danish Hydraulic Institute 2010, p.31).

This means, that a node “Energy User” would not be necessary, specifically for hydropower potential calculations, as it is already possible to calculate them. Nevertheless, it would be interesting to create such a node, in order to get an overview of energy users within a watershed. Further interesting could be the integration of energy use based on water into the node “Water User”. Energy usage for heating, treating or pumping water could be shown in an additional graph over space and time.

It is recommended to model the energy potential like it is described by DHI in order to compare the result data in this thesis with the results achieved by Mike Basin. Necessary for this are more data about the channel dimensions, the water level variations within the channels during the year as well as more precise data of the flow rate within the channels.

73

References

12. References Anderer, P. et al., 2010. Vom Linienpotenzial zum technischenWasserkraftpotenzial – Methode. WasserWirtschaft, (9-2010), pp.17-22. Banzhaf, E. et al., 2011. How Sustainable is Santiago de Chile? Current Performance – Future Trends – Potential Measures, Helmholtz-Centre for Environmental Research – UFZ. Available at: http://www.ufz.de/data/ufz_report_en_4_2010_14286.pdf [Accessed March 30, 2011]. Bartosch, A., 2007. Die Wasserversorgung in einer Metropolregion in Lateinamerika - Das Beispiel Santiago de Chile. Diplomarbeit. Jena: Friedrich-Schiller-Universität Jena. Bauer, C.J., 1998. Slippery Property Rights: Multiple Water Uses And The Neoliberal Model In Chile, 1981-1995. Natural Resources Journal, 38(109), pp.118 - 122. Becker, G.S., 1997. Latin America Owes a Lot to Its “Chicago Boys.” BusinessWeek. Botschaft der Republik Chile in Deutschland, 2011. Landesstruktur. Botschaft der Republik Chile in Deutschland. Available at: http://www.embajadaconsuladoschile.de/index.php?option=com_content&view= article&id=53&Itemid=138&lang=de [Accessed January 30, 2011]. Cai, X., Ringler, Claudia & Rosegrant, Mark W., 2006. Modeling Water Resources Management at the basin Level, Washington, D.C.: IFPRI - International Food Policy Research Institute. Available at: http://www.ifpri.org/sites/default/files/pubs/pubs/abstract/149/rr149.pdf [Accessed February 2, 2011]. Cai, X., Ringler, Claudia & Rosegrant, Mark W., 2001. Does Efficient Water management Matter - Physical and Economic Efficiency of Water Use in the River Basin, Washington, D.C.: International Food Policy Research Institute. Available at: http://www.bvsde.paho.org/bvsacd/cd27/paper72.pdf [Accessed March 24, 2011]. Capurro, C., 2010. Chile - Power Generation. Available at: www.buyusa.gov/chile/en/189.pdf. Cariola, E.C. & Alegria, M.A., 2004. Análisis del proceso de privatización de los sistemas de agua potable y saneamiento urbanos en Chile. Revista de Gestion del Agua de America Latina, 1(2), pp.65 - 85. Available at: http://www.eclac.org/drni/noticias/documentosdetrabajo/5/24325/Rega2.pdf [Accessed March 14, 2011]. Castor y Polux Ltda., 2011. Relieve: Región Metropolitana, Available at: http://mapasdechile.com/relieve_region_metropolitana/index.htm [Accessed March 23, 2011].

