Hiren Solanki, Urmin Vegad, Anuj Kushwaha, Vimal Mishra
Streamflow prediction is crucial for flood monitoring and early warning, which often hampered by bias and uncertainties arising from nonlinear processes, model parameterization, and errors in meteorological forecast. We examined the utility of multiple hydrological models (VIC, H08, CWatM, Noah-MP, and CLM) and machine learning (ML) methods to improve streamflow simulations and prediction. The hydrological models (HMs) were forced with observed meteorological data from the India Meteorological Department (IMD) and meteorological forecast from the Global Ensemble Forecast System (GEFS) to simulate flood peaks and flood inundation areas. We used Multiple Linear Regression, Random Forest (RF), Extreme Gradient Boosting (XGB), and Long Short-Term Memory (LSTM) for the post-processing of simulated streamflow from HMs. Considering the influence of dams is crucial for the effectiveness of HMs and ML methods for improving streamflow simulations and predictions. In addition, ML-based multi-model ensemble streamflow from HMs performs better than individual models, highlighting the need for multi-model-based streamflow forecast systems. The post-processing of streamflow simulated by the hydrological models using ML significantly improved overall streamflow simulations, with limited improvement in high-flow conditions. The combination of physics-based hydrological models, observed climate data, and ML methods improve streamflow predictions for flood magnitude, timing, and inundated area, which can be valuable for developing flood early warning systems in India.
{"title":"Improving Streamflow Prediction Using Multiple Hydrological Models and Machine Learning Methods","authors":"Hiren Solanki, Urmin Vegad, Anuj Kushwaha, Vimal Mishra","doi":"10.1029/2024wr038192","DOIUrl":"https://doi.org/10.1029/2024wr038192","url":null,"abstract":"Streamflow prediction is crucial for flood monitoring and early warning, which often hampered by bias and uncertainties arising from nonlinear processes, model parameterization, and errors in meteorological forecast. We examined the utility of multiple hydrological models (VIC, H08, CWatM, Noah-MP, and CLM) and machine learning (ML) methods to improve streamflow simulations and prediction. The hydrological models (HMs) were forced with observed meteorological data from the India Meteorological Department (IMD) and meteorological forecast from the Global Ensemble Forecast System (GEFS) to simulate flood peaks and flood inundation areas. We used Multiple Linear Regression, Random Forest (RF), Extreme Gradient Boosting (XGB), and Long Short-Term Memory (LSTM) for the post-processing of simulated streamflow from HMs. Considering the influence of dams is crucial for the effectiveness of HMs and ML methods for improving streamflow simulations and predictions. In addition, ML-based multi-model ensemble streamflow from HMs performs better than individual models, highlighting the need for multi-model-based streamflow forecast systems. The post-processing of streamflow simulated by the hydrological models using ML significantly improved overall streamflow simulations, with limited improvement in high-flow conditions. The combination of physics-based hydrological models, observed climate data, and ML methods improve streamflow predictions for flood magnitude, timing, and inundated area, which can be valuable for developing flood early warning systems in India.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"15 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142987986","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 tidal behavior of a well in semiconfined aquifers can be described by a diffusion equation including a leakage term. This approach is valid for thin aquifers, as long as the aquitard has low permeability relative to the aquifer. However, in cases where the aquifer is thick and the permeability of the aquitard is not low, using the existing solutions based on these approximations leads to unsatisfactory outcomes. Alternative solutions for both vertical and horizontal wells were obtained by solving the standard diffusion equation, with leakage expressed as a boundary condition. The solutions can be used to estimate any one of wellbore storage coefficient, skin effect, hydraulic diffusivity, and vertical leakage, given the other three. Furthermore, a nondimensional number, named hydraulic Biot number, was derived mathematically, which forms the basis for a quantitative criterion to assess the applicability of existing solutions. In the case of a vertical well, the existing solution exhibits acceptable error only if the hydraulic Biot number is less than 0.245. The new solution extends this upper limitation to 0.475. However, when the number is greater than 0.475, both the existing solution and new solution are invalid due to the invalid uniform flowrate assumption. For a horizontal well, when the number is less than 0.245, the existing solution is suitable with acceptable error. Our new solution effectively overcomes this limitation. Finally, the new solution was applied to the case of the Arbuckle aquifer to demonstrate the improved validity of the new solution compared to the existing one.
