Water Resources Research最新文献_第10页

Knowledge Extraction via Machine Learning Guides a Topology-Based Permeability Prediction Model 通过机器学习提取知识，为基于拓扑的渗透性预测模型提供指导

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2024-07-12 DOI: 10.1029/2024wr037124

Jia Zhang, Gang Ma, Zhibing Yang, Jiangzhou Mei, Daren Zhang, Wei Zhou, Xiaolin Chang

{"title":"Knowledge Extraction via Machine Learning Guides a Topology-Based Permeability Prediction Model","authors":"Jia Zhang, Gang Ma, Zhibing Yang, Jiangzhou Mei, Daren Zhang, Wei Zhou, Xiaolin Chang","doi":"10.1029/2024wr037124","DOIUrl":"https://doi.org/10.1029/2024wr037124","url":null,"abstract":"The complexity and heterogeneity of pore structure present significant challenges in accurate permeability estimation. Commonly used empirical formulas neglect its microscopic and topological characteristics, thus lacking accuracy and adaptability. While machine learning (ML) and deep learning (DL) models demonstrate promising performance, but encounter challenges of data availability, computational cost, and model interpretability. The present study aims to develop a more robust and accurate permeability prediction model via knowledge extraction from ML model. We first establish an ML model between permeability and the geometry-topology characteristics of porous media using Extreme Gradient Boosting (XGBoost) algorithm. The data set used to fit ML model is prepared from 458 samples of different types of porous media. Using the SHapley Additive exPlanations (SHAP) value, the influence of each feature on permeability prediction is quantified. It is found that the closeness centrality (topology feature), tortuosity, porosity (macroscopic features) and throat diameter, throat length, pore diameter (pore network features) are vital for permeability prediction. Guided by partial dependence calculation, the unknown function relationship between permeability and the top six important features is established. The novel permeability prediction model incorporating topology feature improves the prediction accuracy and demonstrates strong applicability across diverse data sets. This new model presents an optimal balance between simplicity and performance, rendering it a compelling alternative for permeability prediction in porous media. The research provides a novel referable framework of knowledge extraction via ML to reveal the important features and establish the potential relationship that can be extended and applied in other research fields.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141618440","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}

引用次数: 0

The Fragility of Bedform-Induced Hyporheic Zones: Exploring Impacts of Dynamic Groundwater Table Fluctuations 床形诱发的低水位带的脆弱性：探索地下水位动态波动的影响

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2024-07-12 DOI: 10.1029/2023wr036706

L. Wu, J. D. Gomez-Velez, L. Li, K. C. Carroll

{"title":"The Fragility of Bedform-Induced Hyporheic Zones: Exploring Impacts of Dynamic Groundwater Table Fluctuations","authors":"L. Wu, J. D. Gomez-Velez, L. Li, K. C. Carroll","doi":"10.1029/2023wr036706","DOIUrl":"https://doi.org/10.1029/2023wr036706","url":null,"abstract":"Hyporheic zones are commonly regarded as resilient and enduring interfaces between groundwater and surface water in river corridors. In particular, bedform-induced advective pumping hyporheic exchange (bedform-induced exchange) is often perceived as a relatively persistent mechanism in natural river systems driving water, solutes, and energy exchanges between the channel and its surrounding streambed sediments. Numerous studies have been based on this presumption. To evaluate the persistence of hyporheic zones under varying hydrologic conditions, we use a multi-physics framework to model advective pumping bedform-induced hyporheic exchange in response to a series of seasonal- and event-scale groundwater table fluctuation scenarios, which lead to episodic river-aquifer disconnections and reconnections. Our results suggest that hyporheic exchange is not as ubiquitous as generally assumed. Instead, the bedform-induced hyporheic exchange is restricted to a narrow range of conditions characterized by minor river-groundwater head differences, is intermittent, and can be easily obliterated by minor losing groundwater conditions. These findings shed light on the fragility of bedform-induced hyporheic exchange and have important implications for biogeochemical transformations along river corridors.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141597381","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}

引用次数: 0

A Conceptual Framework to Assess Post-Wildfire Water Quality: State of the Science and Knowledge Gaps 评估野火后水质的概念框架：科学现状与知识差距

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2024-07-10 DOI: 10.1029/2023wr036260

Sarah M. Elliott, Michelle I. Hornberger, Donald O. Rosenberry, Rebecca J. Frus, Richard M. Webb

