The silting process of urban reservoirs has been occurring in many regions across the world. However, identifying the main sources of sediment and controlling the silting process in urban reservoirs are still unsolved problems in many regions, mainly in developing countries such as Brazil. In this study, we identify which land use most influences the siltation of reservoirs, and how the different tributary streams contribute to this process in two urban reservoirs located in Campo Grande, Midwestern Brazil. Thus, we applied a sediment source fingerprinting (SSF) approach, associated with land use analysis, and the bathymetric data of reservoirs connected to the stream and drainage network, obtained between the years 2008 and 2018. The reduction in the volume and area of the reservoir during the study period were 45% and 39%, respectively. We found a proportional relationship between the reduction in the reservoir volume and the increase in the impermeable areas of the studied basin. We also noted that the sediments deposited in the reservoir originate from bare soil, banks, and bed in the proportions of 46.9%, 37.1%, and 17.2%, respectively. Our findings show that the use of bathymetric surveys and data on land use and land cover, associated with the source tracing technique, are useful alternatives to identifying sediment mobility in urban basins, especially in those where the drainage network is connected to water courses. We conclude that the factors that most contribute to the silting up of reservoirs are the erosion of banks and beds, sediment remobilization and the connectivity of the drainage network with water courses.
To improve the use of soil and its conservation, precipitation data are necessary. With the Universal Soil Loss Equation (USLE), the study of historical precipitation series is a main factor, but in these series, there are gaps that need to be filled. This study had, as a basis, the methods of weighted likelihood, multiple regression, and weighted likelihood based on multiple regression to fill the gaps of the rainfall data for the rainfall gauges in the Brazilian biomes (Cerrado and Pantanal, municipalities of Campo Grande,
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