Mingzhu Cao, Weiguang Wang, Jia Wei, Giovanni Forzieri, Ingo Fetzer, Lan Wang-Erlandsson
The Loess Plateau in China has experienced a remarkable greening trend due to vegetation restoration efforts in recent decades. However, the response of precipitation to this greening remains uncertain. In this study, we identified and evaluated the main moisture source regions for precipitation over the Loess Plateau from 1982 to 2019 using a moisture tracking model, the modified WAM-2layers model, and the conceptual framework of the precipitationshed. By integrating multiple linear regression analysis with a conceptual hydrologically weighting method, we quantified the effective influence of different environmental factors for precipitation, particularly the effect of vegetation. Our analysis revealed that local precipitation has increased on average by 0.16 mm yr−1 and evaporation by 5.17 mm yr−1 over the period 2000–2019 after the initiation of the vegetation restoration project. Regional greening including the Loess Plateau contributed to precipitation for about 0.83 mm yr−1, among which local greening contributed for about 0.07 mm yr−1. Local vegetation contribution is due to both an enhanced local evaporation as well as an increased local moisture recycling (6.9% in 1982–1999; 8.3% in 2000–2019). Thus, our study shows that local revegetation had a positive effect on local precipitation, and the primary cause of the observed increase in precipitation over the Loess Plateau is due to a combination of local greening and circulation change. Our study underscores that increasing vegetation over the Loess Plateau has exerted strong influence on local precipitation and supports the positive effects for current and future vegetation restoration plans toward more resilient water resources managements.
近几十年来，中国黄土高原的植被恢复呈现出明显的绿化趋势。然而，降水对这种绿化的响应仍然不确定。本研究采用湿度跟踪模型、改进的WAM-2layers模型和降水概念框架，对1982 - 2019年黄土高原降水的主要水汽源区进行了识别和评价。将多元线性回归分析与概念水文加权法相结合，量化了不同环境因子对降水的有效影响，特别是植被对降水的影响。分析表明，2000-2019年植被恢复工程启动后，当地降水平均增加0.16 mm yr - 1，蒸发量平均增加5.17 mm yr - 1。包括黄土高原在内的区域绿化对降水的贡献约为0.83 mm yr−1，其中局部绿化对降水的贡献约为0.07 mm yr−1。当地植被的贡献是由于当地蒸发的增强以及当地水分再循环的增加(1982-1999年为6.9%；2000-2019年8.3%)。因此，我们的研究表明，局地植被对局地降水有积极的影响，黄土高原降水增加的主要原因是局地绿化和环流变化的结合。我们的研究强调了黄土高原植被的增加对当地降水的强烈影响，并支持当前和未来植被恢复计划对更有弹性的水资源管理的积极作用。
{"title":"Revegetation Impacts on Moisture Recycling and Precipitation Trends in the Chinese Loess Plateau","authors":"Mingzhu Cao, Weiguang Wang, Jia Wei, Giovanni Forzieri, Ingo Fetzer, Lan Wang-Erlandsson","doi":"10.1029/2024wr038199","DOIUrl":"https://doi.org/10.1029/2024wr038199","url":null,"abstract":"The Loess Plateau in China has experienced a remarkable greening trend due to vegetation restoration efforts in recent decades. However, the response of precipitation to this greening remains uncertain. In this study, we identified and evaluated the main moisture source regions for precipitation over the Loess Plateau from 1982 to 2019 using a moisture tracking model, the modified WAM-2layers model, and the conceptual framework of the precipitationshed. By integrating multiple linear regression analysis with a conceptual hydrologically weighting method, we quantified the effective influence of different environmental factors for precipitation, particularly the effect of vegetation. Our analysis revealed that local precipitation has increased on average by 0.16 mm yr<sup>−1</sup> and evaporation by 5.17 mm yr<sup>−1</sup> over the period 2000–2019 after the initiation of the vegetation restoration project. Regional greening including the Loess Plateau contributed to precipitation for about 0.83 mm yr<sup>−1</sup>, among which local greening contributed for about 0.07 mm yr<sup>−1</sup>. Local vegetation contribution is due to both an enhanced local evaporation as well as an increased local moisture recycling (6.9% in 1982–1999; 8.3% in 2000–2019). Thus, our study shows that local revegetation had a positive effect on local precipitation, and the primary cause of the observed increase in precipitation over the Loess Plateau is due to a combination of local greening and circulation change. Our study underscores that increasing vegetation over the Loess Plateau has exerted strong influence on local precipitation and supports the positive effects for current and future vegetation restoration plans toward more resilient water resources managements.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"20 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142797825","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}
Teng Xu, Shiqiang Zhang, Chunhui Lu, Jiangjiang Zhang, Yu Ye
