Jingjing Huang, Hang Lyu, Chao Wang, Xiaosi Su, Weihong Dong, Yuyu Wan, Teijun Song, Xiaofang Shen
In this study, we developed a 2.5-D microfluidic experimental platform that enables nondestructive visualization of pore-throat microstructures and the migration processes of residual non-aqueous phase liquids (NAPL) within a three-phase system (water–ice–NAPL) under freeze–thaw conditions. Simulated experiments were then used to investigate the freeze–thaw migration of typical NAPL components. We analyzed the forces within the system during freezing and proposed an expulsion factor (<span data-altimg="/cms/asset/9472be0b-6031-4ca2-99a3-4f3073e667af/wrcr70777-math-0001.png"></span><mjx-container ctxtmenu_counter="145" ctxtmenu_oldtabindex="1" jax="CHTML" role="application" sre-explorer- style="font-size: 103%; position: relative;" tabindex="0"><mjx-math aria-hidden="true" location="graphic/wrcr70777-math-0001.png"><mjx-semantics><mjx-mrow><mjx-msub data-semantic-children="0,1" data-semantic- data-semantic-role="latinletter" data-semantic-speech="upper N Subscript f" data-semantic-type="subscript"><mjx-mi data-semantic-annotation="clearspeak:simple" data-semantic-font="italic" data-semantic- data-semantic-parent="2" data-semantic-role="latinletter" data-semantic-type="identifier"><mjx-c></mjx-c></mjx-mi><mjx-script style="vertical-align: -0.15em; margin-left: -0.085em;"><mjx-mi data-semantic-annotation="clearspeak:simple" data-semantic-font="italic" data-semantic- data-semantic-parent="2" data-semantic-role="latinletter" data-semantic-type="identifier" size="s"><mjx-c></mjx-c></mjx-mi></mjx-script></mjx-msub></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display="inline" unselectable="on"><math altimg="urn:x-wiley:00431397:media:wrcr70777:wrcr70777-math-0001" display="inline" location="graphic/wrcr70777-math-0001.png" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msub data-semantic-="" data-semantic-children="0,1" data-semantic-role="latinletter" data-semantic-speech="upper N Subscript f" data-semantic-type="subscript"><mi data-semantic-="" data-semantic-annotation="clearspeak:simple" data-semantic-font="italic" data-semantic-parent="2" data-semantic-role="latinletter" data-semantic-type="identifier">N</mi><mi data-semantic-="" data-semantic-annotation="clearspeak:simple" data-semantic-font="italic" data-semantic-parent="2" data-semantic-role="latinletter" data-semantic-type="identifier">f</mi></msub></mrow>${N}_{f}$</annotation></semantics></math></mjx-assistive-mml></mjx-container>) to evaluate the migration potential of residual NAPL. The results indicated that the residual NAPL exhibited three primary mechanisms during freezing: expulsion, snap-off, and compression. Expulsion significantly drove the residual NAPL movement during the early stages with fewer freeze–thaw cycles. As the number of cycles increased, snap-off and compression became dominant. This substantially restricted the expulsion of the residual NAPL. These findings have significant theoretical and practical value to understand and predict contaminant mo
{"title":"Residual NAPL Intermittent Expulsion With Increasing Freeze–Thaw Cycles in Saturated Porous Media: Findings From a 2.5-D Microfluidic Platform","authors":"Jingjing Huang, Hang Lyu, Chao Wang, Xiaosi Su, Weihong Dong, Yuyu Wan, Teijun Song, Xiaofang Shen","doi":"10.1029/2025wr042230","DOIUrl":"https://doi.org/10.1029/2025wr042230","url":null,"abstract":"In this study, we developed a 2.5-D microfluidic experimental platform that enables nondestructive visualization of pore-throat microstructures and the migration processes of residual non-aqueous phase liquids (NAPL) within a three-phase system (water–ice–NAPL) under freeze–thaw conditions. Simulated experiments were then used to investigate the freeze–thaw migration of typical