K. S. As, M. A. Münch, G. Trommer, A. Pudelko, T. Behrends, S. Peiffer
Climate change impacts hydrology and biogeochemistry of reservoirs. Thereby, processing of the essential nutrients nitrogen (N) and phosphorus (P) is affected. Clarifying the compounded long-term impact of changed nutrient inputs and effects of climate change on internal nutrient processing requires long-term data sets with sufficient detail. This study evaluates monitoring data from 2000 to 2019 in the German Franconian Lake District, which consists of one shallow (hypertrophic) and three deep reservoirs (meso-to eutrophic), interconnected by a transfer canal. The cascade configuration and continued external load buffer catchment variations, making nutrient trends attributable to internal processing. Mass balances were set up and statistical trends analyses performed for nutrient concentrations, duration of stratification and hypolimnetic anoxia. Across reservoirs, mean water temperature (range: +0.35 to +1.0°C decade−1), stratification (+7 to +18 days decade−1) and hypolimnetic anoxia (+15 to +35 days decade−1) increased significantly. Total phosphorus increased in deep reservoirs (+0.006 to +0.01 mg P L−1 decade−1) and total nitrogen (TN) decreased in all reservoirs (−0.2 to −0.4 mg N L−1 decade−1). Increased rates of nitrate loss could be attributed to enhanced denitrification and earlier algal uptake. Increased total phosphorus concentrations were attributable to increased sediment P-release, induced by prolonged stratification and hypolimnetic anoxia. Primarily, the decrease in TN drove a strong decrease in TN:TP ratio (−4 to −15 mol:mol decade−1), triggering a shift toward N-limitation, associated with proliferation of harmful algae blooms. Identified impacts emphasize the need to consider the potential disruptive effects of intensifying climate change on health and restoration efforts for temperate, eutrophic lakes worldwide.
{"title":"Global Warming Enhances Nitrogen-Limitation in a Temperate Reservoir System Under Continued External Load","authors":"K. S. As, M. A. Münch, G. Trommer, A. Pudelko, T. Behrends, S. Peiffer","doi":"10.1029/2025wr040978","DOIUrl":"https://doi.org/10.1029/2025wr040978","url":null,"abstract":"Climate change impacts hydrology and biogeochemistry of reservoirs. Thereby, processing of the essential nutrients nitrogen (N) and phosphorus (P) is affected. Clarifying the compounded long-term impact of changed nutrient inputs and effects of climate change on internal nutrient processing requires long-term data sets with sufficient detail. This study evaluates monitoring data from 2000 to 2019 in the German Franconian Lake District, which consists of one shallow (hypertrophic) and three deep reservoirs (meso-to eutrophic), interconnected by a transfer canal. The cascade configuration and continued external load buffer catchment variations, making nutrient trends attributable to internal processing. Mass balances were set up and statistical trends analyses performed for nutrient concentrations, duration of stratification and hypolimnetic anoxia. Across reservoirs, mean water temperature (range: +0.35 to +1.0°C decade<sup>−1</sup>), stratification (+7 to +18 days decade<sup>−1</sup>) and hypolimnetic anoxia (+15 to +35 days decade<sup>−1</sup>) increased significantly. Total phosphorus increased in deep reservoirs (+0.006 to +0.01 mg P L<sup>−1</sup> decade<sup>−1</sup>) and total nitrogen (TN) decreased in all reservoirs (−0.2 to −0.4 mg N L<sup>−1</sup> decade<sup>−1</sup>). Increased rates of nitrate loss could be attributed to enhanced denitrification and earlier algal uptake. Increased total phosphorus concentrations were attributable to increased sediment P-release, induced by prolonged stratification and hypolimnetic anoxia. Primarily, the decrease in TN drove a strong decrease in TN:TP ratio (−4 to −15 mol:mol decade<sup>−1</sup>), triggering a shift toward N-limitation, associated with proliferation of harmful algae blooms. Identified impacts emphasize the need to consider the potential disruptive effects of intensifying climate change on health and restoration efforts for temperate, eutrophic lakes worldwide.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"322 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223379","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}
It is seldom realized that whether one uses annual maxima (AM) or partial duration (PD) series for frequency analysis has major implications when predicting the magnitudes and probabilities of smaller, frequently recurring geophysical events. Langbein's seminal 1949 article on “Annual Floods and the Partial-Duration Series” elucidated the differences between the two approaches, providing a theoretical relationship between AM-based return periods and PD-based average recurrence intervals that applies not only to floods but also to other processes modeled using either AM or PD series, such as wind gusts, rain depths, and wave heights. He observed that “… for equivalent floods (i.e., of the same magnitude), the recurrence intervals in the partial-duration series are smaller than in the