Agricultural drought is a complex natural hazard involving multiple variables and has garnered increasing attention for its severe threat to food security worldwide. In the context of climate change and the increased occurrence of drought events, it is crucial to monitor drought drivers and progression to plan the subsequent efforts in drought prevention, adaptation, and migration. However, previous studies on agricultural drought often focused on precipitation or evapotranspiration, overlooking other potential drivers related to crop drought stress. Additionally, macro-level analyses of drought-driving mechanisms struggle to reveal the underlying contexts of varying drought intensities. Northern Italy is one of the most important agricultural regions in Europe and is also a hotspot affected by extreme climate events in the world. In the summer of 2022, an extreme drought struck Europe once again, causing significant damage to the agricultural regions of Northern Italy. However, no studies to date have revealed the potential impacts and extent of extreme drought on this crucial agricultural area at a regional scale. Therefore, a comprehensive understanding of agricultural drought still requires further clarification and differentiated driver analysis. This study proposed a novel framework to comprehensively monitor agricultural drought with ensemble machine learning by constructing an integrated agriculture drought index (IADI) with remote sensing-related data including meteorology, soil, geomorphology, and vegetation conditions. Additionally, the Shapley Additive Explanation (SHAP) explainable model was applied to reveal the driving mechanism behind the drought event that occurred in northern Italy in the summer of 2022. Results indicated that the proposed explainable ensemble machine learning model with multi-source remote sensing products could effectively depict the evolution of agricultural drought with spatially continuous maps on an 8day scales. The SHAP analysis demonstrated that the extreme and severe agricultural drought in the summer of 2022 was closely related to meteorological indicators especially precipitation and land surface temperature, which contributed 68.88% to the drought. Moreover, the new findings also highlighted that soil properties affected the agricultural drought with a contribution of 28.3%. Specifically, in the case of moderate and slight drought conditions, higher clay and soil organic carbon (SOC) content contribute to mitigating drought effects, while sandy and silty soils have the opposite effect, and the contributions from soil texture and SOC are more significant than precipitation and land surface temperature. The proposed research framework could effectively contribute to improving the methodology in agricultural drought research, potentially bringing more instructive insights for drought prevention and mitigation.

The insufficient taking into account of groundwater as a basis for implementing protection measures for coastal wetlands can be related to the damage they are increasingly exposed to. The aim of this study is to demonstrate the pertinence of combining hydrogeological tools with assessment of pollutant fluxes and stable isotopes of O, H and N, as well as groundwater time-tracers to identify past and present pollution sources resulting from human activities and threatening shallow groundwater-dependent ecosystems. A survey combining physico-chemical parameters, major ions, environmental isotopes (O-18, H-2, N-15 and H-3), with emerging organic contaminants including pesticides and trace elements, associated with a land use analysis, was carried out in southern Italy, including groundwater, surface water and lagoon water samples. Results show pollution of the shallow groundwater and the connected lagoon from both agricultural and domestic sources. The N-isotopes highlight nitrate sources as coming from the soil and associated with the use of manure-type fertilizers related to the historical agricultural context of the area involving high-productivity olive groves. Analysis of EOCs has revealed the presence of 8 pesticides, half of which have been banned for two decades and two considered as pollutant legacies (atrazine and simazine), as well as 15 molecules, including pharmaceuticals and stimulants, identified in areas with human regular presence, including rapidly degradable compounds (caffeine and ibuprofen). Results show that agricultural pollution in the area is associated with the legacy of intensive olive growing in the past, highlighting the storage capacity of the aquifer, while domestic pollution is sporadic and associated with regular human presence without efficient modern sanitation systems. Moreover, results demonstrate the urgent need to consider groundwater as a vector of pollution to coastal ecosystems and the impact of pollutant legacies in planning management measures and policies, with the aim of achieving 'good ecological status' for waterbodies.

Extreme weather events are increasingly recognized as major stress factors for forest ecosystems, causing both immediate and long-term effects. This study focuses on the impacts experienced by the forests of Valdisotto, Valfurva, and Sondalo (28% of the total area is covered by forests) in Upper Valtellina (Italy) due to the Vaia storm that occurred in October 2018. To define the immediate impacts of Vaia, we assess the economic value of forest ecosystem services (ESs), particularly those provided by timber production and carbon sequestration, pre- and post-Vaia and during the emergency period. We used the market price method to assess the economic values of timber production and carbon sequestration, as these are considered to be marketable goods. Based on data processed from Sentinel-2 satellite images (with a spatial resolution of 10 m), our results show that, despite the reduction in forest area (-2.02%) and timber stock (-2.38%), the economic value of the timber production increased after Vaia due to higher timber prices (i.e., from a total of 124.97 million to 130.72 million). However, considering the whole emergency period (2019-2020), the total losses are equal to 5.10 million for Valdisotto, 0.32 million for Valfurva, and 0.43 million for Sondalo. Instead, an economic loss of 2.88% is experienced for carbon sequestration, with Valdisotto being the more affected municipality (-4.48% of the pre-Vaia economic value). In terms of long-term impacts, we discuss the enhanced impacts due to the spread of the bark beetle Ips typopgraphus.