NAPL components. We analyzed the forces within the system during freezing and proposed an expulsion factor (<span data-altimg=\"/cms/asset/9472be0b-6031-4ca2-99a3-4f3073e667af/wrcr70777-math-0001.png\"></span><mjx-container ctxtmenu_counter=\"145\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/wrcr70777-math-0001.png\"><mjx-semantics><mjx-mrow><mjx-msub data-semantic-children=\"0,1\" data-semantic- data-semantic-role=\"latinletter\" data-semantic-speech=\"upper N Subscript f\" data-semantic-type=\"subscript\"><mjx-mi data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"italic\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\"><mjx-c></mjx-c></mjx-mi><mjx-script style=\"vertical-align: -0.15em; margin-left: -0.085em;\"><mjx-mi data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"italic\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\" size=\"s\"><mjx-c></mjx-c></mjx-mi></mjx-script></mjx-msub></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00431397:media:wrcr70777:wrcr70777-math-0001\" display=\"inline\" location=\"graphic/wrcr70777-math-0001.png\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow><msub data-semantic-=\"\" data-semantic-children=\"0,1\" data-semantic-role=\"latinletter\" data-semantic-speech=\"upper N Subscript f\" data-semantic-type=\"subscript\"><mi data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"italic\" data-semantic-parent=\"2\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\">N</mi><mi data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"italic\" data-semantic-parent=\"2\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\">f</mi></msub></mrow>${N}_{f}$</annotation></semantics></math></mjx-assistive-mml></mjx-container>) to evaluate the migration potential of residual NAPL. The results indicated that the residual NAPL exhibited three primary mechanisms during freezing: expulsion, snap-off, and compression. Expulsion significantly drove the residual NAPL movement during the early stages with fewer freeze–thaw cycles. As the number of cycles increased, snap-off and compression became dominant. This substantially restricted the expulsion of the residual NAPL. These findings have significant theoretical and practical value to understand and predict contaminant mo","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"53 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147361026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Döndü Sarışen, Fayyaz Ali Memon, Hossein Mohammadi, Raziyeh Farmani
Many researchers have used deterministic models to address issues in intermittent water supply (IWS) systems, such as inequitable distribution, but these models often overlook key uncertainties. IWS systems vary widely in practices and operations, introducing uncertainties in areas like water consumption pattern, supply characteristics, and household tank sizes. To address these challenges, this study proposes a novel framework for assessing uncertainty in model input parameters and applies it to an IWS network using an EPA-SWMM-based hydraulic simulation. In the first phase, uncertainty analysis (UA) uses probabilistic methods and Monte Carlo simulations to evaluate the impact of uncertainties on performance indicators. The second phase applies global sensitivity analysis (SA) (Sobol's method) to identify the most influential parameters. The findings reveal that system performance is primarily governed by supply characteristics, while household tank size exerts a secondary but nonlinear influence on both pressure and consumption based indicators. Excessive household tank size is shown to reduce the pressure and supply equity, whereas moderate tank size improves the fairness of the water distribution. This work provides a foundation for more accurate and reliable IWS modeling approaches.
