High-resolution assessment of soil tillage impacts on groundwater recharge using drone imagery

The distribution of groundwater recharge can be estimated using several methods, but generally, the most appropriate method depends on both physical and study objectives. In this case, a large area in Southern Portugal has been subject to a strong intensification of agricultural practices. This was due to the construction of the Alqueva dam, the largest dam and artificial lake (250 km2) in Western Europe, which has caused a significant land-use change process in recent years. One of the most critical observed effects is the soil tillage process, which causes a great impact on runoff and recharge patterns and consequent soil erosion. For the assessment of groundwater recharge changes in this area, this study intended to make a high-resolution estimation based on drone imagery analysis. Accordingly, two high-resolution digital elevation models (DEM) with 7 cm resolution were created using photogrammetric processing of the images collected by drone. In order to have a representative land-use change, these images were collected before and after soil tillage. The image acquisition process was based on a pre-programmed drone (Unmanned Aerial Vehicle –UAV) with the following flight specifications: 90% frontal overlap and 70% lateral. As the research intended to have a high-accuracy DEM of the soil surface, two perpendicular flights were made. After the photogrammetric processing, a high-resolution output of topography was obtained prior to and after soil tillage. To assess the groundwater recharge changes, the WetSpass-M model was used for the two time frames. This model has the ability to simulate spatially distributed recharge, surface runoff, and evapotranspiration for averaged conditions and adaptive scales or resolutions. Depending on several inputs such as land cover, soil texture, hydrometeorological parameters and topography, the latter stands in this case as the main change between the two time frames. Thus, the groundwater recharge changes were estimated for an area of 55 ha, from which 18.7 ha were subjected to soil tillage. The remaining 36.3 ha were used as validation areas. In conclusion, the usage of drone imagery can be considered a fundamental tool for providing important hints on the impacts of land use and topography changes on the recharge, as well as constituting a methodology framework to support water balance assessments and groundwater resources management through the production of high-resolution spatially distributed recharge estimates.地下水补给的分布可通过多种方法估算，但通常而言，最适宜的方法需同时结合实际物理条件与研究目标确定。本次研究区域为葡萄牙南部大片区域，受阿尔克瓦大坝——西欧最大的大坝与人工湖（面积达250平方千米）——建成的影响，农业活动大幅强化，近年来引发了显著的土地利用变化进程。其中最受关注的影响之一为土壤耕作作业，其对径流、补给模式及土壤侵蚀均造成了显著影响。 为评估该区域的地下水补给变化，本研究旨在基于无人机影像分析开展高分辨率估算。为此，研究团队对无人机采集的影像进行摄影测量处理，生成了两组分辨率为7厘米的高分辨率数字高程模型（Digital Elevation Model, DEM）。为体现具有代表性的土地利用变化，影像分别采集于土壤耕作活动前后。 影像采集采用预编程无人机（Unmanned Aerial Vehicle – UAV），飞行参数设置为前向重叠度90%、旁向重叠度70%。为获取高精度的地表数字高程模型，研究开展了两次正交飞行作业。经摄影测量处理后，分别得到了土壤耕作前后的高分辨率地形数据。 为评估地下水补给变化，本研究针对两个时间节点分别采用WetSpass-M模型进行模拟。该模型可在平均条件与自适应尺度/分辨率下，模拟空间分布式补给、地表径流与蒸散发。模型输入涵盖土地覆盖、土壤质地、水文气象参数及地形等多项数据，而在本次研究中，地形数据是两个时间节点间最主要的变化变量。最终，研究针对55公顷的区域估算了地下水补给变化，其中18.7公顷区域实施了土壤耕作，剩余36.3公顷区域作为验证区。 综上，无人机影像可作为一项核心工具，为揭示土地利用与地形变化对地下水补给的影响提供重要依据，同时也构建了一套方法框架，可通过生成高分辨率空间分布式补给估算结果，为水量平衡评估与地下水资源管理提供支撑。