High temperature extremes accompanied by drought have led to serious ramifications for environmental and socio-economic systems. Thus, improving the predictability of heat-wave events is a high priority. One key to achieving this is to better understand land-atmosphere interactions. Recent studies have documented a hypersensitive regime in the soil moisture-temperature relationship: when soil dries below a critical low threshold, called the soil moisture breakpoint, air temperatures increase at a greater rate as soil moisture declines. Whether such a hypersensitive regime is rooted in land surface processes and whether this soil moisture breakpoint corresponds to a known plant critical value, the permanent wilting point (WP), below which latent heat flux almost ceases, remains unclear. In this study, we explore the mechanisms linking low soil moisture to high air temperatures. From in situ observations, we confirm that the hypersensitive regime acts throughout the chain of energy processes from land to atmosphere. A simple energy-balance model indicates that the hypersensitive regime occurs when there is a dramatic drop in evaporative cooling, which happens when soil moisture dries toward the permanent WP, suggesting that the soil moisture breakpoint is slightly above the permanent WP. Precisely how a model represents the relationship between evapotranspiration and soil moisture is found to be essential to describe the occurrence of the hypersensitive regime. Thus, we advocate that weather and climate models should ensure a realistic representation of land-atmosphere interactions to obtain reliable forecasts of extremes and climate projections, aiding the assessment of heatwave vulnerability and adaptation.
{"title":"Exploring the Mechanisms of the Soil Moisture-Air Temperature Hypersensitive Coupling Regime","authors":"Hsin Hsu, Paul A. Dirmeyer, Eunkyo Seo","doi":"10.1029/2023wr036490","DOIUrl":"https://doi.org/10.1029/2023wr036490","url":null,"abstract":"High temperature extremes accompanied by drought have led to serious ramifications for environmental and socio-economic systems. Thus, improving the predictability of heat-wave events is a high priority. One key to achieving this is to better understand land-atmosphere interactions. Recent studies have documented a hypersensitive regime in the soil moisture-temperature relationship: when soil dries below a critical low threshold, called the soil moisture breakpoint, air temperatures increase at a greater rate as soil moisture declines. Whether such a hypersensitive regime is rooted in land surface processes and whether this soil moisture breakpoint corresponds to a known plant critical value, the permanent wilting point (WP), below which latent heat flux almost ceases, remains unclear. In this study, we explore the mechanisms linking low soil moisture to high air temperatures. From in situ observations, we confirm that the hypersensitive regime acts throughout the chain of energy processes from land to atmosphere. A simple energy-balance model indicates that the hypersensitive regime occurs when there is a dramatic drop in evaporative cooling, which happens when soil moisture dries toward the permanent WP, suggesting that the soil moisture breakpoint is slightly above the permanent WP. Precisely how a model represents the relationship between evapotranspiration and soil moisture is found to be essential to describe the occurrence of the hypersensitive regime. Thus, we advocate that weather and climate models should ensure a realistic representation of land-atmosphere interactions to obtain reliable forecasts of extremes and climate projections, aiding the assessment of heatwave vulnerability and adaptation.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141489684","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}
Yingqi Zhang, Yiwen Han, Na Wen, Junyu Qi, Xiaoyu Zhang, Gary W. Marek, Raghavan Srinivasan, Puyu Feng, De Li Liu, Kelin Hu, Yong Chen
Nitrogen (N) loss is a significant source of water quality pollution in alluvial watersheds. However, the mechanisms linking N loss and elevated CO2 concentration (eCO2) are not well recognized. In this study, we comprehensively calibrated the SWAT model equipped with a dynamic CO2 input and response module to investigate the response mechanisms between multiform N losses and eCO2 in a representative large‐scale watershed. Results revealed nitrate loss under eCO2 exceeding 100% in some upstream zones under the SSP5‐8.5 scenario (P < 0.05) compared to the constant CO2 concentration. This was directly related to the great increase in hydrological variables, which were the carriers of N losses, and the intensive inputs of N fertilizer. Results also found that nitrate leaching was greater than the other two processes for future periods, peaking at 309.3%, as compared to the baseline period. The findings suggested reducing fertilizer inputs by 10%–20% was promising, especially for reducing nitrate loss through runoff and leaching by up to 17.7% and 12.2%. This study explored the mechanisms of increased N loss in response to eCO2 and provided scientific evidence for early warning and making decisions to improve water quality at a large watershed scale.
