Many major cities worldwide have inevitably experienced excessive groundwater pumping due to growing demands for freshwater in urban development. To mitigate land subsidence problems during urbanization, various regulations have been adopted to control groundwater usage. This study examines the transition in the post-subsidence stage, especially in metropolitan areas, to adaptively adjust subsidence prevention strategies for effective groundwater management. Taking the Taipei Basin as an example, historical data reveals significant subsidence of more than 2 m during early urban development, with subsidence hazards largely mitigated over decades. However, the rising groundwater level poses a risk to the stability of engineering excavations. In this study, 29 X-band Cosmo-Skymed constellation (CSK) images were utilized with the Persistent Scatterer InSAR (PSInSAR/PSI) technique to monitor surface displacements during the construction of the Mass Rapid Transit system. Correlating groundwater levels helps identify the heterogeneous hydrogeological environment, and the potential groundwater capacity is assessed. PSI time-series reveal that approximately 2 cm of recoverable land displacements correspond to groundwater fluctuations in the confined aquifer, indicative of the typically elastic behavior of the resilient aquifer system. The estimated groundwater storage variation is about 1.6 million cubic meters, suggesting this potential groundwater capacity could provide available water resources with proper management. Additionally, engineering excavation safety can be ensured with lowered groundwater levels. This study emphasizes the need to balance groundwater resource use with urban development by adjusting subsidence prevention and control strategies to achieve sustainable water management in the post-subsidence stage.
{"title":"Assessing Potential Groundwater Storage Capacity for Sustainable Groundwater Management in the Transitioning Post-Subsidence Metropolitan Area","authors":"Shao-Hung Lin, Jyr-Ching Hu, Shih-Jung Wang","doi":"10.1029/2023wr036951","DOIUrl":"https://doi.org/10.1029/2023wr036951","url":null,"abstract":"Many major cities worldwide have inevitably experienced excessive groundwater pumping due to growing demands for freshwater in urban development. To mitigate land subsidence problems during urbanization, various regulations have been adopted to control groundwater usage. This study examines the transition in the post-subsidence stage, especially in metropolitan areas, to adaptively adjust subsidence prevention strategies for effective groundwater management. Taking the Taipei Basin as an example, historical data reveals significant subsidence of more than 2 m during early urban development, with subsidence hazards largely mitigated over decades. However, the rising groundwater level poses a risk to the stability of engineering excavations. In this study, 29 X-band Cosmo-Skymed constellation (CSK) images were utilized with the Persistent Scatterer InSAR (PSInSAR/PSI) technique to monitor surface displacements during the construction of the Mass Rapid Transit system. Correlating groundwater levels helps identify the heterogeneous hydrogeological environment, and the potential groundwater capacity is assessed. PSI time-series reveal that approximately 2 cm of recoverable land displacements correspond to groundwater fluctuations in the confined aquifer, indicative of the typically elastic behavior of the resilient aquifer system. The estimated groundwater storage variation is about 1.6 million cubic meters, suggesting this potential groundwater capacity could provide available water resources with proper management. Additionally, engineering excavation safety can be ensured with lowered groundwater levels. This study emphasizes the need to balance groundwater resource use with urban development by adjusting subsidence prevention and control strategies to achieve sustainable water management in the post-subsidence stage.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"56 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142670376","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}
Jan Vinogradov, Miftah Hidayat, Mohammad Sarmadivaleh, David Vega-Maza, Stefan Iglauer, Lijuan Zhang, Dajiang Mei, Jos Derksen
Although CO2 geological storage (CGS) is thought to be one of the most promising technologies to sequester the anthropogenic CO2 to mitigate the climate change, implementation of the method is still challenging due to lack of fundamental understanding of controls of wettability, which is responsible for residual trapping of the gas and its flow dynamics. One of the key parameters that controls the wetting state is the zeta potential, ζ, at rock-water and CO2-water interfaces. ζ in systems comprising rocks, carbonated aqueous solutions and immiscible supercritical CO2 have not been measured prior to this study, where we detail the experimental protocol that enables measuring ζ in such systems, and report novel experimental data on the multi-phase ζ. We also demonstrate for the first time that ζ of supercritical CO2-water interface is negative with a magnitude greater that 14 mV. Moreover, our experimental results suggest that presence of multi-valent cations in tested solutions causes a shift of wettability toward intermediate-wet state. We introduce a new parameter that combines multi-phase ζ and relative permeability endpoints to characterize the wetting state and residual supercritical CO2 saturation. Based on these results, we demonstrate that ζ measurements could serve as a powerful experimental method for predicting CGS efficiency and/or for designing injection of aqueous solutions with bespoke composition prior to implementing CGS to improve the residual CO2 trapping in sandstone formations.
