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Effects of uncertainty in soil properties on simulated hydrological states and fluxes at different spatio-temporal scales

机译:不同时空尺度下土壤性质的不确定性对模拟水文状态和通量的影响

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pstrongAbstract./strong Soil properties show high heterogeneity at different spatial scales and their correct characterization remains a crucial challenge over large areas. The aim of the study is to quantify the impact of different types of uncertainties that arise from the unresolved soil spatial variability on simulated hydrological states and fluxes. Three perturbation methods are presented for the characterization of uncertainties in soil properties. The methods are applied on the soil map of the upper Neckar catchment (Germany), as an example. The uncertainties are propagated through the distributed mesoscale hydrological model (mHM) to assess the impact on the simulated states and fluxes. The model outputs are analysed by aggregating the results at different spatial and temporal scales. These results show that the impact of the different uncertainties introduced in the original soil map is equivalent when the simulated model outputs are analysed at the model grid resolution (i.e. 500span class="thinspace"/spanm). However, several differences are identified by aggregating states and fluxes at different spatial scales (by subcatchments of different sizes or coarsening the grid resolution). Streamflow is only sensitive to the perturbation of long spatial structures while distributed states and fluxes (e.g. soil moisture and groundwater recharge) are only sensitive to the local noise introduced to the original soil properties. A clear identification of the temporal and spatial scale for which finer-resolution soil information is (or is not) relevant is unlikely to be universal. However, the comparison of the impacts on the different hydrological components can be used to prioritize the model improvements in specific applications, either by collecting new measurements or by calibration and data assimilation approaches. In conclusion, the study underlines the importance of a correct characterization of uncertainty in soil properties. With that, soil maps with additional information regarding the unresolved soil spatial variability would provide strong support to hydrological modelling applications./p.
机译:> >摘要。土壤特性在不同的空间尺度上表现出高度的异质性,它们的正确表征仍然是大面积地区的关键挑战。该研究的目的是量化由未解决的土壤空间变异性引起的不同类型不确定性对模拟水文状态和通量的影响。提出了三种扰动方法来表征土壤性质的不确定性。例如,将这些方法应用于上内卡河流域的土壤图。不确定性通过分布式中尺度水文模型(mHM)传播,以评估对模拟状态和通量的影响。通过汇总不同时空尺度上的结果来分析模型输出。这些结果表明,当以模型网格分辨率(即500 class =“ thinspace”> m)分析模拟的模型输出时,原始土壤图中引入的不同不确定性的影响是等效的。但是,通过汇总不同空间尺度上的状态和通量(通过不同大小的子汇水面积或粗化网格分辨率)可以识别出一些差异。径流仅对长空间结构的扰动敏感,而分布状态和通量(例如土壤水分和地下水补给)仅对引入原始土壤属性的局部噪声敏感。对较精细的土壤信息是相关的(或不相关的)时间和空间尺度的清晰识别不太可能是普遍的。但是,通过收集新的测量值或通过校准和数据同化方法,可以将对不同水文要素影响的比较用于确定特定应用中模型改进的优先级。总之,这项研究强调了正确表征土壤性质不确定性的重要性。这样,带有未解决的土壤空间变异性的附加信息的土壤图将为水文建模应用提供有力的支持。

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