annual-flood (AM) series,” and that they “… differ markedly for the smaller or more frequent floods, but are nearly equal for the higher floods,” concluding that PD is more appropriate for capturing the actual frequency of occurrence of smaller events. Yet 75 years (and more than 400 citations) later, many still predict frequent events based solely on AM series, while others invoke Langbein's equation to somehow convert AM-based estimates into PD-based estimates. However, when both AM and PD frequency analyses are concurrently performed on geophysical data sets, departures from Langbein's relationship are often observed, suggesting limitations in the underlying assumptions of the formula. These considerations affect various engineering and scientific fields where accurate estimation of frequent, low-recurrence-interval events is needed, underscoring potential biases and misconceptions in many current estimates of such occurrences.
{"title":"Seventy-Five Years Underestimating Frequent Events and Other Frequently Underestimated Implications of Langbein's Equation","authors":"F. Dell’Aira, A. Cancelliere, C. I. Meier","doi":"10.1029/2025wr040530","DOIUrl":"https://doi.org/10.1029/2025wr040530","url":null,"abstract":"It is seldom realized that whether one uses annual maxima (AM) or partial duration (PD) series for frequency analysis has major implications when predicting the magnitudes and probabilities of smaller, frequently recurring geophysical events. Langbein's seminal 1949 article on “Annual Floods and the Partial-Duration Series” elucidated the differences between the two approaches, providing a theoretical relationship between AM-based return periods and PD-based average recurrence intervals that applies not only to floods but also to other processes modeled using either AM or PD series, such as wind gusts, rain depths, and wave heights. He observed that “… <i>for equivalent floods</i> (i.e., of the same magnitude), <i>the recurrence intervals in the partial-duration series are smaller than in the annual-flood</i> (AM) <i>series,</i>” and that they “… <i>differ markedly for the smaller or more frequent floods, but are nearly equal for the higher floods,</i>” concluding that PD is more appropriate for capturing the actual frequency of occurrence of smaller events. Yet 75 years (and more than 400 citations) later, many still predict frequent events based solely on AM series, while others invoke Langbein's equation to somehow convert AM-based estimates into PD-based estimates. However, when both AM and PD frequency analyses are concurrently performed on geophysical data sets, departures from Langbein's relationship are often observed, suggesting limitations in the underlying assumptions of the formula. These considerations affect various engineering and scientific fields where accurate estimation of frequent, low-recurrence-interval events is needed, underscoring potential biases and misconceptions in many current estimates of such occurrences.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"18 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223375","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}
In pothole-dominated catchments, such as those in the Prairie Pothole Region (PPR), potholes strongly influence catchment hydrologic behavior through complex and dynamic fill–spill–connection mechanisms. This complexity—combined with the predominance of ungauged catchments and the lack of high-resolution pothole inventories—poses challenges for both traditional hydrologic models and purely data-driven deep learning approaches. To address this, we developed the δHBV-Pot model within a differentiable modeling framework (δ). This physics-informed deep learning model integrates the conceptual HBV model with a probabilistic algorithm that emulates the aggregate effects of pothole fill–spill–connection processes. Applied to 98 PPR catchments, δHBV-Pot achieves stronger predictive accuracy and physical realism than a purely data-driven Long Short-Term Memory (LSTM) model and two conceptual hydrologic models. The PPR-scale regional δHBV-Pot model successfully simulates hydrologic behavior for the majority of pseudo-ungauged (test) catchments withheld during model development, effectively regionalizing (a) high-flow magnitude and interannual variability, (b) intra-annual flashiness of high-flow and normal flow conditions, and (c) interannual variability in pothole water storage dynamics. Moreover, the model identifies vulnerable catchments with large high-flow magnitude and variability—even in the absence of streamflow data—and delineates catchments with varying temporal variability in pothole water storage without requiring detailed pothole inventories. Our findings highlight the value of combining conceptual hydrology with data-driven deep learning models in pothole-dominated regions. This integrated approach enables the regionalization of high-flow and pothole storage characteristics to ungauged catchments, providing critical insights for vulnerability assessment and the design of sustainable water and ecological management strategies in pothole-dominated landscapes.
