Many river basins will likely face higher hydrologic variability, including extreme floods and droughts, due to climate change, with economic and political consequences. Water treaties that govern international basins could face non-compliance among riparians and inter-state tensions as hydrologic variability increases. Accurate monitoring of water resources is essential to cope with these fluctuations in flow. This paper demonstrates a simple yet robust procedure—the Basist Wetness Index—to predict gauge station (actual water resources) measurements of surface wetness values derived from satellite data (for 1988-2013) and empirically derived flow distributions in two international river basins: Zambezi and Mekong. The paper further undertakes an economic analysis (applied to the Mekong), which identifies not only the economic costs and losses due to extreme fl ow events, but likewise showcases the benefits countries could potentially reap should they be able to make use of such flow data in real time. An illustrative application, using the wetness data and socio-political data, is also performed to highlight the utility of the procedure for research in the field of conflict and cooperation over water. The paper concludes that satellite data modeled with gauge station flow can help reduce the uncertainty inherent in negotiating international water issues. Moreover, the satellite observations can provide near real time monitoring of water resources, and provide valuable lead time for impending droughts and floods. Thus, the approach presented in the article can assist policy makers to devise more efficient and cooperative institutional apparatus.
# 14-005/II (2014-01-06)
- Brian Blankespoor, Development Research Group, World Bank, Washington DC, United States of America; Alan Basist, Weather Predict Consulting, Asheville, North Carolina, United States of America; Ariel Dinar, University of California, Riverside, California, United States of America; Shlomi Dinar, Florida International University, Miami, Florida, United States of America; Harold Houba, VU University Amsterdam, The Netherlands; Neil Thomas, Resource Data Incorporated, Asheville, North Carolina, United States of America
- runoff; remote sensing; surface wetness, hydrological variability; international relations; microwaves, economic optimization, international river basins; Mekong; Zambezi
- JEL codes:
- C53, F51, F53, Q54