{"title":"Zeta Potential of Supercritical CO2-Water-Sandstone Systems and Its Correlation With Wettability and Residual Subsurface Trapping of CO2","authors":"Jan Vinogradov, Miftah Hidayat, Mohammad Sarmadivaleh, David Vega-Maza, Stefan Iglauer, Lijuan Zhang, Dajiang Mei, Jos Derksen","doi":"10.1029/2023wr036698","DOIUrl":"https://doi.org/10.1029/2023wr036698","url":null,"abstract":"Although CO<sub>2</sub> geological storage (CGS) is thought to be one of the most promising technologies to sequester the anthropogenic CO<sub>2</sub> to mitigate the climate change, implementation of the method is still challenging due to lack of fundamental understanding of controls of wettability, which is responsible for residual trapping of the gas and its flow dynamics. One of the key parameters that controls the wetting state is the zeta potential, <i>ζ</i>, at rock-water and CO<sub>2</sub>-water interfaces. <i>ζ</i> in systems comprising rocks, carbonated aqueous solutions and immiscible supercritical CO<sub>2</sub> have not been measured prior to this study, where we detail the experimental protocol that enables measuring <i>ζ</i> in such systems, and report novel experimental data on the multi-phase <i>ζ</i>. We also demonstrate for the first time that <i>ζ</i> of supercritical CO<sub>2</sub>-water interface is negative with a magnitude greater that 14 mV. Moreover, our experimental results suggest that presence of multi-valent cations in tested solutions causes a shift of wettability toward intermediate-wet state. We introduce a new parameter that combines multi-phase <i>ζ</i> and relative permeability endpoints to characterize the wetting state and residual supercritical CO<sub>2</sub> saturation. Based on these results, we demonstrate that <i>ζ</i> measurements could serve as a powerful experimental method for predicting CGS efficiency and/or for designing injection of aqueous solutions with bespoke composition prior to implementing CGS to improve the residual CO<sub>2</sub> trapping in sandstone formations.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"6 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142665233","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}
Zhen Zhou, Laura Riis-Klinkvort, Emilie Ahrnkiel Jørgensen, Christine Lindenhoff, Monica Coppo Frías, Alexander Rietz Vesterhauge, Daniel Haugård Olesen, Makar Lavish, Alexey Dobrovolskiy, Alexey Kadek, Niksa Orlic, Tomislav Grubesa, Luka Drmić, Henrik Grosen, Sune Nielsen, Daniel Wennerberg, Viktor Fagerström, Jenny Axén, David Gustafsson, Peter Bauer-Gottwein
Using Unoccupied Aerial Systems (UAS) equipped with optical RGB cameras and Doppler radar, surface velocity can be efficiently measured at high spatial resolution. UAS-borne Doppler radar is particularly attractive because it is suitable for real-time velocity determination, because the measurement is contactless, and because it has fewer limitations than image velocimetry techniques. In this paper, five cross-sections (XSs) were surveyed within a 10 km stretch of Rönne River in Sweden. Ground-truth surface velocity observations were retrieved with an electromagnetic velocity sensor (OTT MF Pro) along the XS at one m spacing. Videos from a UAS RGB camera were analyzed using both Particle Image Velocimetry (PIV) and Space-Time Image Velocimetry (STIV) techniques. Furthermore, we recorded full waveform signal data using a Doppler radar at multiple waypoints across the river. An algorithm fits two alternative models to the average amplitude curve to derive the correct river surface velocity based on Gaussian models with: (a) one peak, and (b) two peaks. Results indicate that river flow velocity and propwash velocity caused by the drone can be found in XS where the flow velocity is low, while the drone-induced propwash velocity can be neglected in fast and highly turbulent flows. To verify the river flow velocity derived from Doppler radar, a mean PIV value within the footprint of the Doppler radar at each waypoint was calculated. Finally, quantitative comparisons of OTT MF Pro data with STIV, mean PIV and Doppler radar revealed that UAS-borne Doppler radar could reliably measure the river surface velocity.
