Key Objectives:
• Promote interdisciplinary exchange across hydrology, climate science, and environmental engineering
• Showcase cutting-edge approaches for attributing hydrological change across spatial and temporal scales
• Critically evaluate current attribution techniques, including model-based decomposition, scenario analysis, and sensitivity frameworks
• Support the development of actionable tools for sustainable water governance, risk mitigation, and climate resilience
Topics of Interest:
1. Quantitative attribution frameworks for streamflow and runoff changes
2. Disimpassion of climatic and anthropogenic influences in hydrological records
3. Impacts of land use/land cover dynamics and hydraulic infrastructure on watershed hydrology
4. Role of climate change in altering precipitation, evapotranspiration, and storage dynamics
5. Scenario-based simulations using hydrological and Earth system models
6. Data-scarce region modeling: constraints, solutions, and innovations
7. Translating attribution science into policy-relevant insights and integrated water management strategies
Expected Outcomes:
Deepened scientific understanding of the causal factors behind hydrological change
Cross-regional exchange of methods, models, and data-driven approaches
Enhanced collaboration between researchers and decision-makers
Identification of research gaps and methodological needs in hydrological attribution
Understanding how Caribbean watersheds respond to climatic and landscape pressures is essential for
water-resource management in Small Island Developing States (SIDS). Jamaica’s rivers provide domestic
supply, irrigation, hydropower potential, and ecosystem services, yet limited work compares long-term
hydrological behavior across basins with contrasting geology, land cover, and rainfall regimes. This study
examines hydrological change in the Martha Brae, Rio Minho, and Rio Grande watersheds using daily
discharge (1981–2010) separated into baseflow and runoff with WETSPRO. Rainfall trends were assessed
using station data, and monotonic trends were quantified using the Mann–Kendall and Sen’s slope tests.
Dominant lithologies and land-cover classes were identified using geological maps and LULC datasets.
The results show clear divergence in hydrological trajectories across the three basins. In the
metamorphic–volcanic Rio Grande, baseflow increases weakly (τ = 0.0625; Sen’s slope = 2.03×10⁻⁴),
total flow shows a minimal rise (τ = 0.0182), and runoff slightly declines (τ = –0.0426). A significant
increase in rainfall (τ = 0.186, p = 0.021) indicates that rainfall is the main driver, with high forest cover
and permeable lithology promoting enhanced infiltration and groundwater recharge. In the karstic Martha
Brae, modest increases in total flow (τ = 0.065) and baseflow (τ = 0.0783; Sen’s slope = 5.45×10⁻⁵)
correspond with significantly rising rainfall (τ = 0.206, p = 0.012). Here, geology dominates, as the high
storage capacity of limestone aquifers regulates flow and buffers climatic variability. In the alluvial, semi-
arid Rio Minho, small increases in total flow (τ = 0.0801), runoff (τ = 0.0184), and baseflow (τ = 0.0940;
Sen’s slope = 3.64×10⁻⁵) occur despite no significant rainfall trend (τ = –0.025, p = 0.76), showing that
land cover and low-permeability sediments exert the strongest control by limiting infiltration and
sustaining weak baseflow.
These findings have critical implications for Jamaican water supply. Karst basins may continue to provide
reliable dry-season flows due to strong groundwater buffering, while alluvial, agriculturally disturbed
basins remain highly vulnerable to drought and flash-flood extremes. Strengthening forest cover,
protecting recharge zones, and improving land-management practices will be central to enhancing
Jamaica’s climate-resilient water-resource security.
How to cite: Woods, S. and Farrick, K.: An Analysis of Baseflow and Runoff Variability of Jamaican Watersheds, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-924, https://doi.org/10.5194/egusphere-egu26-924, 2026.
