This session offers a platform to exchange concepts, expertise, and methods related to groundwater recharge estimation across disciplines and application contexts.
We invite contributions focusing on the estimation of groundwater recharge across multiple temporal and spatial scales, including studies that compare or combine different methods. Estimation approaches may be based on:
• Field-based measurements from various compartments of the hydrological cycle:
- Land surface water balance components
- Vadose zone measurements (e.g. soil moisture)
- Groundwater heads (water table fluctuations)
- Discharge measurements (baseflow separation)
- Environmental tracers for recharge estimation and model calibration (e.g., stable isotopes, radioisotopes, dissolved gases)
- Including suggestions for improved monitoring concepts
• Model-based approaches (local to global scale), such as:
- Water balance models
- Land surface models
- Physically-based vadose zone or groundwater models
- Hybrid or machine learning-supported methods
- Groundwater time-series models
• Upscaling strategies from point-scale to landscape-scale assessments
• Varying temporal scales from short-term recharge quantification to long-term recharge trends (past or future scenarios)
We welcome studies addressing recharge estimation for various purposes, including (but not limited to) agricultural water management and irrigation, forest management and ecosystem transition, groundwater resource planning, and sustainable management.
Orals: Thu, 7 May, 10:45–12:30 | Room 2.15
Groundwater recharge is a key yet highly uncertain component of the hydrological cycle and is characterized by pronounced variability across temporal and spatial scales. Recharge processes are commonly represented using long-term averages and spatially aggregated concepts, by which the episodic, heterogeneous, and scale-dependent nature of recharge is often obscured. In this presentation, a multiscale perspective on groundwater recharge is presented, covering field observations, regional analyses, and global modeling approaches to illustrate how recharge occurs on timescales ranging from minutes to millennia and from local plots to the planetary scale.
The temporal dimension of recharge is illustrated using examples from arid environments, with a focus on Saudi Arabia. Under current climatic conditions, diffuse groundwater recharge in these regions is typically very low. However, rapid and focused recharge can be generated within minutes during intense rainfall events in areas with exposed karst features, where surface runoff is efficiently channeled into the subsurface. But there are also important processes related to groundwater recharge on much longer timescales. In many arid regions, fossil groundwater is a vital resource that was replenished under past climatic conditions. These paleo-groundwater recharge events represent hydraulic impulses that continue to influence today's groundwater levels and flow patterns, resulting in non-stationary groundwater systems.
The spatial variability of groundwater recharge is examined at local and global scales. Based on exemplary case studies from South Asia, recharge is found to be highly heterogeneous and is controlled by climatic gradients, geological conditions, and intensive human water use, including irrigation return flows. At the global level, groundwater recharge is estimated using neurol networks with eXplainable AI, identifying the dominant factors for groundwater recharge for different climate zones and showing that the control and sensitivity of predictors for groundwater recharge are highly region-specific.
Building on these temporal and spatial perspectives, the implications of groundwater recharge for water quality are highlighted. Using the Hessian Ried (Germany) as an example, a control of recharge rates and residence times in the unsaturated zone on reactive solute transport to groundwater is demonstrated, thereby directly linking recharge dynamics to groundwater quality.
Overall, groundwater recharge is shown to be inherently multiscale and dependent on specific environmental conditions, with important implications for the selection of recharge estimation methods, the temporal and spatial aggregation of groundwater models, and sustainable groundwater management under changing climatic and land-use conditions.
How to cite: Schulz, S., Hillmann, S., Muñoz-Vega, E., Zolezzi-López, J., Richard-Cerda, J. C., Schmidt, I., and Jung, H.: From minutes to millennia, from plots to planet: A spatiotemporal view on groundwater recharge, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14114, https://doi.org/10.5194/egusphere-egu26-14114, 2026.
Despite many efforts to estimate both the spatial and temporal dynamics of groundwater recharge, and to predict how these will be altered by climate change, this crucial part of the water balance remains highly uncertain. Meanwhile, many shallow aquifers are experiencing alarming water level declines due to a combination of high anthropogenic withdrawals and altered precipitation patterns. This work combines recent and long-term datasets from locations throughout the continent of Australia to re-examine how shallow recharge dynamics vary across a diversity of climate types. Available data from a drip logger network demonstrate the interannual variability in rainfall recharge thresholds, with seasonality in the number of recharge events and the rainfall recharge threshold. Historical records of rainfall are then examined to understand the historical return interval of these rainfall volumes, both annually and seasonally. Finally, we examine our results against corresponding data in the historical model runs from the Coupled Model Intercomparison Project (CMIP), to evaluate the realism of the models. The results of this combined methodology provide a more nuanced approach to evaluating the resilience of groundwater supplies in a changing climate.
How to cite: Shanafield, M., Wagener, T., Undorf, S., and Baker, A.: Seasonality in groundwater recharge - Observational evaluation of Earth System model realism, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11189, https://doi.org/10.5194/egusphere-egu26-11189, 2026.
