PICO
We particularly welcome submissions on the following topics:
• Complex inter-linkages between hydroclimatic conditions, food production, and population health, including: extreme weather events, surface and subsurface water resources, surface temperatures, and their impacts on food security, livelihoods, and water- and food-borne illnesses in urban and rural environments.
• Quantitative assessment of surface-water and groundwater resources, and their contribution to agricultural system and ecosystem statuses.
• Spatiotemporal modeling of the availability of water resources, flooding, droughts, and climate change, in the context of water quality and usage for food production, agricultural irrigation, and health impacts over a wide range of spatiotemporal scales.
• Smart infrastructure for water usage, reduction of water losses, irrigation, environmental and ecological health monitoring, such as development of advanced sensors, remote sensing, data collection, and associated modeling approaches.
• Modelling tools for organizing integrated solutions for water supply, precision agriculture, ecosystem health monitoring, and characterization of environmental conditions.
• Water re-allocation and treatment for agricultural, environmental, and health related purposes.
• Impact assessment of water-related natural disasters, and anthropogenic forcing (e.g. inappropriate agricultural practices, and land usage) on the natural environment (e.g. health impacts from water and air, fragmentation of habitats, etc.).
Groundwater contamination risk is influenced by hydroclimatic constraints, abstraction-driven dilution capacity, and ecological sensitivity, rather than chemical levels alone. However, groundwater pesticide assessments generally prioritize sites based on measured concentrations. We developed a groundwater-focused Level of Concern (LOC) indicator that integrates cumulative pesticide mixture toxicity expressed as an ecological Risk Quotient (RQ) derived from reported groundwater concentrations and groundwater Predicted No-Effect Concentrations (PNECGW), baseline water stress (BWS) as a proxy for groundwater scarcity and reduced assimilative capacity, and composite tetrapod biodiversity richness as an index of ecological sensitivity. The aridity index (AI) was retained as a supporting context to interpret recharge limitations and the persistence or mobility of contaminants across climatic zones. The framework was applied across diverse Indian aquifer provinces spanning semi-arid, dry sub-humid, and humid regions, including the Indo-Gangetic Plains and stressed urban aquifers (Delhi; Farrukhabad, Agra, Kanpur, Unnao, Varanasi, Lakhimpur Kheri, Gorakhpur), semi-arid transition and irrigated belts (Jaipur in Rajasthan; Hisar, Ambala, Gurgaon in Haryana), humid floodplains (Nagaon and Dibrugarh in Assam), deltaic and coastal aquifers (North 24 Parganas and South 24 Parganas in West Bengal; Thiruvallur in Tamil Nadu), and hard-rock basalt systems in central India (Bhandara, Amravati, Yavatmal in Maharashtra).
Results show pronounced spatial heterogeneity and two dominant pathways of groundwater vulnerability. In semi-arid provinces with high to extremely high BWS, medium to very high pesticide risk classes align with constrained dilution and persistence, and these sites are predominantly categorized as medium concern (LOC=2). In humid alluvial systems, very high pesticide-risk classes can occur under low to high BWS, consistent with recharge-driven transport and strong groundwater–surface water connectivity. These locations also cluster in the medium concern class (LOC=2). High concern (LOC=1) is identified at Yavatmal, where semi-arid conditions and extremely high BWS coincide with cumulative stress. Low concern classifications (LOC = 3-4) are limited to Kanpur, Gorakhpur, and South 24 Parganas, where cumulative stress is lower under their respective BWS, RQ, and AI classes.
How to cite: Mitra, S. and Ray, S.: Risk Assessment of Pesticides in Groundwater of India: An Integrated Index of Water Stress, Climate, and Biodiversity, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1608, https://doi.org/10.5194/egusphere-egu26-1608, 2026.
