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Evaluation of hydrological effect of stakeholder prioritized climate change adaptation options based on multi-model regional climate projections

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Abstract

An integrated process involving participatory and modelling approaches for prioritizing and evaluating climate change adaptation options for the Kangsabati reservoir catchment is presented here. We assess the potential effects of climate change on water resources and evaluate the ability of stakeholder prioritized adaptation options to address adaptation requirements using the Water Evaluation And Planning (WEAP) model. Two adaptation options, check dams and increasing forest cover, are prioritized using pair-wise comparison and scenario analysis. Future streamflow projections are generated for the mid-21st century period (2021–2050) using four high resolution (~25 km) Regional Climate Models and their ensemble mean for SRES A1B scenario. WEAP simulations indicate that, compared to a base scenario without adaptation, both adaptation options reduce streamflow. In comparison to check dams, increasing forest cover shows greater ability to address adaptation requirements as demonstrated by the temporal pattern and magnitude of streamflow reduction. Additionally, over the 30 year period, effectiveness of check dams in reducing streamflow decreases by up to 40 %, while that of forest cover increases by up to 47 %. Our study highlights the merits of a comparative assessment of adaptation options and we conclude that a combined approach involving stakeholders, scenario analysis, modelling techniques and multi-model projections may support climate change adaptation decision-making in the face of uncertainty.

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Acknowledgments

This work has been supported by the HighNoon project, funded by the European Commission Framework Programme 7 under Grant Nr. 227087.

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Correspondence to Ajay Gajanan Bhave.

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Bhave, A.G., Mishra, A. & Raghuwanshi, N.S. Evaluation of hydrological effect of stakeholder prioritized climate change adaptation options based on multi-model regional climate projections. Climatic Change 123, 225–239 (2014). https://doi.org/10.1007/s10584-014-1061-z

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  • DOI: https://doi.org/10.1007/s10584-014-1061-z

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