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Water is necessary for all biological life and industrial, municipal, agricultural, and residential processes. It is challenging to imagine living without water. Unfortunately, human and natural activities are causing the sources of useable water to become contaminated. Despite having enormous and unique natural water resources, Africa has experienced unprecedented environmental pollution because of the abuse of these resources. Additionally, population increase and urbanization brought by technological advancements have significantly worsened water pollution in Africa. The significant causes of pollution for surface waterways are untreated effluents released into the environment by humans and machines. It is still being determined if the emission goals set by several African countries for surface water discharge have been fulfilled. Wells and boreholes are essential sources of drinking water for Africans. However, because of their location in sterile areas, the natural water quality of these groundwater sources could be better. The primary sources of water pollution in Africa include agricultural activities, mining, roadside discharges, trash from companies and workshops, landfills, and e-waste. Oil leaks are a severe problem in oil-rich African countries. Lake Tanganyika is East Africa's most significant freshwater reservoir, while Lake Victoria is the second-deepest lake in the world. HIGHLIGHTS Evaluate scientific findings on water quality in the lakes on the African continent.; Identify the principal contaminants of surface water.; Pearson Correlation is used to identify the relationship among the water parameters.;

Precipitation plays a critical role in hydrometeorological studies. A predictive analysis of gridded rainfall datasets may provide a cost-effective alternative to conventional rain gauge observations. Here, our objective is to evaluate the performance of satellite and reanalysis precipitation products in the hydrological modeling of a mesoscale watershed. The research also examines the accuracy of hydrological simulations in a sizeable flood-prone watershed in the absence of observed data associated with the myriad water retaining structures present in the catchment. We use three precipitation products, namely Tropical Rainfall Measurement Missions (TRMM) 3B42 Version 7, Climate Forecast System Reanalysis (CFSR), and daily precipitation data recorded at multiple rain gauges in the upper Huai River Basin to simulate streamflow. The Soil & Water Assessment Tool (SWAT) is utilized for runoff modeling, while SWAT-CUP is used to perform sensitivity analysis and to calibrate and validate the simulation results. Nash–Sutcliffe efficiency, percent bias, and Kling-Gupta efficiency (KGE) are employed to evaluate modeling efficiency for three precipitation datasets on different temporal scales. The results indicate that TRMM and CFSR datasets provide satisfactory results on both daily and monthly scales. Specifically, the SWAT model performs better at monthly simulations than daily simulations for all precipitation datasets used. HIGHLIGHTS Examining the applicability of TRMM and CFSR daily precipitation products in simulating runoff from a large watershed.; Calibrating a hydrological model in the absence of data associated with extensive anthropogenic activities for flood prevention and diversion.; Performing streamflow simulations using a SWAT model and parameter calibration and sensitivity analysis using a SUFI-2 algorithm.;

Precipitation plays a critical role in hydrometeorological studies. A predictive analysis of gridded rainfall datasets may provide a cost-effective alternative to conventional rain gauge observations. Here, our objective is to evaluate the performance of satellite and reanalysis precipitation products in the hydrological modeling of a mesoscale watershed. The research also examines the accuracy of hydrological simulations in a sizeable flood-prone watershed in the absence of observed data associated with the myriad water retaining structures present in the catchment. We use three precipitation products, namely Tropical Rainfall Measurement Missions (TRMM) 3B42 Version 7, Climate Forecast System Reanalysis (CFSR), and daily precipitation data recorded at multiple rain gauges in the upper Huai River Basin to simulate streamflow. The Soil & Water Assessment Tool (SWAT) is utilized for runoff modeling, while SWAT-CUP is used to perform sensitivity analysis and to calibrate and validate the simulation results. Nash-Sutcliffe efficiency, percent bias, and Kling-Gupta efficiency (KGE) are employed to evaluate modeling efficiency for three precipitation datasets on different temporal scales. The results indicate that TRMM and CFSR datasets provide satisfactory results on both daily and monthly scales. Specifically, the SWAT model performs better at monthly simulations than daily simulations for all precipitation datasets used. [ABSTRACT FROM AUTHOR]