{"title":"Assessing the Response Mechanisms of Elevated CO2 Concentration on Various Forms of Nitrogen Losses in the Golden Corn Belt","authors":"Yingqi Zhang, Yiwen Han, Na Wen, Junyu Qi, Xiaoyu Zhang, Gary W. Marek, Raghavan Srinivasan, Puyu Feng, De Li Liu, Kelin Hu, Yong Chen","doi":"10.1029/2024wr037226","DOIUrl":"https://doi.org/10.1029/2024wr037226","url":null,"abstract":"Nitrogen (N) loss is a significant source of water quality pollution in alluvial watersheds. However, the mechanisms linking N loss and elevated CO2 concentration (eCO2) are not well recognized. In this study, we comprehensively calibrated the SWAT model equipped with a dynamic CO2 input and response module to investigate the response mechanisms between multiform N losses and eCO2 in a representative large‐scale watershed. Results revealed nitrate loss under eCO2 exceeding 100% in some upstream zones under the SSP5‐8.5 scenario (P < 0.05) compared to the constant CO2 concentration. This was directly related to the great increase in hydrological variables, which were the carriers of N losses, and the intensive inputs of N fertilizer. Results also found that nitrate leaching was greater than the other two processes for future periods, peaking at 309.3%, as compared to the baseline period. The findings suggested reducing fertilizer inputs by 10%–20% was promising, especially for reducing nitrate loss through runoff and leaching by up to 17.7% and 12.2%. This study explored the mechanisms of increased N loss in response to eCO2 and provided scientific evidence for early warning and making decisions to improve water quality at a large watershed scale.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141703509","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}
Optimizing empirical baseflow filters using environmental tracers (e.g., specific electrical conductance (SEC), turbidity) is an effective and efficient way to quantify the contribution of baseflow to total flow. To execute this baseflow separation, three key components are needed: The tracer, the method to estimate tracer concentration in different flow components, and the empirical baseflow filter. However, a comprehensive evaluation of the various combinations of these components, especially with a large sample of catchments, is currently lacking in the literature. Therefore, our study assembles 16 hybrid baseflow filters from two tracers, two concentration estimation methods, and four empirical baseflow filters, and evaluated their performance in baseflow separation and producing two long-term baseflow signatures for 1,100 catchments in the Contiguous United States. Our results suggest that SEC is a superior tracer to turbidity for baseflow separation. Additionally, using monthly maximum and minimum values to represent tracer concentration in flow components produces better separation than using a power function relationship between flow rate and concentration. The four empirical baseflow filters offer a similar level of performance, regardless of the other options used. Yet, some of these filters produce inconsistent results in calculating the baseflow signatures for the catchments. Our analysis shed light on the optimization of hybrid baseflow filters for the accurate quantification of baseflow contribution.
