HESS - recent papers

Spatial pattern regression for meteorological fields interpolation

2026-09-15T12:29:12+02:00

Spatial pattern regression for meteorological fields interpolation
Vihotogbé Houssou and Julie Carreau
Hydrol. Earth Syst. Sci., 30, 5791–5807, https://doi.org/10.5194/hess-30-5791-2026, 2026
Spatial Pattern Regression (SPR) is a new way to reconstruct daily weather fields in regions with few measurement stations. Our approach combines information from past high-resolution simulations with available observations to produce more accurate maps of precipitations and temperature. Tests on both synthetic and real data show clear improvements over common methods, especially when stations are sparse, helping support better hydrological and climate studies.

Integrating propagation and recovery dynamics into groundwater drought vulnerability assessment through exposure, pressure, and aquifer system response

2026-09-15T12:29:12+02:00

Integrating propagation and recovery dynamics into groundwater drought vulnerability assessment through exposure, pressure, and aquifer system response
Katarzyna Sawicka and Klaudia Jurzyk
Hydrol. Earth Syst. Sci., 30, 5809–5832, https://doi.org/10.5194/hess-30-5809-2026, 2026
Groundwater drought impacts depend on rainfall deficits, aquifer storage, and human activities. We analyzed rainfall and groundwater data from three aquifers to compare drought timing, duration, recovery, and spatial patterns. The deepest aquifer had the longest deficits and showed no signs of recovery during the study period. Our framework can support groundwater monitoring and management under combined climate and human pressures.

Impacts of Mediterranean snow droughts on mountain socio-ecohydrology

2026-09-14T12:29:12+02:00

Impacts of Mediterranean snow droughts on mountain socio-ecohydrology
Francesco Avanzi, Stefano Terzi, Mariapina Castelli, Francesca Munerol, Margherita Andreaggi, Marta Galvagno, Andrea Galletti, Tessa Maurer, Christian Massari, Grace Carlson, Manuela Girotto, Giacomo Bertoldi, Edoardo Cremonese, Simone Gabellani, Umberto Morra di Cella, Marco Altamura, Lauro Rossi, and Luca Ferraris
Hydrol. Earth Syst. Sci., 30, 5769–5790, https://doi.org/10.5194/hess-30-5769-2026, 2026
Snow droughts are periods with below-average snow accumulation and are becoming more frequent in a warming climate, yet their ecosystem and societal impacts remain poorly known. Using 13 years of data from 38 Italian catchments, we show that snow droughts reduced snow duration, increased winter melt-out events, and cut summer runoff by ~50 %. Photosynthesis increased by up to 10 % due to earlier meltout. These events also caused widespread water-supply reductions, especially in foothills.

Explicit representation and calibration of different landscape units for a robust catchment DOC export model

2026-09-11T12:29:12+02:00

Explicit representation and calibration of different landscape units for a robust catchment DOC export model
Tam V. Nguyen, Rohini Kumar, José L. J. Ledesma, Pia Ebeling, Jan H. Fleckenstein, and Andreas Musolff
Hydrol. Earth Syst. Sci., 30, 5749–5768, https://doi.org/10.5194/hess-30-5749-2026, 2026
Lumped and landscape-explicit dissolved organic carbon (DOC) models are commonly calibrated using stream DOC concentrations, while internal DOC dynamics in different model compartments are not given enough attention. Our study shows that stream DOC alone is insufficient to constrain internal DOC dynamics. Applying models calibrated in this way under changing boundary conditions may therefore lead to unrealistic results.

Historical evolution of snowpack capacity to buffer rain-on-snow runoff in a large Columbia River headwaters basin

2026-09-10T12:29:12+02:00

Historical evolution of snowpack capacity to buffer rain-on-snow runoff in a large Columbia River headwaters basin
Joel Brown and Joel Harper
Hydrol. Earth Syst. Sci., 30, 5735–5748, https://doi.org/10.5194/hess-30-5735-2026, 2026
We present daily analysis of a 72-year snowpack evolution model driven by climate reanalysis data over a large Columbia River headwaters basin. Trends in cold content and total capillary retention reveal decreasing capacity to buffer against rain-on-snow flood events with the largest changes occurring during the last 5 weeks of the accumulation period. We demonstrate that seasonality of changes in factors related to snowpack buffering capacity is important when assessing rain-on-snow flood risk.

