Estimation of recharge and nutrient leaching at different scales to improve sustainable land and groundwater management

一千万加拿大人依靠地下水作为饮用水源。这种资源不断受到污染的威胁。这是一个日益严重的问题；一项关于加拿大农业环境可持续性的研究报告称，由于化肥用量增加，加拿大各地的水质下降（Eilers等，2010）。因此，Frost在2006年报告说，马尼托巴省大约16%的供水井的硝酸盐含量超过了饮用水标准（10毫克/升NO3-N）。污染物的淋滤受不饱和带的通量控制。季节气候变化导致补给的时空分布发生极端变化。加拿大大草原在融雪和土壤融化期间出现了基于事件的循环补给，其特点是水通量快。快通量意味着高污染风险。这与目前用来确定风险的平均水文条件形成对比。地下水模型是对风险进行量化、评价和预测的重要工具。目前包含气候变率的模型需要大量的时空输入数据来可靠地预测未来状态，因此不能准确地预测地下水污染风险以实现可持续土地和地下水管理。拟议的工作将通过考虑土壤性质的时空变异和气候变化，对可持续土地和地下水管理进行创新研究。这项研究将分三个部分进行评价，(i)补给作为污染物运动的驱动力，（ii）污染物渗入地下水，（iii）补给和浸出对地下水质量的影响。

Ten million Canadians rely on groundwater as a drinking water source. This resource is under continuous threat of contamination. This is a growing problem; a study on environmental sustainability of Canadian agriculture reported a decline in water quality throughout Canada due to increased application of fertilizers (Eilers et al., 2010). As a result, Frost reported in 2006 that approximately 16% of Manitoban water supply wells had nitrate levels above the drinking water guidelines (10 mg/L NO3-N). Leaching of pollutants is controlled by fluxes in the unsaturated zone. Seasonal climatic variability produces extreme changes in both the spatial and temporal distribution of recharge. A recurring event-based recharge in the Canadian Prairies emerges during snowmelt in combination with soil thawing, which is characterized by fast water fluxes. Fast fluxes imply a high risk of contamination. This is in contrast to the average hydrologic conditions currently being used to identify the risk. Groundwater models are a valuable tool for the quantification, evaluation, and prediction of the risk. Present models that include the climatic variability cannot accurately predict the risk of groundwater contamination for sustainable land and groundwater management since they require vast amounts of temporal and spatial input data to predict future states reliably. The proposed work will pursue innovative research on sustainable land and groundwater management by consideration of the temporal and spatial variability of soil properties and the changing climate. The research will be evaluated in three sections, (i) recharge as the driving force of pollutant movement, (ii) pollutants leaching into the groundwater, and (iii) impact of recharge and leaching on groundwater quality. We have previously shown that physically-based recharge modeling using data from low-cost observations has vast potential to predict recharge at the point scale. This work will be extended by focusing on fast fluxes in the unsaturated zone during soil thawing and snow melt situations and by using advanced geostatistical methods for spatial upscaling. Downscaled climate data will be used to identify recharge under changing climate situations. In the second part of the initial 5-year cycle, a robust measurement technique to estimate nitrate leaching rates with a focus on thawing will be established and applied in the field and in the laboratory. The observed pattern and kinetics of nitrate leaching will be used for numerical modeling. Recharge and leaching estimates will be integrated into groundwater modeling using split-operator techniques to identify the state of groundwater and future risk of nitrate contamination. Thus, sophisticated sustainable land and groundwater management policies can be developed based on the knowledge of the temporal and spatial variability of soil and hydrological parameters.