Groundwater recharge in semi-arid hard-rock areas mainly relies on surface water bodies like tanks and small reservoirs. These are key sources of recharge in regions that typically have low recharge rates. In many basins, only a few water bodies provide a significant portion of the total groundwater recharge. However, their actual effectiveness is often measured using surface indicators, such as storage capacity or area, without thoroughly examining how recharge moves through the subsurface. This study aims to fill this gap by assessing recharge efficiency through the identification of the recharge zone of influence (RZOI). The study took place in a 60 km² macro-watershed in a semi-arid area, which includes 14 significant water bodies that together account for nearly 60% of the total groundwater recharge. Understanding how recharge from these water bodies spreads within the aquifer is crucial because of their important role. A three-dimensional groundwater flow model was created using FEFLOW to simulate how the aquifer responds to recharge from the water bodies. The RZOI was defined as the subsurface volume calculated from the difference between groundwater head contours simulated with and without the influence of the water body recharge. Recharge efficiency was calculated as the ratio of the water volume in a water body to the corresponding RZOI volume. The findings reveal considerable differences in both RZOI extent and recharge efficiency throughout the study area. The largest water body, covering about 0.9 km², had a relatively large zone of influence extending over more than 2.5 km². Yet, its recharge efficiency was low, around 17–18%, mainly due to poor infiltration conditions. In contrast, a smaller water body showed the highest recharge efficiency, approximately 38–39%, due to a high infiltration capacity in the vadose zone, around 5–6 mm h⁻¹. Overall, the results suggest that recharge efficiency is mainly influenced by the infiltration capacity and hydraulic conductivity of the vadose zone, with the effect of surface area being relatively minor. The study emphasizes that larger water bodies do not always result in higher recharge efficiency and stresses the importance of assessing aquifers when planning and prioritizing recharge structures in semi-arid hard-rock regions.
How to cite: Narayanamurthi, V.: Recharge zone of influence–based evaluation of groundwater recharge efficiency in a semi-arid hard-rock region, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4410, https://doi.org/10.5194/egusphere-egu26-4410, 2026.
Understanding spatiotemporal groundwater recharge is vital for sustainable water management in Bangladesh, as anthropogenic and climatic factors severely strain available resources. Groundwater recharge in Bangladesh varies widely across its contrasting hydrogeological settings, yet their spatial and temporal dynamics and controlling factors remain insufficiently quantified. This study aims to quantify the spatial and temporal distribution of groundwater recharge across the western hydrogeological zones of Bangladesh and to assess the influence of land use and soil properties on recharge variability. The physically based, spatially distributed water-balance model WetSpass-M was applied to understand the spatial and temporal distribution of groundwater recharge and to examine the influence of geospatial and hydrometeorological parameters on recharge dynamics. Model results reveal a clear upstream–downstream recharge gradient, with persistently low recharge in the clay-dominated Barind uplands and moderate to high recharge in the coastal deltaic plains during the monsoon season. Temporally, recharge is strongly seasonal, occurring predominantly during the monsoon and closely tracking rainfall variability, with negligible dry-season recharge except in irrigated areas. Simulations also indicate declining recharge tendencies in the Barind region, whereas coastal recharge remains comparatively stable. Recharge patterns are strongly controlled by land use and soil properties. Forested and vegetated areas and loam to sandy-loam soils promote recharge, whereas built-up land and clay-rich deposits suppress infiltration. These findings highlight the dominant role of land-surface and subsurface properties in shaping recharge gradients. Future work will extend the analysis temporally and couple WetSpass-M simulated recharge with MODFLOW to support improved groundwater management and site-specific Managed Aquifer Recharge planning in drought- and salinity-prone regions.
How to cite: Uddin, M. Z., Bense, V., Mojid, M. A., and Mustafa, S.: Spatiotemporal dynamics of groundwater recharge in Bangladesh, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1549, https://doi.org/10.5194/egusphere-egu26-1549, 2026.
Groundwater resources are becoming increasingly vulnerable to human activities and climate change due to high water demand, intensive abstraction, and increased evapotranspiration associated with changes in precipitation amounts and patterns. In semi-arid mountain watersheds, groundwater recharge estimation is affected by substantial uncertainty due to the complexity of hydrological processes and the limitations of individual methods. Process-based models, satellite-derived water balance approaches, and groundwater-level analyses capture different components and scales of recharge, and no single method can fully represent recharge dynamics. To address this, this study applies an integrated framework combining SWAT+ hydrological modelling, remotely sensed water balance components, and the Water Table Fluctuation (WTF) method in the Ourika watershed, originating in the High Atlas of Marrakech and draining into the Haouz plain (Morocco). The dominant land use types of the watershed are grasslands and bare lands. The inputs of the SWAT+ model were prepared using the SRTM 30m digital elevation model (DEM). The improved maps of land use land cover from (ESA CCI LC) products were used to test different scenarios and their impact on the water balance. The soil characteristics are determined from FAO soil maps and the Harmonized World Soil Database and hydraulic characteristics are determined using the SPAW model. Daily rainfall is measured at gauge stations, and the meteorological variables such as daily wind speed, relative humidity, solar radiation, and temperature are collected within the watershed. The model was calibrated using daily stream flow data using Sequential Uncertainty Fitting (SUFI-2), which is one of the programs incorporated into R-SWAT interface. The annual recharge, calculated through the physically-based SWAT+ model, was compared to the estimated one using a remote sensing-based water balance approach. For this latter one, the water balance elements were calculated using satellite-derived datasets from GPM (precipitation), SEBAL (actual evapotranspiration), SMAP (soil moisture storage change), and NRCS-CN (runoff). This method provides spatially distributed estimates of recharge and enables direct comparison with SWAT+ outputs. In addition, the Water Table Fluctuation (WTF) method derived from piezometric time series was used as an independent field-based evaluation of recharge dynamics. The integration of both modeling and remote sensing approaches enhances the understanding of recharge dynamics in semi-arid environments and supports the development of sustainable groundwater management strategies in the Ourika watershed.
