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WHERE AND WHEN DO WE NEED WATER? Dr. Francisco J. Meza Project Mentor Dr. Guillermo Podestá Facultad de Agronomía e Ingeniería Forestal Pontificia Universidad.

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Presentation on theme: "WHERE AND WHEN DO WE NEED WATER? Dr. Francisco J. Meza Project Mentor Dr. Guillermo Podestá Facultad de Agronomía e Ingeniería Forestal Pontificia Universidad."— Presentation transcript:

1 WHERE AND WHEN DO WE NEED WATER? Dr. Francisco J. Meza Project Mentor Dr. Guillermo Podestá Facultad de Agronomía e Ingeniería Forestal Pontificia Universidad Católica de Chile

2 Objectives Main objective: Main objective: Characterize the main components of the agricultural hydrological cycle as well as the possible crop yield outcomes of irrigated sectors under ENSO scenarios. Specific objectives were: Specific objectives were: –ENSO impacts on the water cycle and crop growth. –Probability distribution functions of potential and actual evapotranspiration –Identify regions and seasons that are particularly sensitive to water scarcity –Perform preliminary estimates of the benefits of using climate forecasts in agricultural water resources planning.

3 Region Under Study Maipo River Basin

4 Climatic Variability in Chile and El Niño Phenomenon Mean Annual Precipitation ( ) at six Chilean Localities Locality Lat (S) El Niño Normal La Niña Pudahuel Curicó Concepción Temuco Valdivia Puerto Montt

5 Climatic Variability in Chile and El Niño Phenomenon In central Chile, ENSO does have an influence on other meteorological variables that play a fundamental role on reference evapotranspiration (Meza, 2005) In central Chile, ENSO does have an influence on other meteorological variables that play a fundamental role on reference evapotranspiration (Meza, 2005)

6 Water Demands Surface of crops was determined in each section of the basin based on the Chilean Agricultural Census Surface of crops was determined in each section of the basin based on the Chilean Agricultural Census Crop Potential ET was calculated using FAO crop coefficients Crop Potential ET was calculated using FAO crop coefficients –ETp = Kc * ETo Irrigation was triggered ony when soil water budget fell below a threshold level Irrigation was triggered ony when soil water budget fell below a threshold level

7 Soil Water Balance Algorithm

8 ENSO Effect on Water Demands in Central Chile

9 ENSO Forecats for Water Resurces Management In Chile, basins are regulated by the Water Code Bill In Chile, basins are regulated by the Water Code Bill There are water rights that guarantee specific amouts to the holders. This limits the possibility of allocating water according to the demand (i.e. conditioned on ENSO) There are water rights that guarantee specific amouts to the holders. This limits the possibility of allocating water according to the demand (i.e. conditioned on ENSO) Only in a situation of severe water scarcity it will be possible to use climatic-oceanic indices Only in a situation of severe water scarcity it will be possible to use climatic-oceanic indices

10 Getting the right framework Up to this moment the objectives were achieved Up to this moment the objectives were achieved –ENSO does play a role determining different evapotranspiration rates –Greater demands are observed in the second section (where) and during La Niña years (when) –Due to regulatory issues the real decision maker for water allocation is the farmer not the local authority Can farmers take advantage of ENSO information for irrigation management? Can farmers take advantage of ENSO information for irrigation management?

11 Use of ENSO driven climatic information for optimum water allocation Dr. Francisco J. Meza Use of ENSO driven climatic information for optimum water allocation International Workshop on Climate Prediction and Agriculture: Advances and Challenges. May 9-13, Dr. Francisco J. Meza Facultad de Agronomía e Ingeniería Forestal Pontificia Universidad Católica de Chile

12 Droughts in Chile Occurrence of Severe Droughts Occurrence of Severe Droughts Source: Urrutia de Hazbun et al, 1993.

13 Mean Economic Impact of Droughts in Chile (Source: MOP-UC, 1997) Basin Number

14 Can we take advantage of ENSO information for water resources management problems? Requisites of valuable information (ENSO forecast) Requisites of valuable information (ENSO forecast) Climatic Predictability + Systems Vulnerability + Decission Capacity Hansen, J.W., 2002

15 Climatic Predictability (ENSO Forecast)

16 Irrigation Management When water is not a limiting factor, irrigation is reduced to the management of the soil water budget to minimize plant stress. When water is not a limiting factor, irrigation is reduced to the management of the soil water budget to minimize plant stress. When water is scarce the operation of irrigation increases in complexity, becoming a traditional resource allocation problem. When water is scarce the operation of irrigation increases in complexity, becoming a traditional resource allocation problem. Optimum allocation of resources is achieved when the consequences associated to all possible combinations of alternatives and states of the variable are known. Optimum allocation of resources is achieved when the consequences associated to all possible combinations of alternatives and states of the variable are known.

