Agricultural green water scarcity (GWS)—restricted crop growth due to insufficient rainfall—is one of the key challenges in rainfed systems. It limits crop production, which can impact not only farmers' incomes but also lead to more major issues such as food insecurity, conflicts over water resources, and supply chain disruptions.

This study presents a new dataset on monthly GWS of the world’s major crops over the 1990–2019 period. The simulations are performed with a process-based global gridded crop model ACEA utilising best-to-date input datasets on climate, soil, and crop parameters. The results are compared to other relevant datasets across different spatial and temporal scales ensuring the robustness of the GWS estimates. The final files are provided as NetCDF rasters at a 5-arcminute spatial resolution (~8.3 km around the equator) per crop per month of each considered year. Such detailed segregation allows for detecting the effects of changing climate (including droughts and heat waves) on the availability of green water resources and, hence, on the GWS severity across different crops and regions.

This work provides a necessary foundation for further studies on the environmental and socio-economic implications of GWS, paving the way for solutions for more water-sustainable agrifood systems.

How to cite: Mialyk, O.: Global dataset on agricultural green water scarcity in 1990–2019, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1698, https://doi.org/10.5194/egusphere-egu25-1698, 2025.

Understanding crop yield responses to rainfall is essential for food systems adaptation under climate change. While there are ample evidences of crop yield responses to seasonal rainfall variation, the geographic sensitivities and driving mechanisms of sub-seasonal rainfall events remain elusive. We used long-term nationwide observations to explore the sensitivity of maize and soybean yields in response to event-based rainfall across Chinese agroecological regions. While maize and soybean yield showed concave downward responses to event-based rainfall depth at the national scale, these responses were differed considerably among regions. These differences can be primarily explained by soil moisture preceding rainfall events, soil erosion and sunshine hour reduction during rainfall. Our projections reveal that focusing on seasonal rainfall or national-level sensitivity analysis suggests a 0.3-5.9% increase in maize yields due to future rainfall, yet considering spatial variations unveils a contrasting reality, with maize yields declining by 9.1±0.3% under a medium-range emission scenario (SSP2-4.5) by the end of century (2085–2100). The future rainfall effect on soybean yield is the opposite, leading to a 20.6±3.9% reduction nationally without spatial consideration, but an increase (by 7.0±1.0%) when spatial variations are factored in. These findings underscore the critical necessity of incorporating regional variation in yield responses to sub-seasonal rainfall events, which could otherwise lead to vastly different impact estimates, even reversing the expected crop yield response to future rainfall change.

How to cite: Fu, J., Jian, Y., Wang, C., and Zhou, F.: Regionally Variable Responses of Crop Yield to Rainfall Events in China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5346, https://doi.org/10.5194/egusphere-egu25-5346, 2025.

Rapid dietary change to more plant-based diets and reduced animal products consumption is a powerful leverage for plummeting the environmental and climate impacts of food habits, key to achieve international agreements’ targets on climate and biodiversity.  Current eating patterns are shifting towards affluent diets high in sugar, fats, animal-source foods, highly processed products and empty calories. Nutritionally inadequate diets and reduced physical activity rates drive the incidence of overweight and non-communicable diseases, while increasing anthropogenic pressures on the environment.

While the optimal composition of  more sustainable and healthy diets has been extensively studied, the current stage of food systems from which their transformation should begin remains underexplored. In this study, we present a statistical analysis of dietary patterns from 1970 to 2021 of 189 countries and 17 essential foods. We examine the evolution of dietary energy intake along with gross domestic product, both at global and country scale, to identify transitions in countries' food demand and highlight heterogeneities from the global pattern.

Our analysis extends the concept of the nutrition transition from a country process to a globally emerging one, characterized by increasing animal-products caloric intake and declining dietary energy supplied by cereals and plant-based foods. Consistently across high-income countries, the prevalence of sugars in diets declines of 27% towards healthier intakes. Among these countries, we identify transitions in dietary energy supply from animal products to cereals and, less frequently, plant-based foods, providing novel evidence for a reconfiguration of diets towards a reduced reliance on animal-foods, potentially suggesting the onset of a new phase in the nutrition transition.

How to cite: Giordano, V., Tuninetti, M., and Laio, F.: Shifting away from animal-source calories in High-Income countries contrasts global Nutrition Transition patterns, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10698, https://doi.org/10.5194/egusphere-egu25-10698, 2025.

