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首页> 外文期刊>Hydrology and Earth System Sciences >Quantifying water and salt fluxes in a lowland polder catchment dominated by boil seepage: A probabilistic end-member mixing approach
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Quantifying water and salt fluxes in a lowland polder catchment dominated by boil seepage: A probabilistic end-member mixing approach

机译:量化以沸腾渗漏为主的低地田流域中的水和盐通量:一种概率性的末端成员混合方法

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摘要

Upward saline groundwater seepage is leading to surface water salinization of deep lying polders in the Netherlands. Identifying measures to reduce the salt content requires a thorough understanding and quantification of the dominant sources of water and salt on a daily basis. However, as in most balance studies, there are large uncertainties in the contribution from groundwater seepage. Taking these into account, we applied a probabilistic (GLUE) end-member mixing approach to simulate two years of daily to weekly observations of discharge, salt loads and salt concentration of water pumped out of an artificially drained polder catchment area. We were then able to assess the contribution from the different sources to the water and salt balance of the polder and uncertainties in their quantification. Our modelling approach demonstrates the need to distinguish preferential from diffuse seepage. Preferential seepage via boils contributes, on average, 66 % to the total salt load and only about 15 % to the total water flux into the polder and therefore forms the main salinization pathway. With the model we were able to calculate the effect of future changes on surface water salinity and to assess the uncertainty in our predictions. Furthermore, we analyzed the parameter sensitivity and uncertainty to determine for which parameter the quality of field measurements should be improved to reduce model input and output uncertainty. High frequency measurements of polder water discharge and weighted concentration at the outlet of the catchment area appear to be essential for obtaining reliable simulations of water and salt fluxes and for allotting these to the different sources.
机译:向上的盐碱地下水渗漏导致荷兰深层deep的地表水盐化。确定减少盐含量的措施需要每天对水和盐的主要来源进行全面的了解和量化。但是,与大多数平衡研究一样,地下水渗入的贡献也有很大的不确定性。考虑到这些因素,我们采用了概率(GLUE)终端成员混合方法,模拟了从人工排水的田集水区抽出的水的流量,盐负荷和盐浓度的两年至每天的观察。然后,我们能够评估不同来源对田水和盐分平衡的贡献及其定量的不确定性。我们的建模方法表明需要区分优先渗透和弥散渗透。通过沸腾产生的优先渗透平均占总盐分的66%,仅占到into田总水通量的15%,因此形成了主要的盐化途径。利用该模型,我们能够计算出未来变化对地表水盐度的影响,并能够评估我们预测中的不确定性。此外,我们分析了参数的灵敏度和不确定性,以确定应提高现场测量质量的参数,以减少模型输入和输出的不确定性。对于获得可靠的水和盐通量模拟并将它们分配给不同的水源,对area水排放量和集水区出口处的加权浓度进行高频测量似乎至关重要。

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