I

References CDEC-SIC, 2011. Operation statistics years 2001-2010. Available at: https://www.cdecsic.cl/datos/anuario2011_ing.pdf [Accessed August 31, 2011]. Central Energía, 2011. Legislación eléctrica. Central Energía. Available at: http://centralenergia.cl/regulacion/legislacion-electrica-chile/ [Accessed March 7, 2011]. Central Intelligence Agency USA, 2011. CIA - The World Factbook -- Chile. Available at: https://www.cia.gov/library/publications/the-world-factbook/geos/ci.html [Accessed May 19, 2010]. Centro de Demonstración y Capacitación en Tecnologías Apropiadas, 2008. EQUIPO ELECTROMECANICO. Chilectra, 2011. Consumo Mensual para Plantas de Tratamiento de Aguas y Consumo Agrícola. Clough, L.D., 2008. Energy profile of Chile, www.eoearth.com. Available at: http://www.eoearth.org/article/Energy_profile_of_Chile. Comisión Nacional de Energía Chile, 2010. CNE - Comisión Nacional de Energía. Available at: http://www.cne.cl/cnewww/opencms/. Comision Nacional de Riego, 2009. Informe Final. CONAMA Nacional, 2007. Resumen Diagnóstico Ambiental. Recursos Hidricos en la Región Metropolitana de Santiago, Available at: http://www.sinia.cl/1292/articles39509_pdf_agua.pdf [Accessed March 24, 2011]. Danish Hydraulic Institute, 2010. 2_MIKEBASIN_OperatingFramework.pdf. Deutsche Gesellschaft für Technische Zusammenarbeit, 2010. Non-Conventional Renewable Energy in the Chilean Electricity Market. Dirección General de Aguas, 2011. Departamento de Hidrología. Available at: http://dgasatel.moptt.cl/ [Accessed September 6, 2011]. Dirección General de Aguas, 2004. Diagnostico y clasificación de los cursos y cuerpos de agua según objetivos de calidad - Cuenca del Río Maipo, Dirección General de Aguas. Available at: http://www.sinia.cl/1292/articles-31018_Maipo.pdf [Accessed January 30, 2011]. Dixon, D., 2007. Assessment of Waterpower Potential and Development Needs, Palo Alto , California USA: Electric Power Research Institute. Available at: http://www.aaas.org/spp/cstc/docs/07_06_1ERPI_report.pdf [Accessed April 3, 2011]. Energy Information Administration, 2008. International Energy Review Annual 2006. Food and Agriculture Organization of the United Nations, 2010. AQUASTAT - Sistema de

II

References Informacion sobre el Uso del Agua en la Agricultura de la FAO. Available at: http://www.fao.org/nr/water/aquastat/countries/chile/indexesp.stm [Accessed January 30, 2011]. Fthenakis, V. & Kim, H.C., 2010. Life-cycle uses of water in U.S. electricity generation. Renewable and Sustainable Energy Reviews, 7(14), pp.2039-2048. Available at: http://j.mp/Water_LCA. Gesellschaft für Technische Zusammenarbeit, 2007. Energiepolitische Rahmenbedingungen für Strommärkte und erneuerbare Energien - Kapitel Chile. Global Energy Observatory, 2011. Current List of Hydro Power Plants. Available at: http://globalenergyobservatory.org/list.php?db=PowerPlants&type=Hydro [Accessed March 31, 2011]. Gobierno de Chile Ministerio de Obras Publicas Dirección General de Aguas, 2006. Modelación superficial para la cuenca de los ríos Maipo Mapocho. Government of Chile, 1981. Código de Aguas 1981, Guzowski, C. & Recalde, M., 2010. Latin American electricity markets and renewable energysources: The Argentinean and Chilean cases. Hamhaber, P.D.J., 2010. Lecture: Energy Economics, Markets and Society. Harvey, A., 2009. Micro-Hydro Design Manual - A guide to small-scale water power schemes 7th ed., Warwickshire, United Kingdom: Practical Action Publishing. Hoffman, D.A.R., 2009. The Connection: Water Supply and Energy Reserves. Available at: http://www.waterindustry.org/Water-Facts/world-water-6.htm [Accessed March 31, 2011]. Hurdus, A., 2001. The Water-Energy Nexus: Opportunities for integrated Environmental Management. Available at: http://www.usaid.gov/our_work/environment/water/enviro.notes/enviro.notes. water-energy.pdf [Accessed January 16, 2011]. Instituto Nacional de Estadísticas, 2008. Anuario Estadístico Sector Eléctrico 1999-2002, 2003, 2004, 2005, 2006, 2007, 2008. Available at: http://www.ine.cl/canales/chile_estadistico/estadisticas_economicas/energia/an uarios_estadisticos/anuarios.php [Accessed July 6, 2011]. Instituto Nacional de Estadísticas, 2007. Censo Agropecuario 2007- Resultados por Comunas. Available at: http://www.ine.cl/canales/chile_estadistico/censos_agropecuarios/censo_agrope cuario_07_comunas.php. Instituto Nacional de Estadísticas, 2010. Estadísticas del Medio Ambiente 2008, Santiago de Chile.

