From agriculture to mining, to energy, surface water quality monitoring is an essential task. As oil and gas operators work to reduce the consumption of freshwater, it is increasingly important to actively manage fresh and non-fresh water resources over the long term. For large-scale monitoring, manual sampling at many sites has become too time-consuming and unsustainable, given the sheer number of dispersed ponds, small lakes, playas, and wetlands over a large area. Therefore, satellite-based environmental monitoring presents great potential. Many existing satellite-based monitoring studies utilize index-based methods to monitor large water bodies such as rivers and oceans. However, these existing methods fail when monitoring small ponds-the reflectance signal received from small water bodies is too weak to detect. To address this challenge, we propose a new Water Quality Enhanced Index (WQEI) Model, which is designed to enable users to determine contamination levels in water bodies with weak reflectance patterns. Our results show that 1) WQEI is a good indicator of water turbidity validated with 1200 water samples measured in the laboratory, and 2) by applying our method to commonly available satellite data (e.g. LandSat8), one can achieve high accuracy water quality monitoring efficiently in large regions. This provides a tool for operators to optimize the quality of water stored within surface storage ponds and increasing the readiness and availability of non-fresh water.

翻译：从农业到矿业，再到能源行业，地表水质监测都是一项基本任务。随着油气运营商努力减少淡水消耗，长期主动管理淡水和非淡水资源变得愈发重要。对于大规模监测而言，由于大面积分散的池塘、小型湖泊、干盐湖和湿地的数量庞大，人工采样已变得过于耗时且不可持续。因此，基于卫星的环境监测展现出巨大潜力。许多现有的卫星监测研究采用基于指数的方法来监测河流、海洋等大型水体。然而，这些现有方法在监测小型池塘时会失效——从小型水体接收到的反射信号过于微弱而难以检测。为应对这一挑战，我们提出了一种新型水质增强指数（WQEI）模型，该模型旨在使用户能够确定具有弱反射模式水体的污染程度。我们的结果表明：1）经实验室测量的1200份水样验证，WQEI是水体浊度的良好指标；2）通过将我们的方法应用于常用卫星数据（如Landsat8），可以在大区域内实现高效高精度的水质监测。这为运营商提供了一种工具，用以优化地表蓄水池中储存的水质，并提高非淡水的可用性和可获取性。