{"title":"Analyzing and Quantifying Key Sources of Uncertainty in Intermittent Water Supply Simulation: Supply Characteristics, Household Tank Size and Time Series of Water Consumption From the Household Tanks","authors":"Döndü Sarışen, Fayyaz Ali Memon, Hossein Mohammadi, Raziyeh Farmani","doi":"10.1029/2024wr039282","DOIUrl":"https://doi.org/10.1029/2024wr039282","url":null,"abstract":"Many researchers have used deterministic models to address issues in intermittent water supply (IWS) systems, such as inequitable distribution, but these models often overlook key uncertainties. IWS systems vary widely in practices and operations, introducing uncertainties in areas like water consumption pattern, supply characteristics, and household tank sizes. To address these challenges, this study proposes a novel framework for assessing uncertainty in model input parameters and applies it to an IWS network using an EPA-SWMM-based hydraulic simulation. In the first phase, uncertainty analysis (UA) uses probabilistic methods and Monte Carlo simulations to evaluate the impact of uncertainties on performance indicators. The second phase applies global sensitivity analysis (SA) (Sobol's method) to identify the most influential parameters. The findings reveal that system performance is primarily governed by supply characteristics, while household tank size exerts a secondary but nonlinear influence on both pressure and consumption based indicators. Excessive household tank size is shown to reduce the pressure and supply equity, whereas moderate tank size improves the fairness of the water distribution. This work provides a foundation for more accurate and reliable IWS modeling approaches.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"14 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147360150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Veerle C. Bril, Jens de Bruijn, Hans de Moel, Tarun Sadana, Tim Busker, W. J. Wouter Botzen, Jeroen C. J. H. Aerts
Floods are expected to increase in frequency and severity due to climate change. Recent floods have shown that many catchments worldwide are vulnerable to floods, highlighting the need for additional adaptation measures. This study extends the Geographical, Environmental, and Behavioral (GEB) model by coupling it to a hydrodynamic and a flood risk model to assess the effects of dry-proofing, wet-proofing, retention ponds, reforestation, and the creation of natural grassland. A key innovation is the integration of all local-scale models, thereby allowing for a catchment-wide assessment of the impacts of various measures on interlinked hydrological conditions, flood extents and depths, damages, and risk. We apply our method to the Geul catchment (shared between the Netherlands, Belgium and Germany), which was heavily flooded in July 2021. Our results show that reforestation and creation of natural grassland (both 10 km2) reduce flood extent by 12% and average water depth by 10%. Damage is decreased up to 38%. Larger retention ponds (1 m deeper) have a much smaller reduction in flood extent (3%), depth (0.5%) and damage (1.6%), due to limited storage capacity compared to excess rainfall. The building-level adaptation scenarios outperform all nature-based solutions, with dry-proofing reducing more damage (up to 95%) than wet-proofing (around 55%). A cost-benefit analysis shows that several adaptation measures are economically attractive. Overall, our findings show a coupled model is essential for comparing the relative effectiveness of different flood adaptation measures and supporting informed risk management decisions. The open-source model is transferable to other catchments worldwide to guide decision-making.
{"title":"Assessing the Effectiveness of Nature-Based Solutions and Building-Level Flood Risk Reduction Measures: An Open-Source Coupled Model","authors":"Veerle C. Bril, Jens de Bruijn, Hans de Moel, Tarun Sadana, Tim Busker, W. J. Wouter Botzen, Jeroen C. J. H. Aerts","doi":"10.1029/2025wr041436","DOIUrl":"https://doi.org/10.1029/2025wr041436","url":null,"abstract":"Floods are expected to increase in frequency and severity due to climate change. Recent floods have shown that many catchments worldwide are vulnerable to floods, highlighting the need for additional adaptation measures. This study extends the Geographical, Environmental, and Behavioral (GEB) model by coupling it to a hydrodynamic and a flood risk model to assess the effects of dry-proofing, wet-proofing, retention ponds, reforestation, and the creation of natural grassland. A key innovation is the integration of all local-scale models, thereby allowing for a catchment-wide assessment of the impacts of various measures on interlinked hydrological conditions, flood extents and depths, damages, and risk. We apply our method to the Geul catchment (shared between the Netherlands, Belgium and Germany), which was heavily flooded in July 2021. Our results show that reforestation and creation of natural grassland (both 10 km<sup>2</sup>) reduce flood extent by 12% and average water depth by 10%. Damage is decreased up to 38%. Larger retention ponds (1 m deeper) have a much smaller reduction in flood extent (3%), depth (0.5%) and damage (1.6%), due to limited storage capacity compared to excess rainfall. The building-level adaptation scenarios outperform all nature-based solutions, with dry-proofing reducing more damage (up to 95%) than wet-proofing (around 55%). A cost-benefit analysis shows that several adaptation measures are economically attractive. Overall, our findings show a coupled model is essential for comparing the relative effectiveness of different flood adaptation measures and supporting informed risk management decisions. The open-source model is transferable to other catchments worldwide to guide decision-making.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"5 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147361027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel J. Short Gianotti, Meriah J. Gannon, Dara Entekhabi