Effects of spatial soil moisture variability in forest plots on model parametrization and simulated groundwater recharge estimates

2026-09-09T12:29:12+02:00

Effects of spatial soil moisture variability in forest plots on model parametrization and simulated groundwater recharge estimates
Thomas Fichtner, Yuly Juliana Aguilar Avila, Katja Ehrenberg, Stefan Seeger, Martin Maier, Stephan Raspe, and Andreas Hartmann
Hydrol. Earth Syst. Sci., 30, 5711–5734, https://doi.org/10.5194/hess-30-5711-2026, 2026
The study examines how spatial soil moisture variability affects Soil-Vegetation-Atmosphere Transfer (SVAT) model calibration and groundwater recharge estimates in forest ecosystems. It is demonstrated that model-inherent uncertainties outweight the influence of soil moisture variability. The results indicate that reliable groundwater recharge can be achieved using data from three to eleven profiles, offering practical guidance for efficient monitoring and calibration.

Towards a global actual evapotranspiration product for the Copernicus Land Monitoring Service

2026-09-08T12:29:12+02:00

Towards a global actual evapotranspiration product for the Copernicus Land Monitoring Service
Radoslaw Guzinski, Héctor Nieto, José Miguel Barrios, Walid Ghariani, Francoise Gellens-Meulenberghs, Jan De Pue, and Roselyne Lacaze
Hydrol. Earth Syst. Sci., 30, 5593–5646, https://doi.org/10.5194/hess-30-5593-2026, 2026
We present the design of an actual evapotranspiration product which joined the Copernicus Land Monitoring Service portfolio in December 2025. The product relies on free and open data and advanced modelling methods and has global coverage with a 300 m pixel resolution. A prototype dataset was compared against measurements from 206 geographically distributed stations, achieving good results. Such product will find multiple uses, including in water resources management and food security fields.

Spectral analysis of groundwater level time series for robust estimation of aquifer response times

2026-09-08T12:29:12+02:00

Spectral analysis of groundwater level time series for robust estimation of aquifer response times
Timo Houben, Christian Siebert, Thomas Kalbacher, Mariaines Di Dato, Thomas Fischer, and Sabine Attinger
Hydrol. Earth Syst. Sci., 30, 5685–5710, https://doi.org/10.5194/hess-30-5685-2026, 2026
Groundwater is vital but increasingly stressed by climate change and rising water demand. This study estimates how quickly aquifers respond to changes in recharge using a signal-analysis method. Most aquifers reacted within one to ten months, while deeper responded more slowly and proved more resilient to short droughts. The method uses existing monitoring data, offering a practical way to identify vulnerable aquifers and guide groundwater management under climate change.

Hydrochemistry and modeling nitrate concentration in farmland groundwater under different hydrological seasons by integrating hybrid quantum-classical ML, virtual sample generation and AlphaEarth Foundation

2026-09-08T12:29:12+02:00

Hydrochemistry and modeling nitrate concentration in farmland groundwater under different hydrological seasons by integrating hybrid quantum-classical ML, virtual sample generation and AlphaEarth Foundation
Junjie Xu, Xin Wei, Yilei Yu, Lihu Yang, Yuanzheng Zhai, Cuicui Lv, and Xianfang Song
Hydrol. Earth Syst. Sci., 30, 5647–5683, https://doi.org/10.5194/hess-30-5647-2026, 2026
Nitrate from farms and villages often seeps into groundwater, threatening water safety. We studied a farming area in northern China across dry, wet, and normal seasons to track and predict nitrate. Nitrate peaked in the dry season due to evaporation, and manure plus household wastewater supplied three quarters of it. Combining artificial data samples with advanced learning methods, we predicted nitrate accurately. This helps officials find pollution hotspots cheaply and protect rural water.

Technical note: HydroModPy (v1.0) – a Python toolbox for deploying catchment-scale shallow groundwater models

2026-09-08T12:29:12+02:00

Technical note: HydroModPy (v1.0) – a Python toolbox for deploying catchment-scale shallow groundwater models
Alexandre Gauvain, Ronan Abhervé, Bastien Boivin, Alexandre Coche, Martin Le Mesnil, Tristan Babey, Enzo Maugan, Théa Touzeau, Imene Issolah, Clément Roques, Camille Bouchez, Jean Marçais, Sarah Leray, Etienne Marti, Etienne Bresciani, Ronny Figueroa, Mathias Pélissier, Simon Carlier, Luca Guillaumot, Rock S. Bagagnan, Camille Vautier, Laurent Longuevergne, June Sallou, Johan Bourcier, Benoit Combemale, Philip Brunner, Luc Aquilina, and Jean-Raynald de Dreuzy
Hydrol. Earth Syst. Sci., 30, 5571–5592, https://doi.org/10.5194/hess-30-5571-2026, 2026
HydroModPy was developed to make it easier and faster to deploy groundwater models across multiple catchments. Although such models are widely used, setting them up often requires significant time and expertise. HydroModPy automates key steps, from preparing maps and input data to building models and running simulations. It is specifically designed for shallow aquifers and supports transparent, reproducible studies of groundwater. This tool can improve water management, research, and education.

