USGS Grant Number:
Year Established: 2009 Start Date: 2009-09-01 End Date: 2012-08-31
Total Federal Funds: $235,148 Total Non-Federal Funds: $242,866
Principal Investigators: Vijay Singh, Ashok Mishra
Abstract: Droughts in the United States result in an estimated average annual damage of $6 to 8 billion. The estimated loss from the 1988 drought was $40 billion and the estimated loss for the state of Texas alone from the 1996 drought was $6 billion. Like other western states, Texas is a water deficient state and is highly vulnerable to droughts, and its vulnerability is being compounded by rapidly growing population. According to the Water Plan developed by Texas Water Development Board, water shortages during droughts could cost businesses and workers in the state about $9.1 billion by 2010 and $98.4 billion by 2060 and about 85 percent of the states projected population would not have enough water by 2060 (in drought conditions), if an additional 8.8 million acre-feet of water supplies are not developed. Further complicating the Texas water shortage is climate change, which is being much debated these days. The major concern arising from climate change is its effect on water resources in terms of droughts and the resultant impact on different sectors. Changes in the magnitude and frequency of droughts will have extensive impacts on water management, agriculture and aquatic ecosystems. With the projected global temperature increase, scientists generally agree that the global hydrological cycle will intensify and suggest that extremes will become or have already become more common. The objective of this project is therefore threefold: (i) Analysis of multivariate hydrologic droughts: Drought is characterized by severity, areal extent, and duration. Multivariate distributions of these characteristics are needed and they will be derived using copulas. Then, droughts will be characterized by constructing: (a) Severity Duration Frequency curves (SDF), (b) Severity Area Frequency (SAF) curves, and (c) Severity-Interarrival time Frequency (SIF) curves. These curves are important for water resources planning. No such curves have been constructed for Texas surface water resources. (ii) Assessment of drought risk under climate change scenarios. Several questions will be addressed: (a) How much percentage of a basin will undergo a drought in year 2050? (b) What will be the severity of the 2050 drought? (c) Will the drought of 2050 be more severe than the 2020 or 2080 drought? (d) What will be the duration of the drought in 2050 or 2080? (e) How much will be the water deficit in a river in 2050, considering it as a hydrological drought? (f) How will drought properties vary, when compared to the past 50 years? This objective will also attempt to quantify uncertainties in drought characterization, considering primarily climate change and future water demand in the state. The outputs from General Circulation Models (GCMs) are considered, and are downscaled in a second step to the river basin scale using a Bayesian neural network approach. Finally the downscaled meteorological variables are used as input to a macro scale land surface hydrologic model (i.e., VIC model) for investigating future hydrological drought scenarios. (iii) Understanding of low frequency climate variations in association with Southern Oscillation Index (SOI) and Nino indexes: These variations affect Texas and their understanding will help provide improved streamflow forecasting needed for reservoir operations and will aid water management decisions. The lead-time of forecasting will be annual. Research, management practices, and education will benefit from this project. The project outcomes will provide information to understand status of streamflow in rivers for the 21st century. Moreover, the model results will be distributed to user groups who are coping with water scarcity now and likely to face in the future. The project will directly benefit the university researchers, Texas Water Development Board, and USGS through collaborative activity and will have a potential impact on education, public awareness, and administrations. Also, the outcomes of the model will serve as an educational and research tool to promote the understanding impact of climate change on streamflow and its relation with hydrological droughts to undergraduate and graduate students.