Estimation of Water Surface Reflectance and Total Suspended Solid Using MODIS Images for a Reservoir in the Brazilian Semiarid Region.

Reservoirs are essential sources to ensure water supply, especially in regions with a semiarid climate, prone to prolonged drought periods and water scarcity. An exemplary case is the semiarid region of Paraíba State, Brazil. Monitoring of water surface reflectance (WSR) and total suspended solids (TSS) is indispensable to address issues such as erosion, sediment transport, depo sition, reservoir siltation, water pollution, and associated human health risks, ultimately aiding in water resources management. This study introduced a novel approach to estimating the spatiotemporal dynamics of WSR and TSS, utilizing automated methods and MODIS images over 17 years (2000 ~ 2016) for the Epitácio Pessoa Reservoir. Three models, (a) model 1 (M1), (b) model 2 (M2), and (c) model 3 (M3), were employed to estimate WSR and TSS, chosen for their replicability, mathematical simplicity, and ecosystem similarity. A total of 775 images from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite, along with observed data, were used for the estimation. Model M3 yielded the best performance for estimating TSS, with values ranging from 270 ~ 961 mg/L (r = 0.57). Furthermore, a strong correlation (r > 0.93) was observed between the mean reflectance values for pixels sampled using two distinct extraction procedures (longitudinal profile and specific sampling points). This strong correlation underscores the potential utility of MODIS images for effective monitoring of WSR and TSS in comparatively smaller bodies of water in the Brazilian semiarid region. Importantly, this study represents one of the first applications for estimating WSR and TSS for a reservoir situated in a semiarid climate region. The estimates of WSR and TSS could hold significant implications for environmental monitoring and water management of such reservoirs. In conclusion, automated estimation of WSR and TSS could serve as a valuable tool for decision-makers in predicting silting, sediment yield, and reservoir water quality. [ABSTRACT FROM AUTHOR]