Landslides are geomorphological processes that consist in the mobilization of ground, rocks, debris, and mud downslope that cause local erosion problems. The eroded materials can be transported downstream, which implies an additional environmental risk that might lead to catastrophic and significant economic and human losses. Rainfall is usually the main triggering factor for landslides occurrence, but there are other factors such as previous weathering activity, topography, soil properties and vegetation which also play a key role. These drivers have been deeply studied in humid regions, but little is known about the factors controlling landslide incidence in arid and semi-arid environments. The aim of this work was to identify the incidence of landslides in a semiarid badlands system in the SE of the Iberian Peninsula to identify key drivers of this process and to develop a predictive landslide susceptibility model. To do this we built a landslide inventory after an unusual rainy period (five consecutive rainy days representing about 50% of mean annual rainfall in the area). Then, a photogrammetric UAV-based flight allowed us to estimate the total extent of identified landslides, as well as, vegetation coverage distribution and several topographic attributes that were known to influence landslide formation. Our results prove that vegetation cover plays a key role in the occurrence of landslides during prolonged periods of consecutive large amount and low intensity rains. Vegetation in the area is mainly dominated by small shrubs and grasses that prevent water erosion and infiltrated run-on water from upstream areas during most rainfalls. However, most dominant species are characterized by shallow root systems that tramp and increase soil water storage mainly in the upper soil layer but do not retain soil further than surface layers. During prolonged very high magnitude and low intensity rainfalls, such as these studied here, water accumulated in the first 30–50 cm of soil until saturation occurs, favor landslide formation. Topographic variables such as elevation, slope gradient and aspect are also of paramount importance controlling landslide incidence, with most landslides occurring in intermediate parts of steep N and N–W hillslopes. Finally, by combining topographical attributes and the vegetation map obtained from the low cost UAV flight it was possible to developed a non-parametric multivariable model that accurately predicted landslide occurrence during prolonged periods of low intensity rainfall by providing a landslide susceptibility map. This low cost method can be extrapolated to other environments with similar characteristics to foresee these processes. A prevention method as the one developed in this work is key for a correct management with areas with high risk of occurrence of landslides.

滑坡是一种地貌过程，包括动员引起局部侵蚀问题的地面，岩石，碎屑和泥坡。被侵蚀的材料可以向下游运输，这意味着额外的环境风险，可能导致灾难性的重大经济和人员损失。降雨通常是滑坡发生的主要触发因素，但是其他因素，例如先前的风化活动，地形，土壤特性和植被也起着关键作用。这些驱动因素已在潮湿地区进行了深入研究，但对于控制干旱和半干旱环境中滑坡发生率的因素知之甚少。这项工作的目的是确定伊比利亚半岛东南部半干旱荒地系统中滑坡的发生率，从而确定这一过程的关键驱动因素，并开发出可预测的滑坡敏感性模型。为此，我们在一个异常的雨季（连续五个雨天代表该地区年平均降雨量的50％）之后建立了滑坡清单。然后，基于摄影测量的无人机飞行使我们能够估计已识别的滑坡的总范围，以及植被覆盖率分布和一些已知的影响滑坡形成的地形属性。我们的结果证明，在连续的大量低强度降雨的长期过程中，植被覆盖在滑坡的发生中起着关键作用。该地区的植被主要是小的灌木和草丛，在大多数降雨期间，这些灌木丛和草丛可防止水蚀和上游地区的自来水渗入。但是，大多数优势种的特征是浅根系，主要在上部土壤层中践踏并增加土壤水的储存量，但保留的土壤比表层更深。在长时间的高强度和低强度降雨期间（例如此处研究的降雨），水在土壤的前30–50 cm处积累直至饱和，这有利于滑坡的形成。诸如海拔，坡度和坡度之类的地形变量对于控制滑坡发生率也至关重要，其中大多数滑坡发生在陡峭的N和N–W山坡的中间部分。最后，通过结合地形特征和从低成本无人机飞行中获得的植被图，可以开发出非参数多变量模型，通过提供滑坡敏感性图，可以准确地预测低强度降雨长时间内滑坡的发生。可以将此低成本方法外推到具有类似特征的其他环境，以预见这些过程。作为这项工作中开发的一种预防方法，对于在发生滑坡风险高的地区进行正确管理是至关重要的。可以将此低成本方法外推到具有类似特征的其他环境，以预见这些过程。作为这项工作中开发的一种预防方法，对于在发生滑坡风险高的地区进行正确管理是至关重要的。可以将此低成本方法外推到具有类似特征的其他环境中，以预见这些过程。作为这项工作中开发的一种预防方法，对于在发生滑坡风险高的地区进行正确管理是至关重要的。