Understanding whether and why observed flood hazards are changing remains a central challenge for hydrology. While event-based attribution has advanced rapidly, robust attribution of changes in observed flood series remains difficult due to the integration of exogenous climatic forcing with endogenous catchment change (e.g. urbanisation, landuse change) and data quality challenges (especially for extremes). Here we develop and apply a causal-chain framework to detect, attribute, and scale changes in annual maximum floods using observational data. Taking the Shannon catchment in Ireland as an exemplar, we i) identify causal chains to reconstruct annual maximum instantaneous discharge from flood-relevant precipitation indices, ii) separate climate-driven and residual components of observed change, iii) evaluate the emergence of a climate change signal in causal chains by regressing (multiple linear regression) local precipitation indices onto global mean surface temperature (GMST), and iv) employ these results to scale local changes in flood magnitude to observed and future changes in GMST. Results show that increases in flood magnitude across the catchment are predominantly climate-driven, with multi-day precipitation totals representing antecedent conditions, particularly annual 30-day maxima and the number of very wet days in winter, emerging as the dominant causal pathways. These precipitation indices exhibit detectable warming-related signals that have emerged from variability and explain a substantial proportion of observed increasing flood trends at all sites (ranging between 28 and 93 percent). Residual trends highlight the role of endogenous catchment factors, especially data quality, changing hydrometric conditions and arterial drainage. By linking local flood discharge directly to GMST via causal chains, the framework quantifies catchment-specific flood sensitivity expressed as percentage change per degree of warming, enabling scaling to future warming levels. Results indicate that flood sensitivity per degree increase in GMST varies substantially across catchments, ranging from 8 to 18 percent per degree warming across the catchment sample. The approach provides an observation-based framework for flood attribution, leveraging established methods to bridge trend detection, process understanding, and climate scaling. Moreover, the approach can identify sensitive catchments, sentinel indices for monitoring floods and help better inform adaptation strategies. The approach is readily transferable to other catchments and hydrological extremes.
How to cite: Murphy, C., Bile, M., Fordham, S., Wilby, R. L., Donegan, S., Hawkins, E., Hannaford, J., Slater, L., Matthews, T., Harrigan, S., and Ryan, C.: Attributing and Scaling Climate Change Impacts on Floods Through Causal Chains, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5668, https://doi.org/10.5194/egusphere-egu26-5668, 2026.
Urban precipitation reflects complex land–atmosphere interactions. However, the potential influence of vegetation change surrounding cities on urban precipitation remains insufficiently understood.
In this study, we examine the relationship between peri-urban vegetation change and urban precipitation variability by integrating satellite-based vegetation indicators, evapotranspiration modelling frameworks, and atmospheric moisture tracking techniques across a large set of cities worldwide. This approach enables quantification of how vegetation-induced evapotranspiration contributes to urban precipitation variability through atmospheric moisture transport.
Our analysis reveals a coherent hydroclimatic link in which changes in peri-urban vegetation are associated with variations in evapotranspiration and subsequent in urban precipitation. We further explore how this coupling varies across different atmospheric conditions, vegetation landscapes, and urban environments. The results indicate that there are substantial inter-urban differences in the strength of vegetation–precipitation coupling.
By clarifying the interaction mechanism among vegetation changes, evapotranspiration and urban precipitation, this study contributes to a broader understanding of land–atmosphere interaction and hydrological variability. The findings highlight that peri-urban vegetation is an important component of the hydrological cycle and provide insights for understanding hydrological variability under changing environmental conditions.
How to cite: Li, J.: Exploring the Role of Peri-Urban Vegetation Change in Urban Precipitation Variability, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2167, https://doi.org/10.5194/egusphere-egu26-2167, 2026.