How to cite: El Farchouni, A., Hadri, A., Castelli, G., Fakir, Y., Bresci, E., Ouarani, M., and Kchikach, A.: Integrating SWAT+ hydrological modelling and remote sensing analysis to estimate surface water balance and groundwater recharge in the High Atlas of Marrakech and the Haouz plain (Morocco), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21149, https://doi.org/10.5194/egusphere-egu26-21149, 2026.
Groundwater recharge is a major challenge for the sustainable management of water resources, particularly in territories facing increasing water stress linked to climate change and anthropogenic pressures. Nature-Based Solutions (NbS), particularly Nature Water Retention Measures (NWRM), represent a promising approach to enhance natural infiltration processes, with potential benefits for groundwater quality and the territorial resilience.
This study is part of an exploratory approach aimed at analyzing the potential of NbS to promote groundwater recharge at the scale of a rural watershed, located in southern France and characterized by a Mediterranean climate with recharge predominantly driven by precipitation. The objective is to identify suitable areas for the future implementation of NbS and to assess their effects on groundwater recharge and water quality.
The methodology is founded on a scenario-based hydrological modeling approach at the watershed scale, using the SWAT+ model and relying on the integration of spatial data, including topography, soil properties, vegetal cover type, land use. The watershed is discretized into homogeneous hydrological response units (HRUs) in order to coherently represent the main characteristics and associated hydrological processes. Climatic data are then integrated into the model to represent the meteorological conditions required for hydrological simulations. The model is first calibrated using in situ measured discharge data. Sensitivity analyses will allow to identify the parameters that most strongly influence the hydrological functioning of the watershed.
In a second phase, nature-based land management scenarios focusing on NWRM will be simulated, including in particular the implementation of hedgerows and ditches, as well as infiltration basins, in order to assess their potential to improve groundwater recharge compared to a reference situation.
How to cite: Soukrate, I., Le Gal La Salle, C., Ducros, L., and Khaska, S.: Assessing Nature-Based Infiltration Solutions through hydrological modelling to identify suitable areas for groundwater recharge and potential water quality benefits, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19897, https://doi.org/10.5194/egusphere-egu26-19897, 2026.
Accurate estimation of groundwater recharge is of paramount importance to guarantee sustainable groundwater management. However, quantifying recharge in aquifers is a challenge, particularly in irrigated agricultural environments. Indeed, recharge processes are deeply impacted by surface inputs, vegetation dynamics, and vadose zone processes whose effects on both the magnitude and timing of recharge are further influenced by heterogeneous land use and irrigation practices. To handle these complexities, it is highly recommended to adopt sound approaches to minimize uncertainties in recharge estimation.
This study tackles this challenge through the estimation of groundwater recharge in the Crau aquifer in southeastern France. The area is intensively irrigated, and the aquifer is recharged by both precipitation and irrigation water from the Durance River. Groundwater recharge was estimated using a spatially distributed soil water balance model combining three models according to land use. An empirical model was used for bare or sparsely vegetated soils. This model is based on observations measured by a flux tower located on a steppic land representative of the area. For irrigated woody crops and gardening, the recharge was computed using a Kc model that calculates evapotranspiration from the reference ET0 using a Kc crop coefficient. For field crop and irrigated grassland, the STICS crop model was used to depict seasonal variations in the water balance and the impact of agricultural practices on recharge. Implementing such a comprehensive groundwater model requires documenting the parameters of every spatial entity (>100000) by using soil, meteorological land use maps and an assessment of agronomic practices.
The surface model outputs were then validated using a stable isotope mass balance based on measurements of oxygen (δ¹⁸O) and hydrogen (δ²H) isotopes in groundwater, precipitation, and irrigation water. The strong contrast between the isotopic signatures of precipitation and irrigation water is interesting to delineate the different water flows between the surface and the groundwater. By combining surface modeling with isotope-based validation, this approach provides an independent means of validating the modeled recharge components in a context where recharge estimation is highly uncertain and contributes to better groundwater management under increasing climatic and anthropogenic pressures.
How to cite: El Habbazi, C., Chanzy, A., Cognard-Plancq, A.-L., Gillon, M., Marc, V., and Babic, M.: Groundwater recharge estimation using surface modeling and validation with stable water isotopes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5263, https://doi.org/10.5194/egusphere-egu26-5263, 2026.
