Sensitivity of bias correction step on generating hydrological scenarios

Étienne Guilpart, Vahid Espanmanesh, A. Tilmant, Marc-André Bourgault
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Abstract

Significant shifts in hydro-climatic regimes are expected in many parts of the world during the 21st century, affecting the water cycle. Vulnerability, impact, and adaptation studies often use tailored modeling chains to assess the expected effects of climate change, but the robustness of these chains is rarely investigated. This highlights the need for more rigorous evaluation of modeling chains to ensure that they are reliable for informed decision-making processes. To address this gap, we propose a framework for evaluating the sensitivity of hydrological scenario production to the bias correction step. We apply the framework to the Senegal River Basin, using three bias correction methods (linear scale, empirical quantile mapping, and nested bias correction) and three procedures (climate-correction, hydrological-correction, and climate-hydrological-correction). Our results show that the choice of modeling chain has a significant impact on future hydro-climatic trajectories. In particular, the combination of climate-and-hydrological-correction procedures may be optimal when both climate biases and hydrological model errors are significant. Moreover, using multiple bias correction methods can strengthen the ensemble of future hydro-climatic conditions. These findings have implications for vulnerability-impact-adaptation studies and underscore the importance of rigorous modeling chain design and sensitivity analysis.
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偏差修正步骤对生成水文情景的敏感性
预计 21 世纪世界许多地区的水文气候系统将发生重大变化,影响水循环。脆弱性、影响和适应研究通常使用定制的建模链来评估气候变化的预期影响,但很少对这些建模链的稳健性进行调查。这凸显了对建模链进行更严格评估的必要性,以确保它们在知情决策过程中的可靠性。为了弥补这一不足,我们提出了一个评估水文情景制作对偏差修正步骤敏感性的框架。我们将该框架应用于塞内加尔河流域,使用了三种偏差校正方法(线性比例尺、经验量子图和嵌套偏差校正)和三种程序(气候校正、水文校正和气候-水文校正)。我们的研究结果表明,建模链的选择对未来的水文气候轨迹有重大影响。特别是,当气候偏差和水文模型误差都很大时,气候-水文-校正程序的组合可能是最佳选择。此外,使用多种偏差校正方法可以加强对未来水文气候条件的综合分析。这些发现对脆弱性-影响-适应研究具有重要意义,并强调了严格的建模链设计和敏感性分析的重要性。
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