Water sustainability is one of the grand challenges facing society in the twenty-first century. With ongoing land development driven by population growth and climate change that has exacerbated drought, many regions of the world are facing the issues of water scarcity, which threaten the long-term sustainability of water resources. Drought is a recurrent extreme climate event that strongly affects every specter of the natural environment and human life; it has profound socioeconomic consequences, as it typically occurs over long time scales and in virtually all climatic zones. Droughts occur indifferently in high and low rainfall areas and in virtually all climatic zones, although the most severe human consequences happen in arid regions. We proposed to develop a drought early warning system with seasonal predictions of drought onset, and spatial extent in a timely manner. This would provide invaluable information to mitigate the impacts of droughts and reduce related losses. We leveraged the availability of vast data resources from in situ and remotely sensed satellite observation of hydroclimatic variables (e.g., precipitation, streamflow), land surface properties (e.g., soil moisture, snow, vegetation); and recent advances made in dynamical hydrologic simulation, state-of-the-art of data assimilation and statistical methods developed by the PIs and community in the earth system and computational sciences. An integrated cyber-enabled approach helped enhance the accuracy and reliability in drought monitoring/forecasting and also estimating the drought recovery to prevent and mitigate the extentof stress on a society and the conditions that threaten the long-term sustainability of water resources due to water scarcities.

Additionally, drought impacts on stream ecosystems include both direct (loss of water and loss of habitat for aquatic species) and indirect (deterioration of water quality). Thsi project combined hydrologic drought and water quality changes during droughts and represented a multi-stage framework to detect and characterize hydrological droughts, while considering water quality parameters. The method was applied to streamflow stations in the state of California, over the study period of 1950-2010. The framework was assessed and validated based on two drought events declared by the state in 2002 and 2008. Results showed that there were two opposite drought propagation patterns in northern and southern California. In general, northern California indicated more frequent droughts with shorter time to recover. Chronology of drought showed that stations located in southern California have not followed a specific pattern but they experienced longer drought episodes with prolonged drought recovery. In terms of water quality, results showed that droughts either deteriorated or enhanced water systems, depending on the parameter of interest. Increased temperature and decreased dissolved oxygen were observed during droughts which were undesirable changes. In contrast, decreased turbidity was detected in rivers during drought episodes which is desirable in water system. Nevertheless, water quality deteriorated during drought recovery, even after drought terminated.

The framework was extended to 400 streamflow gauges across the Contiguous United States (CONUS) over the study period of 1950-2016. The method was illustrated for the 2012 US drought, which affected most of the nation. Results revealed the duration, frequency, and severity of historical droughts in various regions as well as their spatial consistencies and heterogeneities. Furthermore, duration of each stage of drought (i.e., growth, persistence, and retreat) was also assessed and the spatial patterns were diagnosed across the CONUS.

Last Modified: 11/26/2018
Modified by: Hamid Moradkhani