{"title":"Measuring River Surface Velocity Using UAS-Borne Doppler Radar","authors":"Zhen Zhou, Laura Riis-Klinkvort, Emilie Ahrnkiel Jørgensen, Christine Lindenhoff, Monica Coppo Frías, Alexander Rietz Vesterhauge, Daniel Haugård Olesen, Makar Lavish, Alexey Dobrovolskiy, Alexey Kadek, Niksa Orlic, Tomislav Grubesa, Luka Drmić, Henrik Grosen, Sune Nielsen, Daniel Wennerberg, Viktor Fagerström, Jenny Axén, David Gustafsson, Peter Bauer-Gottwein","doi":"10.1029/2024wr037375","DOIUrl":"https://doi.org/10.1029/2024wr037375","url":null,"abstract":"Using Unoccupied Aerial Systems (UAS) equipped with optical RGB cameras and Doppler radar, surface velocity can be efficiently measured at high spatial resolution. UAS-borne Doppler radar is particularly attractive because it is suitable for real-time velocity determination, because the measurement is contactless, and because it has fewer limitations than image velocimetry techniques. In this paper, five cross-sections (XSs) were surveyed within a 10 km stretch of Rönne River in Sweden. Ground-truth surface velocity observations were retrieved with an electromagnetic velocity sensor (OTT MF Pro) along the XS at one m spacing. Videos from a UAS RGB camera were analyzed using both Particle Image Velocimetry (PIV) and Space-Time Image Velocimetry (STIV) techniques. Furthermore, we recorded full waveform signal data using a Doppler radar at multiple waypoints across the river. An algorithm fits two alternative models to the average amplitude curve to derive the correct river surface velocity based on Gaussian models with: (a) one peak, and (b) two peaks. Results indicate that river flow velocity and propwash velocity caused by the drone can be found in XS where the flow velocity is low, while the drone-induced propwash velocity can be neglected in fast and highly turbulent flows. To verify the river flow velocity derived from Doppler radar, a mean PIV value within the footprint of the Doppler radar at each waypoint was calculated. Finally, quantitative comparisons of OTT MF Pro data with STIV, mean PIV and Doppler radar revealed that UAS-borne Doppler radar could reliably measure the river surface velocity.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"6 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142645886","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 study introduces a novel heat tracing method for estimating lateral groundwater flow velocity induced and sustained by heavy rainfall events in lowland areas, leveraging the distinct temperature difference between rainfall and groundwater. The method is motivated by the observation that the rainfall-induced groundwater temperature signal dissipates along the flow path. To explain the observed temperature anomaly and then estimate the lateral flow velocity, we develop a semi-analytical model for heat transport in the aquifer, accounting for conduction losses to adjacent layers. Our findings reveal that interactions between the aquifer, vadose zone, and bedrock significantly influence the temperature signal, thereby affecting velocity estimation. Inaccuracies in measured aquifer properties, such as thickness, porosity, and thermal conductivity of surrounding layers, increase the uncertainty of velocity estimates. However, variations in aquifer thermal conductivity have a minimal effect on the method's overall accuracy. When estimating multiple parameters, velocity estimates tend to be less reliable, especially if aquifer porosity remains uncertain. This is due to the challenges of simultaneously inverting both velocity and porosity. Overall, this work underscores the potential of using heat as a tracer for assessing lateral groundwater flow following rainfall, offering a practical, low-cost solution applicable in a wide range of settings.
