The changing trend in nitrate concentrations in major aquifers due to historical nitrate loading from agricultural land across England and Wales from 1925 to 2150.
The changing trend in nitrate concentrations in major aquifers due to historical nitrate loading from agricultural land across England and Wales from 1925 to 2150.
复制标题
DOI：
10.1016/j.scitotenv.2015.10.127
复制
发表时间：
2016-01
期刊：
影响因子：
--
通讯作者：
Lei Wang;Marianne Stuart;Melinda Lewis;Rob Ward;D. Skirvin;P. Naden;Adrian L. Collins;M. Ascott
中科院分区：
文献类型：
--
作者：
Lei Wang;Marianne Stuart;Melinda Lewis;Rob Ward;D. Skirvin;P. Naden;Adrian L. Collins;M. Ascott
硝酸盐是农业生产力所必需的，但如果释放到水生系统中可能会造成相当大的问题。农田是英国地下水中硝酸盐的主要来源。由于地下水系统的长时间滞后，从土壤中淋溶出的硝酸盐可能需要几十年的时间才能排放到淡水中。然而，这种硝酸盐时滞在环境水管理中很少被考虑。在此背景下，本文提出了一种在全国范围内模拟地下水硝酸盐浓度的方法，以模拟历史农业用地硝酸盐负荷对地下水硝酸盐浓度演变的影响。为英格兰和威尔士重要含水层的饱和地带建造了另一个基于流程的组成部分。这使用了一个简单的流动模型，该模型需要建模的补给值，以及已公布的含水层属性和厚度数据。还引入了一个空间分布和时间可变的硝酸盐输入函数。利用蒙特卡罗模拟对参数的敏感性进行了分析。该模型使用国家硝酸盐监测数据进行了校准。生成了28个选定含水层区域的年平均硝酸盐浓度时间序列以及1925年至2150年的年度空间分布硝酸盐浓度图。结果表明，16个含水层带硝酸盐浓度呈上升趋势，其余12个含水层带平均硝酸盐浓度呈下降趋势。这一结果也表明地下水硝酸盐通过基流进入河流的趋势。因此，该模型使地下水硝酸盐响应的规模和时间尺度能够纳入来源分配工具，并与减少硝酸盐损失的土地管理备选方案的当前规划一起考虑。
Nitrate is necessary for agricultural productivity, but can cause considerable problems if released into aquatic systems. Agricultural land is the major source of nitrates in UK groundwater. Due to the long time-lag in the groundwater system, it could take decades for leached nitrate from the soil to discharge into freshwaters. However, this nitrate time-lag has rarely been considered in environmental water management. Against this background, this paper presents an approach to modelling groundwater nitrate at the national scale, to simulate the impacts of historical nitrate loading from agricultural land on the evolution of groundwater nitrate concentrations. An additional process-based component was constructed for the saturated zone of significant aquifers in England and Wales. This uses a simple flow model which requires modelled recharge values, together with published aquifer properties and thickness data. A spatially distributed and temporally variable nitrate input function was also introduced. The sensitivity of parameters was analysed using Monte Carlo simulations. The model was calibrated using national nitrate monitoring data. Time series of annual average nitrate concentrations along with annual spatially distributed nitrate concentration maps from 1925 to 2150 were generated for 28 selected aquifer zones. The results show that 16 aquifer zones have an increasing trend in nitrate concentration, while average nitrate concentrations in the remaining 12 are declining. The results are also indicative of the trend in the flux of groundwater nitrate entering rivers through baseflow. The model thus enables the magnitude and timescale of groundwater nitrate response to be factored into source apportionment tools and to be taken into account alongside current planning of land-management options for reducing nitrate losses.