{"title":"Optimal Baseflow Separation Through Chemical Mass Balance: Comparing the Usages of Two Tracers, Two Concentration Estimation Methods, and Four Baseflow Filters","authors":"Yiwen Mei, Dagang Wang, Jinxin Zhu, Guoping Tang, Chenkai Cai, Xinyi Shen, Yi Hong, Xinxuan Zhang","doi":"10.1029/2023wr036386","DOIUrl":"https://doi.org/10.1029/2023wr036386","url":null,"abstract":"Optimizing empirical baseflow filters using environmental tracers (e.g., specific electrical conductance (SEC), turbidity) is an effective and efficient way to quantify the contribution of baseflow to total flow. To execute this baseflow separation, three key components are needed: The tracer, the method to estimate tracer concentration in different flow components, and the empirical baseflow filter. However, a comprehensive evaluation of the various combinations of these components, especially with a large sample of catchments, is currently lacking in the literature. Therefore, our study assembles 16 hybrid baseflow filters from two tracers, two concentration estimation methods, and four empirical baseflow filters, and evaluated their performance in baseflow separation and producing two long-term baseflow signatures for 1,100 catchments in the Contiguous United States. Our results suggest that SEC is a superior tracer to turbidity for baseflow separation. Additionally, using monthly maximum and minimum values to represent tracer concentration in flow components produces better separation than using a power function relationship between flow rate and concentration. The four empirical baseflow filters offer a similar level of performance, regardless of the other options used. Yet, some of these filters produce inconsistent results in calculating the baseflow signatures for the catchments. Our analysis shed light on the optimization of hybrid baseflow filters for the accurate quantification of baseflow contribution.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141489736","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}
C. M. Breen, W. Currier, C. Vuyovich, Z. Miao, L. Prugh
Snow pole time‐lapse photography, in which a snow pole of a known height is installed in front of a camera and photographed repeatedly over the course of a snow season, allows a large network of sites to be established relatively quickly and affordably. However, current approaches for extracting snow depth from snow poles typically relies on time intensive manual photo processing. By integrating computer vision algorithms with snow pole photography, we present a method that uses a keypoint detection model to automatically observe snow height across a network of sites. At 20 snow pole locations from Grand Mesa, CO (n = 9,722 images), our model successfully predicts the top and bottom of the pole with a mean absolute error (MAE) of 1.30 cm. To assess model generalizability, we tested the model on 12 sites in Washington State (n = 1,770 images). When the Colorado trained model was fine‐tuned using a subset of Washington images, the model predicted snow depth with a MAE of 4.0 cm. Best performance was achieved when both data sets were included during training, with a MAE of 2.05 cm for Colorado images and a MAE of 1.14 cm for Washington images. We demonstrate that, especially when trained using a subset of site‐specific data, a keypoint detection model can accelerate snow pole automation. This algorithm brings the hydrology community one step closer to a generalized snow pole detection model, and we call for a future model that integrates across time‐lapse images from additional locations.
雪杆延时摄影是指将已知高度的雪杆安装在相机前，在一个雪季中反复拍摄，这样可以相对快速、经济地建立一个庞大的站点网络。然而，目前从雪柱中提取雪深的方法通常依赖于耗时的人工照片处理。通过将计算机视觉算法与雪柱摄影相结合，我们提出了一种使用关键点检测模型来自动观测整个站点网络的雪高的方法。在科罗拉多州大梅萨的 20 个雪柱位置（n = 9722 张图片），我们的模型成功预测了雪柱的顶部和底部，平均绝对误差 (MAE) 为 1.30 厘米。为了评估模型的通用性，我们在华盛顿州的 12 个地点（n = 1,770 幅图像）测试了该模型。当使用华盛顿州的子集图像对科罗拉多州训练有素的模型进行微调时，该模型预测雪深的 MAE 为 4.0 厘米。如果在训练过程中同时使用两个数据集，则可获得最佳性能，科罗拉多州图像的 MAE 为 2.05 厘米，华盛顿州图像的 MAE 为 1.14 厘米。我们证明，尤其是在使用特定地点的数据子集进行训练时，关键点检测模型可以加速雪极自动化。该算法使水文界离通用雪极检测模型更近了一步，我们呼吁未来的模型能整合更多地点的延时图像。
{"title":"Snow Depth Extraction From Time‐Lapse Imagery Using a Keypoint Deep Learning Model","authors":"C. M. Breen, W. Currier, C. Vuyovich, Z. Miao, L. Prugh","doi":"10.1029/2023wr036682","DOIUrl":"https://doi.org/10.1029/2023wr036682","url":null,"abstract":"Snow pole time‐lapse photography, in which a snow pole of a known height is installed in front of a camera and photographed repeatedly over the course of a snow season, allows a large network of sites to be established relatively quickly and affordably. However, current approaches for extracting snow depth from snow poles typically relies on time intensive manual photo processing. By integrating computer vision algorithms with snow pole photography, we present a method that uses a keypoint detection model to automatically observe snow height across a network of sites. At 20 snow pole locations from Grand Mesa, CO (n = 9,722 images), our model successfully predicts the top and bottom of the pole with a mean absolute error (MAE) of 1.30 cm. To assess model generalizability, we tested the model on 12 sites in Washington State (n = 1,770 images). When the Colorado trained model was fine‐tuned using a subset of Washington images, the model predicted snow depth with a MAE of 4.0 cm. Best performance was achieved when both data sets were included during training, with a MAE of 2.05 cm for Colorado images and a MAE of 1.14 cm for Washington images. We demonstrate that, especially when trained using a subset of site‐specific data, a keypoint detection model can accelerate snow pole automation. This algorithm brings the hydrology community one step closer to a generalized snow pole detection model, and we call for a future model that integrates across time‐lapse images from additional locations.