{"title":"Using Rainfall-Induced Groundwater Temperature Response to Estimate Lateral Flow Velocity","authors":"Kewei Chen, Zhili Guo, Maosheng Yin, Xiuyu Liang, Zhenbo Chang, Shuai Yang, Xiaoou Wei, Xuchen Zhai, Chunmiao Zheng","doi":"10.1029/2023wr036715","DOIUrl":"https://doi.org/10.1029/2023wr036715","url":null,"abstract":"This study introduces a novel heat tracing method for estimating lateral groundwater flow velocity induced and sustained by heavy rainfall events in lowland areas, leveraging the distinct temperature difference between rainfall and groundwater. The method is motivated by the observation that the rainfall-induced groundwater temperature signal dissipates along the flow path. To explain the observed temperature anomaly and then estimate the lateral flow velocity, we develop a semi-analytical model for heat transport in the aquifer, accounting for conduction losses to adjacent layers. Our findings reveal that interactions between the aquifer, vadose zone, and bedrock significantly influence the temperature signal, thereby affecting velocity estimation. Inaccuracies in measured aquifer properties, such as thickness, porosity, and thermal conductivity of surrounding layers, increase the uncertainty of velocity estimates. However, variations in aquifer thermal conductivity have a minimal effect on the method's overall accuracy. When estimating multiple parameters, velocity estimates tend to be less reliable, especially if aquifer porosity remains uncertain. This is due to the challenges of simultaneously inverting both velocity and porosity. Overall, this work underscores the potential of using heat as a tracer for assessing lateral groundwater flow following rainfall, offering a practical, low-cost solution applicable in a wide range of settings.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"29 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637562","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}
Zhesi Cui, Qiyu Chen, Jian Luo, Xiaogang Ma, Gang Liu
Accurately inferring realistic subsurface structures poses a considerable challenge due to the impact of morphology on flow and transport behaviors. Traditional subsurface characterization relies on two primary types of data: hard data, derived from direct subsurface measurements, and soft data, encompassing remotely sensed geophysical information and its interpretation. Existing deep-learning-based methodologies predominantly focus on the transition from multiple observations to subsurface structures. However, implicit non-linear correlations among diverse data sources often remain underutilized, leading to potential bias and errors. In this study, we introduce a multiple-condition fusion network (MCF-Net) to characterize subsurface structures based on both hard and soft data. To harness the full potential of multiple-source subsurface observations, two distinct neural networks extract implicit features from hard and soft data. The integration of these features is achieved through multiple-condition fusion blocks, designed to capture representative characteristics. These blocks are also adept at reconstructing heterogeneous structures and facilitating hydrological parameterization. MCF-Net exhibits accuracy in estimating subsurface structures across various types of subsurface observations. Experimental results underscore the utility and superiority of MCF-Net in applications of hydrogeological modeling.
{"title":"Characterizing Subsurface Structures From Hard and Soft Data With Multiple-Condition Fusion Neural Network","authors":"Zhesi Cui, Qiyu Chen, Jian Luo, Xiaogang Ma, Gang Liu","doi":"10.1029/2024wr038170","DOIUrl":"https://doi.org/10.1029/2024wr038170","url":null,"abstract":"Accurately inferring realistic subsurface structures poses a considerable challenge due to the impact of morphology on flow and transport behaviors. Traditional subsurface characterization relies on two primary types of data: hard data, derived from direct subsurface measurements, and soft data, encompassing remotely sensed geophysical information and its interpretation. Existing deep-learning-based methodologies predominantly focus on the transition from multiple observations to subsurface structures. However, implicit non-linear correlations among diverse data sources often remain underutilized, leading to potential bias and errors. In this study, we introduce a multiple-condition fusion network (MCF-Net) to characterize subsurface structures based on both hard and soft data. To harness the full potential of multiple-source subsurface observations, two distinct neural networks extract implicit features from hard and soft data. The integration of these features is achieved through multiple-condition fusion blocks, designed to capture representative characteristics. These blocks are also adept at reconstructing heterogeneous structures and facilitating hydrological parameterization. MCF-Net exhibits accuracy in estimating subsurface structures across various types of subsurface observations. Experimental results underscore the utility and superiority of MCF-Net in applications of hydrogeological modeling.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"10 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637888","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}
Siyoon Kwon, Paola Passalacqua, Antoine Soloy, Daniel Jensen, Marc Simard
Remote sensing has been widely applied to investigate fluvial processes, but depth retrievals face significant constraints in deep and turbid conditions. This study evaluates the potential for depth retrievals under such challenging conditions using NASA's Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) imagery. We employ interpretable machine learning to construct a hyperspectral regressor for water depth and explore the spectral characteristics of deep and turbid waters in Wax Lake Delta (WLD), Louisiana, USA. The reflectance spectra of WLD show minor effects from depth differences due to turbidity. Nevertheless, a Random Forest with Recursive Feature Elimination (RF-RFE) effectively generalizes high and low turbidity cases in a single model, achieving a <span data-altimg="/cms/asset/0be6b620-fbe1-4182-9d7f-341f8fb2c089/wrcr27583-math-0001.png"></span><mjx-container ctxtmenu_counter="160" ctxtmenu_oldtabindex="1" jax="CHTML" role="application" sre-explorer- style="font-size: 103%; position: relative;" tabindex="0"><mjx-math