Evaluating different roughness approaches and infiltration parameters for vegetation-influenced overland flow in hydrological model

2026-09-02T12:29:12+02:00

Evaluating different roughness approaches and infiltration parameters for vegetation-influenced overland flow in hydrological model
Azam Masoodi and Philipp Kraft
Hydrol. Earth Syst. Sci., 30, 5551–5570, https://doi.org/10.5194/hess-30-5551-2026, 2026
Vegetation affects surface runoff in several ways. Surface roughness is increased by stems and leaves, roots and their remnants enhance infiltration into the soil, and through evaporation, the soil water content changes at the beginning of a rainfall event. Our study investigates, how a simulation model is able to react to these effects. While roughness and infiltration are well covered, initial soil moisture is still an unsolved problem.

Integrating Physical-Based Xinanjiang Model and Deep Learning for Interpretable Streamflow Simulation: A Multi-Source Data Fusion Approach across Diverse Chinese Basins

2026-09-01T12:29:12+02:00

Integrating Physical-Based Xinanjiang Model and Deep Learning for Interpretable Streamflow Simulation: A Multi-Source Data Fusion Approach across Diverse Chinese Basins
Zhaocai Wang, Nannan Xu, Wei Song, Xingxing Zhang, Junhao Wu, and Xi Chen
Hydrol. Earth Syst. Sci., 30, 5521–5549, https://doi.org/10.5194/hess-30-5521-2026, 2026
This study integrates Xinanjiang (XAJ) and Temporal Convolutional Network - Gated Recurrent Unit (TCN-GRU) via Random Forest (RF) for streamflow simulation. It combines XAJ’s physical modeling with TCN-GRU’s temporal analysis. Validated in four hydrologically diverse basins, the model achieves Nash-Sutcliffe Efficiency (NSE) 0.971–0.991, outperforming traditional models. Robust in flood/interval simulations, analysis identifies dew point temperature and evaporation as key factors through three interpretable methods.

Validation of the open-source hydrodynamic model SFINCS on historical river floods at the global scale

2026-09-01T12:29:12+02:00

Validation of the open-source hydrodynamic model SFINCS on historical river floods at the global scale
Tarun Sadana, Jeroen C. J. H. Aerts, Dirk Eilander, Bruno Merz, Hans de Moel, Tim Busker, Veerle C. Bril, and Jens de Bruijn
Hydrol. Earth Syst. Sci., 30, 5491–5519, https://doi.org/10.5194/hess-30-5491-2026, 2026
We evaluated the open-source hydrodynamic model SFINCS using satellite data from 499 historical flood events across 96 countries. Our study shows that larger upstream river basins are modelled more accurately, while using observed river gauges and high-resolution elevation data can improve results. Our findings highlight the importance of large-scale validation with satellite data and sensitivity analyses to enhance future global flood hazard assessments and prediction accuracy.

Impacts of cascading check dams on sediment yield in the Middle Yellow River Basin: insights from 50 years of grid-cell-level simulation

2026-09-01T12:29:12+02:00

Impacts of cascading check dams on sediment yield in the Middle Yellow River Basin: insights from 50 years of grid-cell-level simulation
Yanzhang Huang, Guangyao Gao, Lishan Ran, Yue Wang, and Mingguo Zheng
Hydrol. Earth Syst. Sci., 30, 5473–5490, https://doi.org/10.5194/hess-30-5473-2026, 2026
This study developed an integrative model combining sediment trapping of check dam networks with the Revised Universal Soil Loss Equation, index of connectivity, and sediment delivery ratio to reconstruct grid-scale sediment yield across the middle Yellow River Basin (1970–2020). The proposed model achieved about 20 % increase of simulation accuracy compared to ignoring check dam trapping. The sediment reduction contribution by check dams was quantified and controlling factors were detected.

Hydrological implications of vegetation-associated precipitation recycling during peak growing season over the Loess Plateau

2026-08-27T12:29:12+02:00

Hydrological implications of vegetation-associated precipitation recycling during peak growing season over the Loess Plateau
Jiaxiang Deng, Quan Quan, Shuangcheng Tang, Hanbo Yang, and Xiaoyu Song
Hydrol. Earth Syst. Sci., 30, 5455–5472, https://doi.org/10.5194/hess-30-5455-2026, 2026
This study asks whether planting more vegetation on the Loess Plateau can bring enough extra rain to ease water shortages. By combining rainfall tracking with water balance analysis, we found that the added rain linked to vegetation is generally too small to make up for the extra water used by plant growth. Benefits are limited in sparsely vegetated areas and can turn negative where vegetation is dense, showing that restoration in dry regions has clear water limits.