{"title":"A Conceptual Framework to Assess Post-Wildfire Water Quality: State of the Science and Knowledge Gaps","authors":"Sarah M. Elliott, Michelle I. Hornberger, Donald O. Rosenberry, Rebecca J. Frus, Richard M. Webb","doi":"10.1029/2023wr036260","DOIUrl":"https://doi.org/10.1029/2023wr036260","url":null,"abstract":"Wildfire substantially alters aquatic ecosystems by inducing moderate to catastrophic physical and chemical changes. However, the relations of environmental and watershed variables that drive those effects are complex. We present a Driver-Factor-Stressor-Effect (DFSE) conceptual framework to assess the current state of the science related to post-wildfire water-quality. We reviewed 64 peer-reviewed papers using the DFSE framework to identify drivers, factors, stressors, and effects associated with each study. A total of five drivers were identified and ranked according to their frequency of occurrence in the literature: atmospheric processes > fire characteristics > ecologic processes and characteristics > land surface characteristics > soil characteristics. Commonly reported stressors include increased nutrients, runoff, and sediment transport. Furthermore, although several different factors have been used at least once to explain water-quality effects, relatively few factors outside of precipitation and fire characteristics are frequently studied. We identified several gaps indicating the need for long-term monitoring, multi-factor studies, consideration of organic contaminants, consideration of groundwater, and inclusion of soil characteristics. This assessment expands on other reviews and meta-analyses by exploring causal linkages between influential variables and overall effects in post-wildfire watersheds. Information gathered from our assessment and the framework itself can be used to inform future monitoring plans and as a guide for modeling efforts focused on better understanding specific processes or to mitigate potential risks of post-wildfire water quality.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141597380","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}

引用次数: 0

Congo Basin Water Balance and Terrestrial Fluxes Inferred From Satellite Observations of the Isotopic Composition of Water Vapor 从卫星观测水蒸气同位素组成推断的刚果盆地水平衡和陆地通量

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2024-07-10 DOI: 10.1029/2023wr035092

Sarah Worden, A. Anthony Bloom, John Worden, Paul Levine, Mingjie Shi, Rong Fu

{"title":"Congo Basin Water Balance and Terrestrial Fluxes Inferred From Satellite Observations of the Isotopic Composition of Water Vapor","authors":"Sarah Worden, A. Anthony Bloom, John Worden, Paul Levine, Mingjie Shi, Rong Fu","doi":"10.1029/2023wr035092","DOIUrl":"https://doi.org/10.1029/2023wr035092","url":null,"abstract":"Large spatio-temporal gradients in the Congo basin vegetation and rainfall are observed. However, its water-balance (evapotranspiration minus precipitation, or ET − P) is typically measured at basin-scales, limited primarily by river-discharge data, spatial resolution of terrestrial water storage measurements, and poorly constrained ET. We use observations of the isotopic composition of water vapor to quantify the spatio-temporal variability of net surface water fluxes across the Congo Basin between 2003 and 2018. These data are calibrated at basin scale using satellite gravity and total Congo river discharge measurements and then used to estimate time-varying ET − P over four quadrants representing the Congo Basin, providing first estimates of this kind for the region. We find that the multi-year record, seasonality, and interannual variability of ET − P from both the isotopes and the gravity/river discharge based estimates are consistent. Additionally, we use precipitation and gravity-based estimates with our water vapor isotope-based ET − P to calculate time and space averaged ET and net river discharge within the Congo Basin. These quadrant-scale moisture flux estimates indicate (a) substantial recycling of moisture in the Congo Basin (temporally and spatially averaged ET/P > 70%), consistent with models and visible light-based ET estimates, and (b) net river outflow is largest in the Western Congo where there are more rivers and higher flow rates. Our results confirm the importance of ET in modulating the Congo water cycle relative to other water sources.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141588793","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}

引用次数: 0

Investigating the Intense Sediment Load by Dam-Break Floods Using a Meshless Two-Phase Mathematical Model 利用无网格两相数学模型研究溃坝洪水造成的强沉积负荷

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2024-07-10 DOI: 10.1029/2023wr035399