Drought represents a significant hydroclimatic hazard in arid regions of Asia and Africa, where climate change exacerbates evaporative demand, leading to intensified moisture stress, agricultural disruptions, and water insecurity. This study evaluates the Evaporative Demand Drought Index (EDDI) as a complementary tool to traditional precipitation-based indices, such as the Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI), for monitoring drought dynamics, with a focus on flash droughts and evapotranspiration-driven anomalies. Utilizing high-resolution ERA5-Land reanalysis data (0.1° spatial resolution) from 1983 to 2023, EDDI was computed using the Penman-Monteith formulation across multiple timescales, including sub-weekly (1–3 weeks) and monthly (1–12 months) periods. The analysis encompassed diverse arid zones classified by the Intergovernmental Panel on Climate Change, including the Sahara (SAH), Mediterranean (MED), Arabian Peninsula (ARP), West Central Asia (WCA), Eastern Europe (EEU), West Siberia (WSB), East Siberia (ESB), East Central Asia (ECA), and Tibetan Plateau (TIB). Performance assessment involved modified Mann-Kendall trend tests, Sen’s slope estimation, Spearman rank correlations, run theory for drought characterization (duration, severity, intensity, peak, and frequency), and a case study of the 2010 drought event. Results revealed pronounced spatial and temporal heterogeneities in drought patterns. EDDI exhibited stronger drying trends compared to SPI and SPEI, driven by significant increases in reference evapotranspiration (ETo; 2.0–5.16 mm year⁻¹) and temperature (0.02–0.05°C year⁻¹) across most regions, except the TIB, where wetting trends predominated due to elevational effects. In hyper-arid areas such as SAH and ARP, EDDI identified significant drying in 45–60% of grid cells, in contrast to SPI's wetting signals, underscoring EDDI's sensitivity to atmospheric demand independent of precipitation. Spearman correlations between EDDI and SPEI were notably strong (ρ ranging from -0.83 to -0.91 at 1-month scales), exceeding those with SPI (-0.41 to -0.79), particularly in SAH (-0.91 for EDDI-SPEI). Drought frequency intensified post-2000 in all regions except TIB, with EDDI capturing higher severity in SAH and ARP due to elevated ETo. Run theory analysis showed that, at longer timescales, drought duration, severity, and intensity increased, while frequency decreased; EDDI consistently indicated more acute conditions than SPI in water-limited environments. During the 2010 drought, EDDI detected the onset 2–4 weeks earlier than SPI in ARP and SAH, highlighting its utility for rapid-onset events through sub-monthly sensitivity to ETo anomalies. Spatial progression revealed severe drought (category C4) expanding in SAH and EEU at 6–12-month scales, with EDDI and SPEI aligning more closely than SPI, reflecting the influence of vapor pressure deficits and land-atmosphere feedbacks grounded in the Budyko framework. These findings affirm EDDI's role as an indirect proxy for drought stress via evaporative demand, complementing precipitation-focused indices in arid settings where ETo dominates. Limitations include potential overestimation in irrigated areas and assumptions of stationarity under non-stationary climate conditions. Integration of EDDI into operational early warning systems could enhance proactive management, supporting adaptive strategies like water allocation and resilient agriculture amid projected aridification.
How to cite: Ogunrinde, A. and Ali Shah, S.: Enhancing Drought Early Warning in Arid Asia and Africa: Comparative Performance of the Evaporative Demand Drought Index under Climate Change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2958, https://doi.org/10.5194/egusphere-egu26-2958, 2026.
Reservoirs play a vital role in regulating the spatial and temporal distribution of water resources and meeting downstream demands. However, the impacts of reservoirs on hydrometeorological factors, and how they affect sustainable water management are mostly overlooked in the existing literature. Hence, this research investigates panel regression methodologies to analyze the impacts of reservoirs across 49 catchments in Peninsular India, with specific stress upon the synchronous and lagged impacts of reservoir expansion on groundwater storage, baseflow, and other hydrological states and fluxes. The study found that reservoir expansion had statistically significant effects on both hydrological and climatic factors in Peninsular India, with more than 65% of all tested relationships showing significance. Reservoirs were found to significantly increase evapotranspiration and groundwater storage during the monsoon and post-monsoon seasons. Fixed Effects models, which demonstrated significant basin-specific limitations on hydrological responses, received the majority of the support. Reservoir operations were found to have an impact on regional temperature and precipitation in addition to groundwater, soil moisture, and evaporation. This demonstrates that there is a quantifiable feedback between the atmosphere and the land. In contrast, baseflow responses were feeble and mostly insignificant, reflecting the buffered nature of subsurface channels. Groundwater storage emerged as the most sensitive variable. As a result, the region's reservoirs mainly influence groundwater storage rather than surface factors, indicating a change in the water balance where reservoirs improve subsurface retention and mitigate seasonal shortages. This study highlights the need for integrated reservoir and climate management strategies by showing the potential of a strong novel approach based on panel regression for interpreting the effects of reservoirs on catchment-scale hydrology.
How to cite: Puthenpura, S. and Kasiviswanathan, K. S.: Hydrologic and Climatic Signatures of Reservoir Operations Using Long-term Panel Data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1011, https://doi.org/10.5194/egusphere-egu26-1011, 2026.
