Soil moisture patterns: linking hydrological processes at the event and inter-event time scales

土壤-植被-大气-迁移(SVAT)模型和气候模型需要更好地预测气候变化或土地利用变化的影响。要做到这一点，他们必须比现在更真实地描述土壤水分的横向通量和解释土壤水分的空间变异性，因为植物有效水的异质性可以对地表能量和水分收支产生强烈的影响。这项研究的目的是为了系统地了解三维土壤水分动态以及控制土壤水分空间格局和横向流空间变异性发展的环境或场地条件。注重事件和事件间时间尺度的实地实验将与模拟实验相结合。现场实验将在马尔科姆·纳普研究森林进行。实地测量将遵循嵌套方法，以便包括所有景观单元，并能够探索尺度效应。将在多个地点对整个土壤剖面进行手动测量，并在多个地点连续测量土壤湿度。为了确定土壤水分和蒸腾作用之间的反馈关系，将使用恒热式流量传感器测量土壤流量。三维土壤水分模式将与降水事件期间的侧向流动模式相关，内部地下水位动态也将被描述。雨季和旱季的示踪试验将支持确定侧向次表层流的空间变异性和发生情况。这些实地试验的数据将用于开发和验证分布式水平衡模型，该模型将用于虚拟实验和场景测试模式。该模型将用于确定特定的土壤水分模式是在什么环境条件下形成的。今后，这一新信息将被纳入决策树方法，以确定一个地区可能出现何种类型的土壤水分空间变异性，以及什么是横向水通量的适当表示。这将导致在SVAT模型中更具体地表示横向水文过程，并更好地预测土地利用或气候变化的影响。

Soil-Vegetation-Atmosphere-Transfer (SVAT) models and climate models need to better predict the effects of climate change or land use change. To do so they must describe the lateral moisture fluxes and account for the spatial variability in soil moisture more realistically than at present because heterogeneity in plant available water can have a strong impact on the surface energy and water budgets. The objective of the proposed research is to obtain a systematic understanding of the 3D soil moisture dynamics and the environmental or site conditions controlling the development of spatial soil moisture patterns and spatial variability in lateral flow. Field experiments focusing on both the event and the inter-event time scales will be combined with modeling experiments. The field experiments will be conducted in the Malcolm Knapp Research Forest. The field measurements will follow a nested approach in order to include all landscape units and to be able to explore scale effects. Soil moisture will be measured manually throughout the soil profile at many locations and continuously at several locations. To determine the feedbacks between soil moisture and transpiration, sapflow will be measured with constant heat sapflow sensors. The 3D soil moisture patterns will be related to lateral flow patterns during precipitation events as the internal water table dynamics will be characterized as well. Tracer experiments in the wet and the dry season will support the determination of the spatial variability and occurrence of lateral subsurface flow. The data from these field experiments will be used to develop and validate a distributed water balance model, which will be used in a virtual experiment and scenario testing mode. The model will be used to determine under which environmental conditions specific soil moisture patterns form. In the future this new information will be incorporated in a decision tree approach to determine what type of spatial variability in soil moisture is likely to occur in an area and what would be an appropriate representation of the lateral water fluxes. This will lead to more site specific representations of lateral hydrological processes in SVAT models and better predictions of the effects of land use or climate change.