{"title":"Analytical Solutions for Groundwater Response to Earth Tides in Thick Semiconfined Aquifers","authors":"Xunfeng Lu, Kozo Sato, Roland N. Horne","doi":"10.1029/2023wr036237","DOIUrl":"https://doi.org/10.1029/2023wr036237","url":null,"abstract":"The tidal behavior of a well in semiconfined aquifers can be described by a diffusion equation including a leakage term. This approach is valid for thin aquifers, as long as the aquitard has low permeability relative to the aquifer. However, in cases where the aquifer is thick and the permeability of the aquitard is not low, using the existing solutions based on these approximations leads to unsatisfactory outcomes. Alternative solutions for both vertical and horizontal wells were obtained by solving the standard diffusion equation, with leakage expressed as a boundary condition. The solutions can be used to estimate any one of wellbore storage coefficient, skin effect, hydraulic diffusivity, and vertical leakage, given the other three. Furthermore, a nondimensional number, named hydraulic Biot number, was derived mathematically, which forms the basis for a quantitative criterion to assess the applicability of existing solutions. In the case of a vertical well, the existing solution exhibits acceptable error only if the hydraulic Biot number is less than 0.245. The new solution extends this upper limitation to 0.475. However, when the number is greater than 0.475, both the existing solution and new solution are invalid due to the invalid uniform flowrate assumption. For a horizontal well, when the number is less than 0.245, the existing solution is suitable with acceptable error. Our new solution effectively overcomes this limitation. Finally, the new solution was applied to the case of the Arbuckle aquifer to demonstrate the improved validity of the new solution compared to the existing one.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"328 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988070","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}
Zaiyang Zhou, Yu Kuai, Jianzhong Ge, Bas van Maren, Zhenwu Wang, Kailin Huang, Pingxing Ding, Zhengbing Wang
Physics-informed neural networks (PINNs) are increasingly being used in various scientific disciplines. However, dealing with non-stationary physical processes remains a significant challenge in such models, whereas fluid motions are typically non-stationary. In this study, a PINN-based method was designed and optimized to solve non-stationary fluid dynamics with shallow water equations in a polar coordinate system (PINN-SWEP). It was developed and validated with a classic circular basin case that is well-documented in scientific literature. In the validation case, the wind-induced water surface fluctuations are less than 1 cm, posing challenges in modeling. However, our PINN-SWEP model can accurately simulate such tiny water surface fluctuations and resolve complex fluid motions based on limited and sparse data. A boundary discontinuity problem associated with the use of a polar coordinate system is further discussed and improved, thereby enhancing the applicability of PINN in water research. The methodology can provide an alternative solution for numerical or analytical solutions with high accuracy.
{"title":"Modeling Non-Stationary Wind-Induced Fluid Motions With Physics-Informed Neural Networks for the Shallow Water Equations in a Polar Coordinate System","authors":"Zaiyang Zhou, Yu Kuai, Jianzhong Ge, Bas van Maren, Zhenwu Wang, Kailin Huang, Pingxing Ding, Zhengbing Wang","doi":"10.1029/2024wr037490","DOIUrl":"https://doi.org/10.1029/2024wr037490","url":null,"abstract":"Physics-informed neural networks (PINNs) are increasingly being used in various scientific disciplines. However, dealing with non-stationary physical processes remains a significant challenge in such models, whereas fluid motions are typically non-stationary. In this study, a PINN-based method was designed and optimized to solve non-stationary fluid dynamics with shallow water equations in a polar coordinate system (PINN-SWEP). It was developed and validated with a classic circular basin case that is well-documented in scientific literature. In the validation case, the wind-induced water surface fluctuations are less than 1 cm, posing challenges in modeling. However, our PINN-SWEP model can accurately simulate such tiny water surface fluctuations and resolve complex fluid motions based on limited and sparse data. A boundary discontinuity problem associated with the use of a polar coordinate system is further discussed and improved, thereby enhancing the applicability of PINN in water research. The methodology can provide an alternative solution for numerical or analytical solutions with high accuracy.