It is a challenge for hydrological models to capture complex processes in a basin with limited data when estimating model parameters. This study aims to contribute in this field by assessing the impact of incorporating spatial dimension on the improvement of model calibration. Hence, the main objective of this study was to evaluate the impact of multi-gauge calibration in hydrological model calibration for Ikizdere basin, Black Sea Region in Turkey. In addition, we have incorporated the climate change impact assessment for the study area. Four scenarios were tested for performance assessment of calibration: (1) using downstream flow data (DC), (2) using upstream data (UC), (3) using upstream and downstream data (Multi-Gauge Calibration – MGC), and (4) using upstream and then downstream data (UCDC). The results have shown that using individual gauges for calibration (1 and 2) improve the local predictive capacity of the model. MGC calibration significantly improved the model performance for the whole basin unlike 1 and 2. However, the local gauge calibrations statistical performance, compared to MGC outputs, was better for local areas. The UCDC yields the best model performance and much improved predictive capacity. Regarding the climate change, we did not observe an agreement amongst the future climate projections for the basin towards the end of the century.

在估算模型参数时，水文模型要用有限的数据捕获流域中的复杂过程是一个挑战。这项研究旨在通过评估合并空间尺寸对改进模型校准的影响来为该领域做出贡献。因此，本研究的主要目的是评估多规格校准对土耳其黑海地区伊基兹德河流域水文模型校准的影响。此外，我们已将研究区域的气候变化影响评估纳入其中。测试了四种情况下的校准性能评估：（1）使用下游流量数据（DC），（2）使用上游数据（UC），（3）使用上游和下游数据（多仪表校准– MGC），以及（ 4）先使用上游数据，再使用下游数据（UCDC）。结果表明，使用单独的量规进行校准（1、2）可以提高模型的局部预测能力。与1和2不同，MGC校准显着改善了整个盆地的模型性能。但是，与MGC输出相比，局部仪表校准的统计性能对局部区域更好。UCDC产生了最佳的模型性能并大大提高了预测能力。关于气候变化，到本世纪末，我们对该盆地的未来气候预测并未达成共识。在当地比较好。UCDC产生了最佳的模型性能并大大提高了预测能力。关于气候变化，到本世纪末，我们对该盆地的未来气候预测并未达成共识。在当地比较好。UCDC产生了最佳的模型性能并大大提高了预测能力。关于气候变化，到本世纪末，我们对该盆地的未来气候预测并未达成共识。