Soil organic carbon (SOC) can be heavily influenced by climate change via temperature-enhanced SOC mineralization and by agricultural management via soil degradation from intensive agriculture. In contrast, climate-mitigation leads to sequestering of carbon and increasing SOC and can enhance soil water retention, which may support agricultural production under increasing summer droughts. Here, we investigate how agricultural management–induced changes in soil organic carbon (SOC) interact with climate change to shape future catchment-scale hydrology. The study area is the Broye catchment in western Switzerland. The study employs scenario-based hydrological simulations with the distributed hydrological model mHM, which is driven by CH2025 climate scenarios for Switzerland. These newly available scenarios combine CMIP5-based EURO-CORDEX regional climate simulations and statistical downscaling techniques with insights from CMIP6, to obtain high-resolution (1km × 1km) Swiss climate scenarios. With this model chain, we contrast a no-adaptation pathway characterized by management- and warming-driven SOC decline with SOC-enhancing management pathways that promote SOC accumulation (organic amendments, minimum tillage, or biochar application). We present and discuss the hydrological responses to the two pathways, focussing on changes in evapotranspiration, runoff, and low-flow frequency and evaluate the robustness of responses to climate projection uncertainty. Given that climate projections are often large sources of uncertainty in hydrological simulations, robustness is evaluated based on inter-model agreement, allowing us to distinguish which SOC-induced changes in key processes and metrics (e.g., evapotranspiration, discharge, and low-flow frequency) are consistent and which remain ambiguous.
How to cite: Heinz, M., Schaefli, B., Holzkämper, A., and Raible, C. C.: Agricultural management and Climate Change Impacts on Catchment-Scale Water Fluxes − the Role of Soil Organic Carbon, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9115, https://doi.org/10.5194/egusphere-egu26-9115, 2026.
The Haihe River Basin in northern China is one of the most water-stressed regions characterized by limited natural water resources, intensive groundwater exploitation, and a water use structure dominated by agricultural irrigation. In recent years, partial groundwater recovery has been observed in some areas, driven by large-scale water diversion projects, groundwater abstraction control policies, improved irrigation efficiency, and favorable climatic conditions. However, whether this recovery represents a sustainable transition or a temporary, human-regulated phenomenon under climate variability remains unclear.
In this study, we employ a coupled surface–subsurface hydrological model (CWatM–MODFLOW) to quantify the combined impacts of climate change and human water use on basin-scale water resources. The model explicitly represents surface water–groundwater interactions and dynamically simulates irrigation water demand and other sectoral water withdrawals within the hydrological system.
Model simulations with multiple future climate scenarios are conducted to investigate potential changes in water availability, water demand, and their combined effects on the spatial and temporal patterns of water stress across the basin. By jointly analyzing projected water resources and irrigation-dominated water consumption, this study aims to disentangle the relative contributions of climate forcing and anthropogenic activities to future water scarcity and groundwater sustainability in the Haihe River Basin.
The outcomes of this work are expected to improve understanding of how climate change and human water use may influence water availability and stress patterns in the Haihe River Basin.
How to cite: Chen, Y. and Zhang, J.: Disentangling Climate and Anthropogenic Impacts on water resources in the Haihe River Basin using a coupled surface–subsurface model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4173, https://doi.org/10.5194/egusphere-egu26-4173, 2026.
Water-related ecosystem services (WES) underpin water security but are increasingly threatened by concurrent climate change and land-use change. Yet reliable, generalizable attribution evidence remains limited, because most studies are single-basin and do not explicitly separate climatic and anthropogenic drivers. Here, we implement a scenario-based attribution framework that uses controlled scenario contrasts (climate-only, land-use-only, and coupled scenarios) to quantify and compare the relative contributions of climate and land-use change to two key WES (i.e., water yield and water purification services), and to project WES trajectories for 2020-2100. Using the InVEST Annual Water Yield and Nutrient Delivery Ratio modules, we estimate annual water yield and total nitrogen (TN) export across 17 representative watersheds in China spanning diverse hydroclimatic and landscape settings, and assess WES responses across scenario types. Results show a clear contrast in dominant drivers: climate change affects water yield more than water purification, whereas land-use change affects water purification more than water yield. Climate change contributed >90% to water yields in 15 out of the 17 watersheds; it was 79.4% in the Hei River and only 11.2% in the Yarkant River. For TN export, climate change had a larger influence than land-use change in eight watersheds, exceeding 95% in the Min and Mintuo rivers. For TN export (water purification), climate change had a larger contribution than land-use change in 8 of the 17 watersheds ( >95% in the Min and Mintuo rivers), whereas land-use change dominated in the remaining 9 watersheds ( >95% in the Dongting Lake and Hei River basins). These cross-watershed attribution results identify where climate adaptation versus land-use management is likely to be most effective for sustaining water yield and water quality under future change. The aim of this study is to provide cross-basin attribution evidence that helps target climate adaptation and land-use management to sustain water yield and water quality under future change.