Irrigation plays a crucial role in mitigating the impacts of climate variability and extreme climate events on agricultural productivity, helping to limit drought risks and reduce yield volatility. Given projected increases in the frequency and magnitude drought and water risks to crop production, expansion and intensification of irrigation will be an important component of agricultural adaptation to climate extremes. At the same time, there are significant concerns about the impacts that increased dependence of agriculture on irrigation could have for water resource sustainability and freshwater-dependent ecosystems.

Understanding how climate extremes will alter the value of irrigation is critical for managing these trade-offs, and for supporting development of policies to deliver sustainable and efficient use of water in agriculture. Here, we develop a global gridded modeling framework based on the AquaCrop-OSPy model to estimate the impacts of climate change on the agronomic and economic return on investment from irrigation under multiple potential climate futures. Our initial analyses are focused on quantifying changes in the value added from irrigation for four major crop types – Maize, Wheat, Rice, and Soybean – across four shared socio-economic pathways— SSP245 (moderate), SSP370 (regional rivalry), and SSP5-8.5 (extreme) scenarios – drawing on downscaled climate projections from a range of CMIP6 models out to 2100.

Our analysis highlights hotspots of change in variability of irrigation across major agricultural production systems and hydrologic basins. Our results show that the value of irrigation is likely to increase not only in regions that are currently water stressed but also in those where irrigation has historically been more limited. Furthermore, we demonstrate a significant increase in the inter-annual volatility of irrigation value across many production regions globally, in particular driven by greater variability in precipitation and drought-related production risks. Our findings provide insights to guide the development of irrigation expansion strategies, while also highlighting potential areas where future increases in irrigation could increase potential for conflict over limited water resources.

How to cite: Tyagi, S., Bowden, C., and Foster, T.: Global changes in the value of irrigation as a buffer against climate extremes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11980, https://doi.org/10.5194/egusphere-egu25-11980, 2025.

It is becoming more and more crucial to comprehend and manage the effects of extreme temperatures in order to preserve agricultural productivity and food security as climate change continues to intensify weather variability. Due to the increasing demand for olive products such as olive oil and olives in the world in recent years, olive cultivation has started to be cultivated economically in countries with a Mediterranean climate. This study investigates the future changes in growing degree days (GDD) for olive in southwestern Türkiye during the 21^st century, using convection-permitting simulations under the SSP3-7.0 scenario. Future climate projections based on the SSP3-7.0 scenario suggest pronounced warming trend, particularly in the summer season. In comparison to the reference period of 1995-2014, temperatures in the 2040-49 period are expected to rise by 2.5°C, and by 3.5°C in the 2070-79 period. The second largest warming trends occur in spring and autumn, approaching those of summer in the second projection decade. After the significant decrease in the winter season, the autumn season is expected to experience the second largest reduction in precipitation, with a similar drying trend extending into the spring months in 2070-79, exacerbating the already reduced winter precipitation. Considering the ten-year average of olive production in Türkiye, our study area contains most of the cities with the highest production. Therefore, GDD is calculated for olives over the period between 1 April and 15 October, using a base temperature of 12^oC. The results show a clear increase in GDD for olives in the future climate projections, especially in the second period. This increase indicates that olives will grow faster and mature earlier due to the accumulation of more heat. If the olives ripen too early, this can affect the yield and quality of the oil. Nevertheless, the relative effects of an increase in GDD across phenological stages may expose the plant to the risk of damage due to higher frequency of extreme weather events (e.g. heatwaves and late spring frosts). Insufficient water can lead to slower growth and smaller fruit sizes, and also lower oil content in olives that reduces the production of high-quality extra virgin olive oil. Olive growers in southwest Türkiye can mitigate some of the negative consequences of climate change while preserving their productivity and quality by focusing on climate-resilient types, water conservation, and sustainable farming methods.

This work is funded by the project titled 'ACLIFS - Assessment of Climate Change Impacts on Food Safety and Enhancing the Resilience of Rural Communities' which is implemented under the “Climate Change Adaptation Grant Program (CCAGP)”.

