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

估算不同规模的补给和养分淋滤，以改善可持续的土地和地下水管理

• 批准号: RGPIN-2016-05966
• 负责人: Hollaender, Hartmut
• 金额: $ 1.75万
• 依托单位: University of Manitoba
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=679700
• 关键词: Estimation; recharge; nutrient; leaching; different

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.***

一千万加拿大人依靠地下水作为饮用水源。该资源持续受到污染威胁。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，由于化肥施用量增加，整个加拿大水质下降（Eilers 等，2010）。因此，Frost 在 2006 年报告称，马尼托巴省约 16% 的供水井硝酸盐含量高于饮用水准则（10 毫克/升 NO3-N）。污染物的淋滤受非饱和区通量的控制。季节性气候变化导致补给的空间和时间分布发生极端变化。加拿大大草原在融雪和土壤解冻期间出现基于事件的反复补给，其特点是水通量快速。快速通量意味着污染风险很高。这与目前用于识别风险的平均水文条件形成鲜明对比。地下水模型是量化、评估和预测风险的重要工具。目前包含气候变化的模型无法准确预测可持续土地和地下水管理的地下水污染风险，因为它们需要大量的时间和空间输入数据来可靠地预测未来状态。拟议的工作将通过考虑土壤特性的时空变化和气候变化来进行可持续土地和地下水管理的创新研究。该研究将分三个部分进行评估，（i）补给作为污染物运动的驱动力，（ii）污染物渗滤到地下水中，以及（iii）补给和渗滤对地下水质量的影响。****我们之前已经研究过研究表明，使用低成本观测数据进行基于物理的补给建模具有预测点尺度补给的巨大潜力。这项工作将通过关注土壤解冻和融雪情况下非饱和区的快速通量以及使用先进的地统计方法进行空间升级来扩展。缩小规模的气候数据将用于确定气候变化情况下的补给。在最初五年周期的第二部分，将建立一种稳健的测量技术来估计硝酸盐浸出率，重点是解冻，并在现场和实验室中应用。观察到的硝酸盐浸出模式和动力学将用于数值模拟。使用分算算子技术将补给和淋滤估计整合到地下水模型中，以确定地下水状况和未来硝酸盐污染的风险。*因此，可以根据时空知识制定复杂的可持续土地和地下水管理政策土壤和水文参数的变化。***