{"title":"Regionalization of Hydrologic Behavior and Pothole Water Storage Dynamics in the Prairie Pothole Region","authors":"Javad Rahmani, Chaopeng Shen, Ali A. Ameli","doi":"10.1029/2025wr040280","DOIUrl":"https://doi.org/10.1029/2025wr040280","url":null,"abstract":"In pothole-dominated catchments, such as those in the Prairie Pothole Region (PPR), potholes strongly influence catchment hydrologic behavior through complex and dynamic fill–spill–connection mechanisms. This complexity—combined with the predominance of ungauged catchments and the lack of high-resolution pothole inventories—poses challenges for both traditional hydrologic models and purely data-driven deep learning approaches. To address this, we developed the δHBV-Pot model within a differentiable modeling framework (δ). This physics-informed deep learning model integrates the conceptual HBV model with a probabilistic algorithm that emulates the aggregate effects of pothole fill–spill–connection processes. Applied to 98 PPR catchments, δHBV-Pot achieves stronger predictive accuracy and physical realism than a purely data-driven Long Short-Term Memory (LSTM) model and two conceptual hydrologic models. The PPR-scale regional δHBV-Pot model successfully simulates hydrologic behavior for the majority of pseudo-ungauged (test) catchments withheld during model development, effectively regionalizing (a) high-flow magnitude and interannual variability, (b) intra-annual flashiness of high-flow and normal flow conditions, and (c) interannual variability in pothole water storage dynamics. Moreover, the model identifies vulnerable catchments with large high-flow magnitude and variability—even in the absence of streamflow data—and delineates catchments with varying temporal variability in pothole water storage without requiring detailed pothole inventories. Our findings highlight the value of combining conceptual hydrology with data-driven deep learning models in pothole-dominated regions. This integrated approach enables the regionalization of high-flow and pothole storage characteristics to ungauged catchments, providing critical insights for vulnerability assessment and the design of sustainable water and ecological management strategies in pothole-dominated landscapes.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"1 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223011","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}
Jing Yan, Wenjuan Zheng, Bridget Knight, Harsh Bais, Yan Jin
Plant growth-promoting rhizobacteria (PGPR) have been shown to mediate drought stress by inducing changes in soil physical properties, including water retention and flow dynamics. However, the potential role and underlying mechanisms by which PGPR mediate salt stress through biophysical controls remain poorly understood. To address this gap, we conducted saltwater evaporation experiments using Bacillus subtilis FB17 (UD1022), a PGPR, across multiple scales, including microscale (sessile droplets on glass slides and microchannels packed with a thin layer of sand) and mesoscale (columns packed with sand). Evaporation of NaCl solutions (0, 10, and 20 g/kg) mixed with and without UD1022 was compared. Images of evaporating sessile droplets showed that bacterial cells pinned the contact line, resulting in salt precipitation along the droplet perimeter. In contrast, in the absence of UD1022, salt accumulated at the droplet center. In sand-packed microchannels, salt clusters formed on sand particle surfaces in control samples, whereas in UD1022-treated samples, salt precipitated within pore spaces between sand particles, consistent with contact line pinning. These microscale biophysical effects scaled up to the mesoscale, where column measurements showed that UD1022 increased water retention and reduced saltwater evaporation compared to controls. Mechanistically, whereas unrestricted salt precipitation in control systems spread across the surface and increased the effective evaporation area, bacterial-induced contact line pinning (a) confined salt precipitation to air-water-solid interfaces at the contact line, resulting in partial pore blockage at an early stage, and (b) led to complete pore blockage at a later stage, further decreasing evaporation.