Key words: Growing degree days, convection-permitting model, COSMO-CLM, future projections, SSP3-7.0

How to cite: Sonuç, C. Y., Yaylacı, N., Keske, B., Kaya, F., and Ünal, Y.: Predicting the Impact of Climate Change on Olive Cultivation in Southwestern Türkiye under SSP3-7.0 Scenario, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16073, https://doi.org/10.5194/egusphere-egu25-16073, 2025.

The agriculture industry is increasingly challenged by the rising severity and frequency of extreme weather events. To assess the impact of climate extremes on croplands, various weather stress indices have been employed in studies. However, a region-specific index that effectively captures local variations remains lacking. The primary objective of this study is to identify climate-related stressors that impact agricultural systems at a regional scale. To achieve this, we leverage multiple high-resolution, gridded observational datasets of temperature and precipitation, alongside a large ensemble of statistically downscaled global climate models. These datasets allow us to examine the prevailing and future effects of climate change on major cropping regions across the U.S. over the coming decades. Crop-specific resilience and vulnerabilities across the CONUS are analyzed using a weighted averaging technique, which minimizes redundancy and helps create a tailored, region-specific weather stress index. This research will provide valuable insights into the resilience and stability of crops under varying climate conditions across the CONUS. The resulting weather stress indices will be made publicly available through a Climate Atlas, equipping stakeholders with the information needed to make informed decisions.

How to cite: Vishwakarma, S. and Ashfaq, M.: Assessing agricultural weather stress indices for optimizing crop resilience across CONUS, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11672, https://doi.org/10.5194/egusphere-egu25-11672, 2025.

Water is the main source of sustenance for millions of people living within the Great Ruaha River Basin (GRRB). However, water scarcity resulting from dwindling river discharges has emerged as a major challenge, affecting livelihoods and threatening the survival of dependent ecosystems. With the ongoing global climate change, it is anticipated that water stress in the basin will intensify as a result of disrupted  hydrological cycle. This study assessed the potential changes in discharge resulting from future climate change in the GRRB during the  (i) the mid-future (2036–2065) and (ii) the far future (2071–2099) periods. Five Global Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6), applied under two Shared Socioeconomic Pathways (SSP) scenarios (SSP3-7.0 and SSP5-8.5), were utilized. The calibrated Soil and Water Assessment Tool (SWAT+) was used to evaluate the impact of climate change on discharge patterns. Climate projections indicated that, temperatures are expected to rise by 2–4°C by the end of the century under both scenarios, with evapotranspiration rates increasing by 0–2%. Annual average precipitation is projected to vary by -1% to 3% compared to the historical baseline (1981–2010). Interannual variability showed a projected decrease in precipitation during the mid-future and an increase in the far future. Similarly, long-term annual discharge trends revealed declines in the mid-future under both scenarios, with increases toward the far future. Mean monthly discharge indicated minor changes (-1% to 11%). Low flows are projected to remain relatively stable while high flows will exhibit mixed patterns, ranging from -8% to 7%. These findings highlight increased water stress in the mid-future, with potential recovery in the far future, underscoring the need for sustainable, climate-resilient water management to protect livelihoods and GRRB’s ecosystems in the face of changing climate.

Keywords: Water scarcity, Climate projections, SWAT+

How to cite: Mukama, E. B., Ronoh, E., Addisu Yimer, E., Baptist Mbungu, W., Dondeyne, S., and van Griensven, A.: Future Changes in River Discharge: Insights from CMIP6 Model Simulations for the Great Ruaha River Basin, Tanzania, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21941, https://doi.org/10.5194/egusphere-egu25-21941, 2025.

Groundwater acts as a vital buffer for human activities, offering resilience against environmental, economic, and social challenges. However, the depletion of groundwater resources intensifies these challenges, particularly in Mediterranean regions where water resources are already under significant stress.

This study investigates groundwater drought dynamics in the Bruna River catchment in Tuscany, Italy, with a focus on the temporal and spatial patterns of drought and its attribution to climate change. The analysis employs various hydroinformatics approaches, including the Standardized Precipitation Index (SPI), Standardized Groundwater Index (SGI), a threshold-based method, and the Combined Drought Index (CDI), which integrates precipitation, soil moisture, and vegetation data to monitor agricultural drought, offering early warnings and identifying areas that are either affected or recovering. Furthermore, a SWAT+ gwflow model is being developed to explore drought attribution using both factual and counterfactual climate datasets.