Xiafei Guan, Kailun Hu, Xin Chen, Junliang Gao, Huabin Shi

{"title":"Investigating the Intense Sediment Load by Dam-Break Floods Using a Meshless Two-Phase Mathematical Model","authors":"Xiafei Guan, Kailun Hu, Xin Chen, Junliang Gao, Huabin Shi","doi":"10.1029/2023wr035399","DOIUrl":"https://doi.org/10.1029/2023wr035399","url":null,"abstract":"Extreme precipitation is increasing the risk of dam breaks and formation occurring debris dams. Accurate prediction of dam-break wave propagation is critical to disaster emergency management. Intense bed-load transport by dam-break floods can result in a dramatic change of topography, which in turn may affect flood propagation. However, only a very few studies have investigated the thin intense bed-load layer under dam-break floods. In this paper, a meshless two-phase mathematical model is utilized to examine the water velocity, sediment velocity and volumetric fraction, and bed-load transport flux as well as energy dissipation in bed-load layer. The model is applied to simulate two- and three-dimensional laboratory experiments of dam-break wave over erodible beds. For the two-dimensional experiment, the relative root mean square errors in computed water surface are all below 3.60% and those in profiles of bed-load layer and static bed are mostly below 13.40%. For the three-dimensional case, the relative error in computed highest water level is lower than 5.9%. Sediment stream-wise velocity in bed-load layer follows a power-law vertical distribution while sediment volumetric fraction decreases linearly upwards. Accordingly, a formulation of the vertical distribution of bed-load transport flux, contradictory to the parabolic law in existing studies, is proposed. Most of the water mechanical energy transferred to the sediment is dissipated due to the shear stress in the intense bed-load layer while only a limit part is kept by the sediment grains. Energy dissipation due to sediment shear stress dominates the consumption of total mechanical energy in the two-phase system.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141578109","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}

引用次数: 0

Graph Neural Networks for Pressure Estimation in Water Distribution Systems 用于配水系统压力估算的图神经网络

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2024-07-09 DOI: 10.1029/2023wr036741

Huy Truong, Andrés Tello, Alexander Lazovik, Victoria Degeler

{"title":"Graph Neural Networks for Pressure Estimation in Water Distribution Systems","authors":"Huy Truong, Andrés Tello, Alexander Lazovik, Victoria Degeler","doi":"10.1029/2023wr036741","DOIUrl":"https://doi.org/10.1029/2023wr036741","url":null,"abstract":"Pressure and flow estimation in water distribution networks (WDNs) allows water management companies to optimize their control operations. For many years, mathematical simulation tools have been the most common approach to reconstructing an estimate of the WDNs hydraulics. However, pure physics-based simulations involve several challenges, for example, partially observable data, high uncertainty, and extensive manual calibration. Thus, data-driven approaches have gained traction to overcome such limitations. In this work, we combine physics-based modeling and graph neural networks (GNN), a data-driven approach, to address the pressure estimation problem. Our work has two main contributions. First, a training strategy that relies on random sensor placement making our GNN-based estimation model robust to unexpected sensor location changes. Second, a realistic evaluation protocol that considers real temporal patterns and noise injection to mimic the uncertainties intrinsic to real-world scenarios. As a result, a new state-of-the-art model, GAT with Residual Connections, for pressure estimation is available. Our model surpasses the performance of previous studies on several WDNs benchmarks, showing a reduction of absolute error of ≈40% on average.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141597379","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}

引用次数: 0

Berkeley-RWAWC: A New CYGNSS-Based Watermask Unveils Unique Observations of Seasonal Dynamics in the Tropics 伯克利-RWAWC：基于 CYGNSS 的新型水掩模揭示了热带地区独特的季节动态观测结果

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2024-07-09 DOI: 10.1029/2024wr037060

Tianjiao Pu, Cynthia Gerlein-Safdi, Ying Xiong, Mengze Li, Eric A. Kort, A. Anthony Bloom