Meteorological droughts (persistent precipitation deficits) often, but not always, transition into agricultural droughts (persistent soil moisture deficits). The intensity of agricultural drought, however, can vary for a given precipitation deficit due to a number of catalyzing co-factors beyond precipitation such as atmospheric evaporative demand and temperature. In this study we use Earth System Model data to quantify (a) how warm temperature anomalies affect this evolution from meteorological-to-agricultural drought and (b) how the evolution of droughts from historical and future climate scenarios differ. We benchmark these results against observational data and use a multi-model ensemble to quantify agreement on future drought propagation. Broadly speaking, drought temperatures in the upper third of local distributions correspond with shifts on the order of 5 percentile of the soil moisture distribution. We would expect today's meteorological droughts to propagate into agricultural droughts roughly one drought classification more severe in the SSP3-7.0 scenario in most regions. Even regions with increases in precipitation are likely to see more intense meteorological-to-agricultural drought propagation by the end of the 21st century. Models disagree on drought propagation changes in Africa for the same precipitation deficit, but suggest that all historical droughts would have had worse agricultural droughts in Europe and Eastern North America if they happened under SSP3-7.0. When accounting for precipitation changes—which tend toward more frequent accumulated precipitation deficits—the increased severity of meteorological-to-agricultural drought evolution leads to predictions of major increases in moderate to extreme (D1–D3) drought events in all regions globally by the end of the century.
{"title":"Meteorological to Agricultural Drought Transitions Compounded by Heat Waves in Historical and Future Climates","authors":"Daniel J. Short Gianotti, Meriah J. Gannon, Dara Entekhabi","doi":"10.1029/2024wr039170","DOIUrl":"https://doi.org/10.1029/2024wr039170","url":null,"abstract":"Meteorological droughts (persistent precipitation deficits) often, but not always, transition into agricultural droughts (persistent soil moisture deficits). The intensity of agricultural drought, however, can vary for a given precipitation deficit due to a number of catalyzing co-factors beyond precipitation such as atmospheric evaporative demand and temperature. In this study we use Earth System Model data to quantify (a) how warm temperature anomalies affect this evolution from meteorological-to-agricultural drought and (b) how the evolution of droughts from historical and future climate scenarios differ. We benchmark these results against observational data and use a multi-model ensemble to quantify agreement on future drought propagation. Broadly speaking, drought temperatures in the upper third of local distributions correspond with shifts on the order of 5 percentile of the soil moisture distribution. We would expect today's meteorological droughts to propagate into agricultural droughts roughly one drought classification more severe in the SSP3-7.0 scenario in most regions. Even regions with increases in precipitation are likely to see more intense meteorological-to-agricultural drought propagation by the end of the 21st century. Models disagree on drought propagation changes in Africa for the same precipitation deficit, but suggest that all historical droughts would have had worse agricultural droughts in Europe and Eastern North America if they happened under SSP3-7.0. When accounting for precipitation changes—which tend toward more frequent accumulated precipitation deficits—the increased severity of meteorological-to-agricultural drought evolution leads to predictions of major increases in moderate to extreme (D1–D3) drought events in all regions globally by the end of the century.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"48 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147360151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The filling process of large hydropower reservoirs is an often-overlooked process that can attract most of the attention and criticisms of a dam's lifetime. Understanding what drove past filling efforts and exploring trade-off solutions is therefore critical for regions where hydropower development is flourishing. Yet, there is a lack of methodological frameworks applicable across different contexts (e.g., existing and planned systems) that can characterize how trade-offs evolve under varying hydro-climatological conditions. Here, we focus on the filling strategies of the Upper Mekong hydropower system, one of the largest mega-dam cascades (capacity 1,000 million cubic meters) built in the century. Our ex-post analysis for the period 2008–2016 reveals that the historical filling strategies have largely prioritized electricity production at the expense of downstream hydrological alterations—peak discharge decreased by more than 20% during the filling of the largest dams. On the flipside, there are tangible opportunities for designing better trade-off solutions that would be appealing to all riparian countries and that are robust to different hydro-climatological conditions. Key to this step is the coordination of the filling process of the largest storage facilities.
