Weather extremes have been responsible for widespread economic damage at global scale in the last decades. Agriculture alone absorbed 26% of the overall impact caused by natural hazards in low- and middle-income countries and even in high-income countries yield losses due to extreme weather are relevant. Vulnerability curves are traditionally used to quickly estimate the damage due to extreme events. This study maps the articles published from January 2000 to May 2022 implementing crop vulnerability curves to weather-related extreme events and climate change. Fifty-two articles have been identified through the use of Scopus, Web of Science, Google Scholar and the references of the selected papers. The selected papers have been analysed to determine for which extreme events vulnerability curves have been proposed, which crops have been studied, which explanatory variables have been used to create the curves, which functions are used to develop vulnerability curves and the number of parameters on which the proposed functions rely. Comparisons among the vulnerability curves for the various extremes are proposed, as well as indications of the main drawback of the developed vulnerability curves. Finally, areas where further research is needed are proposed together with recommendations on which elements should be included in vulnerability curve development.

The transboundary Lancang–Mekong River basin has experienced dynamics of cooperation over the past several decades, which is a common emergent response in transboundary coupled human–water systems. Downstream countries rely on the Mekong River for fisheries, agriculture, navigation and ecological services, while upstream countries have been constructing dams to generate hydropower. The dam construction and operation in upstream countries have changed the seasonality of streamflow in downstream countries, affecting their economic benefits. More recently, cooperation between upstream and downstream countries has been enhanced throughout the river basin. In this study, we introduce a quantitative socio-hydrological model to simulate hydrological processes, reservoir operations, economic benefits, policy feedbacks and therefore dynamics of cooperation within the Lancang–Mekong River basin. The model reproduces the observed dynamics of cooperation in the basin revealed by sentiment analysis of news articles. Hydrological variability such as droughts and human activities associated with reservoir operations affect dynamics of cooperation between the riparian countries, with importance attached to indirect political benefits of upstream playing an important role in the enhancement of cooperation. In this way, our study generated understanding of emergent cooperation dynamics in this transboundary river basin, and the socio-hydrological model used here provides a useful new framework to investigate and improve transboundary water management elsewhere.

Groundwater modeling in data-scarce regions faces significant challenges due to the lack of comprehensive, high-quality data, impacting model accuracy. This systematic review of Scopus-indexed papers identifies various approaches to address these challenges, including coupled hydrological-groundwater models, machine learning techniques, distributed hydrological models, water balance models, 3D groundwater flow modeling, geostatistical techniques, remote sensing-based approaches, isotope-based methods, global model downscaling, and integrated modeling approaches. Each methodology offers unique advantages for groundwater assessment and management in data-poor environments, often combining multiple data sources and modeling techniques to overcome limitations. However, these approaches face common challenges related to data quality, scale transferability, and the representation of complex hydrogeological processes. This review emphasizes the importance of adapting methodologies to specific regional contexts and data availability. It underscores the value of combining multiple data sources and modeling techniques to provide robust estimates for sustainable groundwater management. The choice of method ultimately depends on the specific objectives, scale of the study, and available data in the region of interest. Future research should focus on improving the integration of diverse data sources, enhancing the representation of complex hydrogeological processes in simplified models, and developing robust uncertainty quantification methods tailored for data-scarce conditions.

A flow regime is influenced by the degree of hydrologic connection between surface water and groundwater. As this connection becomes more transient and the basin’s runoff response more non-linear, such as for intermittent streams, the need for explicit representation of the groundwater component increases. The present study investigates the connection between Northern Etna groundwater system and the Alcantara river basin in Sicily (Italy). In particular, the upstream part of the basin, whose flow regime is essentially intermittent, is modeled through a modified version of the IHACRES rainfall-runoff model. The structure of the model includes a routing module formulated as a two-store model, with the upper store simulating the quick component of the runoff and recharging the lower store which, in turn, describes the slow component of the runoff and the groundwater extraction and losses. Both stores are conceptualized as simple linear reservoirs, with the lower one that maintains a continuous water balance account of groundwater storage volumes for the upstream basin area with respect to a control cross-section, assumed to be the stream gauging station. The model is calibrated at Moio Alcantara cross-section, where daily streamflow data are available. Model calibration and validation are carried out for the period 1980–1984 and 1986–1988, respectively. A first-order analysis is also performed to assess the sensitivity of model parameters. The adopted configuration is shown to improve model performance with respect to the original IHACRES model, with the proposed formulation able to better capture the interactions between the aquifer and the river.

Floods and droughts are the events that most threaten crop production; however, the impact of floods on crops is still not fully understood and often under-reported. Nowadays, multiple sources of information and approaches support the estimation of agricultural losses due to floods. This study aims to understand the differences in agricultural loss estimates provided by two conceptually different approaches (crop models and expert-based models), evaluating their sensitivity to flood hazard inputs. We investigated the challenges in flood agricultural loss assessments referring to a case study for which, in addition to model simulations, information from surveys and on-site inspections were available. Two crop models (APSIM and WOFOST) and the expert-based model AGRIDE-c were applied to evaluate agricultural yield losses after the flood event of the Panaro River (Emilia-Romagna, Northern Italy) that took place on the 6 December 2020. Two modelling tools were used to reproduce the event: the hydraulic model HEC-RAS and the image-based tool FwDET. Additionally, surveys among local farmers were conducted in the aftermath of the event to evaluate the flood features (water depth, extent and duration) and crop losses. The main findings of the study are that APSIM and WOFOST provide similar estimates of yield losses, while AGRIDE-c tends to underestimate yield losses when the losses over the entire study area are evaluated. The choice of the flood simulation technique does not influence the loss estimation since the difference between the yield loss estimates retrieved from the same model initialized with HEC-RAS or FwDET was always lower than 2%. Information retrieved from the surveys was not sufficient to validate the damage estimates provided by the models but could be used to derive a qualitative picture of the event. Therefore, further research is needed to understand how to effectively incorporate this kind of information in agricultural loss estimation.

The area surrounding the Po River, known as the Po Valley, provides a central contribution in the economy of Italy and is highly devoted to agriculture. Recently it has been hit by multiple droughts, among which the exceptional event of summer 2022 is considered the worst dry period of the past 200 years. In the near future, the frequency of such exceptional events is predicted to rise; thus, a deep knowledge of the past droughts that hit the area, the variables used to characterize the events, the impacts they caused and the mitigation strategies adopted to deal with dry periods is of the utmost importance for policy definitions and planning. This study maps the scientific literature published from 2000 to February 2024 on the topic of drought in the Po Valley using the Scopus and Web of Science databases. Overall, 44 articles have been identified and grouped in three main classes: event identification and characterization, impact analysis and management strategies. The main gaps found in the collected papers are the lack of evaluations of the impacts of drought events on human health, hydroelectric energy production and tourism. Furthermore, comprehensive drought management and planning in the area is never addressed in the considered articles. The mentioned aspects deserve more attention, especially the development of drought management plans and policies and the evaluation of their effectiveness.