{"title":"Microbial Contact Line Pinning: How Bacillus subtilis Reshapes Salt Precipitation and Evaporation","authors":"Jing Yan, Wenjuan Zheng, Bridget Knight, Harsh Bais, Yan Jin","doi":"10.1029/2025wr040899","DOIUrl":"https://doi.org/10.1029/2025wr040899","url":null,"abstract":"Plant growth-promoting rhizobacteria (PGPR) have been shown to mediate drought stress by inducing changes in soil physical properties, including water retention and flow dynamics. However, the potential role and underlying mechanisms by which PGPR mediate salt stress through biophysical controls remain poorly understood. To address this gap, we conducted saltwater evaporation experiments using <i>Bacillus subtilis</i> FB17 (UD1022), a PGPR, across multiple scales, including microscale (sessile droplets on glass slides and microchannels packed with a thin layer of sand) and mesoscale (columns packed with sand). Evaporation of NaCl solutions (0, 10, and 20 g/kg) mixed with and without UD1022 was compared. Images of evaporating sessile droplets showed that bacterial cells pinned the contact line, resulting in salt precipitation along the droplet perimeter. In contrast, in the absence of UD1022, salt accumulated at the droplet center. In sand-packed microchannels, salt clusters formed on sand particle surfaces in control samples, whereas in UD1022-treated samples, salt precipitated within pore spaces between sand particles, consistent with contact line pinning. These microscale biophysical effects scaled up to the mesoscale, where column measurements showed that UD1022 increased water retention and reduced saltwater evaporation compared to controls. Mechanistically, whereas unrestricted salt precipitation in control systems spread across the surface and increased the effective evaporation area, bacterial-induced contact line pinning (a) confined salt precipitation to air-water-solid interfaces at the contact line, resulting in partial pore blockage at an early stage, and (b) led to complete pore blockage at a later stage, further decreasing evaporation.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"43 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223372","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}
Stefan Liess, Heidi A. Roop, Tracy E. Twine, Suzanna Clark, Dena Coffman, Dhondup Dolma, Amanda Farris, Alejandro Fernandez, Jack Gorman, Nathan Meyer
Climate projections for three future shared socioeconomic pathway scenarios from six CMIP6 global climate models (GCMs) were dynamically downscaled over Minnesota with the regional Weather Research and Forecasting model coupled to a lake model at 4-km horizontal resolution representing energy and moisture fluxes over more than 60 lakes inside the state borders. Warming over Minnesota is projected to increase in all seasons, especially in winter. Snow depth and lake ice cover is expected to decrease. However, compared to GCM projections, our results show stronger increases in spring and early summer precipitation, potentially from the extra evaporation over lakes. This trend especially manifests in heavier precipitation events. Precipitation is expected to decrease during the peak growing season in middle and late summer. We anticipate that temperature and precipitation values will be significantly different by the middle and end of the 21st century, respectively, from what has been observed at the beginning of the 21st century. Winters and summers are expected to be up to 7 and 4°C warmer, respectively, especially over northern and central Minnesota. Average spring precipitation may increase by more than 1 mm d−1 over central Minnesota. Despite generally stronger precipitation, winter snow depth is projected to decrease by more than 12 cm, especially around the Lake Superior shores and in northern Minnesota. Lake ice cover is projected to decrease by more than half over deeper lakes. The number of lake ice days per year and days per year with snow depth of more than 2.54 cm may decrease by up to 70 and 55, respectively.