{"title":"Rethinking the Filling Process of Mega-Dam Cascades","authors":"Dung Trung Vu, Thanh Duc Dang, Stefano Galelli","doi":"10.1029/2025wr043034","DOIUrl":"https://doi.org/10.1029/2025wr043034","url":null,"abstract":"The filling process of large hydropower reservoirs is an often-overlooked process that can attract most of the attention and criticisms of a dam's lifetime. Understanding what drove past filling efforts and exploring trade-off solutions is therefore critical for regions where hydropower development is flourishing. Yet, there is a lack of methodological frameworks applicable across different contexts (e.g., existing and planned systems) that can characterize how trade-offs evolve under varying hydro-climatological conditions. Here, we focus on the filling strategies of the Upper Mekong hydropower system, one of the largest mega-dam cascades (capacity <span data-altimg=\"/cms/asset/117b8604-1068-4eb5-9b71-c97201d3d5a2/wrcr70763-math-0001.png\"></span><math altimg=\"urn:x-wiley:00431397:media:wrcr70763:wrcr70763-math-0001\" display=\"inline\" location=\"graphic/wrcr70763-math-0001.png\">\u0000<semantics>\u0000<mrow>\u0000<mo>≥</mo>\u0000</mrow>\u0000${ge} $</annotation>\u0000</semantics></math> 1,000 million cubic meters) built in the <span data-altimg=\"/cms/asset/5f9f365c-5a90-4c71-ad7c-6a7f411c76b5/wrcr70763-math-0003.png\"></span><math altimg=\"urn:x-wiley:00431397:media:wrcr70763:wrcr70763-math-0003\" display=\"inline\" location=\"graphic/wrcr70763-math-0003.png\">\u0000<semantics>\u0000<mrow>\u0000<mn>21</mn>\u0000<mrow>\u0000<mi mathvariant=\"normal\">s</mi>\u0000<mi mathvariant=\"normal\">t</mi>\u0000</mrow>\u0000</mrow>\u0000$21mathrm{s}mathrm{t}$</annotation>\u0000</semantics></math> century. Our ex-post analysis for the period 2008–2016 reveals that the historical filling strategies have largely prioritized electricity production at the expense of downstream hydrological alterations—peak discharge decreased by more than 20% during the filling of the largest dams. On the flipside, there are tangible opportunities for designing better trade-off solutions that would be appealing to all riparian countries and that are robust to different hydro-climatological conditions. Key to this step is the coordination of the filling process of the largest storage facilities.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"54 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147334454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Joren Janzing, Niko Wanders, Marit van Tiel, Manuela I. Brunner
Streamflow droughts are spatial phenomena that are generally not restricted to individual rivers or catchments. However, many studies spatially limit their drought analysis, for example focusing on a specific country or catchment only, which makes it difficult to study spatiotemporal drought evolution in detail. Here, we analyze the spatiotemporal dynamics of streamflow droughts over the larger Alpine region using spatially-explicit and high-resolution simulations from the hydrological model PCR-GLOBWB2.0. Specifically, we apply a novel spatial and temporal clustering algorithm to track streamflow drought events in space and time. Our results show that spatially-extensive streamflow droughts (500km of river network) typically experience phases of growth and recovery, during which extensive drought events sometimes consist of several spatially-distinct sub-events. Streamflow droughts behave differently in different geographic regions. Drought extent is often limited by the Alpine mountain range and the mountain river network is less frequently part of spatially-extensive drought events than the surrounding lowland rivers. Furthermore, the spatial evolution of streamflow drought is affected by different hydrometeorological drivers. Rainfall deficits are the most dominant driver of spatially-extensive streamflow drought in the study domain, but many drought events result from the interplay of multiple processes. The dominant drivers of streamflow droughts change over time as the affected domain changes. Since drought extent can influence the effectiveness of drought impact mitigation strategies, a better understanding of the spatiotemporal dynamics of streamflow drought has important implications for future water management.