Learning evaporative fraction with memory

2026-08-25T12:29:12+02:00

Learning evaporative fraction with memory
Wenli Zhao, Alexander J. Winkler, Markus Reichstein, Rene Orth, and Pierre Gentine
Hydrol. Earth Syst. Sci., 30, 5373–5394, https://doi.org/10.5194/hess-30-5373-2026, 2026
We used explainable machine learning that incorporates memory effects to study how plants respond to weather and drought. Using data from 90 sites worldwide, we show that memory plays a key role in regulating plant water stress. Forests and savannas rely on longer past conditions than grasslands, reflecting differences in rooting depth and water use. These insights improve our ability to anticipate ecosystem vulnerability as droughts intensify.

Towards a semi-asynchronous method for hydrological modeling in climate change studies

2026-08-25T12:29:12+02:00

Towards a semi-asynchronous method for hydrological modeling in climate change studies
Frédéric Talbot, Simon Ricard, Guillaume Drolet, Annie Poulin, Jean-Luc Martel, Richard Arsenault, and Jean-Daniel Sylvain
Hydrol. Earth Syst. Sci., 30, 5411–5453, https://doi.org/10.5194/hess-30-5411-2026, 2026
This study compares three hydrological modeling approaches for assessing climate change impacts on water systems. It evaluates the conventional method alongside a fully- and semi-asynchronous methods, which excels in capturing extreme events but faces challenges with event timing. The results highlight the potential of the semi-asynchronous method as an innovative and robust tool for hydrological modeling under climate change.

Modeling the long-term fate of injected CO2 in saline aquifers: An integrated framework coupling multiphase flow, dissolution, reaction, and ripening

2026-08-25T12:29:12+02:00

Modeling the long-term fate of injected CO2 in saline aquifers: An integrated framework coupling multiphase flow, dissolution, reaction, and ripening
Ruiqi Chen, Wenjie Xu, Yunmin Chen, Qingping Li, Tianyuan Zheng, and Bo Guo
Hydrol. Earth Syst. Sci., 30, 5395–5409, https://doi.org/10.5194/hess-30-5395-2026, 2026
Geological carbon sequestration is a promising strategy to mitigate climate change. We developed an integrated numerical framework that combines injection, dissolution, mixing, reactions, and ripening. Key results indicate that dissolution restricts plume lateral migration and constitutes about 40 % of storage. Geochemical reactions contributes less than 1 % but promotes dissolution and long-term security. Over tens of millennia, ripening redistributes residual CO₂, forming a stable gas cap.

Process diagnostics of snowmelt runoff in global hydrological and land surface models – Part 1: A systematic evaluation across basins of increasing complexity

2026-08-21T12:29:12+02:00

Process diagnostics of snowmelt runoff in global hydrological and land surface models – Part 1: A systematic evaluation across basins of increasing complexity
Xiangyong Lei, Haomei Lin, Kaihao Zheng, and Peirong Lin
Hydrol. Earth Syst. Sci., 30, 5343–5372, https://doi.org/10.5194/hess-30-5343-2026, 2026
Snowmelt runoff is a critical freshwater resource. This study assesses how well 15 large-scale models and runoff products simulate its volume, peak, and timing across 1455 snow-dominated basins, with special attention to model performance in increasingly complex basin environments. Our results reveal common biases and identify model types with relative strengths, providing guidance for water-resource planning and sustainable water management under global warming.

Technical note: A Water Analysis Trailer for Environmental Research (WATER)

2026-08-21T12:29:12+02:00

Technical note: A Water Analysis Trailer for Environmental Research (WATER)
Aaron James Neill, David Windhorst, Philipp Kraft, Amir Sahraei, and Lutz Breuer
Hydrol. Earth Syst. Sci., 30, 5327–5342, https://doi.org/10.5194/hess-30-5327-2026, 2026
Understanding water flow paths and pollutant transport requires high-temporal-frequency measurements from multiple water sources distributed in space. A new mobile platform is presented that can autonomously measure stable water isotopes and water quality parameters for 72 water samples per day, currently acquirable from up to 11 sources. Proof-of-concept, value of the collected data, and considerations for future use are exemplified by deployment of the system to a small headwater catchment.