The increasing frequency and intensity of hot and dry extremes under climate change are expected to reduce crop yields and their stability. Irrigation and diverse crop rotations have separately been shown to buffer against the negative impacts of such extremes, potentially leading to higher and more stable yields compared with rainfed cropping and monoculture. Yet, their joint effects remain unquantified across a broad range of pedoclimatic conditions and field management practices. Using the newly developed USDA crop sequence boundary data and remotely sensed estimates of annual irrigation occurrence, we quantified the combined effects of crop diversity, prevalence of irrigation, and dry-spell length and temperature on county-level corn and soybean yields in the USA from 2008 to 2023. We also assessed how these factors jointly influence yield stability, defined as low interannual yield variability and measured via the yield standard deviation over the same period. Initial results show that, where rainfed agriculture was more prevalent, corn and soybean yields and their stability were higher with more diversity in rotated crops independently of dry-spell length and temperature. Conversely, under widespread irrigation, more stable corn and soybean yields were generally associated with higher rotational diversity under long or warm dry spells. Under the same conditions, soybean, but not corn, yields were higher with more diverse rotations. Under both longer and warmer dry spells, corn and soybean yields increased with diversity and even more so under higher irrigation prevalence, suggesting that the capacity of rotational diversity to mitigate yield losses under adverse climatic conditions is amplified by irrigation.
How to cite: Suliman, M., Bassiouni, M., D'Odorico, P., Bommarco, R., and Vico, G.: Irrigation amplifies the benefits of rotational diversity on crop yields and their stability under climatic extremes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13693, https://doi.org/10.5194/egusphere-egu26-13693, 2026.
Climate change–induced droughts have intensified water stress in rain-fed agricultural systems, challenging traditional management practices that often optimize for single objectives, such as yield or water use efficiency. Tea fields in Pinglin, Taiwan, are particularly sensitive to hydroclimatic variability, as tea growth and quality depend strongly on soil moisture dynamics, evapotranspiration, and microclimatic conditions.
Previous studies have demonstrated that organic and conventional tea fields exhibit distinct soil water dynamics and energy partitioning, suggesting potential trade-offs between water use, microclimate regulation, and production-related management objectives.
Building on existing empirical and modeling-based insights into tea field hydrology, this study aims to reframe tea plantation management through the lens of a Water–Energy–Food Nexus. By treating management as a clear multi-objective decision problem, we reframe the competing objectives between water availability, irrigation, energy dynamics, and food production relevant to tea yield and quality.
To operationalize this decision framework at the field level, this study employs the Conditional Water Depletion Index (CWDI) to translate physical water demand (evapotranspiration) and supply(rainfall and irrigation) into a dimensionless indicator of system scarcity. The CWDI effectively represents the vulnerability and sensitivity of the tea field. This quantified state serves as the basis for informing the timing and intensity of management interventions.
By clarifying the structure of water–energy–production trade-offs in tea fields, this exploratory study provides a conceptual and analytical basis for future research that may incorporate dynamic decision-making and learning-based approaches to enhance agricultural resilience under increasing climate and water uncertainties.
How to cite: Chen, H. and Hsu, S.-Y.: Toward a Multi-objective Decision Framing for Tea Fields Management under Water Stress, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19977, https://doi.org/10.5194/egusphere-egu26-19977, 2026.
A rational evaluation of virtual land and water resource flows within the grain trade can potentially serve: (i) to mitigate regional resource scarcity, (ii) as the basis for agricultural water and land resource management, and (iii) to support policymakers in making strategic choices for resource redistribution and sustainable development. Failing to reflect real-world agricultural production systems and irrigation-driven resource management practices, existing evaluation frameworks consider only the virtual water and land content embedded in traded grain, neglecting the marginal productivity enhancement effect of irrigation under cropland constraints. In this study, a modified framework was developed to incorporate irrigation effects into virtual water and land resource accounting and was applied to an empirical analysis of interprovincial grain transfers in China, where arable land resources are strictly constrained. The results indicate that China's land and water productivity under irrigated agriculture are 2.18- and 1.32-fold greater than under rainfed agriculture, respectively; however, the irrigation provision rate remains below 50%. Failure to consider the role of irrigation leads to contradictory evaluation results for virtual water and land flows in certain trade routes, thereby generating misleading policies. Aiming at the 2030 grain production target, this study further explores the feasibility of boosting grain production capacity by expanding irrigation coverage using water resources saved through efficiency improvements. Furthermore, the modified trade framework is utilized to identify optimal pathways for interprovincial production increases. By altering the perspective of virtual water and land resource assessment, this study provides a basis for agricultural layout optimization, irrigation development, and water resource management policies.