Nordic agricultural drainage systems have traditionally been designed for the removal of excess water from spring snowmelt and autumn rainfall; however, as the crops grow, increased evapotranspiration coupled with typical low precipitation in the early growing season can result in moisture shortages. Controlled drainage (CD) offers a more adaptive solution by regulating outflow and maintaining higher water table depths (WTDs), thereby enhancing soil moisture retention and reducing nutrient losses. While the hydrological benefits of CD are well established, its potential to quantify sub-irrigation, the additional water required to maintain optimal root-zone moisture, remains insufficiently explored. In this study, we applied FLUSH, a process-based two-dimensional hydrological model, to assess whether controlled subsurface drainage systems can be used to estimate sub-irrigation demand in a flat agricultural field in northern Finland. Three water-management scenarios were simulated: conventional drainage (CV), CD, and controlled subsurface drainage with sub-irrigation (CD-SI). Multi-year simulations were used to evaluate WTD dynamics, drain discharge, groundwater outflow, and upward water movement under different scenarios. Model results show that elevating drainage control levels increases water retention and can generate upward flow from drains during dry periods, partially meeting crop water demand. Scenario comparisons confirm that the CD-SI (sub-irrigation) scenario introduces a consistent subsurface inflow, while CV and CD present minimal upward fluxes. Evapotranspiration patterns are primarily climate-driven, with only moderate increases under CD and CD-SI due to improved soil moisture availability. Both controlled and sub-irrigated systems reduce cumulative and daily drain discharge, indicating enhanced infiltration and storage within the root zone. These findings also show that CD systems with continuous monitoring can provide valuable information for estimating sub-irrigation demand, especially in soils with high microporosity and hydraulic conductivity. Overall, the study highlights the potential of integrated drainage and sub-irrigation strategies to support climate-responsive water management in Nordic agriculture.
How to cite: Bhattacharjee, J., Salo, H., Mäkelä, M., and Koivusalo, H.: Integrating Controlled Drainage and Sub-Irrigation demand: Insights from FLUSH simulations in a Nordic agricultural field, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1070, https://doi.org/10.5194/egusphere-egu26-1070, 2026.
Rice‑growing regions underlain by shallow aquifers require irrigation strategies that simultaneously satisfy crop water demand, sustain groundwater recharge, and ensure an appropriate response to the increasingly frequent occurrence of water scarcity in many geographical areas. Traditional approaches, typically based on field‑scale experiments or conceptual water‑balance models, struggle to represent the complex interactions among irrigation practices, soil-water-crop processes, and groundwater dynamics at broader spatial scales.
To address this limitation, we developed QGIS‑SWAP‑Paddy, a novel GIS‑integrated modelling framework for simulating lowland agricultural systems across multiple spatial scales. The framework couples a semi-distributed SWAP (https://www.swap.wur.nl/) based agro‑hydrological model with a channel‑network module embedded within the QGIS environment. Simulations are driven by thematic maps and information stored in a GeoPackage database, including soil data, land use, irrigation management, groundwater depth, and agro‑meteorological conditions. This architecture enables the systematic integration of diverse inputs — maps, time series, field measurements, parameter estimates for soil hydraulic properties, crop development, and alternative irrigation management — into a coherent modelling workflow.
The framework has been applied to the Lomellina region in northern Italy, located in the largest rice‑growing district in Europe. After calibration and validation, initial applications of QGIS-SWAP-Paddy highlight its capacity to support scenario analyses for contrasting irrigation strategies, including wet seeding with continuous flooding, dry seeding with delayed flooding, and Alternate Wetting and Drying (AWD). The system is designed to be integrated with external models — most notably MODFLOW (https://www.usgs.gov/software/modflow-6-usgs-modular-hydrologic-model) — to simulate groundwater flow and quantify the impacts of irrigation management on aquifer dynamics. This coupling, currently being developed within the PROMEDRICE project (https://promedrice.org/; PRIMA-Section2-2022), will enable comprehensive assessments of water‑reuse mechanisms and groundwater sustainability in rice‑based irrigation systems.
QGIS‑SWAP‑Paddy produces both aggregated outputs (e.g., time series of irrigation requirements and deep percolation at domain or sub‑domain scale) and spatially explicit outputs such as maps of first‑aquifer recharge, representing a powerful tool for scientific research and operational decision‑support in lowland irrigated agricultural areas.
How to cite: Gilardi, G. L. C., Rienzner, M., Tkachenko, D., Romani, M., and Facchi, A.: QGIS‑SWAP‑Paddy: a modelling framework to simulate irrigation and aquifer recharge in lowland rice area. First application to the Lomellina rice district (northern Italy), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9767, https://doi.org/10.5194/egusphere-egu26-9767, 2026.
Groundwater recharge estimation remains a key challenge for the design of sustainable irrigation systems operating within complex territorial areas and ecosystem constraints, particularly under climate change, which alters water availability, precipitation regimes, and agro-hydrological dynamics. This study presents a coupled agro-hydrological and groundwater modelling framework specifically developed to quantify irrigation-driven recharge and to assess managed aquifer recharge adaptation measures under climate change scenarios. The framework integrates the agro-hydrological model IdrAgra with the numerical groundwater flow model MODFLOW and is applied to a highly urbanized region near Milan (representing the Italian pilot area of the MAURICE Interreg project - CE0100184). In this area, irrigation contributes to groundwater recharge at magnitudes comparable to or exceeding those of precipitation, as the most spread irrigation methods are surface and flood. Within this pilot action, winter irrigation was tested during two seasons (2023–2024 and 2024–2025) as an agricultural managed aquifer recharge (Ag-MAR) strategy, with the objective of evaluating its feasibility and effectiveness in enhancing groundwater availability during drought periods.
Detailed data on irrigation management, irrigation timing and daily channel discharges were collected both in winter and during the agricultural season and were then used to simulate the daily soil water balance in the vadose zone with the IdrAgra model. The resulting spatially and temporally distributed percolation fluxes were used as recharge inputs for the MODFLOW model, allowing the quantification of groundwater storage variations induced by the adaptation strategy. Both models were implemented on a common 100 m resolution grid covering approximately 326 km².
