Optimizing Irrigation Water Management on the Global Change Context in a Mediterranean Region

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Optimizing Irrigation Water Optimizing Irrigation Water Management on the Global Management on the Global

Change Context in a Change Context in a Mediterranean RegionMediterranean Region



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Objetive

To analyse the impact of Water Framework Directive, the Common Agricultural Policy Reform and the Climate Change on the management, the productivity and the economic efficiency of irrigation at farm level.

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ueroLocation:

Central Part of the Guadalquivir Valley

Location:

Central Part of the Guadalquivir Valley

Crop:

Irrigated Grain Maize

Crop:

Irrigated Grain Maize

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MethodologyMethodology

Crop DataCrop Data

Irrigation DataIrrigation Data

Socioeconomic DataSocioeconomic Data

Climatic DataClimatic Data

WADI Political Scenarios

CAP+WFD

WADI Political Scenarios

CAP+WFD

Climate Change Scenarios

Climate Change Scenarios

DSSAT ModelDSSAT Model

Hydraulic Irrigation Model

Hydraulic Irrigation Model

Seasonal Economic Optimization ModelSeasonal Economic Optimization Model

GCM Model &

Downscaling

GCM Model &

Downscaling

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INT

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Crop, Soil and Climatic DataCrop, Soil and Climatic Data

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Irrigation Optimisation ModelIrrigation Optimisation Model

Seasonal Model of Irrigation Management

Soil Water Balance Model

Farm Irrigation Model

Crop Production Model

Economic Optimisation Model

Net Profit (€/ha)

Irrigation Productivity (Kg/m3)

Economic Efficiency (€/m3)

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Net Profit (€/ha)



The model proposed by Allen et al. (1998) was used to calculate a daily water balance in the soil-plant-atmosphere complex. Potential and actual evapotranspiration were estimated by the method of dual crop coefficients, taking into account the water stress conditions.

The model proposed by Allen et al. (1998) was used to calculate a daily water balance in the soil-plant-atmosphere complex. Potential and actual evapotranspiration were estimated by the method of dual crop coefficients, taking into account the water stress conditions.


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Net Profit (€/ha)



A mathematical model was developed in order to simulate all phases (advance, storage, depletion and recession) of furrow irrigation with free runoff. For drip irrigation system modelling, an Application Efficiency of 90%, a drip discharge of 2.3 L/h and a density of 6666 drips/ha were assumed.

A mathematical model was developed in order to simulate all phases (advance, storage, depletion and recession) of furrow irrigation with free runoff. For drip irrigation system modelling, an Application Efficiency of 90%, a drip discharge of 2.3 L/h and a density of 6666 drips/ha were assumed.


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Net Profit (€/ha)



The Jensen’s model (Jensen, 1968) was used to estimate the actual crop yield:

In order to relate the yield response factors Kyi, calibrated from DSSAT results, to the sensitivity index of Jensen’s model, a polynomial function proposed by Kipkorir and Raes (2002) was used.

The Jensen’s model (Jensen, 1968) was used to estimate the actual crop yield:

In order to relate the yield response factors Kyi, calibrated from DSSAT results, to the sensitivity index of Jensen’s model, a polynomial function proposed by Kipkorir and Raes (2002) was used.

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Net Profit (€/ha)



Dynamic Programming was implemented as the method for economic optimisation, in which each irrigation event was considered as a stage of the process. As objective function, the maximization of net profit of agricultural production was defined.

Dynamic Programming was implemented as the method for economic optimisation, in which each irrigation event was considered as a stage of the process. As objective function, the maximization of net profit of agricultural production was defined.


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1. The irrigation optimisation model used the daily values of reference evapotranspiration calculated in DSSAT for each climatic data series.

2. Daily evolution of basal crop coefficient was determined as the relation between potential transpiration and reference evapotranspiration calculated by DSSAT model.

3. Successive DSSAT simulations were run, by introducing different water stress levels in every phase of crop development. The values of yield response factors Kyi were determined through lineal regression between the relative yield and the relative evapotranspiration obtained by DSSAT for each individual period of crop growth.

1. The irrigation optimisation model used the daily values of reference evapotranspiration calculated in DSSAT for each climatic data series.

2. Daily evolution of basal crop coefficient was determined as the relation between potential transpiration and reference evapotranspiration calculated by DSSAT model.

3. Successive DSSAT simulations were run, by introducing different water stress levels in every phase of crop development. The values of yield response factors Kyi were determined through lineal regression between the relative yield and the relative evapotranspiration obtained by DSSAT for each individual period of crop growth.

Integration: DSSAT Model and the Irrigation Optimisation Model

Integration: DSSAT Model and the Irrigation Optimisation Model

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•The climate change scenario forecasted for the year 2020 were taken from the CGCM2 model outputs, provided by the Canadian Centre for Climate Modelling and Analysis.

•The IPCC SRES A2 scenario for greenhouse gases emissions (IPCC, 2001) was considered.

•In order to downscaling the forecasted climatic data, the outputs of LARS-WG weather generator were perturbing according to the CGCM2 results.

•The climate change scenario forecasted for the year 2020 were taken from the CGCM2 model outputs, provided by the Canadian Centre for Climate Modelling and Analysis.

•The IPCC SRES A2 scenario for greenhouse gases emissions (IPCC, 2001) was considered.

•In order to downscaling the forecasted climatic data, the outputs of LARS-WG weather generator were perturbing according to the CGCM2 results.

Climate Change ScenarioClimate Change Scenario

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Agricultural and Water Policies Combined Scenarios

Agricultural and Water Policies Combined Scenarios

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Irrigation Modernization Scenarios

Irrigation Modernization Scenarios

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Climate Change and Crop Water Requirements


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Forecasted Weather DataYear: 2020

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Historical Weather DataYears: 1961-2004

44 Years

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Minimum Temperature

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Crop Production FunctionCrop Production Function

y = 0.389x

R2 = 0.857 Initial Stage

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Net Profit, Economic Efficiency...Net Profit, Economic Efficiency...

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Irrigation ManagementIrrigation Management

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Irrigation ManagementIrrigation Management

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Irrigation

Soil Water Depletion

Readily Available Water

Baseline Scenario

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Dep

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Soil Water Depletion

Readily Available Water

Global Sustainability Scenario

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ConclusionsConclusions

1. Climate change scenario used in this study predicted an increment of net irrigation requirements in 40.2 mm.

2. Maize production experimented a remarkable loss in profitability and economic efficiency in the context of agricultural and water policies induced by the Global Sustainability and World Markets scenarios.

3. The irrigation systems based on medium levels of modernization were able of assimilate the new paradigm that transposition of the Water Framework Directive, the revision of the CAP and the climate change supposed.

1. Climate change scenario used in this study predicted an increment of net irrigation requirements in 40.2 mm.

2. Maize production experimented a remarkable loss in profitability and economic efficiency in the context of agricultural and water policies induced by the Global Sustainability and World Markets scenarios.

3. The irrigation systems based on medium levels of modernization were able of assimilate the new paradigm that transposition of the Water Framework Directive, the revision of the CAP and the climate change supposed.

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Optimizing Irrigation Water Management on the Global Change Context in a Mediterranean Region

Technology

Transcript of Optimizing Irrigation Water Management on the Global Change Context in a Mediterranean Region