aria-hidden="true" location="graphic/wrcr27583-math-0001.png"><mjx-semantics><mjx-mrow><mjx-msup data-semantic-children="0,1" data-semantic- data-semantic-role="latinletter" data-semantic-speech="upper R squared" data-semantic-type="superscript"><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: 0.363em;"><mjx-mn data-semantic-annotation="clearspeak:simple" data-semantic-font="normal" data-semantic- data-semantic-parent="2" data-semantic-role="integer" data-semantic-type="number" size="s"><mjx-c></mjx-c></mjx-mn></mjx-script></mjx-msup></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display="inline" unselectable="on"><math altimg="urn:x-wiley:00431397:media:wrcr27583:wrcr27583-math-0001" display="inline" location="graphic/wrcr27583-math-0001.png" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><msup data-semantic-="" data-semantic-children="0,1" data-semantic-role="latinletter" data-semantic-speech="upper R squared" data-semantic-type="superscript"><mi data-semantic-="" data-semantic-annotation="clearspeak:simple" data-semantic-font="italic" data-semantic-parent="2" data-semantic-role="latinletter" data-semantic-type="identifier">R</mi><mn data-semantic-="" data-semantic-annotation="clearspeak:simple" data-semantic-font="normal" data-semantic-parent="2" data-semantic-role="integer" data-semantic-type="number">2</mn></msup></mrow>${R}^{2}$</annotation></semantics></math></mjx-assistive-mml></mjx-container> of <span data-altimg="/cms/asset/72894ba6-f575-4543-815c-e895d335c31f/wrcr27583-math-0002.png"></span><mjx-container ctxtmenu_counter="161" ctxtmenu_oldtabindex="1" jax="CHTML" role="application" sre-explorer- style="font-size: 103%; position: relative;" tabindex="0"><mjx-math aria-hidd
{"title":"Depth Mapping in Turbid and Deep Waters Using AVIRIS-NG Imagery: A Study in Wax Lake Delta, Louisiana, USA","authors":"Siyoon Kwon, Paola Passalacqua, Antoine Soloy, Daniel Jensen, Marc Simard","doi":"10.1029/2023wr036875","DOIUrl":"https://doi.org/10.1029/2023wr036875","url":null,"abstract":"Remote sensing has been widely applied to investigate fluvial processes, but depth retrievals face significant constraints in deep and turbid conditions. This study evaluates the potential for depth retrievals under such challenging conditions using NASA's Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) imagery. We employ interpretable machine learning to construct a hyperspectral regressor for water depth and explore the spectral characteristics of deep and turbid waters in Wax Lake Delta (WLD), Louisiana, USA. The reflectance spectra of WLD show minor effects from depth differences due to turbidity. Nevertheless, a Random Forest with Recursive Feature Elimination (RF-RFE) effectively generalizes high and low turbidity cases in a single model, achieving a <span data-altimg=\"/cms/asset/0be6b620-fbe1-4182-9d7f-341f8fb2c089/wrcr27583-math-0001.png\"></span><mjx-container ctxtmenu_counter=\"160\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/wrcr27583-math-0001.png\"><mjx-semantics><mjx-mrow><mjx-msup data-semantic-children=\"0,1\" data-semantic- data-semantic-role=\"latinletter\" data-semantic-speech=\"upper R squared\" data-semantic-type=\"superscript\"><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: 0.363em;\"><mjx-mn data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"integer\" data-semantic-type=\"number\" size=\"s\"><mjx-c></mjx-c></mjx-mn></mjx-script></mjx-msup></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00431397:media:wrcr27583:wrcr27583-math-0001\" display=\"inline\" location=\"graphic/wrcr27583-math-0001.png\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow><msup data-semantic-=\"\" data-semantic-children=\"0,1\" data-semantic-role=\"latinletter\" data-semantic-speech=\"upper R squared\" data-semantic-type=\"superscript\"><mi data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"italic\" data-semantic-parent=\"2\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\">R</mi><mn data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic-parent=\"2\" data-semantic-role=\"integer\" data-semantic-type=\"number\">2</mn></msup></mrow>${R}^{2}$</annotation></semantics></math></mjx-assistive-mml></mjx-container> of <span data-altimg=\"/cms/asset/72894ba6-f575-4543-815c-e895d335c31f/wrcr27583-math-0002.png\"></span><mjx-container ctxtmenu_counter=\"161\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidd","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"98 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637891","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}
W. K. Jaeger, J. Antle, S. B. Gingerich, D. Bigelow
Groundwater resources frequently trend toward unsustainable levels because, absent effective institutions, individual water users generally act independently without considering the impacts on other users. Hydro-economic models (HEMs) of human-natural systems can play a positive role toward successful groundwater management by yielding valuable knowledge and insight. The current study explores how an HEM that captures essential physical and economic characteristics of a system can shed light on the system's processes and dynamics to benefit stakeholders, managers, and also researchers. These propositions are illustrated using the Harney Basin, Oregon, which has seen large groundwater declines in the past 20 years. The HEM shows that: (a) although current groundwater pumping rates will gradually raise costs and reduce well yields, irrigators gain the highest aggregate economic return by continuing current pumping; (b) lowland areas of the basin are hydrologically connected, which limits the efficacy of remedies focused on regulations only in some portions of the basin; (c) community expectations regarding the efficacy of several proposed solutions are overly optimistic; and (d) the study's scenarios identify interventions that would stabilize the groundwater system and prevent additional adverse impacts on residential and livestock wells and groundwater-dependent ecosystems. These interventions would require limiting groundwater pumping by nearly half and reducing annual profits by $7.5–$9.0M. The HEM also demonstrated its value to researchers: its insights shifted attention toward questions about Oregon's existing groundwater institutions and their inability to adaptively manage the transition from abundant groundwater to scarce groundwater in a timely manner.
