The sub-tropical region of West Africa is not only vulnerable to the negative effects of climate change but also to the changes in land management. The goal of this study was to model streamflow in the Mono River Basin (MRB) for the period before (1964–1986) and after (1988–2011) dam construction. The Soil and Water Assessment Tool (SWAT) using input data such as a digital elevation model, soil and land use, and daily climate data model was set up, calibrated and validated for the period before dam construction (SIM1) and after dam construction (SIM2). The model sensitivity analysis, calibration and uncertainty analysis were performed based on daily observed streamflow using the Sequential Uncertainty Fitting procedure (SUFI-2) algorithm. The change in seasonal and annual streamflow between SIM1 and SIM2 was assessed and linked with land use/cover change between 1975 and 2000. The SWAT model shows satisfactory performance with Kling-Gupta Efficiency (KGE) ≥ 0.60 and percent bias |PBIAS| ≤ ±20 during calibration and KGE ≥ 0.50 and |PBIAS| ≤ ±15 during validation of SIM1 and SIM2. The results further showed that the construction of the dam affected the hydrological system of the catchment with a change in annual average streamflow between SIM1 and SIM2 of −14.13%, −19.86% and 3.66% at Athiéme, Tététou and Corrokope stations, respectively. The simulated average streamflow amplitude of SIM2 has decreased globally compared to SIM1. Therefore, the changes detected in land use/cover may have affected the average streamflow in response to the difference in amplitude simulated streamflow of SIM1 and SIM2. The finding of this analysis demonstrated that the impacts of dam construction on streamflow are challenging and crucial for water resource management in MRB.

The Intergovernmental Panel on Climate Change has predicted that sub-tropical regions are more vulnerable to climate change’s negative effects (CC). Additionally, to CC, land use and land cover (LULC) changes and dam construction, often neglected, play an important role in the spatial and temporal distribution of water balance components (WBC) for agricultural production and socio-ecological equilibrium. This study aimed to analyze and compare the changes in LULC and WBC for the period before Nangbéto dam construction (1964–1986) and the period after its construction (1988–2010) in the Mono River Basin (MRB). To this end, the study used mainly WBC extracted from the validated Soil and Water Assessment Tool and LULC data of 1975–2000 in the MRB to explore their temporal distributions and the link in their changes. The results showed that mean actual monthly evapotranspiration, percolation, water yield, surface runoff, groundwater, and lateral flow represent 51%, 17.5%, 15.9%, 9.4%; 5.7% and 0.4%, respectively, of total water balance between 1964 and 1986. The same components represented 51%, 9.1%, 20.4%, 6.3%, 10.6% and 2.6%, respectively, between 1988 and 2010. The contribution of these WBC in the mean-annual (1964–1986) period was for actual evapotranspiration (31.3%), water yield (25.9%), percolation (17.7%), groundwater (14.71%), surface runoff (9.94%) and lateral flow (0.40%). Meanwhile, between 1988 and 2010, the contribution of actual evapotranspiration, water yield, percolation, groundwater, surface runoff and lateral flow is 49.8%,19.9%, 11.2%, 10.3%, 6.1%, and 2.5%, respectively. The results showed that the peaks of the actual evapotranspiration, surface runoff, percolation and water yield appeared in September, corresponding to a month after the maximum rainfall in August. However, our more detailed analysis showed that a significant decrease in forest and savanna and an increase in croplands led to a decrease in actual evapotranspiration and lateral flow over the second simulation period compared to the first period of simulation over the MRB scale. These findings showed that sustainable management and conservation of natural vegetation are crucial for integrated water resource management and conservation in MRB.

This study aims to assess simulated surface runoff before and after dam construction in the Mono catchment (West Africa) using two lumped models: GR4J (Rural Engineering with 4 Daily Parameters) and IHACRES (Identification of unit Hydrographs and Component flows from Rainfall, Evapotranspiration and Stream data) over two different periods (1964–1986 and 1988–2010). Daily rainfall, mean temperature, evapotranspiration and discharge in situ data were collected for the period 1964–2010. After the model's initialization, calibration and validation; performances analysis have been carried out using multi-objectives functions developed in R software (version 3.5.3). The results indicate that statistical metrics such as the coefficient of determination (R²), the Kling–Gupta Efficiency (KGE), the Nash–Sutcliffe coefficient (NSE) and the Percent of Bias (PBIAS) provide satisfactory insights over the first period of simulation (1964–1986) and low performances over the second period of simulation (1988–2010). In particular, IHACRES model underestimates extreme high runoff of Mono catchment between 1964 and 1986. Conversely, GR4J model overestimates extreme high runoff and has been found to be better for runoff prediction of the river only between 1964 and 1986. Moreover, the study deduced that the robustness of runoff simulation between 1964 and 1986 is better than between 1988 and 2010. Therefore, the weakness of simulated runoff between 1988 and 2010 was certainly due to dam management in the catchment. The study suggests that land cover changes impacts, soil proprieties and climate may also affect surface runoff in the catchment.