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":4.6,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141692141","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 Tibetan Plateau is well-known for its expansive wetland environments. Hydric soils, a fundamental component of these environments, exhibit diverse hydraulic characteristics attributable to their varied botanical and mineralogical composition and their inherent porous structures. Nonetheless, research on the hydraulic properties of such soils in Tibet remains notably underrepresented relative to European and Canadian regions. Consequently, in this study, we evaluate the effectiveness of different unsaturated hydraulic schemes in equilibrium and examine the parameter uncertainty of 14 undisturbed samples collected from four soligenous wetlands. The findings suggest that both the van Genuchten and Kosugi functions, when integrated with the Peters-Iden-Durner (PDI) model, yield a nearly consistent fit to experimental observations and demonstrate strong identifiability of parameters. This indicates that the PDI model can accurately characterize hydraulic properties across the complete moisture range of hydric soils. Analysis of samples with a low clay content and no sphagnum suggests that the intertwined, twisted, and hollow residues of herbaceous vascular tissues do not create a distinct, independent macro-pore system. Therefore, the unimodal scheme integrating the PDI model is adequate. However, for samples that exhibit nonmonotonicity of the first-order derivative of the retention curve, such as uncompacted samples containing sphagnum or samples rich in clay, the integration of the PDI model into the bimodal scheme boosts accuracy while having almost negligible impact on identifiability. The varied observed hydraulic properties of only 14 samples underscore the necessity for extensive hydric-soil sampling and hydraulic analysis across the expansive and varied wetland landscapes on the Tibetan Plateau.
{"title":"Hydraulic Properties Within the Complete Moisture Range of Hydric Soil on the Tibetan Plateau","authors":"X. Wang, Z. L. Wang, W. Yang, R. Liu","doi":"10.1029/2023wr036018","DOIUrl":"https://doi.org/10.1029/2023wr036018","url":null,"abstract":"The Tibetan Plateau is well-known for its expansive wetland environments. Hydric soils, a fundamental component of these environments, exhibit diverse hydraulic characteristics attributable to their varied botanical and mineralogical composition and their inherent porous structures. Nonetheless, research on the hydraulic properties of such soils in Tibet remains notably underrepresented relative to European and Canadian regions. Consequently, in this study, we evaluate the effectiveness of different unsaturated hydraulic schemes in equilibrium and examine the parameter uncertainty of 14 undisturbed samples collected from four soligenous wetlands. The findings suggest that both the van Genuchten and Kosugi functions, when integrated with the Peters-Iden-Durner (PDI) model, yield a nearly consistent fit to experimental observations and demonstrate strong identifiability of parameters. This indicates that the PDI model can accurately characterize hydraulic properties across the complete moisture range of hydric soils. Analysis of samples with a low clay content and no sphagnum suggests that the intertwined, twisted, and hollow residues of herbaceous vascular tissues do not create a distinct, independent macro-pore system. Therefore, the unimodal scheme integrating the PDI model is adequate. However, for samples that exhibit nonmonotonicity of the first-order derivative of the retention curve, such as uncompacted samples containing sphagnum or samples rich in clay, the integration of the PDI model into the bimodal scheme boosts accuracy while having almost negligible impact on identifiability. The varied observed hydraulic properties of only 14 samples underscore the necessity for extensive hydric-soil sampling and hydraulic analysis across the expansive and varied wetland landscapes on the Tibetan Plateau.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141489688","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}
Gustavo Facincani Dourado, David E. Rheinheimer, John T. Abaztoglou, Joshua H. Viers
