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I am an Assistant Professor of Environmental Engineering at the University of Cincinnati, and a member of the Hydrosystems Research Group at the University of Massachusetts, Amherst. My research focuses on increasing the resilience of water systems to climate variability and change through the use of advanced climate science and coupled hydrologic-human system simulation, in combination with innovative water resources management techniques and methods for decision-making under uncertainty. The work of my lab at the University of Cincinnati has so far been supported by grants from the World Bank, Army Corps of Engineers, National Center for Atmospheric Research, California Department of Water Resources, and Ohio Water Research Center.
Hydrologic models are fundamental elements of the water system planning workflow. As such, we strive always for improvements and innovations in hydrologic modeling techniques, algorithms, and applications.
Yemen is ranked 154th out of 187 countries in the Human Development Index, a ranking that has generally held steady since 1990. Yemen continues to grapple with the decline of its water resources. In terms of per capita water availability, Yemen is the most water-stressed country in the world and one of the ten poorest in terms of all available resources. The typical paradigm for international aid tends to divide funds and efforts into three categories: relief, recovery and development. The international community tends to respond to natural or political disasters with large sums of financial and material aid, which result in no meaningful reduction in vulnerability to the next (and often imminent) crisis. This paper suggests (based upon a case study of a World Food Program food-for-work initiative in Hajja and Hodeidah, Yemen) that investments of labor, materials and funds in food or financial relief (emergency response) should be coupled with innovative and uncompromising commitment to improvements in Water, Sanitation and Health (WASH)-related policies, practices (e.g., hand-washing, community-led total sanitation), and infrastructure (e.g., watershed improvements, cisterns, water filters, wells, rainwater harvesting systems, hillside terraces, latrines, toilets, etc.) that result directly in local ownership of greater food security, health, and control of water resources (including invulnerability to and resilience in the recovery from floods and droughts).
The decision tree framework provides resource-limited project planners and program managers with a cost-effective and effort-efficient, scientifically defensible, repeatable, and clear method for demonstrating the robustness of a project to climate change. At the conclusion of this process, the project planner is empowered to confidently communicate the method by which the vulnerabilities of the project have been assessed, and how the adjustments that were made (if any were necessary) improved the project’s feasibility and profitability. The framework adopts a “bottom-up” approach to risk assessment that aims at a thorough understanding of a project’s vulnerabilities to climate change in the context of other nonclimate uncertainties (for example, economic, environmental, demographic, or political). It helps to identify projects that perform well across a wide range of potential future climate conditions, as opposed to seeking solutions that are optimal in expected conditions but fragile to conditions deviating from the expected. The decision tree employs a stress test for project/system climate change risk assessment, and advanced analytical tools for climate change risk management. In addition to addressing the fundamental science issues, the decision tree was designed with the economic use of human and financial resources in mind. The goal was to develop a tool that would be applicable to all water resources projects, but to allocate effort to projects in a way that is consistent with their potential sensitivity to climate risk. To do so, the process was designed to be hierarchical, with successive stages or phases of analysis triggered only if shown to be warranted during the explorations of the previous phase. The procedure consists of four increasingly intensive phases: Phase 1 Project Screening; Phase 2 Initial Analysis; Phase 3 Climate Stress Test; and Phase 4 Climate Risk Management. The result is that risk management effort is expended in proportion to the need. The decision tree has been applied to six World Bank projects to date: the Upper Arun Hydropower Project, Nepal, the Mwache Multipurpose Reservoir, Kenya, the Cutzamala Water System, Mexico, the Poko Hydropower Project, Indonesia, the Matenggeng Pumped Storage Project, Indonesia, and a study of the resilience of the urban water system under the jurisdiction of SACMEX in Mexico City, Mexico.