The Moulouya basin in Morocco is one of many river basins around the world that are regulated with physical flow control, a range of regulations and storage structures. The water budget of the basin is unbalanced; the available water resources are insufficient for agricultural productivity, nature conservation and ecosystem services. This study evaluates spatial and temporal distributions of actual evapotranspiration, groundwater recharge and surface runoff for the period 2000–2020 using the WetSpass-M model in the Moulouya basin, Morocco. The WetSpass-M model’s input data are created in grid maps with the ArcGIS tool. They include monthly meteorological parameters (e.g., temperature, wind speed, rainfall,), soil map, land cover, topography, slope and groundwater depth. A good correlation has been observed between the simulated groundwater recharge and base flow, with the value of R2 = 0.98. The long-term spatial and temporal average annual precipitation of 298 mm is distributed as 45 mm (15.1%) groundwater recharge and 44 mm (14.8%) surface runoff, while 209 mm (70.1%) is lost through evapotranspiration. The simulated results showed that the average groundwater recharge of 15.1 mm (30%) falls during the summer and spring seasons, while the remaining 29.5 mm (70%) occurs during the winter and autumn seasons. Annually, 2430 million m3 of water recharges to the groundwater system from the rainfall for the entire basin. The study’s findings would help local stakeholders and policymakers in developing sustainable and effective management of available surface water and groundwater resources in the Moulouya basin.
Urban surfaces are often covered by impermeable materials such as concrete and asphalt which intensify urban runoff and pollutant concentration during storm events, and lead to the deterioration of the quality of surrounding water bodies. Detention ponds are used in urban stormwater management, providing two-fold benefits: flood risk reduction and pollution load minimization. This paper investigates the performance of nine proposed detention ponds (across the city of Renton, Washington, USA) under different climate change scenarios. First, a statistical model was developed to estimate the pollutant load for the current and future periods and to understand the effects of increased rainfall on stormwater runoff and pollutant loads. The Personal Computer Storm Water Management Model (PCSWMM) platform is employed to calibrate an urban drainage model for quantifying stormwater runoff and corresponding pollutant loads. The calibrated model was used to investigate the performance of the proposed nine (9) detention ponds under future climate scenarios of 100-year design storms, leading to identifying if they are likely to reduce stormwater discharge and pollutant loads. Results indicated significant increases in stormwater pollutants due to increases in rainfall from 2023 to 2050 compared to the historical period 2000–2014. We found that the performance of the proposed detention ponds in reducing stormwater pollutants varied depending on the size and location of the detention ponds. Simulations for the future indicated that the selected detention ponds are likely to reduce the concentrations (loads) of different water quality constituents such as ammonia (NH3), nitrogen dioxide (NO2), nitrate (NO3), total phosphate (TP), and suspended solids (SS) ranging from 18 to 86%, 35–70%, 36–65%, 26–91%, and 34–81%, respectively. The study concluded that detention ponds can be used as a reliable solution for reducing stormwater flows and pollutant loads under a warmer future climate and an effective adaptation option to combat climate change related challenges in urban stormwater management.
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