Preliminary findings highlight obvious temporal and spatial drought patterns, even when utilizing short time series. The SGI exhibits strong temporal correlations with SPI12, SPI24, and the monthly threshold Q20. Moreover, SGI demonstrates good temporal and spatial alignment with CDI, underscoring its utility in groundwater drought assessments.

Future efforts will focus on finalizing and validating the SWAT+ gwflow model by calibrating it against observed data and performing sensitivity analyses. The validated model will facilitate an in-depth exploration of groundwater drought attribution by comparing outcomes under factual and counterfactual climate scenarios. These analyses aim to enhance the understanding of groundwater drought, which can inform water resource management and policy decisions.

How to cite: Elsaidy, A., Addisu Yimer, E., Villani, L., and van Griensven, A.: Temporal and Spatial Patterns of Groundwater Drought in the Bruna River Catchment, Italy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2746, https://doi.org/10.5194/egusphere-egu25-2746, 2025.

The flow duration curve (FDC) serves as an essential tool for analyzing streamflow variability and supporting effective river management. However, constructing FDCs in ungauged basins presents a significant challenge due to the lack of sufficient data. This study leverages data-driven approach to predict FDCs in ungauged basins, thus offering practical solutions for improving hydrological forecasting and enhancing water resource management. The research aims to identify the key hydrologic, meteorological, and topographic factors influencing FDCs, and by evaluating different combinations of predictor variables, it assesses the influence of various precipitation metrics on flow predictions while comparing the performance of data-driven models. The study predicted low (Q_80%, Q_90%, Q_95%), medium (Q_30%, Q_40%, Q_50%, Q_60%, Q_70%), and high flows (Q_5%, Q_10%, Q_20%), including extreme low flows (Q_95%) and extreme high flows (Q_5%). Feature importance analysis highlighted the watershed area and precipitation as critical for high flow predictions, and land use and basin characteristics influenced medium and low flows. Scenario testing confirmed that including all variables resulted in the most accurate predictions. Interestingly, variations in precipitation metrics had minimal impact on model performance, suggesting the prominence of other predictors. These results emphasize the potential of data-driven approaches in improving FDC predictions, particularly in diverse hydrological contexts where conventional methods fall short. This study highlights the potential of advanced hydroinformatics techniques to predict FDCs in ungauged basins, improving the accuracy of hydrological forecasting and water resource management through innovative, data-driven methodologies.

Funding: This work was supported by Korea Environment Industry & Technology Institute(KEITI) through the Water Management Project for Drought, funded by Korea Ministry of Environment(MOE) (2022003610004).

How to cite: Yoon, J., Yi, S., Lee, C., Lee, S., Ji, J., Lee, E., and Yi, J.: Predicting Flow Duration Curves in Ungauged Basins Using Data-Driven Approaches, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7508, https://doi.org/10.5194/egusphere-egu25-7508, 2025.

Predicting streamflow in ungauged catchments using regionalization methods has been extensively studied. While numerous free and open-source software (FOSS) tools exist for predicting regional flow-duration curves (FDCs) at ungauged sites, a general FOSS tool specifically designed to generate continuous streamflow series from these FDCs is lacking. This study introduces FDC2Q_t, an R-package developed within a collaboration between the University of Bologna, the Po River Basin Authority, and the Emilia-Romagna Regional Authority. FDC2Qt generates long synthetic hourly streamflow series in ungauged catchments, utilizing a regional dataset of daily streamflow observations from neighboring sites and basin morphoclimatic descriptors. The methodology comprises three key steps: (1) FDC Prediction: a regional period-of-record FDC is predicted for the ungauged site by combining an index-flow approach (Castellarin et al., WRR, 2004) with a region of influence approach (Burn, WRR, 1990); (2) Daily Streamflow Synthesis:  a synthetic daily streamflow series is generated at the ungauged site using a non-linear spatial interpolation method based on FDCs (Smakhtin et al., HSJ, 1997; Smakhtin, J. Hydrol., 2001), referencing one or more observed daily streamflow series from neighboring catchments; (3) Hourly Streamflow Downscaling: the synthetic daily series is downscaled to an hourly time step using a scaling law that primarily considers the morphological features of the ungauged catchment. Validation experiments demonstrate that the synthetic hourly streamflows accurately capture the primary hydrological characteristics of observed streamflow series and exhibit reliability comparable to that of hourly streamflow series simulated by regionalized lumped rainfall-runoff models.