III

References Intergovernmental Panel on Climate Change (IPCC), 2007. Summary for Policymakers, Cambridge, United Kingdom and New York, NY, USA: Intergovernmental Panel on Climate Change (IPCC). Available at: http://www.pnud.cl/recientes/IPCCReport.pdf [Accessed April 2, 2011]. Jones, W.D., 2008. How Much Water Does It Take to Make Electricity? ieee spectrum, April 2008. Available at: http://spectrum.ieee.org/energy/environment/howmuch-water-does-it-take-to-make-electricity [Accessed March 31, 2011]. Mentor, Jr., J., 2001. Trading Water, trading Places: Water Marketing in Chile and the Western United States. Available at: http://www.awra.org/proceedings/dundee01/Documents/Mentor.pdf [Accessed March 13, 2011]. Meza, F.J., 2003. ENSO EFFECTS ON REFERENCE EVAPOTRANSPIRATION (ETo)AT THE MAIPO RIVER BASIN, CHILE. Available at: http://www.google.com/url?sa=t&source=web&cd=2&ved=0CCwQFjAB&url=http %3A%2F%2Fams.confex.com%2Fams%2Fpdfpapers%2F68893.pdf&rct=j&q=evapo transpiration%20santiago%20chile&ei=rIlwTuH9JsZOrD5iaQJ&usg=AFQjCNHJtiO7Wo7cAq8g0Yo2e82Sh5IAYA&sig2=veO0gh6sx6ecS bN929EiIQ&cad=rja [Accessed April 13, 2011]. Ministerio de Energía, 2011. Generación Bruta Sic_Sing 1996-2011. Molina C., J.D., Martinez A., V.J. & Rudnick, H., 2010. Technological impact of NonConventional Renewable Energy in the Chilean Electricity System. Available at: http://web.ing.puc.cl/~power/paperspdf/ICIT2010.pdf [Accessed March 13, 2011]. Nauditt, A., Ribbe, L. & Gaese, H., 2002. Wasserressourcenmanagement in Chile. Technology Resource Management & Development - Special Issue: Water Management, 2, p.19. Available at: http://www.tt.fhkoeln.de/publications/ittpub301202_5.pdf [Accessed March 8, 2011]. Neary, D.G. & Garcia-Chevesich, P., 2008. Climate Change Impacts on Municipal, Mining,and Agricultural Water Supplies in Chile, Arizona. Available at: http://www.fs.fed.us/rm/pubs_other/rmrs_2008_neary_d002.pdf [Accessed March 29, 2011]. Nischler, G. et al., 2011. GIS-basierte Potenzialanalyse der Wasserkraft. In 7. Internationale Energiewirtschaftstagung an der TU Wien. Wien, Austria, p. 16. Available at: http://www.eeg.tuwien.ac.at/eeg.tuwien.ac.at_pages/events/iewt/iewt2011/uplo ads/fullpaper_iewt2011/P_306_Nischler_Gernot_31-Jan-2011,_17:04.pdf. Ocean Thermal Energy Corporation, 2011. Potable Water Production. Available at: http://www.otecorporation.com/index.php/potable_water_production.html [Accessed April 5, 2011]. Pace Energy and Climate Center, 2000. Consumption of Water Resources, White Plains,