The project domain includes areas characterized by three distinct water management regimes: (i) non-irrigated areas, where groundwater recharge is driven exclusively by precipitation; (ii) areas managed by the Est Ticino Villoresi Irrigation Consortium, where structured irrigation networks and monitoring data allow irrigation-driven recharge to be quantified at the irrigation sub-district scale; and (iii) areas managed by individual users, where operational data are limited. IdrAgra was applied consistently across the entire domain, ensuring a coherent representation of crop growth, irrigation practices, soil water balance, and resulting groundwater recharge despite heterogeneous data availability.
The modelling framework was used to (i) quantify the effect of winter irrigation on groundwater recharge during the two experimental seasons, and (ii) evaluate it based on three different regional climate model projections (over the period 2026–2050), combined with alternative spatial distributions of winter irrigation.
Experimental results highlight that the percolation fluxes from the winter irrigated fields are relevant and model simulations show that extending this Ag-MAR strategy to sufficiently large areas a significant contribution to groundwater recharge is obtained. This study demonstrates the effectiveness of coupling agro-hydrological and groundwater models to represent irrigation-induced recharge processes, providing robust decision-support tools for the design and evaluation of Ag-MAR strategies under current and future climate conditions.
How to cite: Riva, R. E., Colombo, P., Weber, E., Piuri, V., and Gandolfi, C.: Quantifying irrigation-driven groundwater recharge through coupled agro-hydrological and groundwater modelling: an Ag-MAR case study from the MAURICE project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17813, https://doi.org/10.5194/egusphere-egu26-17813, 2026.
Posters on site: Thu, 7 May, 08:30–10:15 | Hall A
Intercatchment groundwater flow (IGF) quantifies groundwater fluxes across catchment boundaries, enabling the classification of catchments as either groundwater importers (gaining catchments) or exporters (losing catchments). It is a key component of the unclosed water balance equation that cannot be measured directly. The growing availability of large-sample datasets, gridded meteorological data, and satellite products provides an opportunity to develop a data integration framework to gain insights into this elusive hydrological variable.
This study focuses on the quantification of IGF for the European catchments included in the EStreams dataset. Precipitation and streamflow time series are provided in EStreams, while actual evapotranspiration data were gathered from the Global Land Evaporation Amsterdam Model (GLEAM) version 4. To identify the primary drivers of IGF, a random forest model was trained using a selection of catchment attributes as input variables, with IGF as the target variable. Permutation Variable Importance (PVI) was used to assess feature relevance, and the Maximal Information Coefficient (MIC) was calculated as an alternative method to quantify the relationship between catchment attributes and IGF.
Results of this work highlight the potential of a data integration framework to better characterize the unclosed water balance in European catchments and reveal key factors influencing IGF estimates.
ACKNOWLEDGMENTS: This study has been funded by a Humboldt Research Fellowship for Postdoctoral Researcher from the Alexander von Humboldt Foundation.
How to cite: Yeste, P. and Bronstert, A.: Intercatchment groundwater flow and unclosed water balance: a large-sample evaluation across European catchments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1557, https://doi.org/10.5194/egusphere-egu26-1557, 2026.
Climate variability and intensifying water use are increasingly altering groundwater systems in semi-arid regions, challenging sustainable water resources management at large spatial scales. The Upper Guadiana Basin (UGB), covering an area of approximately 16,000 km² in central Spain, is a representative groundwater-dependent agricultural system, where long-term irrigation-driven abstractions have caused persistent aquifer depletion. In this context, the development of coupled large-scale hydrological–hydrogeological modeling frameworks, where the main objective of the hydrological model is to calculate groundwater recharge, is essential to realistically assess groundwater dynamics under climate and water-use change.
In this study, we assessed basin-scale groundwater recharge using the mesoscale Hydrologic Model (mHM) for the period 2006–2018. The model was forced with gridded precipitation and temperature data, and calibrated by fitting river-flow at several gauging stations. Model results indicated substantially lower groundwater recharge compared to values expected from hydrogeological knowledge of the basin. This discrepancy is interpreted as evidence that, in the absence of explicit groundwater abstraction schemes, mHM implicitly compensates irrigation-induced groundwater losses by reducing simulated recharge, since this is the only way to minimize baseflow and thus fit the observed measurements during dry periods. Consequently, simulated recharge would represent an “actual groundwater recharge” that integrates both climatic controls and groundwater pumping impacts, rather than natural recharge alone.
To demonstrate that the discrepancy between natural recharge and that calculated by the model may be due to the high rates of groundwater extraction for irrigation, we analytically estimated this discrepancy by combining the irrigated areas from CORINE Land Cover (Coordination of Information on the Environment from the European Environment Agency’s Copernicus Land Monitoring Service) and SIGPAC (Sistema de Información Geográfica de Parcelas Agrícolas) datasets, with crop-specific irrigation requirements derived from FAO guidelines.
The results show that the difference between natural recharge and that calculated by the model is equal to the estimate obtained when considering crop water demand. This finding is of paramount importance for the development of large-scale regional models in arid areas where aquifers are severely overexploited and pumping rates are typically unknown, either due to the lack of meters or the presence of hundreds of unlicensed wells. In these cases, the recharge calculated with the hydrological model allows pumping effects to be incorporated indirectly, representing a major methodological advance and substantially improving model representativeness. Moreover, the results enable the characterization of the spatial distribution of pumping, facilitating the identification of the most critically overexploited areas and supporting the implementation of targeted management measures to improve water resources governance.