Inter-annual precipitation in California is highly variable, and future projections indicate an increase in the intensity and frequency of hydroclimatic “whiplash.” Understanding the implications of these shocks on California's water system and its degree of resiliency is critical from a planning perspective. Therefore, we quantify the resilience of reservoir services provided by water and hydropower systems in four basins in the western Sierra Nevada. Using downscaled runoff from 10 climate model outputs, we generated 200 synthetic hydrologic whiplash sequences of alternating dry and wet years to represent a wide range of extremes and transitional conditions used as inputs to a water system simulation model. Sequences were derived from upper (wet) and lower (dry) quintiles of future streamflow projections (2030–2060). Results show that carryover storage was negatively affected in all basins, particularly in those with lower storage capacity. All basins experienced negative impacts on hydropower generation, with losses ranging from 5% to nearly 90%. Reservoir sizes and inflexible operating rules are a particular challenge for flood control, as in extremely wet years spillage averaged nearly the annual basins' total discharge. The reliability of environmental flows and agricultural deliveries varied depending on the basin, intensity, and duration of whiplash sequences. Overall, wet years temporarily rebound negative drought effects, and greater storage capacity results in higher reliability and resiliency, and lesser volatility in services. We highlight potential policy changes to improve flexibility, increase resilience, and better equip managers to face challenges posed by whiplash while meeting human and environmental needs.
{"title":"Stress Testing California's Hydroclimatic Whiplash: Potential Challenges, Trade-Offs and Adaptations in Water Management and Hydropower Generation","authors":"Gustavo Facincani Dourado, David E. Rheinheimer, John T. Abaztoglou, Joshua H. Viers","doi":"10.1029/2023wr035966","DOIUrl":"https://doi.org/10.1029/2023wr035966","url":null,"abstract":"Inter-annual precipitation in California is highly variable, and future projections indicate an increase in the intensity and frequency of hydroclimatic “whiplash.” Understanding the implications of these shocks on California's water system and its degree of resiliency is critical from a planning perspective. Therefore, we quantify the resilience of reservoir services provided by water and hydropower systems in four basins in the western Sierra Nevada. Using downscaled runoff from 10 climate model outputs, we generated 200 synthetic hydrologic whiplash sequences of alternating dry and wet years to represent a wide range of extremes and transitional conditions used as inputs to a water system simulation model. Sequences were derived from upper (wet) and lower (dry) quintiles of future streamflow projections (2030–2060). Results show that carryover storage was negatively affected in all basins, particularly in those with lower storage capacity. All basins experienced negative impacts on hydropower generation, with losses ranging from 5% to nearly 90%. Reservoir sizes and inflexible operating rules are a particular challenge for flood control, as in extremely wet years spillage averaged nearly the annual basins' total discharge. The reliability of environmental flows and agricultural deliveries varied depending on the basin, intensity, and duration of whiplash sequences. Overall, wet years temporarily rebound negative drought effects, and greater storage capacity results in higher reliability and resiliency, and lesser volatility in services. We highlight potential policy changes to improve flexibility, increase resilience, and better equip managers to face challenges posed by whiplash while meeting human and environmental needs.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141489734","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}
Chenglong Cao, Jiangjiang Zhang, Wei Gan, Tongchao Nan, Chunhui Lu
Seawater intrusion (SI) poses a substantial threat to water security in coastal regions, where numerical models play a pivotal role in supporting groundwater management and protection. However, the inherent heterogeneity of coastal aquifers introduces significant uncertainties into SI predictions, potentially diminishing their effectiveness in management decisions. Data assimilation (DA) offers a solution by integrating various types of observational data with the model to characterize heterogeneous coastal aquifers. Traditional DA techniques, like ensemble smoother using the Kalman formula (ESK) and Markov chain Monte Carlo, face challenges when confronted with the non-linearity, non-Gaussianity, and high-dimensionality issues commonly encountered in aquifer characterization. In this study, we introduce a novel DA approach rooted in deep learning (DL), referred to as ESDL, aimed at effectively characterizing coastal aquifers with varying levels of heterogeneity. We systematically investigate a range of factors that impact the performance of ESDL, including the number and types of observations, the degree of aquifer heterogeneity, the structure and training options of the DL models. Our findings reveal that ESDL excels in characterizing heterogeneous aquifers under non-linear and non-Gaussian conditions. Comparison between ESDL and ESK under different experimentation settings underscores the robustness of ESDL. Conversely, in certain scenarios, ESK displays noticeable biases in the characterization results, especially when measurement data from non-linear and discontinuous processes are used. To optimize the efficacy of ESDL, attention must be given to the design of the DL model and the selection of observational data, which are crucial to ensure the universal applicability of this DA method.
