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Coupling pre-season farmers planning and optimal water supply management to mitigate climate change impacts

Master of Science Thesis by Matteo Mainardi
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Matteo Mainardi

on 30 March 2013

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Transcript of Coupling pre-season farmers planning and optimal water supply management to mitigate climate change impacts

2. climate
change impacts assessment Coupling pre-season farmers planning
and optimal water supply management
to mitigate climate change impacts introduction methodology
formalization case study Potential impacts
of climate change Adaptation
measures Closing
the loop Master Thesis by Matteo Mainardi

Supervisor: Prof. Andrea Castelletti
Co-supervisors: Eng. Matteo Giuliani, Prof. Claudio Gandolfi results conclusions and recommendations Agricultural
Sector Lake Como water system Climatic and behavioral scenarios 1. methodology effectiveness assessment Farmers' Decision-Making Problem Water Supply Management
Optimization Problem The Coupled Model Decision Maker: Olginate dam manager
Stakeholders:
5 irrigation districts
9 hydropower plants
municipalities on the lake shores
other downstream stakeholders Climatic scenarios
Current climate (measurements)
Forecasted climate (projections)
Behavioral scenarios
Lower Bound: no adaptation/information exchange
Upper Bound: co-adaptation/information exchange Objectives:
1. water deficits reductions
2. maximum potential effects of climate change
3. potential changes in crop production activities Projected climatic conditions Q-Q downscaling method (Déqué, 2007)
Variables of interest: Temperature, Precipitation, Humidity, Wind speed, Net radiation Current climatic conditions Crop choice Water Supply demand supply Proportion of water withdrawal for agriculture (FAO, Aquastat, 2007) Relative changes in annual runoff (IPCC, 2008) Change in the future
recurrence of 100-year
droughts (IPCC, 2001, 2008) Reference: climate and water use in 1961-90. The acronyms ECHAM4 and HadCM3 indicate two General Circulation Models used to forecast climatic conditions in the future at a global scale. FDMP Planning decisions
Management decisions
State variables
Disturbances Farmers' Design Objective: maximize income Water Supply Systems Maximum daily temperature in current and forecasted climate Monthly precipitation in current and forecasted climate Crop Growth Model Distributed Parameter Model Water Balance
Module Crop Growth
Module water demand daily biomass transpiration hydro-climatic scenario growth stage real yield max yield max biomass Water deficits (LB vs UB) LB: Water demand and Muzza flow rate LB: permanent grass and maize
UB: tomatoes Forecasted climatic conditions Crop choice Water deficits (LB vs UB) LB: Water demand and Muzza flow rate LB: permanent grass and maize
UB: mainly permanent grass UB: Water demand and Muzza flow rate Lower Bounds Upper Bounds Conclusions water deficits minimization in current climate
climate change impacts mitigation thanks to adaptation strategies Objective: build the methodology Results: strong effectiveness of the methodology Future developments crop production costs
model of crop prices
crop growth model refinement
sharing rules among irrigation districts
hydrologic relationship between Adda river and groundwater
model diagnostics
advanced optimization algorithm for FDMP Farmers' Decision-Making
Problem Water Supply
Management
Optimization
Problem demand supply Water Demand thank you Como, December 20 , 2012 th UB: Water demand and Muzza flow rate Climate change impacts 1. Crop choices in UB: from tomatoes to grass 2. Water deficits
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