Bergez, Jacques Eric, Robert, Marion and Thomas, Alban (2018) A stochastic dynamic programming approach to analyze adaptation to climate change - application to groundwater irrigation in India. European Journal of Operational Research, 265 (3). pp. 1033-1045.

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Identification Number : 10.1086/699210


Agricultural sustainability under climate change is a major challenge in semi-arid countries, mainly because of over-exploited water resources. This article explores short- and long-term consequences of farmers’ adaptation decisions on groundwater resource use, under several climate change scenarios. We model farmer decisions on crop choice, investment in irrigation and water application rates, using a stochastic dynamic programming model with embedded year and season decision stages. Several sources of risk are considered that may impact farmer decisions, with poor rainfall affecting crop yield and market prices, while driving crop and borewell failure probabilities. We further investigate the performance of water management policies for groundwater resource conservation. This is achieved through policy simulations from a calibrated version of the stochastic dynamic model, using data from a field survey in the Berambadi watershed, Karnataka state, southern India. The most relevant and novel aspect of our model is the joint consideration of i) investment decisions about irrigation over a long-term horizon and with the probability of borewell failure, ii) several water management policies, iii) detailed farmers’ water practices and the representation of crop choice for each agricultural season with crop failure.

Item Type: Article
Language: English
Date: March 2018
Refereed: Yes
Uncontrolled Keywords: Stochastic dynamic programming, environment and climate change, Strategic planning
JEL Classification: H23 - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
O13 - Agriculture; Natural Resources; Energy; Environment; Other Primary Products
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 07 May 2018 14:40
Last Modified: 02 Apr 2021 15:57
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