{"title":"Spatiotemporal Dynamics of Streamflow Drought in the Larger Alpine Region","authors":"Joren Janzing, Niko Wanders, Marit van Tiel, Manuela I. Brunner","doi":"10.1029/2025wr040503","DOIUrl":"https://doi.org/10.1029/2025wr040503","url":null,"abstract":"Streamflow droughts are spatial phenomena that are generally not restricted to individual rivers or catchments. However, many studies spatially limit their drought analysis, for example focusing on a specific country or catchment only, which makes it difficult to study spatiotemporal drought evolution in detail. Here, we analyze the spatiotemporal dynamics of streamflow droughts over the larger Alpine region using spatially-explicit and high-resolution simulations from the hydrological model PCR-GLOBWB2.0. Specifically, we apply a novel spatial and temporal clustering algorithm to track streamflow drought events in space and time. Our results show that spatially-extensive streamflow droughts (<span data-altimg=\"/cms/asset/015ed394-9132-4abc-95fd-1c91ccf16f7e/wrcr70746-math-0001.png\"></span><mjx-container ctxtmenu_counter=\"28\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/wrcr70746-math-0001.png\"><mjx-semantics><mjx-mrow><mjx-mo data-semantic- data-semantic-role=\"inequality\" data-semantic-speech=\"greater than or equals\" data-semantic-type=\"relation\"><mjx-c></mjx-c></mjx-mo></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00431397:media:wrcr70746:wrcr70746-math-0001\" display=\"inline\" location=\"graphic/wrcr70746-math-0001.png\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow><mo data-semantic-=\"\" data-semantic-role=\"inequality\" data-semantic-speech=\"greater than or equals\" data-semantic-type=\"relation\">≥</mo></mrow>${ge} $</annotation></semantics></math></mjx-assistive-mml></mjx-container>500km of river network) typically experience phases of growth and recovery, during which extensive drought events sometimes consist of several spatially-distinct sub-events. Streamflow droughts behave differently in different geographic regions. Drought extent is often limited by the Alpine mountain range and the mountain river network is less frequently part of spatially-extensive drought events than the surrounding lowland rivers. Furthermore, the spatial evolution of streamflow drought is affected by different hydrometeorological drivers. Rainfall deficits are the most dominant driver of spatially-extensive streamflow drought in the study domain, but many drought events result from the interplay of multiple processes. The dominant drivers of streamflow droughts change over time as the affected domain changes. Since drought extent can influence the effectiveness of drought impact mitigation strategies, a better understanding of the spatiotemporal dynamics of streamflow drought has important implications for future water management.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"15 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147320160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Siyang Yao, Jutao Liu, Gang Li, Huiming Han, Gang Wang, Ning Liao
The hydrological regime, particularly flooding duration and depth, is one of the primary driving factors for the vegetation pattern in floodplain lakes. Climate change-induced droughts are extending shoal exposure times, potentially amplifying the impact of temperature on plant growth. However, the nonlinear interactive effects of hydrological and temperature factors on the vegetation growth pattern remain poorly understood. This study integrated a hydrodynamic model, an interpretable machine learning and a geographical detector to develop a robust framework for analyzing the individual and interactive impacts of these factors on the vegetation growth pattern. Applied to Poyang Lake—a Ramsar Convention conservation wetland—we found that temperature factors can exert stronger effect intensities than hydrological factors during extreme droughts. Interactive analyses revealed that flooding duration and cumulative temperature formed the strongest factor pair, with synergistic interactions exhibiting two distinct patterns—one stronger than each single factor yet weaker than their sum, the other outperforming their combined individual effects. Notably, under high-temperature stress, the flooding duration exhibited a critical transition: its effect shifted from negative to positive as the duration increased. Furthermore, sensitivity analysis demonstrated that vegetation was more sensitive to the hydrological factor within these interactive effects, highlighting their dominant role in regulating vegetation dynamics under hydrothermal stress. By unraveling hydrothermal interaction synergies and critical threshold shifts, this study provides water resources managers with actionable insights to formulate adaptive policies for floodplain wetland conservation under climate change.