{"title":"County-Scale Climate Projections Over Minnesota and the Effects of Lakes","authors":"Stefan Liess, Heidi A. Roop, Tracy E. Twine, Suzanna Clark, Dena Coffman, Dhondup Dolma, Amanda Farris, Alejandro Fernandez, Jack Gorman, Nathan Meyer","doi":"10.1029/2025wr040415","DOIUrl":"https://doi.org/10.1029/2025wr040415","url":null,"abstract":"Climate projections for three future shared socioeconomic pathway scenarios from six CMIP6 global climate models (GCMs) were dynamically downscaled over Minnesota with the regional Weather Research and Forecasting model coupled to a lake model at 4-km horizontal resolution representing energy and moisture fluxes over more than 60 lakes inside the state borders. Warming over Minnesota is projected to increase in all seasons, especially in winter. Snow depth and lake ice cover is expected to decrease. However, compared to GCM projections, our results show stronger increases in spring and early summer precipitation, potentially from the extra evaporation over lakes. This trend especially manifests in heavier precipitation events. Precipitation is expected to decrease during the peak growing season in middle and late summer. We anticipate that temperature and precipitation values will be significantly different by the middle and end of the 21st century, respectively, from what has been observed at the beginning of the 21st century. Winters and summers are expected to be up to 7 and 4°C warmer, respectively, especially over northern and central Minnesota. Average spring precipitation may increase by more than 1 mm d<sup>−1</sup> over central Minnesota. Despite generally stronger precipitation, winter snow depth is projected to decrease by more than 12 cm, especially around the Lake Superior shores and in northern Minnesota. Lake ice cover is projected to decrease by more than half over deeper lakes. The number of lake ice days per year and days per year with snow depth of more than 2.54 cm may decrease by up to 70 and 55, respectively.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"8 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223009","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}
Weiming Kang, Jie Tian, Dongxiang Xue, Heye Reemt Bogena, Johan Alexander Huisman, Chansheng He
Preferential flow (PF) critically influences water and energy dynamics in frozen soils, yet its quantification and mechanisms remain poorly understood due to observational challenges. This study proposes a novel method to identify PF by analyzing soil temperature response times across depths. The method detects thermal anomalies—such as earlier or synchronized temperature peaks across depths—indicate rapid, advective heat transfer driven by PF and phase-change latent heat. We conducted our investigation in the Qilian Mountain areas using a network of soil temperature stations. Our findings reveal that PF significantly enhances magnitude and speed of energy transfer to deeper soil. Furthermore, the frequency of PF varies significantly across the partially frozen, frozen and partially thawing phases, as well as across different sites and depths, driven by shifts soil properties and meteorological forcing. Using random forest analysis, we identified key spatial drivers related to soil pore structure: soil organic carbon (partially frozen phase), residual soil moisture (frozen phase), and wilting point (partially thawed phase). Furthermore, classification and regression tree analysis revealed that the snowmelt rates and maximum near-surface (5 cm) soil temperatures are the primary temporal drivers of PF. Our study demonstrates that PF can be effectively identified by analyzing soil temperatures at various depths. By utilizing temperature-based detection during the frozen phase and moisture monitoring in the unfrozen phase, we can better correlate PF with soil hydrothermal conditions, ultimately elucidating the complex mechanisms governing water and energy dynamics during the freeze-thaw cycle.
{"title":"Characterization of Preferential Flow Occurrence During Freeze-Thaw Cycles","authors":"Weiming Kang, Jie Tian, Dongxiang Xue, Heye Reemt Bogena, Johan Alexander Huisman, Chansheng He","doi":"10.1029/2025wr041926","DOIUrl":"https://doi.org/10.1029/2025wr041926","url":null,"abstract":"Preferential flow (PF) critically influences water and energy dynamics in frozen soils, yet its quantification and mechanisms remain poorly understood due to observational challenges. This study proposes a novel method to identify PF by analyzing soil temperature response times across depths. The method detects thermal anomalies—such as earlier or synchronized temperature peaks across depths—indicate rapid, advective heat transfer driven by PF and phase-change latent heat. We conducted our investigation in the Qilian Mountain areas using a network of soil temperature stations. Our findings reveal that PF significantly enhances magnitude and speed of energy transfer to deeper soil. Furthermore, the frequency of PF varies significantly across the partially frozen, frozen and partially thawing phases, as well as across different sites and depths, driven by shifts soil properties and meteorological forcing. Using random forest analysis, we identified key spatial drivers related to soil pore structure: soil organic carbon (partially frozen phase), residual soil moisture (frozen phase), and wilting point (partially thawed phase). Furthermore, classification and regression tree analysis revealed that the snowmelt rates and maximum near-surface (5 cm) soil temperatures are the primary temporal drivers of PF. Our study demonstrates that PF can be effectively identified by analyzing soil temperatures at various depths. By utilizing temperature-based detection during the frozen phase and moisture monitoring in the unfrozen phase, we can better correlate PF with soil hydrothermal conditions, ultimately elucidating the complex mechanisms governing water and energy dynamics during the freeze-thaw cycle.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"51 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223377","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}
