Effects of uncertainty in soil properties on simulated hydrological states and fluxes at different spatio-temporal scales
Effects of uncertainty in soil properties on simulated hydrological states and fluxes at different spatio-temporal scales
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DOI：
10.5194/hess-21-2301-2017
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发表时间：
2017-05
影响因子：
6.3
通讯作者：
G. Baroni;M. Zink;Rohini Kumar;L. Samaniego;S. Attinger
中科院分区：
文献类型：
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作者：
G. Baroni;M. Zink;Rohini Kumar;L. Samaniego;S. Attinger
抽象的。土壤特性在不同空间尺度上表现出高度异质性，其正确表征仍然是大面积的关键挑战。该研究的目的是量化未解决的土壤空间变异性引起的不同类型的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，这些方法应用于内卡河上游流域（德国）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。通过聚合不同空间和时间尺度的结果来分析模型输出。这些结果表明，当在模型网格分辨率（即 500 m）下分析模拟模型输出时，原始土壤图中引入的不同不确定性的影响是等效的。然而，通过聚合不同空间尺度的状态和通量（通过不同大小的子流域或粗化网格分辨率）可以识别出一些差异。水流仅对长空间结构的扰动敏感，而分布状态和通量（例如土壤湿度和地下水补给）仅对引入原始土壤特性的局部噪声敏感。清晰地识别与更高分辨率的土壤信息相关（或不相关）的时间和空间尺度不太可能具有普遍性。然而，通过收集新的测量数据或通过校准和数据同化方法，可以通过比较对不同水文组成部分的影响来确定特定应用中模型改进的优先顺序。总之，该研究强调了正确表征土壤性质不确定性的重要性。这样，包含有关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强有力的支持。
Abstract. 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. 500 m). 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.