{"title":"Berkeley-RWAWC: A New CYGNSS-Based Watermask Unveils Unique Observations of Seasonal Dynamics in the Tropics","authors":"Tianjiao Pu, Cynthia Gerlein-Safdi, Ying Xiong, Mengze Li, Eric A. Kort, A. Anthony Bloom","doi":"10.1029/2024wr037060","DOIUrl":"https://doi.org/10.1029/2024wr037060","url":null,"abstract":"The UC Berkeley Random Walk Algorithm WaterMask from CYGNSS (Berkeley-RWAWC) is a new data product designed to address the challenges of monitoring inundation in regions hindered by dense vegetation and cloud cover as is the case in most of the Tropics. The Cyclone Global Navigation Satellite System (CYGNSS) constellation provides data with a higher temporal repeat frequency compared to single-satellite systems, offering the potential for generating moderate spatial resolution inundation maps with improved temporal resolution while having the capability to penetrate clouds and vegetation. This paper details the development of a computer vision algorithm for inundation mapping over the entire CYGNSS domain (37.4°N–37.4°S). The sole reliance on CYGNSS data sets our method apart in the field, highlighting CYGNSS's indication of water existence. Berkeley-RWAWC provides monthly, low-latency inundation maps starting in August 2018 and across the CYGNSS latitude range, with a spatial resolution of 0.01° × 0.01°. Here we present our workflow and parameterization strategy, alongside a comparative analysis with established surface water data sets (SWAMPS, WAD2M) in four regions: the Amazon Basin, the Pantanal, the Sudd, and the Indo-Gangetic Plain. The comparisons reveal Berkeley-RWAWC's enhanced capability to detect seasonal variations, demonstrating its usefulness in studying tropical wetland hydrology. We also discuss potential sources of uncertainty and reasons for variations in inundation retrievals. Berkeley-RWAWC represents a valuable addition to environmental science, offering new insights into tropical wetland dynamics.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141578091","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}

引用次数: 0

Next Generation Public Supply Water Withdrawal Estimation for the Conterminous United States Using Machine Learning and Operational Frameworks 利用机器学习和操作框架估算美国大陆下一代公共供水取水量

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2024-07-09 DOI: 10.1029/2023wr036632

Ayman Alzraiee, Richard Niswonger, Carol Luukkonen, Josh Larsen, Donald Martin, Deidre Herbert, Cheryl Buchwald, Cheryl Dieter, Lisa Miller, Jana Stewart, Natalie Houston, Scott Paulinski, Kristen Valseth

{"title":"Next Generation Public Supply Water Withdrawal Estimation for the Conterminous United States Using Machine Learning and Operational Frameworks","authors":"Ayman Alzraiee, Richard Niswonger, Carol Luukkonen, Josh Larsen, Donald Martin, Deidre Herbert, Cheryl Buchwald, Cheryl Dieter, Lisa Miller, Jana Stewart, Natalie Houston, Scott Paulinski, Kristen Valseth","doi":"10.1029/2023wr036632","DOIUrl":"https://doi.org/10.1029/2023wr036632","url":null,"abstract":"Estimation of human water withdrawals is more important now than ever due to uncertain water supplies, population growth, and climate change. Fourteen percent of the total water withdrawal in the United States is used for public supply, typically including deliveries to domestic, commercial, and occasionally including industrial, irrigation, and thermoelectric water withdrawal. Stewards of water resources in the USA require estimates of water withdrawals to manage and plan for future demands and sustainable water supplies. This study compiled the most comprehensive conterminous United States water withdrawal data set to date and developed a machine learning framework for estimating public supply withdrawals and associated uncertainty for the period 2000–2020. The modeling approach provides service area resolution estimates to allow for annual and monthly water withdrawal estimation while incorporating a complex array of driving factors that include hydroclimatic, demographic, socioeconomic, geographic, and land use factors. Model results reveal highly variable and lognormally distributed per-capita water withdrawal, spanning from 30 to 650 gallons per capita per day (GPCD), across community, regional, and national scales, with pronounced seasonal variations. Analysis of estimated withdrawal trends indicates that the national annual average withdrawal experienced a decline at a rate of 0.58 GPCD/year during the period from 2000 to 2020. Model interpretation reveals a complex interplay between public supply withdrawal and key predictors, including population size, warm-season precipitation, counts of large buildings and houses, and areas of urban and commercial land use. The developed models can forecast future public supply driven by various climate, demographic, and socioeconomic scenarios.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141577997","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}

引用次数: 0

Inter-Regional Food-Water-Income Synergy Through Bi-Level Crop Redistribution Model Coupled With Virtual Water: A Case Study of China’s Hetao Irrigation District 通过与虚拟水耦合的双级作物再分配模型实现区域间粮食-水-收入协同：中国河套灌区案例研究

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2024-07-09 DOI: 10.1029/2023wr036572