IV

References New York: Pace University. Available at: http://www.powerscorecard.org/issue_detail.cfm?issue_id=5. Pacific Institute, 2005. 100 Largest Desalination Plants Planned, in Construction, or in Operation - January 1, 2005. Available at: http://www.worldwater.org/data20062007/Table21.pdf [Accessed April 5, 2011]. Pacific Institute, 2006. Desalination, With a Grain of Salt, Oakland, California. Available at: www.pacinst.org/reports/desalination [Accessed April 5, 2011]. Paz Aedo, M., 2009. Wasser, Demokratie und Menschenrechte: das chilenische „Modell“. Procivil Ingeniería Ltda., 2007. Estimación Potencial Hidroeléctrico Asociado a Obras de Riego Existentes o en Proyecto - Resumen de Resultados, Santiago de Chile, Chile: CNE & CNR. Ramboll, K.N., 2006. Ocean Energy EC contractors’ meeting. Available at: http://ec.europa.eu/research/energy/pdf/gp/gp_events/ocean_energy/0940_coordinated_action_on_ocean_energy_en.pdf [Accessed March 31, 2011]. Rosegrant, M.W. et al., 2000. Integrated Economic-Hydrologic Water Modeling at the Basin Scale: The Maipo River Basin, Washington, D.C.: International Food Policy Research Institute. Available at: http://www.ifpri.org/sites/default/files/publications/eptdp63.pdf [Accessed March 24, 2011]. Rubio, E., 2008. Anexo Cuenca Maipo. Sauvet-Goichon, B., 2006. Ashkelon desalination plant - A successful challenge. Available at: http://www.desline.com/articoli/8020.pdf [Accessed April 5, 2011]. Schröder, U., 2009. Erhebung des Kleinwasserkraftpotentials inder Schweiz. Simon, L.M., 2009. Die „Nachhaltigkeitsperformance" der Wasser- und Sanitärversorgung in Santiago de Chile. Eine politisch-geographische Untersuchung. Sociedad Eléctrica Santiago S.A., 2008. Eléctrica Santiago. Available at: http://www.electricasantiago.cl/electricasantiagowebneo/index.aspx?channel=61 48 [Accessed September 1, 2011]. Superintendencia de Servicios Sanitarios, 2009. Informe de gestión del sector sanitario 2008. Available at: http://www.siss.cl/articles-3687_informegestion.pdf [Accessed March 14, 2011]. Superintendencia de Servicios Sanitarios - Gobierno de Chile, 2011. Cumplimiento de planes de desarrollo. Available at: http://www.siss.gob.cl/577/w3-propertyvalue3526.html [Accessed September 3, 2011]. The Ashden Awards, 2011. Micro-hydro. Available at: http://www.ashdenawards.org/micro-hydro.

V

References Thirlwell, G.M., Madramootoo, C.A. & Heathcote, I.W., 2007. Energy-water Nexus: Energy Use in theMunicipal, Industrial, and Agricultural Water Sectors. Available at: http://www.policyresearch.gc.ca/doclib/Thirlwell_energy_water_nexus.pdf [Accessed April 2, 2011]. TU Braunschweig, 2004. Landschaftszonen-Exkursion 2003 - Brasilien, Paraguay, Chile und Argentinien, Braunschweig: Technische Universität. Available at: http://www.tubraunschweig.de/Medien-DB/geooekologie/index.html [Accessed November 12, 2010]. U.S. Department of Energy, 2007. Energy Demands on Water Resources, U.S. Department of Energy. Available at: http://www.sandia.gov/energy-water/docs/121RptToCongress-EWwEIAcomments-FINAL.pdf. UN Water, 2009. Water in a Changing World, Paris, France and London, United Kingsdom: UNESCO. Wikipedia, 2011. Chicago Boys. Wikipedia. Available at: http://en.wikipedia.org/wiki/Chicago_Boys. World Economic Forum, 2011. Global Risks 2011. Available at: http://www.oliverwyman.com/ow/pdf_files/Global_Risks_2011.pdf [Accessed January 24, 2011]. World Meteorological Organization, 2011. World Weather Information Service - Santiago. Available at: http://worldweather.wmo.int/028/c00103.htm [Accessed June 17, 2011]. www.climate-zone.com, 2004. Climate information for Chile - Climate Zone. Climate information for Chile. Available at: http://www.climate-zone.com/climate/chile/ [Accessed January 30, 2011]. Zawya Projects, 2011. DEWA - Jebel Ali M Station - Desalination Plant, Available at: http://www.zawya.com/middleeast/projects/project.cfm/pid110307063924/DEWA%20%20Jebel%20Ali%20M%20Station%20-%20Desalination%20Plant.