How to cite: Salehi Siavashani, N., Pujades Garnes, E., and Jurado, A.: Assessing Actual Groundwater Recharge under Climate Variability and Irrigation Pressure in the Upper Guadiana Basin (Central Spain), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2301, https://doi.org/10.5194/egusphere-egu26-2301, 2026.
How to cite: Sariago, R., Baquedano, C., Sánchez-Gómez, A., Jimenez, J., Martínez-León, J., de la Losa Roman, A., Santamarta, J. C., and García-Gil, A.: Groundwater recharge assessment in a data-scarce semi-arid volcanic island using evapotranspiration-constrained process-based modelling , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9330, https://doi.org/10.5194/egusphere-egu26-9330, 2026.
Groundwater of the Zagreb alluvial aquifer in northwestern Croatia represents an extremely important natural resource that supplies drinking and industrial water to the City of Zagreb and its surrounding area. The aquifer system consists of Quaternary sediments, within which an alluvial aquifer of intergranular porosity has developed. The thickness of the aquifer varies from approximately 10 m in the western part of the area to up to 100 m within the eastern structural depression. Hydraulic conductivity is very high and, based on pumping test results, reaches values of up to 3600 m/day in the vicinity of the Sava River. The aquifer is unconfined and is recharged through both infiltration of precipitation and leakage from the Sava River riverbed. Previous studies have estimated groundwater recharge using groundwater balance calculations, which were subsequently verified by a numerical groundwater flow model. For the purposes of numerical modelling, the alluvial aquifer area was divided into three polygons with different groundwater recharge values: (i) areas with a thin or absent semipermeable covering layer at the top of the aquifer, (ii) marginal aquifer areas to the north and south, composed predominantly of fine-grained deposits, and (iii) urban areas. Although the calibration results of the model are decent and the obtained recharge values appear realistic, there is still a need for more accurate and detailed determination of groundwater recharge in both spatial and temporal domains, with respect to both leakage from the Sava River and precipitation percolation. To address these limitations, extensive investigations are planned within the framework of the bilateral Croatian–Slovenian project GWQualityPath2070 (HRZZ: IPS-2024-02-5367). The research program comprises the analysis of the isotopic composition of groundwater, river water, and precipitation, the investigation of surface water and groundwater dynamics, and the integration of the SWAT semi-distributed hydrological model with a numerical groundwater flow model. Expected results of the research activities, in general—and in particular those related to the groundwater recharge model—will provide a solid basis for further research, primarily focused on analyses of climate change impacts on the quantitative status of groundwater, as well as the effects of different agricultural practices and land use on groundwater quality.
How to cite: Larva, O., Brkić, Ž., and Šanjek, R.: A Groundwater Recharge Model for the Zagreb Aquifer System (Croatia): Current Status and Proposed Enhancements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14358, https://doi.org/10.5194/egusphere-egu26-14358, 2026.
Sustainable groundwater management in irrigated agricultural regions demands accurate quantification of human-induced water fluxes. In the high Venetian plain (Northeast Italy), irrigation represents both a crucial agricultural input and a significant source of aquifer recharge. However, growing efforts to enhance irrigation efficiency for river ecosystem preservation may inadvertently reduce groundwater replenishment. This study addresses the pressing need to enhance integrated surface–subsurface hydrological models (ISSHMs) by improving the representation of irrigation practices and crop water use.
Our approach integrates detailed spatio-temporally variable irrigation water (IW) flux estimates into the CATHY (CATchment HYdrology) model, constrained by Earth Observation (EO) data. Specifically, the IW fluxes are obtained through a water balance approach that combines daily meteorological and NDVI data at 250-m spatial resolution. They are then used for model forcing, whereas model verification is carried out through comparison with different soil moisture remote sensing products. The aim of this study is to reduce uncertainty in water balance components and better simulate surface–groundwater interactions in agriculturally intensive landscapes.
We demonstrate that the integration of EO-driven irrigation estimates into ISSHMs provides a robust framework for evaluating the trade-offs between irrigation efficiency and aquifer recharge. The resulting models can provide critical insights into water use dynamics under varying regulatory and climatic scenarios, thus supporting more informed water governance strategies across multiple sectors.
How to cite: Ortenzi, S., Gatto, B., Massari, C., Chiesi, M., Moriondo, M., Fibbi, L., and Camporese, M.: Earth Observation-based Irrigation Dynamics to enhance Integrated Surface–Subsurface Hydrological Models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19730, https://doi.org/10.5194/egusphere-egu26-19730, 2026.
This research proposes a framework that combines satellite-based actual evapotranspiration (ETa) estimates with coupled process-based hydrological and groundwater modeling to quantify irrigation water use and its influence on the landscape water balance in Lower Saxony, Germany. Spatially distributed ETa is derived from the Landsat Provisional ETa Science Product and compared with simulated evapotranspiration from a semi-distributed hydrological model based on natural conditions without irrigation. Net irrigation is estimated as the difference between satellite-based ETa and simulated non-irrigated ETa. The groundwater model is subsequently used to simulate spatial and temporal changes in groundwater levels resulting from irrigation-related withdrawals, and groundwater recharge provided by the hydrological model.
