A dynamic intertemporal optimization approach to assess water scarcity costs and long-term adaptation investments for enhancing irrigation system resilience

Increasing water scarcity due to global warming and growing water demand over time poses a significant threat to agricultural income and rural livelihoods in arid and semiarid regions worldwide. Common tools based on static optimization or myopic simulations support the policies that focus on short-term gains but cannot address the long-term investment needs for sustainable water and food system transformations. This study develops a dynamic intertemporal optimization model to contribute to the assessment of long-term investment pathways for enhancing the resilience of water systems under growing environmental challenges. The model was applied for the analysis of water scarcity and climate damage costs, proactive endogenous technology change and intertemporally optimal investments in irrigation system transition. The practical relevance of the model was demonstrated by a numerical application in the case of Uzbekistan (in Central Asia), which may face about 13.8 % agricultural income loss due to the moderate impact of climate change ( SSP2-RCP4.5 ) if there is no adaptation action. The model results indicate that the adoption of improved (drip and sprinkler) irrigation technologies has significant potential for enhancing crop production benefits, increasing the Equivalent Annual Net Benefit by 2.5 – 16.4 %. The results also underline the importance of the subsidy policies for the wider adoption of improved irrigation technologies and enhancement of farming income. The presented modeling framework can be adapted (by changing the model database and setup) to assess intertemporally optimal investments and environmental effects of upscaling irrigation and crop production technologies in regions beyond the study area.