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"19 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142987985","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}
Octavia Crompton, Gabriel Katul, Sally E. Thompson
Describing flow resistance from the properties of an underlying surface is a challenge in surface hydrology. Runoff models must specify a resistance formulation or “roughness scheme”—describing the functional relationship between flow resistance and flow depth/velocity—and its parameters. Uncertainty in runoff predictions derives from both the selected roughness scheme (e.g., Darcy Weisbach, Manning's, or laminar flow equations), and its parameterization with a roughness coefficient (e.g., Manning's <span data-altimg="/cms/asset/2a3656c5-62e3-412d-a272-a537de64215e/wrcr27631-math-0001.png"></span><mjx-container ctxtmenu_counter="453" ctxtmenu_oldtabindex="1" jax="CHTML" role="application" sre-explorer- style="font-size: 103%; position: relative;" tabindex="0"><mjx-math aria-hidden="true" location="graphic/wrcr27631-math-0001.png"><mjx-semantics><mjx-mrow><mjx-mi data-semantic-annotation="clearspeak:simple" data-semantic-font="italic" data-semantic- data-semantic-role="latinletter" data-semantic-speech="n" data-semantic-type="identifier"><mjx-c></mjx-c></mjx-mi></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display="inline" unselectable="on"><math altimg="urn:x-wiley:00431397:media:wrcr27631:wrcr27631-math-0001" display="inline" location="graphic/wrcr27631-math-0001.png" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mi data-semantic-="" data-semantic-annotation="clearspeak:simple" data-semantic-font="italic" data-semantic-role="latinletter" data-semantic-speech="n" data-semantic-type="identifier">n</mi></mrow>$n$</annotation></semantics></math></mjx-assistive-mml></mjx-container>). Both choices are informed by model calibration to data, usually discharge, and, if available, velocity. In this study, a Saint Venant Equation-based runoff model is calibrated to discharge and velocity data from 112 rainfall simulator experiments. The results are used to identify the optimal roughness scheme among four widely-used options for each experiment, and to explore whether surface properties can be used to select the optimal roughness scheme and its coefficient. Among the tested roughness schemes, a transitional flow equation provided the best fit to the plurality of experiments. The most suitable roughness scheme for a given experiment was not related to measured surface properties. Regression models predicted the calibrated roughness coefficients with adjusted <span data-altimg="/cms/asset/26faa875-27e4-4e97-a2cb-aab07ded999f/wrcr27631-math-0002.png"></span><mjx-container ctxtmenu_counter="454" ctxtmenu_oldtabindex="1" jax="CHTML" role="application" sre-explorer- style="font-size: 103%; position: relative;" tabindex="0"><mjx-math aria-hidden="true" location="graphic/wrcr27631-math-0002.png"><mjx-semantics><mjx-mrow><mjx-msup data-semantic-children="0,1" data-semantic- data-semantic-role="latinletter" data-semantic-speech="r squared" data-semantic-type="superscript"><mjx-mi data-semantic-annotation="clearspeak:simple" data-semantic-fon