By linking satellite-based evapotranspiration with hydrological and groundwater modeling, the proposed framework provides a method to quantify spatially and temporally varying irrigation water use and to assess its effects on groundwater levels at the landscape scale. While demonstrated for Lower Saxony, Germany, the framework is transferable to other regions where satellite-based evapotranspiration data and hydrological/hydrogeological information are available. It can be applied to analyse irrigation impacts on groundwater systems and to support assessments of groundwater sustainability under increasing agricultural water use and climate variability.
How to cite: Brettin, J., Schröter, K., and Riedel, G.: Quantifying Irrigation Water Use and Groundwater Dynamics using Earth Observation Data in Combination with Hydrological Modeling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11015, https://doi.org/10.5194/egusphere-egu26-11015, 2026.
Traditional surface irrigation remains the most widespread practice in the Po Plain, supporting one of Italy’s most productive agricultural regions. The system relies on large river withdrawals that are distributed through an extensive network of unlined, often centuries-old canals supplying agricultural fields. Although frequently criticized for inefficiency, surface irrigation generates hydrological effects that extend well beyond direct crop water supply. Indeed, percolation from irrigated soils and seepage from open channels contribute substantially to groundwater recharge, thereby moderating seasonal fluctuations in surface water availability and alleviating drought stress.
Despite its hydrological relevance, irrigation-induced groundwater recharge in the Po Plain remains poorly quantified. The region exhibits a highly complex hydrological system, dominated by strong surface water–groundwater interactions, while detailed data on irrigation practices, water deliveries, land use information and dynamic shallow water table fluctuations are limited. Robust estimates of the contribution of traditional irrigation to aquifer replenishment are therefore essential for sustainable water resources management, particularly in case of relevant climatic variability.
Within the MidAS-Po project, a comprehensive methodological framework was developed to quantify groundwater recharge across the entire Po Plain, accounting for contributions from both percolation from irrigated fields and seepage from unlined irrigation channels. The approach integrates two components. First, the distributed agro-hydrological model IdrAgra was applied to simulate the daily soil water balance and estimate percolation from agricultural soils. Second, recharge associated with canal seepage was assessed using a simplified methodology based on the estimation of the channel distribution efficiency.
The results indicate that recharge of aquifers induced by traditional surface irrigation accounts for between 50% and 65% of total recharge. The lower percentage is obtained when considering the role of the saturated soil zone in limiting percolation flows, and allowing root uptake from the capillary fringe in those areas of the Po Plain, where the aquifer is shallow; the higher percentage reflects the results of a simulation in which free drainage conditions were assumed at the base of the rooted soil volume. Given the considerable limitations in the knowledge of the spatial distribution of the phreatic aquifer depth, it is currently impossible to say which of the two estimates is more accurate.
These findings challenge conventional views on traditional irrigation efficiency, highlighting that water “losses” from irrigated fields and open channels are not merely waste but represent an important source of aquifer recharge. Further refinements are needed to improve these estimates. In particular, shallow water table depth data are currently not sufficiently accurate in terms of spatial resolution and are inadequate for capturing the seasonal and inter-annual fluctuations. Enhanced data on shallow water table depth would strengthen the model performance, improving estimates of crop irrigation requirements and of groundwater recharge.
How to cite: Gharsallah, O., Cazzaniga, S., Chiaradia, E. A., D'Amico, M. E., Rienzner, M., and Gandolfi, C.: Traditional Irrigation in the Po Plain: Inefficient Practice or Key Contributor to Groundwater Recharge? , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3973, https://doi.org/10.5194/egusphere-egu26-3973, 2026.
Agricultural Managed Aquifer Recharge (Ag-MAR) has emerged as a sustainable water management technique that utilizes farmland, particularly during fallow periods, to intentionally flood fields and replenish underground aquifers, thereby storing water for future use. Quantifying the benefits of Ag-MAR and evaluating its cost-effectiveness remains challenging due to strong nonlinear interactions between surface–subsurface processes, which generally require numerical modeling approaches that are still poorly established for Ag-MAR systems.
This study presents the initial development of a numerical modeling framework to evaluate the effectiveness of different Ag-MAR practices in the Lomellina area (1,250 km2) in Northern Italy, Europe’s largest rice-producing district. In this region, excess surface water is typically available during the winter months (November–February). Although winter flooding of rice fields has been promoted in recent years by the EU Rural Development Programme (CAP) for agronomic and environmental purposes, its hydrological benefits remain largely unquantified. Ag-MAR in the region may occur through deliberate field flooding or infiltration from irrigation canals, yet the relative importance of these pathways and their long-term impacts on groundwater resources are still unknown.
The proposed framework couples (a) recharge rates calculated using QGIS-SWAP-Paddy, a semi-distributed version of the SWAP model (https://www.swap.alterra.nl/), implementing also the irrigation/drainage network, and (b) groundwater flow rates calculated using the MODFLOW-6 model (https://www.usgs.gov/software/modflow-6-usgs-modular-hydrologic-model). QGIS-SWAP-Paddy provides transient net percolation rates from agricultural fields and the irrigation canal network, accounting for land-use, soil variability, and irrigation practices throughout the year. MODFLOW-6 uses QGIS-SWAP-Paddy’s percolation rates to simulate seasonal and interannual groundwater dynamics across the domain, including interactions with major rivers (Po, Ticino, and Sesia) and minor surface water bodies.
