A stochastic dynamic programming approach to analyze adaptation to climate change – Application to groundwater irrigation in India

•Uncertainty and risk significantly influence farmers’ decisions.•Farmer decisions are modeled by a stochastic dynamic programming approach.•Farmer decisions concern investment in irrigation, crop choice, irrigation strategy.•Water management policies under climate change scenarios are investigated....

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Vydané v:European journal of operational research Ročník 265; číslo 3; s. 1033 - 1045
Hlavní autori: Robert, Marion, Bergez, Jacques-Eric, Thomas, Alban
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 16.03.2018
Elsevier
Predmet:
(B) Scenarios
(D) OR in agriculture
(D) OR in environment and climate change
(D) Strategic planning
(I) Stochastic programming
Life Sciences
(D) OR in environment and climate change
(I) Stochastic programming
(D) Strategic planning
(D) OR in agriculture
(B) Scenarios
scenarios
stochastic programming
climate change
strategic planning
ISSN:0377-2217, 1872-6860
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Popis
Shrnutí:•Uncertainty and risk significantly influence farmers’ decisions.•Farmer decisions are modeled by a stochastic dynamic programming approach.•Farmer decisions concern investment in irrigation, crop choice, irrigation strategy.•Water management policies under climate change scenarios are investigated. 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, and (iii) detailed farmers’ water practices and the representation of crop choice for each agricultural season with crop failure.
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2017.08.029