{"title":"Uniting Surface Properties With Hydrodynamic Roughness in Shallow Overland Flow Models","authors":"Octavia Crompton, Gabriel Katul, Sally E. Thompson","doi":"10.1029/2024wr037176","DOIUrl":"https://doi.org/10.1029/2024wr037176","url":null,"abstract":"Describing flow resistance from the properties of an underlying surface is a challenge in surface hydrology. Runoff models must specify a resistance formulation or “roughness scheme”—describing the functional relationship between flow resistance and flow depth/velocity—and its parameters. Uncertainty in runoff predictions derives from both the selected roughness scheme (e.g., Darcy Weisbach, Manning's, or laminar flow equations), and its parameterization with a roughness coefficient (e.g., Manning's <span data-altimg=\"/cms/asset/2a3656c5-62e3-412d-a272-a537de64215e/wrcr27631-math-0001.png\"></span><mjx-container ctxtmenu_counter=\"453\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/wrcr27631-math-0001.png\"><mjx-semantics><mjx-mrow><mjx-mi data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"italic\" data-semantic- data-semantic-role=\"latinletter\" data-semantic-speech=\"n\" data-semantic-type=\"identifier\"><mjx-c></mjx-c></mjx-mi></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00431397:media:wrcr27631:wrcr27631-math-0001\" display=\"inline\" location=\"graphic/wrcr27631-math-0001.png\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow><mi data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"italic\" data-semantic-role=\"latinletter\" data-semantic-speech=\"n\" data-semantic-type=\"identifier\">n</mi></mrow>$n$</annotation></semantics></math></mjx-assistive-mml></mjx-container>). Both choices are informed by model calibration to data, usually discharge, and, if available, velocity. In this study, a Saint Venant Equation-based runoff model is calibrated to discharge and velocity data from 112 rainfall simulator experiments. The results are used to identify the optimal roughness scheme among four widely-used options for each experiment, and to explore whether surface properties can be used to select the optimal roughness scheme and its coefficient. Among the tested roughness schemes, a transitional flow equation provided the best fit to the plurality of experiments. The most suitable roughness scheme for a given experiment was not related to measured surface properties. Regression models predicted the calibrated roughness coefficients with adjusted <span data-altimg=\"/cms/asset/26faa875-27e4-4e97-a2cb-aab07ded999f/wrcr27631-math-0002.png\"></span><mjx-container ctxtmenu_counter=\"454\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/wrcr27631-math-0002.png\"><mjx-semantics><mjx-mrow><mjx-msup data-semantic-children=\"0,1\" data-semantic- data-semantic-role=\"latinletter\" data-semantic-speech=\"r squared\" data-semantic-type=\"superscript\"><mjx-mi data-semantic-annotation=\"clearspeak:simple\" data-semantic-fon","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"29 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142967888","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}
Christian Roumelis, Fabian Willert, Maria Scaccia, Susan Welch, Rachel Gabor, Jesús Carrera, Albert Folch, Miquel Salgot, Audrey H. Sawyer
Coastal aquifers experience water table fluctuations that push and pull water and air through organic-rich soils. This exchange affects the supply of oxygen, dissolved organic carbon (DOC), and nitrogen (N) to shallow aquifers and influences groundwater quality. To investigate the fate of N species, we used a meter-long column containing a sequence of natural organic topsoil and aquifer sediments. A fluctuating head was imposed at the column bottom with local, nitrate-rich groundwater (16.5 mg/L NO3-N). We monitored in-situ redox potential and collected pore water samples for analysis of inorganic N species and DOC over 16 days. Reactive processes were more complex than anticipated. The organic-rich topsoil remained anaerobic, while mineral sediments beneath alternated between aerobic, when the water table dropped and sucked air across preferential flow paths, and anaerobic conditions, when the water table was high. A fluid flow and reactive transport model shows that when the water table rises into organic-rich soils, it limits the flow of oxygen, while the soils release DOC, which stimulates the removal of nitrate from groundwater by denitrification. At the end of the experiment, we introduced seawater to the column to mimic a storm surge. Seawater mobilized N and DOC from shallow soil horizons, which could reach the aquifer if the surge is long enough. These processes are relevant for groundwater quality in developed coastal areas with anthropogenic N sources, as climate change and rising seas will drive changes in water table and flood dynamics.