How to cite: Wu, N., Gerbens-Leenes, W., Yi, J., and Cao, X.: Assessing the Real Impact of Inter-provincial Grain Trade on Water and Land Resources in China: A Modified Framework Incorporating Irrigation Productivity, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20656, https://doi.org/10.5194/egusphere-egu26-20656, 2026.
Climate change is altering the frequency and intensity of hydrological extremes, amplifying their consequences for agriculture and food security. In regions already burdened by socioeconomic vulnerabilities, agricultural losses from floods and similar events can disrupt food systems far beyond crop produce availability alone. Despite growing recognition of these cascading effects, methods to estimate food security impacts—while remaining compatible with local data and time constraints—are still limited. This study introduces a practical framework for translating post-disaster assessments into indicators of food availability, access, and utilization, placing affected communities at the center of the analysis and offering insights into food stability. We apply this approach to the 2015 floods in Malawi, estimating that crop losses equated to food sufficient for over 300,000 people and dietary balance for nearly 2.3 million, with disproportionate impacts on poorer districts. Although simplified, the methodology is transparent, replicable, and adaptable to other disaster contexts, providing actionable evidence for policy and recovery strategies aimed at safeguarding food security.
How to cite: Galli, N., Govoni, C., and Rulli, M. C.: Quantifying Food Security Impacts of Hydrological Disasters Through Post-Event Assessments , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20821, https://doi.org/10.5194/egusphere-egu26-20821, 2026.
Assessing the reliability of irrigation water-allocation plans under climate change is essential for sustainable agriculture, especially when alternative water sources such as reclaimed water are considered. This study evaluates an irrigation allocation plan for a sorghum–wheat rotation in Kinmen, Taiwan, combining stakeholder engagement, climate analysis, stochastic rainfall simulation, and system modeling. Two local workshops with farmers and experts were conducted to refine feasible irrigation practices and design paired experimental and control fields for subsequent calibration. Historical rainfall from the Kinmen weather station (2005–2025) indicates fewer rainy days and more concentrated events in the recent decade, suggesting increasing rainfall extremity. Future climate scenarios (SSP2-4.5 and SSP5-8.5) were bias-corrected using quantile-based adjustment over 2015–2025, then analyzed for seasonal shifts and extremes. Rainfall temporal structure was simulated using the NEOPRENE Neyman–Scott framework, while XGBoost models were trained on observations to generate daily meteorological variables and reference evapotranspiration. These climate inputs drove a WEAP-based irrigation allocation model coupled with the MABIA method to estimate yields, water use, and economic performance over a 20-year planning horizon. Results show that weekly irrigation increases yields but yields the lowest net profit due to higher labor and energy costs. Under SSP2-4.5 (wetter and more evenly distributed rainfall), a three-week irrigation interval maximizes profit, whereas under SSP5-8.5 (more concentrated rainfall and longer dry spells), a two-week interval provides the best balance between yield stability and cost. The framework provides decision support for robust irrigation planning under uncertain future climate conditions.
How to cite: Hsu, S.-C., Chen, Y.-R., and Yu, H.-L.: Reliability of Irrigation Water Allocation under Climate Change: A WEAP–MABIA Assessment for Kinmen Using Stochastic Rainfall and ML-Based Weather Generation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20921, https://doi.org/10.5194/egusphere-egu26-20921, 2026.