S. Leader, N. Kettridge, C. Mendoza, D. Hannah, K. J. Devito
Shallow lakes are important ecosystems highly susceptible to water-level fluctuations and desiccation caused by climate cycles and anthropogenic pressures. To better predict and manage the impacts of disturbance we examined the natural variability over a 20-year period, that spans the range of long-term (decadal) weather cycles, and the controls on water-level deviation (WLD) of 26 shallow lakes that include all configurations of lake types and glacial landscapes typical in the Boreal Plains (BP) of Canada. Water budgets and hydrochemical analyses show that dominant lake water-budget components vary spatially and temporally with different geological settings and land covers that influence the scale and magnitude of lake-groundwater connectivity and surface-water inflow. However, over decadal weather cycles similar ranges in WLD were observed across all glacial geologies and shallow lake types. Lake geometry and evaporation interacted with lake-catchment characteristics to further impact the dynamics and memory of water levels to interannual and decadal weather patterns. In all lake-catchment types, lake bathymetry and outflow sill elevation determined overall storage which controls maximum water level elevation during wet years and extent of desiccation during drought years. This research demonstrates that in sub-humid glaciated continental landscapes, such as the BP, lake management strategies founded on lake permanence and fluctuation magnitudes are of limited value. Rather, focus should be placed on documenting the long-term WLD and considering the interaction of landscape characteristics and internal lake mechanisms that enable different lake types in such heterogeneous landscapes to recover and persist over decadal meteorological cycles.
{"title":"Influence of Landscape and Lake Characteristics on Long-Term Water-Level Responses in Shallow Lakes of the Sub-Humid Boreal Plains, Canada","authors":"S. Leader, N. Kettridge, C. Mendoza, D. Hannah, K. J. Devito","doi":"10.1029/2025wr040903","DOIUrl":"https://doi.org/10.1029/2025wr040903","url":null,"abstract":"Shallow lakes are important ecosystems highly susceptible to water-level fluctuations and desiccation caused by climate cycles and anthropogenic pressures. To better predict and manage the impacts of disturbance we examined the natural variability over a 20-year period, that spans the range of long-term (decadal) weather cycles, and the controls on water-level deviation (WLD) of 26 shallow lakes that include all configurations of lake types and glacial landscapes typical in the Boreal Plains (BP) of Canada. Water budgets and hydrochemical analyses show that dominant lake water-budget components vary spatially and temporally with different geological settings and land covers that influence the scale and magnitude of lake-groundwater connectivity and surface-water inflow. However, over decadal weather cycles similar ranges in WLD were observed across all glacial geologies and shallow lake types. Lake geometry and evaporation interacted with lake-catchment characteristics to further impact the dynamics and memory of water levels to interannual and decadal weather patterns. In all lake-catchment types, lake bathymetry and outflow sill elevation determined overall storage which controls maximum water level elevation during wet years and extent of desiccation during drought years. This research demonstrates that in sub-humid glaciated continental landscapes, such as the BP, lake management strategies founded on lake permanence and fluctuation magnitudes are of limited value. Rather, focus should be placed on documenting the long-term WLD and considering the interaction of landscape characteristics and internal lake mechanisms that enable different lake types in such heterogeneous landscapes to recover and persist over decadal meteorological cycles.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"16 46 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146210365","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}
Identifying the optimal threshold of a peaks over threshold (POT) series is crucial for effective flood distribution analysis and decision-making for risk reduction. Here we propose a threshold detection method based on the Shuffled Complex Evolution (SCE-UA) optimization algorithm that can automatically identify the global optimal threshold without any objective specification. Results show that the proposed method efficiently located the optimal threshold with fewer than approximately 4–13 times the number of goodness of fit tests and Anderson-Darling tests compared to traditional methods at 10 river gauge stations across China. The automatically identified threshold matched well with the threshold identified by graphical diagnostics, and it reduced fitting biases of the generalized Pareto model over commonly used fixed thresholds. This detection method was subsequently applied to a large-scale flood distribution analysis across 380 stations of the Eastern Monsoon Region of China. The range of optimal thresholds for the POT series was between 0.14 m3/s and 49,062.53 m3/s, with a median value of 293.55 m3/s for the 380 stations. The high-flow threshold was particularly high in wet regions and low in arid/semiarid regions. It is also shown that small dry catchments with lower elevation, lower field capacity, and larger saturated hydraulic conductivity tend to display heavier flood tails (i.e., a higher probability of extreme flood occurrence). Our study demonstrates the potential of an SCE-UA-based threshold detection framework for large-scale flood distribution analysis and also provides a general framework for automatic extraction of excess extremes.