{"title":"Water Table Fluctuations Control Nitrate and Ammonium Fate in Coastal Aquifers","authors":"Christian Roumelis, Fabian Willert, Maria Scaccia, Susan Welch, Rachel Gabor, Jesús Carrera, Albert Folch, Miquel Salgot, Audrey H. Sawyer","doi":"10.1029/2024wr038087","DOIUrl":"https://doi.org/10.1029/2024wr038087","url":null,"abstract":"Coastal aquifers experience water table fluctuations that push and pull water and air through organic-rich soils. This exchange affects the supply of oxygen, dissolved organic carbon (DOC), and nitrogen (N) to shallow aquifers and influences groundwater quality. To investigate the fate of N species, we used a meter-long column containing a sequence of natural organic topsoil and aquifer sediments. A fluctuating head was imposed at the column bottom with local, nitrate-rich groundwater (16.5 mg/L NO<sub>3</sub>-N). We monitored in-situ redox potential and collected pore water samples for analysis of inorganic N species and DOC over 16 days. Reactive processes were more complex than anticipated. The organic-rich topsoil remained anaerobic, while mineral sediments beneath alternated between aerobic, when the water table dropped and sucked air across preferential flow paths, and anaerobic conditions, when the water table was high. A fluid flow and reactive transport model shows that when the water table rises into organic-rich soils, it limits the flow of oxygen, while the soils release DOC, which stimulates the removal of nitrate from groundwater by denitrification. At the end of the experiment, we introduced seawater to the column to mimic a storm surge. Seawater mobilized N and DOC from shallow soil horizons, which could reach the aquifer if the surge is long enough. These processes are relevant for groundwater quality in developed coastal areas with anthropogenic N sources, as climate change and rising seas will drive changes in water table and flood dynamics.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"72 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142967886","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}
Shufeng Qiao, Rui Ma, Yunquan Wang, Ziyong Sun, Helen Kristine French, Yanxin Wang
Understanding the change in soil hydraulic conductivity with temperature is key to predicting groundwater flow and solute transport in cold regions. The most commonly used models for hydraulic conductivity during freeze‒thaw cycles only consider the flow of capillary water in the soil and neglect water flowing along thin films around the particle surface. This paper proposed a new hydraulic conductivity model of frozen soil via the Clausius–Clapeyron equation based on an unsaturated soil hydraulic conductivity model over the entire moisture range using an analogy between freeze‒thaw and dry‒wet processes in soils. The new model used a single equation to describe the conductivity behaviors resulting from both capillary and adsorption forces, thus accounting for the effect of both capillary water and thin liquid film around soil. By comparison with other existing models, the results demonstrated that the new model is applicable to various types of soils and that the predicted hydraulic conductivity is in the highest agreement with the observed data, while reducing the root mean square error by 38.9% compared to the van Genuchten–Mualem model. Finally, our new model was validated with thermal–hydrological benchmark problem and laboratory experiment result. The benchmark results indicated that the advective heat transfer was more significant, and the phase change was completed earlier when considering both capillary and adsorption forces than when only considering capillary forces. Furthermore, the coupled flow–heat model with the new hydraulic conductivity expression replicated well the results from a laboratory column experiment.
{"title":"A New Capillary and Adsorption‒Force Model Predicting Hydraulic Conductivity of Soil During Freeze‒thaw Processes","authors":"Shufeng Qiao, Rui Ma, Yunquan Wang, Ziyong Sun, Helen Kristine French, Yanxin Wang","doi":"10.1029/2023wr036857","DOIUrl":"https://doi.org/10.1029/2023wr036857","url":null,"abstract":"Understanding the change in soil hydraulic conductivity with temperature is key to predicting groundwater flow and solute transport in cold regions. The most commonly used models for hydraulic conductivity during freeze‒thaw cycles only consider the flow of capillary water in the soil and neglect water flowing along thin films around the particle surface. This paper proposed a new hydraulic conductivity model of frozen soil via the Clausius–Clapeyron equation based on an unsaturated soil hydraulic conductivity model over the entire moisture range using an analogy between freeze‒thaw and dry‒wet processes in soils. The new model used a single equation to describe the conductivity behaviors resulting from both capillary and adsorption forces, thus accounting for the effect of both capillary water and thin liquid film around soil. By comparison with other existing models, the results demonstrated that the new model is applicable to various types of soils and that the predicted hydraulic conductivity is in the highest agreement with the observed data, while reducing the root mean square error by 38.9% compared to the van Genuchten–Mualem model. Finally, our new model was validated with thermal–hydrological benchmark problem and laboratory experiment result. The benchmark results indicated that the advective heat transfer was more significant, and the phase change was completed earlier when considering both capillary and adsorption forces than when only considering capillary forces. Furthermore, the coupled flow–heat model with the new hydraulic conductivity expression replicated well the results from a laboratory column experiment.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"1 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142940196","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}
R. Blaine McCleskey, Robert L. Runkel, Sheila F. Murphy, David A. Roth
Stream discharge is often determined by wading the stream and measuring the point velocity at fixed widths and depths. However, there are conditions when wading measurements are not safe or the measurements are poor because of high turbulence, rocky streambeds, non-standard velocity distributions, shallow or sheet flow, aquatic plants, or inaccessibility due to ice. Under these conditions, it is often preferable to determine discharge using salt slug addition and downstream measurement of salt concentration with time. A new method for determining stream discharge using specific conductance as a surrogate for salt concentrations is presented. The method adapts an approach that accurately calculates the specific conductance by utilizing ionic molal conductivities to determine the concentration of salt. The method was applied at four mountainous stream sites where a total of twenty-nine slug-additions were performed. The discharge determined from the new method was compared to four alternative methods including discharge from continuous injection, slug addition with discrete sample calibration, wading measurements with velocity measurement, and a stream gage. The discharge ranged from 21.5 to 778 L/s and the median difference between the new method and the traditional methods was −0.01%. Additionally, the p-value (0.75) determined from a paired t-test indicates that there is no significant difference between the discharge determined from the new and alternative discharge methods. The primary advantage of the new method is that it obviates the need to collect and analyze discrete samples to accurately quantify the specific conductance-salt surrogate relationship, allowing for rapid, low-cost determination of discharge.