How to cite: Huang, X., Yu, C., and Xu, Z.: Predicting water ecosystem services under prospective climate and land-use change scenarios in typical watersheds distributed across China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7783, https://doi.org/10.5194/egusphere-egu26-7783, 2026.
The Mediterranean basin is particularly vulnerable to climate change. These changes are potentially impacting groundwater resources and aquifer recharge. In this context, reducing vulnerability to hydrological extremes (drought and flooding) and preserving both the quantity and quality of the resource are two key priorities for public authorities. Hydrogeological simulations are conducted based on different climate scenarios to provide information on how the resource may evolve in various scenarios. The hydrographic basin of the Lez spring is located in southern France. It is a basin composed of Upper Cretaceous and Lower Jurassic rocks, which are highly karstified. The spring of this basin is used to supply drinking water to the Montpellier metropolitan area (approximately 400,000 residents), generating strong pressure on this resource. The hydrogeological catchment of the Asserdoune karst spring, located in northern Morocco, is actively used to supply Beni Mellal (280,000 residents) with drinking water. The two main objectives of this study are (i) to assess long-term trends in climatic (rainfall, temperature, potential evapotranspiration) and hydrological variables (spring and river discharges) and (ii) to develop hydrological projections based on CMIP6 climate projections under the SSP2-4.5 and SSP5-8.5. For the Lez spring, these climate projections are coupled with anthropogenic withdrawal projections, developed in collaboration with water managers. The trend analysis results indicated a strong increase in temperature and evapotranspiration, but contrasting trends in precipitation between France and Morocco. The modeling of groundwater recharge and availability under different climatic and anthropogenic scenarios could provide a better understanding of the evolution of the resource at different time horizons, and support the decisions taken by water resource managers.
How to cite: Fabre, E., Jourde, H., Tramblay, Y., Hanich, L., and Brunet, P.: Modeling Climate Change and Human Pressure in Karst Systems: Insights from Mediterranean Springs in France and Morocco, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20232, https://doi.org/10.5194/egusphere-egu26-20232, 2026.
Pakistan, endowed with substantial water and glacier resources in the Upper Indus Basin (UIB), relies heavily on the Tarbela Reservoir for hydropower generation, irrigation, and flood control. As the world's largest earth-fill dam, Tarbela spans a 169,600 km² catchment with an average annual inflow of 79 billion cubic meters, supplying approximately 33% of Pakistan's energy needs. However, climate change-induced variations in precipitation, temperature, and melt patterns pose risks to its reliability. This study assesses the reservoir's response for hydropower generation using the Hydrologic Engineering Center's Reservoir System Simulation (HEC-ResSim) model, integrating historical hydrological data to simulate operations under observed conditions.
Using the data sourced from the Water and Power Development Authority (WAPDA), three modules of HEC-ResSim's were used: Watershed Setup for defining stream alignments, reservoirs, and computational points; Reservoir Network for configuring physical parameters (e.g., elevation-storage-area relationships) and operational rules (e.g., flood control, conservation, and inactive levels); and Simulation for running daily computations with HEC-DSSVue for data management and visualization. Alternatives incorporated time-series inputs from DSS files, with Excel used for supplementary calibration and analysis.
Simulations replicated reservoir behavior, revealing seasonal dynamics: low inflows and power generation in winter (December-February) due to reduced melt, peaking in monsoon (June-September) from rainfall and snowmelt. Annual power generation fluctuated, with notable dips (e.g., around 2013) attributed to water scarcity or operational constraints, despite consistent capability. Inflow-outflow comparisons highlighted storage roles in regulating flows. Model accuracy was validated for 2012-2014 against observed data, yielding Nash-Sutcliffe Efficiency (NSE) of 0.987, Index of Agreement of 0.99, and R² of 0.99, confirming robust simulation of power outputs relative to inflows.
