Using spatially explicit soil mapping and modelling to understand and mitigate nitrate leaching in an agricultural catchment

项目摘要本研究使用数字土壤制图方法，N模型和农业管理策略，以映射和减轻氮损失的地下水在诺森伯兰郡北部的一个脆弱的集水区。它将增加我们的理解，驱动土壤氮动态的空间变异性的因素在一个规模，是相关的生产农场和特定领域的农艺建议。该项目的主要目标是：a）通过现场监测和土壤氮动态建模，确定硝酸盐淋溶和Fell砂岩含水层污染的来源，B）确定并证明这些特定地区硝酸盐淋溶与农业实践之间的关系，c）评估缓解战略的影响（天然硝化抑制剂、缓释肥料、捕捞作物）对不同土壤类型的氮素淋溶的影响，而不影响作物产量; d）建立一个经过校准和验证的贝里克地区土壤中硝酸盐淋溶的氮素动态模型。为了实现这些目标，该项目分为具体的任务，包括：审查目前的知识控制硝酸盐淋溶的因素和缓解策略，在北方温作物系统（文献综述），监测和模拟硝酸盐淋溶，测试拟议的缓解策略，并预测空间变异性的N淋溶在不同的管理策略下的下降砂岩流域。将使用多孔杯法N淋溶测量，过去的作物管理，电导率和伽马辐射计土壤传感器，以映射土壤特性，和数字高程模型（DEM），所有集成使用最新的数字土壤制图（DSM）技术的详细信息，在流域的氮淋溶的空间变异性的驱动因素进行研究。将在高风险领域实施选定的缓解战略，并将在全年收集有关硝酸盐淋失和作物生长的数据。理想的情况是，鼓励土地所有者采用带状办法来执行措施，以便能够与标准做法进行一些比较。土壤氮动态模型（NDICEA）将使用土壤性质和硝态氮淋失的观测数据进行校准和验证。校正后的模型将被用来预测不同的农业管理措施对硝酸盐淋溶到地下水的影响，从农业集水区。在这项研究的最后，我们希望能够确定可变的土壤类型和关键的土壤特性，可以支持硝酸盐淋溶从农业集水区。我们将确定适当有效的流域管理技术，以减轻硝酸盐淋溶，其结果将是一个证明，为农民，这些战略的工作，以减少硝酸盐淋溶，而不影响生产力。我们将有验证模型和方法来预测硝酸盐淋溶的基础上可测量的属性，可用于识别不同的管理措施下不同类型的土壤硝酸盐淋溶的风险。

Project summaryThis study uses digital soil mapping approaches, N models and agricultural management strategies to map and mitigate N losses to groundwater in a vulnerable catchment in north Northumberland. It will increase our understanding of the factors driving the spatial variability of soil-N dynamics at a scale that is relevant for producing farm and field-specific agronomic recommendations. The main objectives of this project are: a) To identify the source of Nitrate leaching and contamination of the Fell Sandstone aquifer through infield monitoring and soil N dynamic modelling, b) To identify and demonstrate the relation between nitrate leaching and agricultural practices in those specific areas, c) To evaluate the impact of mitigation strategies (natural nitrification inhibitors, slow release fertilizers, catch crops) on N leaching for different soil types without compromising crop production, and d) To produce a calibrated and validated N-dynamic model of nitrate leaching within soils relevant to the Berwick area. To achieve these objectives the project is divided into specific tasks including: review of current knowledge on factors controlling nitrate leaching and mitigation strategies in northern temperature cropping systems (literature review), monitoring and modelling of nitrate leaching, testing of proposed mitigation strategies, and predicting spatial variability of N leaching under different management strategies in the Fell Sandstone catchment. The factors driving spatial variability of N leaching in the catchment will be studied using porous cup methods for N leaching measurement, detailed information on past crop management, conductivity and Gamma-Radiometer soil sensors to map soil properties, and Digital Elevation Models (DEM), all integrated using the latest Digital Soil Mapping (DSM) techniques. Selected mitigation strategies will be implemented in high risk fields and data regarding nitrate leaching and crop growth will be collected throughout the year. Ideally, landowners will be encouraged to use a strip approach to implementing the measures so that some comparisons with standard practice are possible. The soil N dynamic model (NDICEA) will be calibrated and validated using observed data of soil properties and nitrate leaching. The calibrated model will be used to predict impact of different agricultural management practices on nitrate leaching to ground water from agricultural catchments. At the end of this research we expect to be able to identify variable soil types and key soil properties that can support nitrate leaching from an agriculture catchment. We will identify appropriately effective catchment management techniques to mitigate nitrate leaching and the result will be a proof for farmers that these strategies work to reduce nitrate leaching without compromising productivity. We will have validated model and approach to predict nitrate leaching based on measurable properties that can be used to identify risk of nitrate leaching from different soil types under different management practices.