{"title":"Stream Discharge Determinations Using Slug Additions and Specific Conductance","authors":"R. Blaine McCleskey, Robert L. Runkel, Sheila F. Murphy, David A. Roth","doi":"10.1029/2024wr037771","DOIUrl":"https://doi.org/10.1029/2024wr037771","url":null,"abstract":"Stream discharge is often determined by wading the stream and measuring the point velocity at fixed widths and depths. However, there are conditions when wading measurements are not safe or the measurements are poor because of high turbulence, rocky streambeds, non-standard velocity distributions, shallow or sheet flow, aquatic plants, or inaccessibility due to ice. Under these conditions, it is often preferable to determine discharge using salt slug addition and downstream measurement of salt concentration with time. A new method for determining stream discharge using specific conductance as a surrogate for salt concentrations is presented. The method adapts an approach that accurately calculates the specific conductance by utilizing ionic molal conductivities to determine the concentration of salt. The method was applied at four mountainous stream sites where a total of twenty-nine slug-additions were performed. The discharge determined from the new method was compared to four alternative methods including discharge from continuous injection, slug addition with discrete sample calibration, wading measurements with velocity measurement, and a stream gage. The discharge ranged from 21.5 to 778 L/s and the median difference between the new method and the traditional methods was −0.01%. Additionally, the p-value (0.75) determined from a paired <i>t</i>-test indicates that there is no significant difference between the discharge determined from the new and alternative discharge methods. The primary advantage of the new method is that it obviates the need to collect and analyze discrete samples to accurately quantify the specific conductance-salt surrogate relationship, allowing for rapid, low-cost determination of discharge.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"48 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142940197","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}
Manhua Luo, Hailong Li, Gang Li, Wei Wang, Shengchao Yu, Qian Ma, Yan Zheng
Coastal groundwater dynamics and solute transport were influenced by multiple factors including aquitards, tides, evaporation, and slope breaks in coastal aquifers. However, quantification of the impacts of these factors on groundwater flow and salinity distribution remains a challenge. In this study, both field observations and numerical modeling were applied to investigate hydraulic heads and groundwater salinity in a tidal flat with large-scale seepage faces at Laizhou Bay, China. Results showed that seepage-face evaporation increased groundwater salinity landward and promoted groundwater and salt exchange within the intertidal zone significantly in comparison to the case without evaporation. Seawater infiltrated the aquifer on the left of the slope break and discharged on the right, forming a groundwater circulation cell, which notably influenced leakage flow between unconfined and confined aquifers through the aquitard. The aquitard prevented approximately 85% of inland freshwater discharge near the slope break, resulting in the formation of two atypical freshwater discharge tubes in the upper and middle intertidal zones. Two additional groundwater circulation cells developed in the lower intertidal zone due to the spring-neap tidal cycle. The outflow and inflow fluxes over a spring-neap tidal cycle were numerically estimated to be 1.46 and 1.27 m2/d, respectively, with evaporation accounting for 45% of the outflow flux. These findings provide significant insights for further investigations on groundwater dynamics and solute transport in multi-layered coastal aquifers, and have strong implications for biogeochemical processes within the intertidal zone.
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