The accurate prediction of groundwater contamination is challenging due to uncertainties arising from the inherent heterogeneity of aquifers, inadequate site characterization, and limitations in conceptual mathematical models. These factors can result in an underestimation of contaminant concentrations. For effective contaminant prevention and control, it is important to estimate the probability of exceeding the allowed threshold for contaminant concentrations, known as the failure probability of groundwater contamination. Computing small failure probabilities using classical Monte Carlo simulation (MCS) requires computing a large number of samplers to converge to a stationary target value, which is time-consuming. To address this, in this paper, we develop a novel approach for calculating small failure probabilities, known as subset simulation (SS) coupled with preconditioned Crank-Nicolson Markov chain Monte Carlo (pCN-SS), which combines subset simulation with preconditioned Crank-Nicolson Markov chain Monte Carlo (pCN-MCMC) to promote computational efficiency. We have tested the performance of the proposed algorithm in both a mathematical example and a numerical case study of groundwater contamination. The results demonstrate that pCN-SS provides improved accuracy and efficiency for evaluating small failure probabilities for high-dimensional groundwater contamination, specifically for hydraulic conductivity as a source of uncertainty. Compared to classical MCS and traditional SS, pCN-SS requires fewer model evaluations but produces stable and accurate results.
{"title":"Estimation of Small Failure Probability in High-Dimensional Groundwater Contaminant Transport Modeling Using Subset Simulation Coupled With Preconditioned Crank-Nicolson MCMC","authors":"Teng Xu, Shiqiang Zhang, Chunhui Lu, Jiangjiang Zhang, Yu Ye","doi":"10.1029/2024wr038260","DOIUrl":"https://doi.org/10.1029/2024wr038260","url":null,"abstract":"The accurate prediction of groundwater contamination is challenging due to uncertainties arising from the inherent heterogeneity of aquifers, inadequate site characterization, and limitations in conceptual mathematical models. These factors can result in an underestimation of contaminant concentrations. For effective contaminant prevention and control, it is important to estimate the probability of exceeding the allowed threshold for contaminant concentrations, known as the failure probability of groundwater contamination. Computing small failure probabilities using classical Monte Carlo simulation (MCS) requires computing a large number of samplers to converge to a stationary target value, which is time-consuming. To address this, in this paper, we develop a novel approach for calculating small failure probabilities, known as subset simulation (SS) coupled with preconditioned Crank-Nicolson Markov chain Monte Carlo (pCN-SS), which combines subset simulation with preconditioned Crank-Nicolson Markov chain Monte Carlo (pCN-MCMC) to promote computational efficiency. We have tested the performance of the proposed algorithm in both a mathematical example and a numerical case study of groundwater contamination. The results demonstrate that pCN-SS provides improved accuracy and efficiency for evaluating small failure probabilities for high-dimensional groundwater contamination, specifically for hydraulic conductivity as a source of uncertainty. Compared to classical MCS and traditional SS, pCN-SS requires fewer model evaluations but produces stable and accurate results.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"61 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142797823","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}
Fang-Fang Li, Hou-Liang Lu, Guang-Qian Wang, Jun Qiu
Global warming has changed both the amount of global precipitation and the atmospheric capacity to retain water. In this paper, a novel definition of the long-term Capturability of Atmospheric Water (CAW) based on horizontal atmospheric water transport is proposed, describing the ability of a certain area to intercept and convert the atmospheric water transported by horizontal moisture flux into local precipitation. The significant decrease of the CAW in Amazon and Congo rainforests and Inside Greenland indicates that these areas were having less precipitation with the same water vapor in the past 42 years, while in Asia (especially China), CAW is showing a large-scale increasing trend, verifying the regional humidifying. Considering the change of both the CAW and the background atmospheric water simultaneously, their mismatch degree is also investigated. The positive mismatch in Qinghai Tibet Plateau, Greenland, and the Andes, suggests higher susceptibility to climate change, and in the areas of negative mismatch (Amazon, Maritime Continent, southeastern China, the Eastern United States, India, and Japan), a more stable precipitation response to climate change is expected. The proposed concept of CAW provides a novel perspective to analyze the precipitation response to climate change on a global scale.
