In this study, we used moderate resolution imaging spectroradiometer (MODIS) satellite images to quantify the sedimentation processes in a cascade of six hydropower dams along a 700-km transect in the Paranapanema River in Brazil. Turbidity field measurement acquired over 10 years were used to calibrate a turbidity retrieval algorithm based on MODIS surface reflectance products. An independent field dataset was used to validate the remote sensing estimates showing fine accuracy (RMSE of 9.5 NTU, r = 0.75, N = 138). By processing 13 years of MODIS images since 2000, we showed that satellite data can provide robust turbidity monitoring over the entire transect and can identify extreme sediment discharge events occurring on daily to annual scales. We retrieved the decrease in the water turbidity as a function of distance within each reservoir that is related to sedimentation processes. The remote sensing-retrieved turbidity decrease within the reservoirs ranged from 2 to 62% making possible to infer the reservoir type and operation (storage versus run-of-river reservoirs). The reduction in turbidity assessed from space presented a good relationship with conventional sediment trapping efficiency calculations, demonstrating the potential use of this technology for monitoring the intensity of sedimentation processes within reservoirs and at large scale.
Measurement and evaluation of soil erosion and consequent sediment yield are fundamental in the planning and management of watersheds, as they allow the identification of critical areas susceptible to erosive processes. This study analyzed the sediment yield generated by water erosion in the Indaia River Basin, Alto São Francisco, Minas Gerais, by using the SWAT hydrological model. From a regional/local scale, the initial simulation of the variables (flow and solid discharge) was performed on a monthly scale from 1988 to 2017. Then, parameter-sensitivity analysis, calibration, and validation of the model were executed. In the monthly calibration (1988 to 2007), the performance of the simulations for flow was R2=0.92 and NSE=0.91 and for total solid discharge R2=0.51 and NSE=0.50. In the monthly validation (2008 to 2017) for flow, R2=0.85 and NSE=0.82 was obtained and for total solid discharge R2=0.19 and NSE=0.16. Despite the unsatisfactory result in the validation stage, the model was able to analyze the distribution of sediment production by sub-basins or even by the Hydrologic Response Unit (HRU). Therefore, a sediment-yield map was generated which qualitatively indicated a tendency for greater erosive processes in the central portion of the basin. The results will support public policies mitigating environmental degradation of the Indaia River Basin.
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