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Investigating the impact of conceptual model uncertainty and diverging climate change scenarios on groundwater nitrate concentration predictions

机译:调查概念模型不确定性和不同的气候变化情景对地下水硝酸盐浓度预测的影响

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At the European scale, nitrate concentration is the most important parameter that determines groundwater quality. Since in most cases nitrate input into the aquifer is a non-point source pollution problem, measures to reduce nitrate leaching have to be designed on the aquifer scale. In this context we have coupled the unsaturated, vertical soil water and nitrogen transport model S1MWASER/STOTRASIM with the saturated groundwater flow and transport model FEFLOW in a sequential manner to simulate groundwater nitrate concentrations for the Westliches Leibnitzer Feld aquifer (45 km~2) in southeast Austria. However, in Austria, information about the crops grown is only available as percentages on an aggregated level of cadastral municipalities. Thus, from a conceptual point of view, delineation of the spatial distributions of groundwater recharge and nitrogen leaching time series from arable land are highly uncertain. Within this work, three different approaches consisting of increasing spatial and crop differentiation are employed to investigate the impact on groundwater nitrate concentrations: (ⅰ) grain maize production for the entire model area, (ⅱ) one crop rotation per cadastral municipality, and (ⅲ) a stochastic procedure that accounts for the unknown crop grown and applied nitrogen fertilizer amount on each particular lot. Furthermore, the influence of four climate change projections on groundwater, where the predicted temperature and precipitation time series have been statistically downscaled, is investigated. Different combinations of soil water and nitrate leachates are processed as input distributions to saturated groundwater flow and transport modelling. In terms of mean nitrate leaching concentrations, the prediction uncertainty due to the different approaches of spatial and crop differentiation is significantly larger than that due to climate projections. It is shown that even the two climate projections yielding maximum and minimum groundwater recharge and nitrogen leaching do not meaningfully alter the resulting groundwater nitrate concentrations in general. However, at certain locations mean groundwater nitrate concentrations changes are of the order of 20% until 2100.
机译:在欧洲范围内,硝酸盐浓度是决定地下水质量的最重要参数。由于在大多数情况下,向含水层中输入硝酸盐是一个面源污染问题,因此必须在含水层规模上设计减少硝酸盐浸出的措施。在这种情况下,我们已按顺序将饱和的垂直非饱和土壤水和氮运移模型S1MWASER / STOTRASIM与饱和地下水流和运移模型FEFLOW耦合在一起,以模拟维斯特利奇莱布尼策费尔德含水层(45 km〜2)中的地下水硝酸盐浓度。奥地利东南部。但是,在奥地利,有关作物收成的信息只能以地籍市政总水平的百分比形式获得。因此,从概念上讲,从耕地中确定地下水补给的空间分布和氮的淋洗时间序列非常不确定。在这项工作中,采用了三种不同的方法,包括提高空间和作物的分化程度,以研究对地下水硝酸盐浓度的影响:(ⅰ)整个模型区的谷物玉米产量,(ⅱ)每个地籍市一次作物轮作,和(ⅲ )一种随机程序,用于说明未知的作物生长情况以及在每个特定批次上施用的氮肥量。此外,还研究了四个气候变化预测对地下水的影响,其中预测温度和降水时间序列已按统计方式缩减。将土壤水和硝酸盐渗滤液的不同组合作为饱和地下水流和输运模型的输入分布进行处理。就平均硝酸盐浸出浓度而言,由于空间和作物分化方法不同而产生的预测不确定性明显大于气候预测带来的不确定性。结果表明,即使两个产生最大和最小地下水补给量和氮淋失的气候预测值,也通常不会有意义地改变由此产生的地下水硝酸盐浓度。但是,在某些地方,直到2100年,地下水硝酸盐的平均浓度变化约为20%。

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