17 Traditional Approach Assumes that Water Demands are constant (i.e. fixed at climatological values) Assumes that Water Demands are constant (i.e. fixed at climatological values) Uses Doorenbos and Kassam empirical equations or Jensen´s formula to estimate yield changes as a function of actual evapotranspiration Uses Doorenbos and Kassam empirical equations or Jensen´s formula to estimate yield changes as a function of actual evapotranspiration Jensen´s formula (Jensen, 1968)

18 Traditional Approach Mathematical programming formulation Mathematical programming formulation Objective Function Constraints

19 ENSO based Approach Since ENSO does influence reference evapotranspiration, it is reasonable to incorporate that information and perform an optimization conditioned on ENSO phase Since ENSO does influence reference evapotranspiration, it is reasonable to incorporate that information and perform an optimization conditioned on ENSO phase The problem is rewritten as The problem is rewritten as Where o represents El Niño, Normal or La Niña phase

20 Expected Value of Information The information (ENSO forecast) will be valuable if at least one of the optimal actions (i.e. irrigation strategies) associated with the forecast information differs from the one selected without forecast. The information (ENSO forecast) will be valuable if at least one of the optimal actions (i.e. irrigation strategies) associated with the forecast information differs from the one selected without forecast. According to Bayes´ theorem one can calculate the expected value of information as: According to Bayes´ theorem one can calculate the expected value of information as:

21 Case Study Maipo River Basin Parameters used Parameters used

22 Results Expected Value of Information for the different phases of ENSO Expected Value of Information for the different phases of ENSO Available water at each irrigation time was equivalent to 55 mm Available water at each irrigation time was equivalent to 55 mm

23 Results Expected Value of Information as a function of different levels of water supply Expected Value of Information as a function of different levels of water supply

24 Results So far results show that ENSO information can be used to select an irrigation strategy, representing a case of perfect information (i.e. the forecasted evapotranspiration is equal to the observed one in susequent periods) So far results show that ENSO information can be used to select an irrigation strategy, representing a case of perfect information (i.e. the forecasted evapotranspiration is equal to the observed one in susequent periods) A more realistic approach should be a case where irrigation strategy is revised based on A more realistic approach should be a case where irrigation strategy is revised based on –a) Previous water demands –b) Forecasted evapotranspiration In that situation the decision maker can correct wrong allocations due to climate variability In that situation the decision maker can correct wrong allocations due to climate variability

25 Results Evolution of the objective function of the decision maker that allocates water using El Niño forecasts and the one that bases his decision on historical ETc values Evolution of the objective function of the decision maker that allocates water using El Niño forecasts and the one that bases his decision on historical ETc values Value of Forecast

26 Conclussions and Future Steps In locations where ENSO signal has an effect on water demands there is an economic potential for climate forecasts in water resources allocation at the farm level. In locations where ENSO signal has an effect on water demands there is an economic potential for climate forecasts in water resources allocation at the farm level. The expected value of information is not a monotonic function because when water is very scarce the allocation decissions are limitted. The expected value of information is not a monotonic function because when water is very scarce the allocation decissions are limitted. The next step is to refine the translation of yields because they also are affected by climatic variability (use process based crop simulation models) The next step is to refine the translation of yields because they also are affected by climatic variability (use process based crop simulation models)

27 Where and When do we Need Water? Summary of Scientific Activities Summary of Scientific Activities Regional Water Demand Model Conditioned on ENSO phases Regional Water Demand Model Conditioned on ENSO phases Assessment of potential use of ENSO information for Irrigation Management Assessment of potential use of ENSO information for Irrigation Management Communication and Dissemination Communication and Dissemination –84th AMS Annual Meeting, Seattle Washington –Local Seminar Climatic Variability and Change: Issues in Water Resources, Agriculture and Forest Ecosystems Dr Carlos Nobre, CPTEC Dr Carlos Nobre, CPTEC Dr Bonifacio Fernandez. School of Engineering Dr Bonifacio Fernandez. School of Engineering Dr Francisco Meza. ATI participant Dr Francisco Meza. ATI participant

28 Summary of Scientific Activities –85th AMS Annual Meeting, San Diego, California –Papers: Meza, F.J Use of ENSO driven climatic information for optimum irrigation under drought conditions: Preliminary assessment based on model results. Climate Research: submitted. Meza, F.J Use of ENSO driven climatic information for optimum irrigation under drought conditions: Preliminary assessment based on model results. Climate Research: submitted. Meza, F.J Obtaining daily precipitation parameters from meteorological yearbooks. Agricultural and Forest Meteorology: submitted. Meza, F.J Obtaining daily precipitation parameters from meteorological yearbooks. Agricultural and Forest Meteorology: submitted. Meza, F.J Variability of reference evapotranspiration and water demands. association to ENSO at the Maipo river basin, Chile. Global and Planetary Change: In press Meza, F.J Variability of reference evapotranspiration and water demands. association to ENSO at the Maipo river basin, Chile. Global and Planetary Change: In press

29 "You don't get points for predicting rain. You get points for building arks." "You don't get points for predicting rain. You get points for building arks." – Lou Gerstner, IBM CEO (Quoted by Richard Katz, UCAR) – Lou Gerstner, IBM CEO (Quoted by Richard Katz, UCAR) QUESTIONS???? QUESTIONS????


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