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Assessment of catchment response and calibration of a hydrological model using high-frequency discharge-nitrate concentration data

机译:利用高频硝酸盐浓度数据评估流域响应并建立水文模型

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This study uses a high-frequency discharge and nitrate concentration dataset from the Weida catchment in Germany for the catchment scale hydrologic response analysis. Nitrate transport in the catchment is mostly conservative as indicated by the nitrate stable isotope (δ~(15)N and δ~(18)O) analysis. Discharge-nitrate concentration data from the catchment show distinctive patterns, suggesting flushing and dilution response. A self-organizing feature map-based methodology was employed to identify such patterns or cluster in the datasets. Based on knowledge of the catchment conditions and prevailing understanding of discharge-nitrate concentration relationship, the clusters were characterized into five qualitative flow responses: (1) baseflow; (2) subsurface flow increase; (3) surface runoff increase; (4) surface runoff recession; and (5) subsurface flow decrease. Such qualitative flowpaths were used as soft data for a multi-objective calibration of a hydrological model (WaSiM-ETH). The calibration led to a reasonable simulation of overall discharge (Nash-Sutcliffe coefficient: 0.84) and qualitative flowpaths (76% agreement). A prerequisite for using such methodology is limited biogeochemical transformation of nitrate (such as denitrification).
机译:本研究使用德国Weida流域的高频流量和硝酸盐浓度数据集进行流域规模水文响应分析。如硝酸盐稳定同位素(δ〜(15)N和δ〜(18)O)分析所示,流域中的硝酸盐运移大多是保守的。流域的硝酸盐排放浓度数据显示出独特的模式,表明冲洗和稀释反应。使用基于自组织特征图的方法来识别数据集中的这种模式或聚类。基于对流域条件的了解和对排放物-硝酸盐浓度关系的普遍了解,将这些聚类描述为五个定性的流动响应:(1)基流; (2)地下流量增加; (3)地表径流增加; (4)地表径流衰退; (5)地下流量减少。这些定性流径被用作软数据,用于水文模型(WaSiM-ETH)的多目标校准。通过校准,可以对总排放量(纳什-苏克利夫系数:0.84)和定性流径(一致性为76%)进行合理的模拟。使用这种方法的先决条件是硝酸盐的有限生物地球化学转化(例如反硝化)。

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