{"title":"A Deep Learning-Based Data Assimilation Approach to Characterizing Coastal Aquifers Amid Non-Linearity and Non-Gaussianity Challenges","authors":"Chenglong Cao, Jiangjiang Zhang, Wei Gan, Tongchao Nan, Chunhui Lu","doi":"10.1029/2023wr036899","DOIUrl":"https://doi.org/10.1029/2023wr036899","url":null,"abstract":"Seawater intrusion (SI) poses a substantial threat to water security in coastal regions, where numerical models play a pivotal role in supporting groundwater management and protection. However, the inherent heterogeneity of coastal aquifers introduces significant uncertainties into SI predictions, potentially diminishing their effectiveness in management decisions. Data assimilation (DA) offers a solution by integrating various types of observational data with the model to characterize heterogeneous coastal aquifers. Traditional DA techniques, like ensemble smoother using the Kalman formula (ES<sub>K</sub>) and Markov chain Monte Carlo, face challenges when confronted with the non-linearity, non-Gaussianity, and high-dimensionality issues commonly encountered in aquifer characterization. In this study, we introduce a novel DA approach rooted in deep learning (DL), referred to as ES<sub>DL</sub>, aimed at effectively characterizing coastal aquifers with varying levels of heterogeneity. We systematically investigate a range of factors that impact the performance of ES<sub>DL</sub>, including the number and types of observations, the degree of aquifer heterogeneity, the structure and training options of the DL models. Our findings reveal that ES<sub>DL</sub> excels in characterizing heterogeneous aquifers under non-linear and non-Gaussian conditions. Comparison between ES<sub>DL</sub> and ES<sub>K</sub> under different experimentation settings underscores the robustness of ES<sub>DL</sub>. Conversely, in certain scenarios, ES<sub>K</sub> displays noticeable biases in the characterization results, especially when measurement data from non-linear and discontinuous processes are used. To optimize the efficacy of ES<sub>DL</sub>, attention must be given to the design of the DL model and the selection of observational data, which are crucial to ensure the universal applicability of this DA method.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141489809","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 soil freezing characteristic curve (SFCC) plays a crucial role in investigating the soil freezing-thawing process. Due to the challenges associated with measuring the SFCC, there is a shortage of high-quality or rigorous test results with sufficient metadata to be effectively used for applications. Current researchers typically conduct freezing tests to measure the SFCC and assume a singular SFCC when studying the freezing-thawing process of soils, although limited studies indicated that there is a hysteresis during the freezing and thawing process. In this paper, a series of freezing-thawing tests were performed to assess the SFCC, utilizing a precise nuclear magnetic resonance apparatus. The test results reveal a hysteresis between the SFCC obtained from the freezing process and that from the thawing process. Through analyzing the test results, the hysteresis mechanism of the SFCC is attributed to supercooling. Supercooling inhibits initial pore ice formation during freezing, causing a drastic liquid water-ice phase change once supercooling ends. Despite being considered closely related, the hysteresis of the SFCC differs from the soil water characteristic curve (SWCC), and the models used to simulate the hysteresis of SWCC cannot directly be used. To address the impact of supercooling on soil freezing-thawing hysteresis, a novel theoretical model is proposed. Comparisons between the measured and predicted results affirm the validity of the proposed model.
