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:从农业到采矿,到能源,地表水质监测是一项基本任务。随着石油和天然气操作者努力减少淡水的消耗量,积极管理淡水和非淡水资源越来越重要。对于大规模监测而言,许多地点的人工取样工作已变得过于耗时和不可持续,因为分散的池塘、小湖泊、花环和湿地在大面积地区数量众多,因此,卫星环境监测具有巨大潜力。许多现有的卫星监测研究利用基于指数的方法来监测河流和海洋等大型水体。然而,在监测小型水体收到的小型水池反射信号时,这些现有方法已变得过于薄弱,无法探测。为了应对这一挑战,我们提出了一个新的水质强化指数模式,其目的是使用户能够确定水体中的污染程度,反映模式薄弱。我们的结果表明:(1) 水质量监测是水状况的一个良好指标,用实验室测量的1200个水样进行验证。通过将我们的方法应用于共同获得的卫星数据(例如,LandSA-S-S-AQ-S-AQ-E-I),可以提供高质量的高质量水储存工具。一个高准确性地质量的系统,可以在水库中提供高质量监测。在水质量中提供高质量和高质量数据。