{"title":"Advancing Sustainable Groundwater Management With a Hydro-Economic System Model: Investigations in the Harney Basin, Oregon","authors":"W. K. Jaeger, J. Antle, S. B. Gingerich, D. Bigelow","doi":"10.1029/2023wr036972","DOIUrl":"https://doi.org/10.1029/2023wr036972","url":null,"abstract":"Groundwater resources frequently trend toward unsustainable levels because, absent effective institutions, individual water users generally act independently without considering the impacts on other users. Hydro-economic models (HEMs) of human-natural systems can play a positive role toward successful groundwater management by yielding valuable knowledge and insight. The current study explores how an HEM that captures essential physical and economic characteristics of a system can shed light on the system's processes and dynamics to benefit stakeholders, managers, and also researchers. These propositions are illustrated using the Harney Basin, Oregon, which has seen large groundwater declines in the past 20 years. The HEM shows that: (a) although current groundwater pumping rates will gradually raise costs and reduce well yields, irrigators gain the highest aggregate economic return by continuing current pumping; (b) lowland areas of the basin are hydrologically connected, which limits the efficacy of remedies focused on regulations only in some portions of the basin; (c) community expectations regarding the efficacy of several proposed solutions are overly optimistic; and (d) the study's scenarios identify interventions that would stabilize the groundwater system and prevent additional adverse impacts on residential and livestock wells and groundwater-dependent ecosystems. These interventions would require limiting groundwater pumping by nearly half and reducing annual profits by $7.5–$9.0M. The HEM also demonstrated its value to researchers: its insights shifted attention toward questions about Oregon's existing groundwater institutions and their inability to adaptively manage the transition from abundant groundwater to scarce groundwater in a timely manner.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"11 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637473","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}
Xudan Zhu, Frank Berninger, Liang Chen, Johannes Larson, Ryan A. Sponseller, Hjalmar Laudon
Over the past few decades, many catchments in Northern hemisphere have experienced increases in dissolved organic carbon (DOC) concentrations, resulting in a brownish color of the water, known as aquatic browning. Several mechanisms have been proposed to explain browning, but consensus regarding the relative importance of recovery from acid deposition, climate change, and land management remains elusive. To advance our understanding of browning mechanisms, we explored DOC trends across 13 nested boreal catchments, leveraging concurrent hydrological, chemical, and terrestrial ecosystem data to quantify the contributions of different drivers on observed trends. We first identified the related environmental factors, then attributed the individual trends of DOC to potential drivers across space and time. Our results showed that all catchments exhibited increased DOC trends from 2003 to 2021, but the DOC response rates differed by five-fold. No single mechanism could fully explain the browning; instead, sulfate deposition, climate-related factors, and site properties jointly controlled the variation in DOC trends. Specifically, the long-term increases in DOC were primarily driven by recovery from sulfate deposition, followed by increases in terrestrial productivity, temperature, and discharge. However, catchment area and landcover type also regulated the response rate of DOC to these drivers, creating spatial heterogeneity in browning among sub-catchments despite similar deposition and climate forcing. Interestingly, browning has weakened in the last decade as sulfate deposition has fully recovered and other current drivers are insufficient to sustain the long-term increases. Our results highlight that multifaceted, spatially structured, and nonstationary drivers must be accounted for to predict future DOC changes.
