Modeling hydrological responses of karst spring to storm events: example of the Shuifang spring (Jinfo Mt., Chongqing, China)
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Reproduction of hydrographs at karst springs has been an approach of understanding the karst aquifer, which normally acts as drains for the groundwater flow. However, its numerical modeling is difficult since factors for the internal geometry and connectedness are unknown and hard to quantify. Hydrographs of the karst aquifer with well-developed conduits in Shuifang spring catchment were obtained from the automatic gauging station at the spring orifice. Data as to the conduit system were also obtained based on results and analyses of tracer tests. With these data, the hydrological responses of Shuifang spring to storm events were simulated by storm water management model (SWMM) developed by USA EPA (Environmental Protection Agency). Nash–Sutcliffe efficiencies are used to compare the computed flow to the observed, which are 0.95 and 0.92 for calibration and validation. SWMM was verified and applicable in karst conduit drainage system. The model illustrated correctly quick recharge through conduits and slow and low inflow from the fissured aquifer matrix. The SCS-CN (soil conservation service-curve number) infiltration method was used for computation of losses and runoff. Field tests indicated that permeability was extremely high but different in karst area, which was less sensitive to the computed runoff when exceeded the common value provided by SWMM. Therefore, an improved quantitative infiltration model for karst area will make SWMM possible to be a useful tool for assessing and reproducing spring hydrographs.
KeywordsKarst spring Modeling SWMM Conduit flow Tracer tests
Funding for this study was provided by the National Eleventh Five-Year Supporting Program (No. 2006BAC01A16), the National Natural Science Foundation (No. 40672165), Academician foundation of Science and Technology Committee of Chongqing (Award No. 2007BC7001 to Prof. Yuan D), and the USAID-SWU China Environmental Project. Thanks are extended to Dr. Lian Y for the opportunity to use SWMM, and also to Dr. Zhang C, Dr. Goldscheider N, Lettingue M, Yang P, Wang J and Kuang Y for their help of field work, and Prof. Liu Z for his helpful comments.
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