{"title":"Freezing-Thawing Hysteretic Behavior of Soils","authors":"Jidong Teng, Antai Dong, Sheng Zhang, Xiong Zhang, Daichao Sheng","doi":"10.1029/2024wr037280","DOIUrl":"https://doi.org/10.1029/2024wr037280","url":null,"abstract":"The soil freezing characteristic curve (SFCC) plays a crucial role in investigating the soil freezing-thawing process. Due to the challenges associated with measuring the SFCC, there is a shortage of high-quality or rigorous test results with sufficient metadata to be effectively used for applications. Current researchers typically conduct freezing tests to measure the SFCC and assume a singular SFCC when studying the freezing-thawing process of soils, although limited studies indicated that there is a hysteresis during the freezing and thawing process. In this paper, a series of freezing-thawing tests were performed to assess the SFCC, utilizing a precise nuclear magnetic resonance apparatus. The test results reveal a hysteresis between the SFCC obtained from the freezing process and that from the thawing process. Through analyzing the test results, the hysteresis mechanism of the SFCC is attributed to supercooling. Supercooling inhibits initial pore ice formation during freezing, causing a drastic liquid water-ice phase change once supercooling ends. Despite being considered closely related, the hysteresis of the SFCC differs from the soil water characteristic curve (SWCC), and the models used to simulate the hysteresis of SWCC cannot directly be used. To address the impact of supercooling on soil freezing-thawing hysteresis, a novel theoretical model is proposed. Comparisons between the measured and predicted results affirm the validity of the proposed model.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141463624","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}
Fuhai Sun, Bo Xiao, Giora J. Kidron, Joshua Heitman
Soil surface cover is one of the most critical factors affecting soil water vapor transport, especially in drylands where water is limited, and the water movement occurs predominantly in the form of vapor instead of liquid. Biocrusts are an important living ground cover of dryland soils and play a vital role in modifying near-surface soil properties and maintaining soil structure. The role of biocrusts in mediating soil water vapor transport during daytime water evaporation and nighttime condensation remains unclear. We investigated the differences in vapor diffusion properties, vapor adsorption capacity, and water evaporation between bare soil and three types of biocrusts (cyanobacterial, cyanobacterial-moss mixed, and moss crusts) in the Chinese Loess Plateau. Our results showed that the three types of biocrusts had 5%–39% higher vapor diffusivity than bare soil. At the same level of ambient relative humidity and temperature, the initial vapor adsorption rates and cumulative adsorption amounts of the biocrusts were 10%–70% and 11%–85% higher than those of bare soil, respectively. Additionally, the late-stage evaporation rate of cyanobacterial-, cyanobacterial-moss mixed-, and moss-biocrusts were 31%–217%, 79%–492%, and 146%–775% higher than that of bare soil, respectively. The effect of biocrusts on increasing vapor transport properties was attributed to the higher soil porosity, clay content, and specific surface area induced by the biocrust layer. All of these modifications caused by biocrusts on surface soil vapor transport properties suggest that biocrusts play a vital role in reshaping surface soil water and energy balance in drylands.