Due to the characteristics of the hydrogeological system, namely, the flooding of vast rice-growing areas and the presence of very shallow groundwater levels, recharge in QGIS-SWAP-Paddy depends on groundwater levels, while the groundwater level simulated by MODFLOW-6 depends on percolation rates estimated in QGIS-SWAP-Paddy.
Currently, the two models have been calibrated independently. QGIS-SWAP-Paddy has been calibrated using irrigation discharge data and a reference groundwater level map, interpolated using geostatistical methods, as the lower boundary condition. Conversely, the groundwater flow model, using the recharge rates produced by the QGIS-SWAP-Paddy model as input, was calibrated against observed groundwater levels in various wells from 2018–2020, successfully reproducing observed seasonal fluctuations.
The next step is to develop a code that allows the two models to be explicitly coupled monthly to improve the estimation of both percolation rates and the groundwater balance. If necessary, the calibration and validation of the integrated model will therefore be repeated, considering the irrigation discharges delivered to the district and the groundwater levels observed during the period 2018–2020. Once this step has been completed, the model will be ready to simulate Ag-MAR scenarios.
This study was carried out in the context of the PROMEDRICE project (https://promedrice.org/; PRIMA-Section2–2022) funded, for the Italian partners, by MUR (Italian Ministry of University and Research).
How to cite: Baják, P., Gilardi, G., Pedretti, D., Facchi, A., Masetti, M., Sangalli, L., Sorichetta, A., Tkachenko, D., and Valtorta, M.: Assessing the Ag-MAR potential in a rice-dominated alluvial plain in Northern Italy by combining MODFLOW-6 and QGIS-SWAP-Paddy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17207, https://doi.org/10.5194/egusphere-egu26-17207, 2026.
Groundwater recharge (GWR) is a key parameter for sustainable groundwater management and for predicting future groundwater availability. Its importance is increasing as global environmental and anthropogenic pressures intensify stress on groundwater resources. This study aims to improve point-scale estimates of GWR by constraining unsaturated-zone models at three sites that differ in vegetation and soil cover. Model optimization was performed using volumetric water content (θ) alone and θ in combination with soil water stable isotopes (δ18O and δ2H).
The newly implemented isotope module in HYDRUS-1D, which accounts for isotope fractionation, was successfully applied under semi-arid conditions. Strong monsoon dynamics caused large temporal variations in observed θ, which were challenging for the model to reproduce accurately, whereas vertical profiles of isotope concentrations were simulated more precisely. Estimated recharge rates over a 236-day period ranged from <1 cm to 31 cm for models optimized with θ and isotopes, and from <1 cm to 15 cm for models optimized with θ alone. Despite similar soil classes and short spatial distances, GWR exhibited pronounced heterogeneity across the study area in Tamil Nadu, South India. These findings highlight the use of multiple data types for model calibration, with isotope data providing additional constraints on the simulated recharge rates.
How to cite: Richard-Cerda, J. C., Schmidt, I., Koeniger, P., Karthikeyan, B., Schneider, M., and Schulz, S.: Improving punctual groundwater recharge estimate modeling by including stable water isotopes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13724, https://doi.org/10.5194/egusphere-egu26-13724, 2026.
Brandenburg is one of the driest regions in Germany and is highly dependent on groundwater resources for both drinking water supply and the growing demand for irrigated agriculture. Groundwater levels across the state are declining, and climate change is expected to further exacerbate this trend. The groundwater recharge rate (GWR) is a key parameter for the sustainable management of groundwater resources. However, its quantification it remains challenging, as it cannot be measured directly at spatial scales relevant for hydrological units in a landscape context.
In this study, we use daily data from several cosmic-ray neutron sensors (CRNS), which provide non-invasive measurements of soil moisture in the near-surface root zone at the hectare scale, to calibrate the soil hydrological model HYDRUS-1D. This calibration yields scale-effective soil hydraulic parameters and allows us to derive the downward water flux below the root zone as an approximation of GWR at the field scale.
The analysis is based on a unique six-year data set from the Potsdam Soil Moisture Observatory (PoSMO), a densely instrumented cluster located at and around an agricultural research site. The approximately 10-hectare area comprises multiple agricultural plots and extends along a gentle slope towards a lake. It is situated above a Pleistocene unconfined aquifer, with a groundwater table depth of 1 to 10 meters. At the heart of the instrumentation are eight continuously operated CRNS in combination with more than 25 point-scale soil moisture profiles measuring at depths of up to 1 m. A variety of additional measurements, including soil texture, hydraulic properties, continuous soil moisture measurements at depth, and groundwater level monitoring, provide a solid basis for validating the model and recording the relevant hydrological processes at the site.
In various simulation experiments, we evaluate the added value of using different soil moisture products for model calibration. To analyze long-term trends and fluctuations in GWR, we drive the calibrated model with historical weather data from over 50 years. We investigate changes in GWR under different climatic conditions and discuss the associated uncertainties, particularly in relation to the site's scarce water balance.
How to cite: Scheiffele, L., Munz, M., Francke, T., Heistermann, M., and Oswald, S. E.: From rain to recharge: insights into field scale soil moisture and water flux dynamics at the Potsdam Soil Moisture Observatory (PoSMO), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7848, https://doi.org/10.5194/egusphere-egu26-7848, 2026.