VI

Annex

13. Annex Annex 1: List of Institutions and Contact Persons in Chile Institution

Contact Person

Date

DGA

Andrea Osses Vargas

07.04.2011

Ingeniería Alemana S.A.

Joachim Vogdt

07.04.2011

Universidad de Chile

Ximena Vargas

20.04.2011

Aguas Andinas S.A.

Carlos Berroeta

28.04.2011

Sociedad Nacional de Agricultura

Ema Budinich

03.06.2011

CNR

Marcial Gonzalez

06.06.2011

Chilectra

Guillermo Pérez del Río

07.06.2011

DOH

Reinaldo Fuentealba

13.06.2011

DOH

Eduardo Santibáñez

14.06.2011

DOH

José Luis Larroucau

14.06.2011

SMAPA

Iván Aranda Saldaña

15.06.2011

CNR

Gaston Sagredo

Sociedad del Canal de Maipo

Orlando Peralta

Junta de Vigilancia Río Mapocho

Manuel González Hernández

21.06.2011 02.06.2011; 23.06.2011 24.06.2011

Junta de Vigilancia Río Mapocho

Roberto Araya

Universidad de Chile

James McPhee

Universidad de Chile

José Marin

28.06.2011 08.04.2011; 29.06.2011 30.06.2011

Universidad de Chile

Marcelo Olivares

30.06.2011

SISS

Gabriel Zamorano

01.07.2011

Junta de Vigilancia Río Maipo

Javier Carvallo

05.07.2011

VII

Annex Annex 2: Energy Laws Chile Since 1981 several laws and regulations have been implemented into the Chilean electricity sector, which led to the privatisation of the governmental electricity suppliers. Until now, the government, represented by the National Energy Commission (CNE), has a regulatory and controlling function, although an indicative plan of works (Plan indicativo de obras) is prepared annually for the expected expansion of power plants based on demand analysis. This plan is an instrument to define the prices but there is no duty to implement it (Gesellschaft für Technische Zusammenarbeit 2007). The following five laws represent the key elements of the regulatory framework in the Chilean electricity sector.

Law Decree No. 4, General Law of Electricity Services (LGSE) This law decree has been enacted on May 12th, 2006 by the Ministry of Economy, Development and Reconstruction, “that establishes the consolidated, coordinated and systematized text of Law Decree No. 1, dated 1982, General Law of Electricity Services (LGSE), on electricity matters” (Deutsche Gesellschaft für Technische Zusammenarbeit 2010). It regulates the production, transportation, distribution, concessions and electricity tariffs.

Law 19.940 (Short Law I) This law has been published on March 13th, 2004. It amends the General Law of Electricity Services with the primary objective of regulating the decision making and the development of the expansion of electricity transmission (Central Energía 2011; Deutsche Gesellschaft für Technische Zusammenarbeit 2010).

It is designed to allow smaller energy producers to connect to the national grid. The law assured small producers the right to sell energy at node, or market prices. The law fully or partially released renewable energy producers from paying transmission tolls on surpluses under 20 MW.