{"title":"Biocrusts Critical Regulation of Soil Water Vapor Transport (Diffusion, Sorption, and Late-Stage Evaporation) in Drylands","authors":"Fuhai Sun, Bo Xiao, Giora J. Kidron, Joshua Heitman","doi":"10.1029/2023wr036520","DOIUrl":"https://doi.org/10.1029/2023wr036520","url":null,"abstract":"Soil surface cover is one of the most critical factors affecting soil water vapor transport, especially in drylands where water is limited, and the water movement occurs predominantly in the form of vapor instead of liquid. Biocrusts are an important living ground cover of dryland soils and play a vital role in modifying near-surface soil properties and maintaining soil structure. The role of biocrusts in mediating soil water vapor transport during daytime water evaporation and nighttime condensation remains unclear. We investigated the differences in vapor diffusion properties, vapor adsorption capacity, and water evaporation between bare soil and three types of biocrusts (cyanobacterial, cyanobacterial-moss mixed, and moss crusts) in the Chinese Loess Plateau. Our results showed that the three types of biocrusts had 5%–39% higher vapor diffusivity than bare soil. At the same level of ambient relative humidity and temperature, the initial vapor adsorption rates and cumulative adsorption amounts of the biocrusts were 10%–70% and 11%–85% higher than those of bare soil, respectively. Additionally, the late-stage evaporation rate of cyanobacterial-, cyanobacterial-moss mixed-, and moss-biocrusts were 31%–217%, 79%–492%, and 146%–775% higher than that of bare soil, respectively. The effect of biocrusts on increasing vapor transport properties was attributed to the higher soil porosity, clay content, and specific surface area induced by the biocrust layer. All of these modifications caused by biocrusts on surface soil vapor transport properties suggest that biocrusts play a vital role in reshaping surface soil water and energy balance in drylands.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141463716","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}
Tristan Babey, Zach Perzan, Sam Pierce, Brian Rogers, Lijing Wang, Rosemary W. H. Carroll, John R. Bargar, Kristin Boye, Kate Maher
In mountainous watersheds, floodplain sediments are typically characterized by gravel bed layers capped by an overlying soil unit that serves as a hotspot for biogeochemical reactivity. However, the influence of soil biogeochemistry on gravel bed underflow composition remains unclear, especially during hydrological transitions that alter the vertical connectivity between overlaying soils and the underlying gravel bed. This study investigates these dynamics by measuring hydraulic gradients and water compositions over three hydrological years in a typical mountainous, low-order stream floodplain in the Upper Colorado River Basin. Results indicate that the timing of hydrological conditions strongly influences the vertical exchanges that control water quality. Specifically, during flooding events such as beaver ponding, that induce downward flushing of the soil, anoxic conditions prevalent in the biogeochemically active soil are transferred downstream via gravel bed underflow. Conversely, snowmelt and drought conditions increase oxic conditions in the gravel bed due to diminished hydrological connectivity with the overlying soil. To compare water quality response to hydrological transitions across similar floodplain environments, we propose a conceptual model that quantifies the inundation-induced flushing of soil porewater to measure solute exchange efficiency with the gravel bed solute convergence efficiency (SCE). This model provides a framework for quantifying biogeochemical processes in hydrological underflow systems, which is critical for water and elemental budgets in these globally important mountainous ecosystems.
{"title":"Mountainous Floodplain Connectivity in Response to Hydrological Transitions","authors":"Tristan Babey, Zach Perzan, Sam Pierce, Brian Rogers, Lijing Wang, Rosemary W. H. Carroll, John R. Bargar, Kristin Boye, Kate Maher","doi":"10.1029/2024wr037162","DOIUrl":"https://doi.org/10.1029/2024wr037162","url":null,"abstract":"In mountainous watersheds, floodplain sediments are typically characterized by gravel bed layers capped by an overlying soil unit that serves as a hotspot for biogeochemical reactivity. However, the influence of soil biogeochemistry on gravel bed underflow composition remains unclear, especially during hydrological transitions that alter the vertical connectivity between overlaying soils and the underlying gravel bed. This study investigates these dynamics by measuring hydraulic gradients and water compositions over three hydrological years in a typical mountainous, low-order stream floodplain in the Upper Colorado River Basin. Results indicate that the timing of hydrological conditions strongly influences the vertical exchanges that control water quality. Specifically, during flooding events such as beaver ponding, that induce downward flushing of the soil, anoxic conditions prevalent in the biogeochemically active soil are transferred downstream via gravel bed underflow. Conversely, snowmelt and drought conditions increase oxic conditions in the gravel bed due to diminished hydrological connectivity with the overlying soil. To compare water quality response to hydrological transitions across similar floodplain environments, we propose a conceptual model that quantifies the inundation-induced flushing of soil porewater to measure solute exchange efficiency with the gravel bed solute convergence efficiency (SCE). This model provides a framework for quantifying biogeochemical processes in hydrological underflow systems, which is critical for water and elemental budgets in these globally important mountainous ecosystems.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141489821","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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