Jieling Yin, Xin Li, Bernie A. Engel, Jiayi Ding, Xin Xing, Shikun K. Sun, Yubao B. Wang

{"title":"Inter-Regional Food-Water-Income Synergy Through Bi-Level Crop Redistribution Model Coupled With Virtual Water: A Case Study of China’s Hetao Irrigation District","authors":"Jieling Yin, Xin Li, Bernie A. Engel, Jiayi Ding, Xin Xing, Shikun K. Sun, Yubao B. Wang","doi":"10.1029/2023wr036572","DOIUrl":"https://doi.org/10.1029/2023wr036572","url":null,"abstract":"Incorporating water footprints and virtual water into crop redistribution provides a new approach for efficient water resources utilization and synergistic development of water surplus and scarce regions. In this work, the absolute and comparative advantage of the production-based blue and gray water footprint (PWFblue and PWFgray), the calorie-based blue water footprint (CWFblue) and the net benefit-based blue water footprint (NBWFblue) were used as coefficients to establish a bi-level crop redistribution model. The mode considers upper-level decision makers interested in maximizing food security and ecological security and lower-level decision makers interested in water use efficiency, water use benefits and net benefits. The model was applied in the Hetao Irrigation District (HID), China. The results showed that after optimization, the PWFblue, CWFblue, NBWFblue, and gray water footprint (GWF) of the HID were reduced by 23.32%, 5.60%, 17.40%, and 6.67%, respectively. National benefits were improved, especially when considering synergistic optimization, although the net benefits of HID was affected. The calorie supply increased by 9.6 × 109 kcal, the GWF decreased by 8.29 × 106 m3, and water use efficiency and benefits were improved in China. In contrast, the calorie supply and the net benefits of the HID decreased, while the GWF increased. Moreover, multiple stakeholders were involved in crop redistribution and required national synergies. The bi-level model proved more suitable than the multi-objective model. The model proposed in this work considers synergies outside the region in crop redistribution within the region, and can provide new insight for water and soil resources management in arid and semi-arid regions.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141578090","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}

引用次数: 0

Integrating a Water Tracer Model Into WRF-Hydro for Characterizing the Effect of Lateral Flow in Hydrologic Simulations 将水体示踪模型纳入 WRF-Hydro，在水文模拟中描述侧向流的影响

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2024-07-08 DOI: 10.1029/2023wr034938

Huancui Hu, L. Ruby Leung, Francina Dominguez, David Gochis, Xingyuan Chen, Stephen Good, Aubrey Dugger, Laurel Larsen, Michael Barlage

{"title":"Integrating a Water Tracer Model Into WRF-Hydro for Characterizing the Effect of Lateral Flow in Hydrologic Simulations","authors":"Huancui Hu, L. Ruby Leung, Francina Dominguez, David Gochis, Xingyuan Chen, Stephen Good, Aubrey Dugger, Laurel Larsen, Michael Barlage","doi":"10.1029/2023wr034938","DOIUrl":"https://doi.org/10.1029/2023wr034938","url":null,"abstract":"Most current land models approximate terrestrial hydrological processes as one-dimensional vertical flow, neglecting lateral water movement from ridges to valleys. Such lateral flow is fundamental at catchment scales and becomes crucial for finer-scale land models. To test the effect of incorporating lateral flow toward three-dimensional representations of hydrological processes in the next generation land models, we integrate a water tracer model into the WRF-Hydro framework to track water movement from precipitation to discharge and evapotranspiration. This hydrologic-tracer integrated system allows us to identify the key mechanisms by which lateral flow affects the flow paths and transit times in WRF-Hydro. By comparing modeling experiments with and without lateral routing in two contrasting catchments, we determine the impacts of lateral flow on the transit times of precipitation event-water. Results show that with limited hydrologic connectivity, lateral flow extends the transit times by reducing (increasing) event-water drainage loss (accumulation) in ridges (valleys) and allowing reinfiltration of infiltration-excess flow, which is missing in most land models. On the contrary with high hydrologic connectivity, lateral flow can effectively accelerate the water release to streams and reduce the transit time. However, the transit times are substantially underestimated by the model compared with isotope-derived estimates, indicating model limitations in representing flow paths and transit times. This study provides some insights on the fundamental differences in terrestrial hydrology simulated by land models with and without lateral flow representation.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141578093","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}

引用次数: 0