VIII

Annex Law 20.018 (Short Law II) This law has been enacted on May 19th, 2005 by the Ministry of the Economy, Development and Reconstruction. This law is the result of an uncertainty over the availability of Argentinean natural gas hindering the estimations of future prices and revenue levels from electricity sales. It also establishes incentives for technologies for the generation of electricity from nonconventional renewable energies while supporting also small medium sized plants (Central Energía 2011; Deutsche Gesellschaft für Technische Zusammenarbeit 2010). It obligates generators to receive an increasing share of their energy from renewable sources. Furthermore, it concludes that new energy generation contracts must incorporate a 5% share of energy from renewable sources starting in 2010, with possible fines in place from 2014 onwards. The quota of renewable energy will then increase starting in 2014 by 0.5% each year until 2025, when generators must secure that 10% of their power is generated through renewable sources.

Law 20.257 (Non-Conventional Renewable Energies Law) This law has been enacted on April 1st, 2008 and modifies the LGSE regarding the generation of electricity using non-conventional renewable sources In this new law, those firms which commercialize more than 200 MW, both in the SIC and the SING, are constrained to show a share of NRES out of the total of electricity traded (Deutsche Gesellschaft für Technische Zusammenarbeit 2010; Guzowski & Recalde 2010; Central Energía 2011).

Law 20.220 to Safeguard the Security of Supply to Regulated Customers and the Adequacy of Electricity Systems This law has been enacted on September 14th, 2007. It modifies the LGSE with respect to safeguarding the security of supply to regulated customers and the adequacy of electricity systems. It considers court action for termination of contracts and bankruptcy of

companies

(Central

Energía

2011;

Deutsche

Gesellschaft

für

Zusammenarbeit 2010).

IX

Technische

Annex Annex 3: Water Rights Chile

There is one main law existing in Chile dealing with water rights: The Water Codex (Código de Aguas), which is based on the Water Codex from 1981 (Nauditt et al. 2002). It declares that water is a public property and that the state can grant private rights of usage (Bauer 1998).

Further key features of the Water Codex are (Government of Chile 1981): •

the judicial separation of water rights and land ownership,

•

the recording of all water rights and transactions of the Water Cadastre under the Water Directorate,

•

the Water Directorate carries out all measurements, researches and is authorized to grant water use rights,

•

state authority is constrained; it is allowed to control the correct granting of new rights,

•

etc.

Of course there are critical points as well (Bauer 1998; Mentor, Jr. 2001; Nauditt et al. 2002): •

The rights of the private water users are extended; they can decide how to maintain and distribute the water, furthermore it is very difficult to loose once owned water rights,

•

Owners of water rights are not obliged to use all allocated water,

•

Insufficient control of water quality and low governmental influence on ecological protection of water bodies,

•

In some regions more water amounts are granted than available,

•

etc.

X

Annex The reform of the Water Codex was started in 1992 and was finally passed in 2005. The “Chicago Boys”3 advised the Chilean government that market mechanisms would lead to motivate water users in saving water, selling their surplus and transfer water rights to higher value users in other sectors (Mentor, Jr. 2001). Since the reformed Water Codex entered into force, an accountability and payment obligation has been introduced, if not all allocated water is used by the owners of the water rights. However, the system still doesn’t question the water property rights of those, who purchased them during the dictatorship of Augusto Pinochet nor from those, who have bought the rights on the open water market, without letting the government obtain any return from these transactions and licenses (Paz Aedo 2009).

3

The “Chicago Boys” are a group of Chilean economists who have studied from 1956 to 1970 largely at the University of Chicago and were inspired by the ideas of Friedrich August von Hayek and Milton Friedman. Under the rule of Augusto Pinochet they became influential in the fields of economics and socio-politics. These economists were convinced of the superiority of free markets, which they tried to realize through privatization and deregulation measures (Becker 1997; Wikipedia 2011).

XI