How to cite: Spadoni, A., Foraci, R., Di Lorenzo, M., Simonelli, T., and Castellarin, A.: An Open-Source Tool for Generating Hourly Synthetic Streamflow Series in Ungauged Basins Using Regional Flow-Duration Curves, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18192, https://doi.org/10.5194/egusphere-egu25-18192, 2025.

Effective water resource management in hydrologically diverse regions requires the integration of advanced decision-support systems with collaborative approaches. This study presents the development and application of the ERA TOOL, a hydroinformatics platform designed to evaluate water resources across multiple jurisdictions in Colombia. Initially developed through collaboration between the Stockholm Environment Institute (SEI) and regional environmental authorities (CARs), the tool has been implemented for four CARs and is currently being adapted for a fifth, highlighting its scalability and adaptability to diverse hydrological and institutional contexts.

The ERA TOOL builds on the framework of the Regional Water Assessment (ERA, by its acronym in Spanish), a process mandated by Colombian policy to assess water availability, quality, and vulnerability while addressing anthropogenic pressures. By integrating localized hydrological modeling using the Water Evaluation and Planning (WEAP) system and geospatial analyses, the tool provides a comprehensive Decision Support System (DSS) for evaluating current conditions and projecting future scenarios under climate variability and increasing demands.

Key features of the ERA TOOL include dynamic visualizations of regional indicators such as flow duration curves, groundwater recharge, and surface water availability and quality indicators, all presented through an intuitive, interactive interface. The platform also facilitates the co-design of solutions by incorporating feedback from stakeholders during its development and deployment. This collaborative process ensures that the tool meets the specific needs of each CAR, enhancing institutional capacity and fostering a shared understanding of water resource dynamics.

The implementation across multiple CARs has demonstrated the versatility of the ERA TOOL in addressing diverse regional climates and challenges, from hydrological extremes to water allocation and quality management. By linking data-driven insights with participatory processes, the tool has empowered decision-makers to implement evidence-based strategies that promote equitable and sustainable water governance. All platforms developed are freely accessible, with the latest version available for consultation at the following link: https://latinoamericasei.shinyapps.io/ERA_CARDER/.

This ongoing initiative underscores the potential for replicating and adapting hydroinformatics solutions across regions with varying hydrological and institutional conditions. It provides a model for leveraging innovative tools and participatory research to bridge gaps between technical expertise and practical application in water resource management.

How to cite: Forero-Hernández, A. T., González-Ayala, C. A., Aedo-Quililongo, S., and Santos-Santos, T. F.: Leveraging Hydroinformatics and Stakeholder Engagement for Regional Water Resource Management in Colombia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14432, https://doi.org/10.5194/egusphere-egu25-14432, 2025.

Seasonal water flow patterns in Central Valley rivers within California's Sacramento-San Joaquin Delta watershed have been profoundly disrupted by dams, conveyance systems, and land use changes. These alterations have led to habitat degradation, declines in fish populations, and reduced ecosystem services. Environmental flows—quantities and qualities of instream water essential for ecosystem health—are critical for sustainable water management. However, implementing environmental flows in Central Valley rivers necessitates significant changes to current water management practices, with uncertain implications for other water uses. The COllaboratory for EQuity in Water Allocations (COEQWAL), a publicly funded initiative, seeks to improve understanding of California’s water future through participatory scenario planning. As part of COEQWAL, we investigate the impacts of water operation alternatives and climate scenarios on maintaining environmental flows based on Functional Flow targets, which represent flow regime components that support key ecosystem functions. We demonstrate that allocating specific monthly water volumes as an environmental water budget—tailored to river basin and water year type—can achieve these targets. Furthermore, we evaluate how climate warming influences the feasibility of achieving environmental flows under various water management scenarios. Our results highlight both the opportunities and challenges associated with managing environmental flows in California’s Central Valley rivers. They also provide valuable insights into the interplay between water management strategies and ecological outcomes, helping guide sustainable management practices for the future.

How to cite: Yi, S., Stanford, B., Yarnell, S., Murdoch, L., and Grantham, T.: Assessing Environmental Flows in the Central Valley Across Different Management Scenarios, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5361, https://doi.org/10.5194/egusphere-egu25-5361, 2025.