Results underscore climate vulnerabilities, with flow variations over decades impacting generation efficiency amid unpredictable weather, floods, and droughts. The ongoing Tarbela 5th Extension (adding 1,530 MW via three 510 MW units, increasing total capacity from 4,888 MW to 6,418 MW) promises enhanced utilization. Conclusions emphasize HEC-ResSim's utility for real-time decision-making and scenario evaluation. Future studies could employ advanced versions, incorporate climate projections (e.g., from CMIP6), and compare pre- and post-extension scenarios to optimize sustainable hydropower amid UIB's evolving hydrology.
How to cite: Butt, A. Q., Shangguan, D., and Wu, J.: Evaluating Hydrological Alterations Due to Climate Change: Insights from HEC-ResSim Simulations in the Indus river fed Tarbela Reservoir , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2100, https://doi.org/10.5194/egusphere-egu26-2100, 2026.
Runoff in the UYRB has changed due to the combined effects of climate change and human activities. However, comprehensive spatiotemporal attribution studies are still lacking. This study analyzes and attributes runoff changes across different temporal scales (annual, drawdown, and refill periods) and spatial scales (entire basin and five zones). The effects of climate change and land use/land cover change (LUCC) on runoff are quantified using the SWAT+ model. The main driving factors are identified by comparing their contributions with observed runoff changes.
From the baseline period (1961-2000) to the impact period (2001-2023), annual runoff in the UYRB decreased by 34.60 billion m³/yr, while runoff increased by 21.53 billion m³/yr during the drawdown period and decreased by 40.29 billion m³/yr during the refill period. These trends were generally consistent across all zones. Climate change was the dominant factor driving annual runoff changes (77.69%), followed by increased water consumption (13.41%) and LUCC (5.85%). Climate change reduced annual runoff in most zones due to the combined effect of reduced precipitation and increased potential evapotranspiration. However, during the drawdown and refill periods, reservoir operation emerged as another significant driving factor influencing runoff changes. This study provides valuable insights into water resource management in a changing environment.
How to cite: Han, Y., Zhong, P., Wang, Y., Qian, X., Ben, M., and Song, Z.: Spatiotemporal attribution of runoff changes in the upper Yangtze River Basin using the SWAT+ model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-389, https://doi.org/10.5194/egusphere-egu26-389, 2026.
Abstract
Groundwater-dependent ecosystems (GDEs) play a crucial role in maintaining ecological stability and biodiversity, particularly in arid and semi-arid regions. However, in many areas, the location and extent of GDEs remain unidentified, and existing protective measures are insufficient. This study investigates terrestrial GDEs within the North China Plain (NCP), a region increasingly affected by groundwater depletion due to rapid urbanization and intensive agriculture. By integrating multi-source remote sensing datasets, Random Forest (RF) modeling, and GIS-based Multi-Criteria Decision Analysis (MCDA), we mapped the spatial distribution and assessed the temporal dynamics of GDEs across the region. Predictor variables included hydrological and vegetation indices, land cover, and topographic factors. The RF model was trained on georeferenced points and optimized through hyperparameter tuning. Spatiotemporal analysis revealed divergent trends in GDE distribution, with declines likely driven by groundwater stress or land degradation, while expansions likely attributed to improved groundwater recharge, increased ecological conservation efforts, and land use changes. Comparative analysis indicates that most of the GDEs identified in recent years have newly emerged, while a moderate proportion remained stable. Moderate-to high-probability GDE zones identified via MCDA were consistently classified as GDEs by the RF model, highlighting the robustness of this integrated framework. These findings offer critical insights into the evolving distribution of GDEs and provide a decision-support framework for ecological monitoring and sustainable groundwater management.
Keywords: Groundwater-dependent ecosystems; Terrestrial GDE; North China Plain; Random Forest; Multi-Criteria Decision Analysis; GDE dynamics
How to cite: Batsuuri, B.: Spatial Identification and Dynamics of Groundwater-Dependent Ecosystems in the North China Plain: An Integrated Random Forest and Multi-Criteria Decision Analysis Approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9975, https://doi.org/10.5194/egusphere-egu26-9975, 2026.
