Accurate assessment of water resources at the watershed level is crucial for effective integrated watershed management. While semi-distributed/distributed models require complex structures and large amounts of input data, conceptual models have gained attention as an alternative to watershed modeling. In this paper, the performance of the GR4J conceptual model for runoff simulation in the Gambia watershed at Simenti station is analyzed over the calibration (1981–1990) and validation period (1991–2000 and 2001–2010). The main inputs to conceptual models like GR4J are daily precipitation data and potential evapotranspiration (PET) measured from the same catchment or a nearby location. Calibration of these models is typically performed using the Nash–Sutcliffe daily efficiency with a bias penalty as the objective function. In this case, the GR4J model is calibrated using four optimization parameters. To evaluate the effectiveness of the model's runoff predictions, various statistical measures such as Nash–Sutcliffe efficiency, coefficient of determination, bias, and linear correlation coefficient are calculated. The results obtained in the Gambia watershed at Simenti station indicate satisfactory performance of the GR4J model in terms of forecast accuracy and computational efficiency. The Nash–Sutcliffe (Q) values are 0.623 and 0.711 during the calibration period (1981–1990) and the validation period (1991–2000), respectively. The average annual flow observed during the calibration period is 0.385 mm while it increases with a value of 0.603 mm during the validation period. As for the average flow simulated by the model, it is 0.142 mm during the calibration period (i.e., a delay of 0.142 mm compared to the observed flow), 0.626 mm in the validation period (i.e., an excess of 0.023 mm compared to the observed flow). However, this study is significant because it shows significant changes in all metrics in the watershed sample under different scenarios, especially the SSP245 and SSP585 scenarios over the period 2021–2100. These changes suggest a downward trend in flows, which would pose significant challenges for water management. Therefore, it is clear that sustainable water management would require substantial adaptation measures to cope with these changes.

准确评估流域水资源对于有效的流域综合管理至关重要。虽然半分布式/分布式模型需要复杂的结构和大量的输入数据，但概念模型作为分水岭建模的替代方案而受到关注。本文对冈比亚流域 Simenti 站径流模拟的 GR4J 概念模型在校准期（1981-1990 年）和验证期（1991-2000 年和 2001-2010 年）的性能进行了分析。GR4J 等概念模型的主要输入是每日降水数据和从同一流域或附近位置测量的潜在蒸散量 (PET)。这些模型的校准通常使用 Nash–Sutcliffe 日效率和偏差罚分作为目标函数来执行。在本例中，GR4J 模型使用四个优化参数进行校准。为了评估模型径流预测的有效性，计算了纳什-萨特克利夫效率、决定系数、偏差和线性相关系数等各种统计指标。在冈比亚流域Simenti站获得的结果表明GR4J模型在预报精度和计算效率方面表现令人满意。校准期 (1981-1990) 和验证期 (1991-2000) 期间的 Nash–Sutcliffe (Q) 值分别为 0.623 和 0.711。校准期间观测到的年平均流量为0.385毫米，而验证期间则增加了0.603毫米。对于模型模拟的平均流量，校准期间为0.142 mm（即与观测流量相比延迟了0.142 mm），验证期间为0.626 mm（即与观测流量相比超出了0.023 mm）。观察到的流量）。然而，这项研究意义重大，因为它显示了不同情景下流域样本中所有指标的显着变化，特别是2021-2100年期间的SSP245和SSP585情景。这些变化表明流量呈下降趋势，这将对水资源管理构成重大挑战。因此，可持续水管理显然需要大量的适应措施来应对这些变化。