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Updated: Jun 8, 2026

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Quantitative assessment of groundwater vulnerability using index system and transport simulation, Huangshuihe
Cheng Yu1, Yingying Yao, Gregory Hayes
1Center for Water Research, College of Engineering, Peking University, Beijing, China. beimingyu@gmail.com
Abstract:
Groundwater vulnerability assessment has been an increasingly important environment management tool. The existing vulnerability assessment approaches are mostly index systems which have significant disadvantages. There need to be some quantitative studies on vulnerability indicators based on objective physical process study. In this study, we tried to do vulnerability assessment in Huangshuihe catchment in Shandong province of China using both contaminant transport simulations and index system approach. Transit time of 75% of hypothetical injected contaminant concentration was considered as the vulnerability indicator. First, we collected the field data of the Huangshuihe catchment and the catchment was divided into 34 sub areas that can each be treated as a transport sub model. Next, we constructed a Hydrus1D transport model of Huangshuihe catchment. Different sub areas had different input values. Thirdly, we used Monte-Carlo simulation to improve the collected data and did vulnerability assessment using the statistics of the contaminant transit time as a vulnerability indicator. Finally, to compare with the assessment result by transport simulation, we applied two index systems to Huangshuihe catchment. The first was DRASTIC system, and the other was a system we tentatively constructed examining the relationships between the transit time and the input parameters by simply changing the input values. The result of comparisons between the two index systems and transport simulation approach suggested partial validation to DRASTIC, and the construction of the new tentative index system was an attempt of building up index approaches based on physical process simulation.
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