{"title":"Impact of Hydrological Regime and Temperature on Vegetation Growth Patterns in Floodplain Lakes Under Extreme Drought","authors":"Siyang Yao, Jutao Liu, Gang Li, Huiming Han, Gang Wang, Ning Liao","doi":"10.1029/2025wr042618","DOIUrl":"https://doi.org/10.1029/2025wr042618","url":null,"abstract":"The hydrological regime, particularly flooding duration and depth, is one of the primary driving factors for the vegetation pattern in floodplain lakes. Climate change-induced droughts are extending shoal exposure times, potentially amplifying the impact of temperature on plant growth. However, the nonlinear interactive effects of hydrological and temperature factors on the vegetation growth pattern remain poorly understood. This study integrated a hydrodynamic model, an interpretable machine learning and a geographical detector to develop a robust framework for analyzing the individual and interactive impacts of these factors on the vegetation growth pattern. Applied to Poyang Lake—a Ramsar Convention conservation wetland—we found that temperature factors can exert stronger effect intensities than hydrological factors during extreme droughts. Interactive analyses revealed that flooding duration and cumulative temperature formed the strongest factor pair, with synergistic interactions exhibiting two distinct patterns—one stronger than each single factor yet weaker than their sum, the other outperforming their combined individual effects. Notably, under high-temperature stress, the flooding duration exhibited a critical transition: its effect shifted from negative to positive as the duration increased. Furthermore, sensitivity analysis demonstrated that vegetation was more sensitive to the hydrological factor within these interactive effects, highlighting their dominant role in regulating vegetation dynamics under hydrothermal stress. By unraveling hydrothermal interaction synergies and critical threshold shifts, this study provides water resources managers with actionable insights to formulate adaptive policies for floodplain wetland conservation under climate change.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"71 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147292484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Adhish Virupaksha, François Lehmann, Hussein Hoteit, Anis Younes, Marwan Fahs, Thomas Nagel
Deep learning neural networks (DLNNs) hold great potential for modeling groundwater flow, but their performance depends on data availability. Physics-informed neural networks (PINNs) help to reduce the reliance of DLNNs on data by integrating physical laws into the training process. This approach is increasingly used in applications related to groundwater flow. However, most applications remain limited to steady-state conditions in confined aquifers. Training PINNs for unconfined aquifers and under dynamic conditions is challenging due to the nonlinearity of the governing equations and the large number of required collocation points. The applicability of PINNs in such a case is still poorly investigated. The main objective of this paper is to fill this gap by focusing on the treatment of time derivatives in PINNs. Thus, three PINNs approaches based on continuous time (i.e., standard PINNs), discrete time and time decomposition are adapted and compared. A comprehensive explanation of the principles of discrete PINNs for modeling groundwater flow is provided. The performance of these three approaches is investigated using several test cases involving variable boundary conditions or pumping rates. The results demonstrate the superiority of the discrete-time approach in both accuracy and training efficiency. The advantages of this approach become more pronounced as the complexity of the velocity and pressure head fields increases. This approach can be 10 times more efficient than standard PINNs in training time because it allows for optimizing the number of collocation points and reducing both the number of training parameters and training epochs.