{"title":"Several Mechanisms Drive the Heterogeneity in Browning Across a Boreal Stream Network","authors":"Xudan Zhu, Frank Berninger, Liang Chen, Johannes Larson, Ryan A. Sponseller, Hjalmar Laudon","doi":"10.1029/2023wr036802","DOIUrl":"https://doi.org/10.1029/2023wr036802","url":null,"abstract":"Over the past few decades, many catchments in Northern hemisphere have experienced increases in dissolved organic carbon (DOC) concentrations, resulting in a brownish color of the water, known as aquatic browning. Several mechanisms have been proposed to explain browning, but consensus regarding the relative importance of recovery from acid deposition, climate change, and land management remains elusive. To advance our understanding of browning mechanisms, we explored DOC trends across 13 nested boreal catchments, leveraging concurrent hydrological, chemical, and terrestrial ecosystem data to quantify the contributions of different drivers on observed trends. We first identified the related environmental factors, then attributed the individual trends of DOC to potential drivers across space and time. Our results showed that all catchments exhibited increased DOC trends from 2003 to 2021, but the DOC response rates differed by five-fold. No single mechanism could fully explain the browning; instead, sulfate deposition, climate-related factors, and site properties jointly controlled the variation in DOC trends. Specifically, the long-term increases in DOC were primarily driven by recovery from sulfate deposition, followed by increases in terrestrial productivity, temperature, and discharge. However, catchment area and landcover type also regulated the response rate of DOC to these drivers, creating spatial heterogeneity in browning among sub-catchments despite similar deposition and climate forcing. Interestingly, browning has weakened in the last decade as sulfate deposition has fully recovered and other current drivers are insufficient to sustain the long-term increases. Our results highlight that multifaceted, spatially structured, and nonstationary drivers must be accounted for to predict future DOC changes.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"64 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637890","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}
Xiaoli Wang, Yong Tian, Jiang Yu, M. Lancia, Ji Chen, Kai Xiao, Y. Zheng, Charles B. Andrews, Chunmiao Zheng
River deltas typically have high population density and support a wide range of intensive and prosperous socioeconomic activities. The hydrological processes in these regions are complex, primarily due to the interactions among the river, aquifer, and sea. However, a systematic and quantitative elaboration of the river‐aquifer‐sea interactions is still lacking. Here we developed an integrated hydrological flow model for the Pearl River Delta (PRD), which contains the world’s largest urban area in both size and population, to gain a deeper understanding of the complexities in the river‐aquifer‐sea interactions. The model performance was validated and cross‐checked via observations at gauging stations and independent remote‐sensing products (e.g., soil moisture, ET and total water storage anomalies). Based on the 10‐year simulation results (2004‐2013), the major findings of this study are as follows: 1) accurate representation of the tidal effect is important not only for simulating short‐term flow dynamics but also for capturing the characteristics of long‐term hydrological fluxes and states; 2) the flow‐model‐computed average groundwater discharge rate per unit length of the coastline for the PRD is 3.01 m3/d/m, which is comparable with those derived from water budget approaches but 1‐2 orders of magnitude lower than the total submarine groundwater discharge (SGD) estimated by using isotope tracer‐based methods; 3) the temporal variation of SGD is controlled by tidal forcing on an hourly time scale, but by terrestrial hydrological processes on monthly and annual time scales; and 4) an integrated hydrological flow model can be used to identify distinct and large subsurface zones sensitive to tidal fluctuations, quantifying the pivotal role of ocean tides in shaping the coastal groundwater system. This study represents a first step in using an integrated hydrological model to explore river‐aquifer‐sea interactions and their effects on the regional groundwater system simultaneously driven by meteorological and tidal forcings.This article is protected by copyright. All rights reserved.