Climate change is altering precipitation regimes and temperature conditions, thereby modifying hydrological processes and water availability at the catchment scale. At the same time, land use change driven by human activities reshapes land surface characteristics, imperviousness, and energy balance, further influencing evapotranspiration and runoff generation. Understanding the combined effects of climate variability and land use change is therefore essential for assessing future hydrological responses and supporting sustainable water resources management. This study investigates the impacts of land use change under climate change on key hydrological variables in the Mudan Reservoir catchment in southern Taiwan, with a particular focus on changes in evapotranspiration and runoff.
Historical land use data from multiple periods are first compiled into a consistent land use database with unified classification schemes and spatial resolution. Land use transition patterns, temporal trends, and spatial hotspots of change are analyzed to characterize historical land use dynamics. Future land use scenarios are then simulated using the Patch-generating Land Use Simulation (PLUS) model, which integrates land expansion analysis and patch-based cellular automata to capture both transition mechanisms and realistic landscape patterns. These simulations provide spatially explicit land use projections at different future time horizons, serving as a foundation for hydrological analysis.
Climate forcing is derived from statistically downscaled AR6 climate projections provided by the Taiwan Climate Change Projection and Information Platform (TCCIP), representing future changes in precipitation and temperature. A long-term catchment water balance framework is established to quantify major hydrological components, including precipitation, evapotranspiration, and runoff. The relationship between land use composition and hydrological partitioning is examined, with particular emphasis on the evapotranspiration-to-precipitation ratio (ET/P) and runoff response under different land use conditions. A simplified land use–ET/P relationship is developed and applied in conjunction with future land use scenarios and climate projections to assess changes in evapotranspiration and runoff.
The results provide insights into how land use change and climate change jointly influence hydrological variability in reservoir catchments. By explicitly linking human-driven land use dynamics with climate-induced hydrological change, this study contributes to a better understanding of coupled human–natural systems and offers scientific support for reservoir operation and adaptive water resources management under a changing climate.
How to cite: Kuo, C.-M., Chanthaharn, P., Chen, Z.-M., and Chen, C.-N.: Impacts of Land Use Change on Catchment Hydrological Variables under Climate Change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3627, https://doi.org/10.5194/egusphere-egu26-3627, 2026.
There are growing concerns regarding the hydrological impacts of native forest loss and exotic plantation expansion; yet these effects remain poorly constrained in regions where climate variability associated with the El Niño–Southern Oscillation (ENSO) may mask underlying land cover change signals. In addition, legacy soil conditions inherited from previous land uses can further modulate hydrological responses. This study examines the combined influence of land cover change, and ENSO variability on river flow dynamics in coastal catchments of central Chile.
Using a 45-year hydroclimatic dataset (1979–2023), we analysed seasonal and annual streamflow trends across four catchments with contrasting land cover trajectories. Significant streamflow declines were detected in four catchments, particularly during summer, when water availability is most critical. Catchments experiencing 4–9% native forest loss exhibited reduced baseflows, whereas catchments with largely preserved native forest cover maintained or even increased summer flows. Interaction analyses indicate that native forest cover enhances precipitation–runoff conversion, while exotic plantations reduce runoff efficiency (precipitation × land cover interactions; R² = 0.46–0.77, negative slopes). ENSO phases alone explained little streamflow variability (R² < 0.04), but significant ENSO-precipitation interactions across all catchments (p < 0.001) highlight an indirect, yet consistent, climatic influence.
To extend these observational findings and explore underlying hydrological processes, a physically-based hydrological model (SWAT) was implemented for the study catchments. Model calibration and validation show satisfactory performance, providing a robust basis for scenario-based simulations. Ongoing modelling explores the relative and combined impacts of land cover change and climate variability on streamflow under current conditions. The integration of long-term observations with process-based modelling offers new insights into how vegetation change modulates hydrological resilience to climate variability, with important implications for water security and ecosystem management in this type of regions.
How to cite: Escanilla-Minchel, R., Holden, J., and Smith, M.: Land Cover Change Modulates River Flow Responses to Climate Variability in Central Chile, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13658, https://doi.org/10.5194/egusphere-egu26-13658, 2026.
