Department of Geosciences and Geological and Petroleum Engineering, Missouri University of Science and Technology, McNutt Hall, 1400 N. Bishop Ave, Rolla, MO, 65401, USA.
College of Science, University of Misan, Amarah, Iraq.
Environ Sci Pollut Res Int. 2019 Nov;26(31):31981-31997. doi: 10.1007/s11356-019-06355-9. Epub 2019 Sep 6.
Watershed vulnerability and the characterization of potential risk are important inputs for decision support tools in assessing watershed health. Most previous studies have focused on the assessment of the environmental risk using physicochemical properties of surface water and mathematical models to predict the health of a watershed. Here, we present a new methodology for evaluating watershed vulnerability using the analytic hierarchy process (AHP) and weighted overlay analysis. The new methodology provides an inexpensive approach for assessing areas that need more investigation based on known factors such hydrogeological, geological, and climate parameters without the need for site-specific physicochemical data. The proposed method was implemented using six main factors that influence water quality: land use, soil type, precipitation, slope, depth to groundwater, and bedrock type. Vulnerability was predicted for ten sub-watersheds within the Eagle Creek Watershed in Indiana using publicly available data input into geographic information system. Combination of watershed susceptibility assessment and GIS spatial analysis tools was used to produce the maps that show the susceptible zones within a watershed. A comparison of the resulting vulnerability estimates showed the expected significant positive correlations with measurements of nitrate, phosphate, temperature, and electrical conductivity. Likewise, the vulnerability estimates negatively correlated with dissolved oxygen and E. coli. Furthermore, the validation of the proposed approach revealed that the areas predicted to have high vulnerability did have lower water quality indices; the results showed a high negative correlation (r = 0.77, p < 0.05) between water quality index (WQI) and vulnerability which strongly suggests this method can be used successfully to assess a watershed's susceptibility.
流域脆弱性和潜在风险特征是评估流域健康的决策支持工具的重要输入。大多数先前的研究都集中在使用地表水的物理化学性质和数学模型来评估环境风险，以预测流域的健康状况。在这里，我们提出了一种使用层次分析法 (AHP) 和加权叠加分析评估流域脆弱性的新方法。该新方法提供了一种廉价的方法，可以根据已知因素（如水文地质、地质和气候参数）评估需要更多调查的区域，而无需特定于地点的物理化学数据。该方法使用影响水质的六个主要因素来实施：土地利用、土壤类型、降水、坡度、地下水深度和基岩类型。使用公共可获得的数据输入地理信息系统，对印第安纳州鹰溪流域的十个次流域进行了脆弱性预测。将流域敏感性评估与 GIS 空间分析工具相结合，生成了显示流域内易感区域的地图。对得出的脆弱性估计值的比较表明，与硝酸盐、磷酸盐、温度和电导率的测量值存在预期的显著正相关。同样，脆弱性估计值与溶解氧和大肠杆菌呈负相关。此外，对所提出方法的验证表明，预测具有高脆弱性的区域确实具有较低的水质指数；结果表明水质指数 (WQI) 和脆弱性之间存在高度负相关 (r = 0.77, p < 0.05)，这强烈表明该方法可成功用于评估流域的敏感性。