{"title":"Complex Effects of Tides on Coastal Groundwater Revealed by High‐Resolution Integrated Flow Modeling","authors":"Xiaoli Wang, Yong Tian, Jiang Yu, M. Lancia, Ji Chen, Kai Xiao, Y. Zheng, Charles B. Andrews, Chunmiao Zheng","doi":"10.1029/2022wr033942","DOIUrl":"https://doi.org/10.1029/2022wr033942","url":null,"abstract":"River deltas typically have high population density and support a wide range of intensive and prosperous socioeconomic activities. The hydrological processes in these regions are complex, primarily due to the interactions among the river, aquifer, and sea. However, a systematic and quantitative elaboration of the river‐aquifer‐sea interactions is still lacking. Here we developed an integrated hydrological flow model for the Pearl River Delta (PRD), which contains the world’s largest urban area in both size and population, to gain a deeper understanding of the complexities in the river‐aquifer‐sea interactions. The model performance was validated and cross‐checked via observations at gauging stations and independent remote‐sensing products (e.g., soil moisture, ET and total water storage anomalies). Based on the 10‐year simulation results (2004‐2013), the major findings of this study are as follows: 1) accurate representation of the tidal effect is important not only for simulating short‐term flow dynamics but also for capturing the characteristics of long‐term hydrological fluxes and states; 2) the flow‐model‐computed average groundwater discharge rate per unit length of the coastline for the PRD is 3.01 m3/d/m, which is comparable with those derived from water budget approaches but 1‐2 orders of magnitude lower than the total submarine groundwater discharge (SGD) estimated by using isotope tracer‐based methods; 3) the temporal variation of SGD is controlled by tidal forcing on an hourly time scale, but by terrestrial hydrological processes on monthly and annual time scales; and 4) an integrated hydrological flow model can be used to identify distinct and large subsurface zones sensitive to tidal fluctuations, quantifying the pivotal role of ocean tides in shaping the coastal groundwater system. This study represents a first step in using an integrated hydrological model to explore river‐aquifer‐sea interactions and their effects on the regional groundwater system simultaneously driven by meteorological and tidal forcings.This article is protected by copyright. All rights reserved.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47300774","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 change in heat storage (Gc) is an essential component of a lake's energy balance, and its importance for lake evaporation (Ew) has been widely recognized. However, the effect of Gc on Ew exhibits diversity across time dimensions. The controls on Gc and the effects of Gc on Ew estimates at different time scales remain largely unexplored. To address these gaps, we identified the primary controls on Gc at an eddy covariance site in a large shallow lake (Lake Taihu) and quantified the role of Gc in estimating Ew on three (hourly, daily, and monthly) time scales based on two energy balance‐based Ew models. Our results indicate that the diurnal variation of Gc is dominated by net radiation and peaks around noon, while the seasonal variation of Gc is mainly controlled by air temperature and peaks in spring. In contrast, the daily variation of Gc is subjective to a confluence of factors—net radiation, wind speed, and relative humidity—displaying more stochasticity than that on the other two time scales. We also found that the importance of Gc for Ew estimates decreases as the time scale extends. Compared to the two models disregarding Gc, considering the effect of Gc enhances the average Kling‐Gupta efficiency (KGE) values of the two models by 1.33, 0.42, and 0.08 on the three time scales, respectively. Overall, this study highlights the importance of time scales in evaluating the effect of Gc on Ew estimates.
{"title":"The Importance of Heat Storage for Estimating Lake Evaporation on Different Time Scales: Insights From a Large Shallow Subtropical Lake","authors":"P. Bai, Yongsheng Wang","doi":"10.1029/2023WR035123","DOIUrl":"https://doi.org/10.1029/2023WR035123","url":null,"abstract":"The change in heat storage (Gc) is an essential component of a lake's energy balance, and its importance for lake evaporation (Ew) has been widely recognized. However, the effect of Gc on Ew exhibits diversity across time dimensions. The controls on Gc and the effects of Gc on Ew estimates at different time scales remain largely unexplored. To address these gaps, we identified the primary controls on Gc at an eddy covariance site in a large shallow lake (Lake Taihu) and quantified the role of Gc in estimating Ew on three (hourly, daily, and monthly) time scales based on two energy balance‐based Ew models. Our results indicate that the diurnal variation of Gc is dominated by net radiation and peaks around noon, while the seasonal variation of Gc is mainly controlled by air temperature and peaks in spring. In contrast, the daily variation of Gc is subjective to a confluence of factors—net radiation, wind speed, and relative humidity—displaying more stochasticity than that on the other two time scales. We also found that the importance of Gc for Ew estimates decreases as the time scale extends. Compared to the two models disregarding Gc, considering the effect of Gc enhances the average Kling‐Gupta efficiency (KGE) values of the two models by 1.33, 0.42, and 0.08 on the three time scales, respectively. Overall, this study highlights the importance of time scales in evaluating the effect of Gc on Ew estimates.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49526451","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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