{"title":"Modeling Transient Groundwater Flow in Unconfined Aquifers Under Dynamic Conditions Using Physics-Informed Neural Networks","authors":"Adhish Virupaksha, François Lehmann, Hussein Hoteit, Anis Younes, Marwan Fahs, Thomas Nagel","doi":"10.1029/2025wr040754","DOIUrl":"https://doi.org/10.1029/2025wr040754","url":null,"abstract":"Deep learning neural networks (DLNNs) hold great potential for modeling groundwater flow, but their performance depends on data availability. Physics-informed neural networks (PINNs) help to reduce the reliance of DLNNs on data by integrating physical laws into the training process. This approach is increasingly used in applications related to groundwater flow. However, most applications remain limited to steady-state conditions in confined aquifers. Training PINNs for unconfined aquifers and under dynamic conditions is challenging due to the nonlinearity of the governing equations and the large number of required collocation points. The applicability of PINNs in such a case is still poorly investigated. The main objective of this paper is to fill this gap by focusing on the treatment of time derivatives in PINNs. Thus, three PINNs approaches based on continuous time (i.e., standard PINNs), discrete time and time decomposition are adapted and compared. A comprehensive explanation of the principles of discrete PINNs for modeling groundwater flow is provided. The performance of these three approaches is investigated using several test cases involving variable boundary conditions or pumping rates. The results demonstrate the superiority of the discrete-time approach in both accuracy and training efficiency. The advantages of this approach become more pronounced as the complexity of the velocity and pressure head fields increases. This approach can be 10 times more efficient than standard PINNs in training time because it allows for optimizing the number of collocation points and reducing both the number of training parameters and training epochs.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"190 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147292607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Cihan, Y. Guglielmi, S. Glubokovskikh, M. Cao, J. Rutqvist, P. Jordan, M. Reagan, J. Birkholzer
Assessing large-scale pressurization at the regional scale—a possible outcome of large subsurface storage applications such as wastewater injection and geological carbon sequestration—presents significant computational challenges. These challenges are particularly pronounced when accounting for complex geologic structures with multiple reservoir and caprock layers, fault zones, and wells. This study introduces a computationally efficient model that integrates single-phase semi-analytical solutions with a boundary element (BE) approach. The model simulates pressure propagation in multilayered 3D systems, including vertical faults, caprock, basement, and confining units. We apply this new model to a representative scenario involving CO2 injection near a partially sealing fault with verification against an independent two-phase flow model. Results demonstrate that our model accurately captures far-field pressure responses and that, outside the CO2 plume zone, pressure predictions from single-phase and two-phase models are nearly identical. This supports the use of single-phase models like ours for efficient estimation of far-field pressure changes. Additionally, we demonstrate its effectiveness at a large scale, incorporating multiple wells and faults. With its ability to represent multiple wells, fault zones, and geological heterogeneity, our model is well suited for assessments of basin-scale pressurization. Its computational efficiency also makes it a promising tool for integration with optimization frameworks aimed at designing and managing injection strategies in faulted storage systems.
{"title":"A Boundary Element Model for Assessing Large-Scale Pressurization in Faulted Geological Storage Systems","authors":"A. Cihan, Y. Guglielmi, S. Glubokovskikh, M. Cao, J. Rutqvist, P. Jordan, M. Reagan, J. Birkholzer","doi":"10.1029/2025wr041198","DOIUrl":"https://doi.org/10.1029/2025wr041198","url":null,"abstract":"Assessing large-scale pressurization at the regional scale—a possible outcome of large subsurface storage applications such as wastewater injection and geological carbon sequestration—presents significant computational challenges. These challenges are particularly pronounced when accounting for complex geologic structures with multiple reservoir and caprock layers, fault zones, and wells. This study introduces a computationally efficient model that integrates single-phase semi-analytical solutions with a boundary element (BE) approach. The model simulates pressure propagation in multilayered 3D systems, including vertical faults, caprock, basement, and confining units. We apply this new model to a representative scenario involving CO<sub>2</sub> injection near a partially sealing fault with verification against an independent two-phase flow model. Results demonstrate that our model accurately captures far-field pressure responses and that, outside the CO<sub>2</sub> plume zone, pressure predictions from single-phase and two-phase models are nearly identical. This supports the use of single-phase models like ours for efficient estimation of far-field pressure changes. Additionally, we demonstrate its effectiveness at a large scale, incorporating multiple wells and faults. With its ability to represent multiple wells, fault zones, and geological heterogeneity, our model is well suited for assessments of basin-scale pressurization. Its computational efficiency also makes it a promising tool for integration with optimization frameworks aimed at designing and managing injection strategies in faulted storage systems.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"131 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147287584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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