Assessing the evolution of the hydrology of a catchment with multiple human influences over a long period remains an open question. Among these influences, changes in land use represent a potentially major driver of long-term hydrological change. Over the past centuries, many catchments have experienced significant transformations in land cover and water uses, leading to substantial consequences on flow regime and water balance components. In France, forested area has significantly increased over the past 150 years, and this land use long-term dynamics is reflected in Allier catchment (Massif Central) covering approximately 2700 km2. Originally dominated by 46% of cultivated land in the late 19th century, this catchment experienced a decline to 17% in the 21th century to the benefit of forests, which increased from 16% to 47% over the same period.
This study aims to analyze how long-term change in land use and other human activities has modified the catchment hydrology, and to quantify the relative contribution of each type of influence. The proposed methodology is based on hydrological modelling with J2000, a spatially distributed model that allows to reconstruct different water balance components, taking into account land use dynamics, water withdrawals, and reservoir management. Historical information from maps, archives, combined with hydroclimatic data, is used to define 3 30-year periods considered as stationary over a 150-year timeline. Model simulations are performed for each period considering uncertainty related to data availability and quality in order to evaluate changes in streamflow dynamics and water balance components.
This work presents the overall framework of a project aiming at representing historical long-term land use changes in hydrology modelling. By focusing on the historical evolution of land use, the project explores the impact of all anthropogenic drivers on the hydrology of the catchment. Results are expected to enhance the interpretation of past hydrological changes and to open perspectives for future modelling in anthropogenic catchments.
How to cite: Kate, F., Mimeau, L., and Vidal, J.-P.: A proposed framework for disentangling land use change from other influences on catchment hydrology, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10156, https://doi.org/10.5194/egusphere-egu26-10156, 2026.
Against the backdrop of escalating global climate change and human activities, vegetation cover dynamics, as a vital ecological indicator, have profound implications for ecosystem protection, making its monitoring an imperative for sustainable management. The Northwest Plain Region of Shandong Province, a vital agricultural and economic zone in China, experiences vegetation dynamics that significantly influence regional climate regulation and water resource conservation. By integrating normalized difference vegetation index (NDVI) with climatic and anthropogenic data, trend analysis, partial correlation, and GeoSHAP were used to comprehensively assess the spatiotemporal evolution and key driving factors of vegetation cover in the Northwest Plain of Shandong Province (2000–2024). The findings indicate an overall upward trend in vegetation cover, particularly in areas with concentrated human activities. Climatic factors, such as evaporation and temperature, exhibit a positive correlation with vegetation growth, while land use changes emerge as one of the key drivers influencing vegetation dynamics. The findings offer a scientific foundation for ecological protection and land management in the Northwest Plain of Shandong and similar regions, supporting informed decision-making for effective vegetation restoration and conservation strategies.
How to cite: Sun, J., Shi, Y., and Huang, J.: The Impact of Climate Change and Human Activities on Spatiotemporal Variations in Vegetation Coverage in the Northwest Plain Region of Shandong Province, China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4465, https://doi.org/10.5194/egusphere-egu26-4465, 2026.
For more than a millenia, human activities have significantly altered various aspects of the hydrological cycle through structural interventions and land-use and land-cover changes. Understanding the magnitude and impacts of these alterations is critical to define a near-natural water cycle. In this study, we clustered more than 1,500 German catchments from the CAMELS-DE dataset into near-natural and non-natural groups based on a comprehensive set of criteria. These criteria regard artificial structures (e.g., dam, reservoir, weir, and others in-stream structures), land-use land-cover characteristics (e.g., fraction of agricultural and artificial lands), and water abstractions (e.g., surface and groundwater abstractions). We then selected a range of hydrological indicators, including actual evapotranspiration, runoff-related metrics, soil moisture, groundwater recharge, and groundwater-level dynamics to evaluate the impact of alterations. Values for these indicators will be derived for both near-natural and non-natural catchment groups using publicly available in situ observations, remote-sensing products, and hydrological modelling approaches. By comparing hydrological indicators across catchment groups while accounting for topographical and geological catchment characteristics, this study aims to improve our understanding of the impacts of human activities on different components of the hydrological cycle to ultimately restore near-natural and resilient conditions.
How to cite: Nguyen, T., Siebert, C., Musolff, A., Fleckenstein, J., and Merz, R.: How do anthropogenic activities affect key hydrological indicators in German catchments?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13344, https://doi.org/10.5194/egusphere-egu26-13344, 2026.