{"title":"An Efficient Global Automatic Threshold Detection Algorithm for Large-Scale Flood Distribution Analysis","authors":"Jiaojiao Gou, Chiyuan Miao, Jinlong Hu, Qi Zhang, Qingyun Duan","doi":"10.1029/2024wr039398","DOIUrl":"https://doi.org/10.1029/2024wr039398","url":null,"abstract":"Identifying the optimal threshold of a peaks over threshold (POT) series is crucial for effective flood distribution analysis and decision-making for risk reduction. Here we propose a threshold detection method based on the Shuffled Complex Evolution (SCE-UA) optimization algorithm that can automatically identify the global optimal threshold without any objective specification. Results show that the proposed method efficiently located the optimal threshold with fewer than approximately 4–13 times the number of goodness of fit tests and Anderson-Darling tests compared to traditional methods at 10 river gauge stations across China. The automatically identified threshold matched well with the threshold identified by graphical diagnostics, and it reduced fitting biases of the generalized Pareto model over commonly used fixed thresholds. This detection method was subsequently applied to a large-scale flood distribution analysis across 380 stations of the Eastern Monsoon Region of China. The range of optimal thresholds for the POT series was between 0.14 m<sup>3</sup>/s and 49,062.53 m<sup>3</sup>/s, with a median value of 293.55 m<sup>3</sup>/s for the 380 stations. The high-flow threshold was particularly high in wet regions and low in arid/semiarid regions. It is also shown that small dry catchments with lower elevation, lower field capacity, and larger saturated hydraulic conductivity tend to display heavier flood tails (i.e., a higher probability of extreme flood occurrence). Our study demonstrates the potential of an SCE-UA-based threshold detection framework for large-scale flood distribution analysis and also provides a general framework for automatic extraction of excess extremes.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"280 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146210364","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}
Zeren Ning, Tomohiro Nakashima, Kaoru Inaba, Takaaki Shimizu, Hyoun-Tae Hwang, Walter A. Illman
Improving the accuracy of subsurface heterogeneity characterization remains a key component in better understanding groundwater flow and contaminant transport. Heat tracer tests can provide temperature measurements, in addition to head data, that can be used for mapping heterogeneity. Here, the performance of head and temperature data in characterizing the hydraulic conductivity (K) distribution is investigated with a three-dimensional highly parameterized model using the pilot point method. The performance results are evaluated qualitatively and quantitatively in various aspects, including K fields comparison, head and temperature matches for both model calibration and validation, as well as through identifiability and sensitivity analyses. Results of this study reveal that: (a) K fields obtained by inverting head data show finer details of heterogeneity, while small scale heterogeneity is smoothed when inverting temperature data; (b) combination of heat and temperature data improves the prediction of heat tracer tests; (c) increasing data density yields more heterogeneity information and further improves prediction performance; and (d) identifiability and sensitivity analyses suggest that head and temperature data contain nonredundant information of K heterogeneity. These results jointly suggest that the integration of transient head and temperature data shows promising potential in improving the delineation of subsurface K distribution and obtaining reliable predictions of head responses and heat plume migration.
