Abstract
Drought is a serious concern in arid environments and directly impacts water resources. Kuwait has experienced a number of prolonged dry periods since 1962 which are interrupted by short, variable torrential rains that are vital to the region's freshwater recharge. This rainfall (avg. 131mm/yr) is the primary driver of hydrological change due to Kuwait's relatively flat topography (0m - 360m). Surface runoff from these floods typically flows through wadis into small depressions. We hypothesize that prolonged drought and less frequent albeit more extreme rainfall events (>20mm/day) are altering water supply, drainage networks, and other landforms (e.g. wadis, depressions, dunes). Using Kuwait as a study area, the Standard Precipitation Index (SPI) was generated utilizing GPCP and TMPA rainfall data from 1901 - 2000 and 1998 - 2014 respectively to evaluate the drought magnitude, duration, and frequency. Drainage networks, depressions, and ephemeral channels were delineated and measured (size, location, stream order) utilizing remote sensing images from Landsat TM (VIS), ASTER (DEM, TIR and VNIR), SRTM (DEM), and ENVISAT ASAR between 1999 and 2014. In addition, KEPA dust fallout was compared to landform magnitude changes. SPI results identified five periods of prolonged dryness. This included the longest duration (SPI index <0) in 1962 - 1966 for a period of 60 months (avg. 77mm/yr). Similar stretches include 53 months with minimal interruption of dryness (<15%) from 1981-1985 (avg. 98mm/yr), 44 months from 1987-1990 (avg. 76mm/yr), 34 months from 2001-2003 (avg. 87mm/yr), and 34 months from 2007-2010 (avg. 85mm/yr). The correlation between resultant images and GLDAS-derived surface runoff, precipitation data, rain gauge data, and dust fallout data demonstrate the relationship between drought, precipitation and shifting landscapes in arid regions. In areas where prolonged dryness occurs, understanding the relationship between physiographic changes and the hydrologic cycle is necessary to validate long-term hydrologic models and identify impacts of climate change.