Modeling Water Budget And Drought Index With High-resolution Land Cover Mapping And Spatial Sampling In A Coastal Low-lying Urbanizing Watershed

Nowadays, the meteorological, hydrological, agricultural and urban droughts focus respectively on precipitation shortages, streamflow decreases, topsoil water deficits and water supply scarcities; thus it is absence of integrated drought indices that can reflect the terrestrial hydrological processes comprehensively. Moreover, most of the previous watershed hydrological process researches based on the land cover changes were incapable of meeting the relevant high-resolution and continued updating requirements, which were obviously too coarse for urban watershed and cannot describe their underlying surface situation timely and precisely. The selected area of study is a sub-basin of the main stream of River Hai, which covers 2744.44km2. The data used for the study were the 1:10000-scale Digital Line Graphic (DLG) map surveyed and mapped in 2002 and the Google Earth (GE) satellite images which were mainly taken during 2009-2010. A stratified, two-phase spatial sampling method was used to assess the changes of land cover and the Impervious Cover Ratio (ICR) between 2002 and 2010. High-resolution land cover data was collected based on the DLG map. The GE images were mainly used for desktop statistics and were helpful to GPS field survey. The sampling and statistics result showed that the ICR of 2002 was 18.31% and increased to 34.46% in 2010. Based on the 2002 land cover statistics, a sub-watershed covers 267.82km2 was then chosen for SWAT modeling. It was situated at the center of the sub-basin and was typical of overlaying with the intensive built-up area and the newly rapid expansion area. The main hydrological processes of each sub-catchment, including runoff producing, infiltration, retention and drainage were modeled based on the 2002 land cover scenario from 1990 to 2009. A Cumulated Water Deficit Index (CWDI) was created. Both the single indices, such as soil moisture storage index, surface water storage index, water yield index etc., and the integrated index of CWDI were used to perform the drought distribution, showing that, the soil moisture storage is more sensitive to the difference between the built-up area and the non-built area. The compositive evaluation result was remarkably affected by meteorological factors, and portion of the sub-catchments was closely related to the surface water storage capacities. The modeling result of the sub-watershed can be expanded to the whole sub-basin area. The CWDI integrates the streamflow, surface water storage and soil moisture storage capacities and preferably perform the terrestrial water profit and loss situation at both macroscopic and microscopic scale. It broadens the existing urban drought indices that merely from the standpoint of water supply and synthetically evaluates hydrological drought in the urban watershed. Each factor of the CWDI is separately correspondent with linear water space, region water space and land cover and does have the guidance to the spatial planning. The high-resolution land cover mapping and spatial sampling helped describe the substrate situation of the reference year and the typical scenario precisely and making the spatial resolution of drought recognition reach the precision of 102m×102m at 10~3km~2 scale.