Understanding the complex interplay between hydrology, agricultural productivity, and ecosystem health is critical for sustainable catchment management under future climate and socioeconomic change. The Upper Main Catchment in Bavaria is a productive rainfed agriculture region with efficient sectoral water allocation and established cropping systems. This balance may be increasingly threatened by projected changes in temperature, precipitation patterns and water availability under future climate scenarios. Rising irrigation demands, coupled with shifts in crop phenology and soil nutrient dynamics, could intensify pressure on water resources and ecological stability. As such, this calls for integrated, forward-looking assessments to capture the dynamic interlinkages between water, food and ecosystem entities across diverse future pathways.
The present study employs a coupled modeling framework using the Soil and Water Assessment Tool (SWAT+) and the Water Evaluation and Adaptation Planning (WEAP) model to evaluate the water-food-ecosystem nexus under climate-driven socioeconomic scenarios. The framework is applied under three Shared Socioeconomic Pathway (SSP) scenarios, SSP126, SSP370 and SSP585, using bias-corrected climate projections from five Global Climate Models (GCMs) sourced from the ISIMIP3b dataset. A historically calibrated SWAT+ model simulates streamflow, percolation, crop yield, irrigation water demand and nitrate dynamics under 15 future scenario combinations (3 SSPs × 5 GCMs). WEAP simulations assess how much of the estimated irrigation demand can be met, allowing evaluation of unmet demands across sectors and time periods.
Scenario-specific projections are used to assess increase in irrigation demand and shortfalls, yield variability and soil nitrate accumulation. By integrating SWAT+-simulated demands with WEAP allocation outcomes, the study identifies spatial and seasonal mismatches between crop water requirements and available supply. Trade-off analysis highlights how future changes in water availability affect agricultural productivity and nitrate loading risks, revealing tensions between maximizing yield and maintaining environmental sustainability. Scenario-driven differences reveal potential stress hotspots, in both spatial and temporal scales. The ensemble spread across GCMs and SSPs underscores the uncertainty associated with climate projections, highlighting the need for resilient strategies for a range of plausible futures. The findings provide a critical evidence base to support integrated water, agriculture, and ecosystem management in Bavaria.
How to cite: Prakash, S., Ayyappan Preetha Kumari, S., and Huang, J.: Integrated Modeling of the Water–Food–Ecosystem Nexus in the Upper Main Catchment under Future Climate and Socioeconomic Scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21523, https://doi.org/10.5194/egusphere-egu26-21523, 2026.
The current works aims to identify the perspectives of agricultural sector practitioners on climate risk and their response strategies for improving climate resilience, in Greece, using a recently published nationally representative survey data (Serafeim et al. in 2025).
Based on the survey, almost every responder related to the agricultural sector (i.e. farmers), believes in the existence of climate crisis, while 84,2% of them has experienced environmental changes in their region, including extreme phenomena like droughts, rising temperatures, forest fires, and flooding, all of which pose a significant threat to agricultural production in Greece. Despite this notably high level of awareness the responders highlighted a low level of preparedness, since only 2.6% of the agricultural related group has attended training on either climate change or disaster preparedness. However, there is a high level of adaptive readiness, given that 71.1% showed a strong willingness to attend such training sessions.
These results underscore the need for specific training and adaptation policies based on local perceptions to enhance the resilience of the agricultural communities of the Mediterranean region. This can be done by capitalizing the use of national perception data to inform the development of an evidence-based climate change adaptation strategy to address the resilience gap in rural livelihoods.
References
Serafeim, A. V., Perdios, A., Emmanouil, S., Kritidou, E., Ntona, M. M., Aspioti, A., Georgaki, M. N., Papailiopoulou, M. and Kanellaki, M.V. (2025). National survey-based investigation of climate risk perceptions and adaptation readiness in Greece [Dataset]. Dryad. https://doi.org/10.5061/dryad.t1g1jwtg1.
How to cite: Kanellaki, M. V., Kritidou, E., Perdios, A., Emmanouil, S., Ntona, M. M., Aspioti, A., Georgaki, M. N., and Serafeim, A. V.: Climate Change Perceptions and Resilience Readiness among Agricultural Practitioners in Greece: Evidence from a National Survey Dataset, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14776, https://doi.org/10.5194/egusphere-egu26-14776, 2026.
