ABSTRACT

The estimation of total suspended matter (TSM) concentration is crucial in monitoring, evaluating, and protecting water quality. Many empirical and semi-analytical models have been established for clear or extremely turbid water bodies; however, only a few are applicable to inland, extremely turbulent deep rivers. Using in situ data from the water of the Manwan reservoir, we developed a robust algorithm to estimate the TSM concentration in the Manwan reservoir, with a root mean square error (RMSE) ≤ 4.43 mg L⁻¹ and a mean absolute percentage error (MAPE) of 23.2%, indicating the feasibility of the empirical model for estimating TSM. The empirical model was then applied to 251 Small Satellite Constellation for Environment and Disaster Monitoring and Forecasting loaded with the Charge Coupled Device (HJ-CCD) images to derive TSM distribution maps from 2009 to 2018. The estimated TSM concentrations exhibited significant spatial and seasonal changes, revealing relationships among TSM, wind speed, and precipitation. The spatial heterogeneity was significantly higher downstream than upstream in the reservoir due to watershed inputs and anthropogenic dredging activity. The temporal heterogeneity of TSM, significantly higher in summer and autumn than in winter and spring, was mainly caused by seasonal rainfall. Our study shows that the empirical model for HJ-CCD images can be used to quantitatively monitor the TSM in inland rivers.

摘要

总悬浮物（TSM）浓度的估算对于监测，评估和保护水质至关重要。对于清澈或极其浑浊的水体，已经建立了许多经验和半分析模型。但是，只有少数几个适用于内陆湍急的深河。利用来自漫湾水库水的原位数据，我们开发了一种鲁棒的算法来估算漫湾水库中的TSM浓度，均方根误差（RMSE）≤4.43 mg L ^-1平均绝对百分比误差（MAPE）为23.2％，表明经验模型用于估算TSM。然后将经验模型应用于251个小卫星星座，用于环境和灾害监测与预报，并加载了电荷耦合器件（HJ-CCD）图像，以得出2009年至2018年的TSM分布图。估计的TSM浓度表现出明显的空间和季节变化，揭示了TSM，风速和降水之间的关系。由于集水区输入和人为疏activity活动，水库下游的空间异质性明显高于上游。在夏季和秋季，TSM的时间异质性明显高于冬季和春季，这主要是由季节性降雨引起的。