{"title":"Three-Dimensional Geostatistical Inverse Analyses of Transient Head and Temperature Data From a Long-Term Heat Tracer Test","authors":"Zeren Ning, Tomohiro Nakashima, Kaoru Inaba, Takaaki Shimizu, Hyoun-Tae Hwang, Walter A. Illman","doi":"10.1029/2025wr041599","DOIUrl":"https://doi.org/10.1029/2025wr041599","url":null,"abstract":"Improving the accuracy of subsurface heterogeneity characterization remains a key component in better understanding groundwater flow and contaminant transport. Heat tracer tests can provide temperature measurements, in addition to head data, that can be used for mapping heterogeneity. Here, the performance of head and temperature data in characterizing the hydraulic conductivity (<i>K</i>) distribution is investigated with a three-dimensional highly parameterized model using the pilot point method. The performance results are evaluated qualitatively and quantitatively in various aspects, including <i>K</i> fields comparison, head and temperature matches for both model calibration and validation, as well as through identifiability and sensitivity analyses. Results of this study reveal that: (a) <i>K</i> fields obtained by inverting head data show finer details of heterogeneity, while small scale heterogeneity is smoothed when inverting temperature data; (b) combination of heat and temperature data improves the prediction of heat tracer tests; (c) increasing data density yields more heterogeneity information and further improves prediction performance; and (d) identifiability and sensitivity analyses suggest that head and temperature data contain nonredundant information of <i>K</i> heterogeneity. These results jointly suggest that the integration of transient head and temperature data shows promising potential in improving the delineation of subsurface <i>K</i> distribution and obtaining reliable predictions of head responses and heat plume migration.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"402 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146223373","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}
This work considers the design-for-control of water distribution networks (WDN) for the joint optimization of performance and cost-related objectives. In particular, we focus on the problem of optimizing the placement (design) and settings (control) of pressure reducing valves to minimize leakage at minimum cost. We present an integrative hybrid method combining the complementary advantages of deterministic and evolutionary algorithms (EA) to efficiently approximate the Pareto front of the resulting non-convex bi-objective mixed-integer non-linear program. Design decisions are fixed by an outer multi-objective EA, while a non-linear programming solver is called during the fitness evaluation stage to compute continuous control settings. The algorithm is applied to case study and operational networks and evaluated against alternative heuristic methods based on computational performance and quality of the solutions returned. Our results show that the proposed method converges faster and more consistently than existing approaches, producing better trade-offs between cost and leakage reduction. In particular, the Pareto front approximations computed using the proposed integrative hybrid method are characterized by a more marked knee (i.e., more efficient trade-offs), while the achieved computational improvements facilitate the integration of expert feedback into the design-for-control of WDNs during offline planning.
{"title":"Hybrid Evolutionary-Exact Optimization Method for the Bi-Objective Design-For-Control of Water Distribution Networks","authors":"Aly-Joy Ulusoy, Ivan Stoianov","doi":"10.1029/2025wr040688","DOIUrl":"https://doi.org/10.1029/2025wr040688","url":null,"abstract":"This work considers the design-for-control of water distribution networks (WDN) for the joint optimization of performance and cost-related objectives. In particular, we focus on the problem of optimizing the placement (design) and settings (control) of pressure reducing valves to minimize leakage at minimum cost. We present an integrative hybrid method combining the complementary advantages of deterministic and evolutionary algorithms (EA) to efficiently approximate the Pareto front of the resulting non-convex bi-objective mixed-integer non-linear program. Design decisions are fixed by an outer multi-objective EA, while a non-linear programming solver is called during the fitness evaluation stage to compute continuous control settings. The algorithm is applied to case study and operational networks and evaluated against alternative heuristic methods based on computational performance and quality of the solutions returned. Our results show that the proposed method converges faster and more consistently than existing approaches, producing better trade-offs between cost and leakage reduction. In particular, the Pareto front approximations computed using the proposed integrative hybrid method are characterized by a more marked knee (i.e., more efficient trade-offs), while the achieved computational improvements facilitate the integration of expert feedback into the design-for-control of WDNs during offline planning.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"326 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2026-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146205041","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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