{"title":"Long-Term Capturability of Atmospheric Water on a Global Scale","authors":"Fang-Fang Li, Hou-Liang Lu, Guang-Qian Wang, Jun Qiu","doi":"10.1029/2023wr034757","DOIUrl":"https://doi.org/10.1029/2023wr034757","url":null,"abstract":"Global warming has changed both the amount of global precipitation and the atmospheric capacity to retain water. In this paper, a novel definition of the long-term Capturability of Atmospheric Water (CAW) based on horizontal atmospheric water transport is proposed, describing the ability of a certain area to intercept and convert the atmospheric water transported by horizontal moisture flux into local precipitation. The significant decrease of the CAW in Amazon and Congo rainforests and Inside Greenland indicates that these areas were having less precipitation with the same water vapor in the past 42 years, while in Asia (especially China), CAW is showing a large-scale increasing trend, verifying the regional humidifying. Considering the change of both the CAW and the background atmospheric water simultaneously, their mismatch degree is also investigated. The positive mismatch in Qinghai Tibet Plateau, Greenland, and the Andes, suggests higher susceptibility to climate change, and in the areas of negative mismatch (Amazon, Maritime Continent, southeastern China, the Eastern United States, India, and Japan), a more stable precipitation response to climate change is expected. The proposed concept of CAW provides a novel perspective to analyze the precipitation response to climate change on a global scale.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"211 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142793211","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}
Marja Haagsma, Catherine E. Finkenbiner, David C. Noone, Gabriel J. Bowen, Christopher Still, Richard P. Fiorella, Stephen P. Good
Land surface models (LSMs) play a crucial role in elucidating water and carbon cycles by simulating processes such as plant transpiration and evaporation from bare soil, yet calibration often relies on comparing LSM outputs of landscape total evapotranspiration (ET) and discharge with measured bulk fluxes. Discrepancies in partitioning into component fluxes predicted by various LSMs have been noted, prompting the need for improved evaluation methods. Stable water isotopes serve as effective tracers of component hydrologic fluxes, but data and model integration challenges have hindered their widespread application. Leveraging National Ecological Observation Network measurements of water isotope ratios at 16 US sites over 3 years combined with LSM-modeled fluxes, we employed an isotope-enabled mass balance framework to simulate ET isotope values (δET) within three operational LSMs (Mosaic, Noah, and VIC) to evaluate their partitioning. Models simulating δET values consistent with observations were deemed more reflective of water cycling in these ecosystems. Mosaic exhibited the best overall performance (Kling-Gupta Efficiency of 0.28). For both Mosaic and Noah there were robust correlations between bare soil evaporation fraction and error (negative) as well as transpiration fraction and error (positive). We found the point at which errors are smallest (x-intercept of the multi-site regression) is at a higher transpiration fraction than is currently specified in the models. Which means that transpiration fraction is underestimated on average. Stable isotope tracers offer an additional tool for model evaluation and identifying areas for improvement, potentially enhancing LSM simulations and our understanding of land-surface hydrologic processes.
{"title":"Using an Isotope Enabled Mass Balance to Evaluate Existing Land Surface Models","authors":"Marja Haagsma, Catherine E. Finkenbiner, David C. Noone, Gabriel J. Bowen, Christopher Still, Richard P. Fiorella, Stephen P. Good","doi":"10.1029/2024wr037530","DOIUrl":"https://doi.org/10.1029/2024wr037530","url":null,"abstract":"Land surface models (LSMs) play a crucial role in elucidating water and carbon cycles by simulating processes such as plant transpiration and evaporation from bare soil, yet calibration often relies on comparing LSM outputs of landscape total evapotranspiration (<i>ET</i>) and discharge with measured bulk fluxes. Discrepancies in partitioning into component fluxes predicted by various LSMs have been noted, prompting the need for improved evaluation methods. Stable water isotopes serve as effective tracers of component hydrologic fluxes, but data and model integration challenges have hindered their widespread application. Leveraging National Ecological Observation Network measurements of water isotope ratios at 16 US sites over 3 years combined with LSM-modeled fluxes, we employed an isotope-enabled mass balance framework to simulate <i>ET</i> isotope values (<i>δET</i>) within three operational LSMs (Mosaic, Noah, and VIC) to evaluate their partitioning. Models simulating <i>δET</i> values consistent with observations were deemed more reflective of water cycling in these ecosystems. Mosaic exhibited the best overall performance (Kling-Gupta Efficiency of 0.28). For both Mosaic and Noah there were robust correlations between bare soil evaporation fraction and error (negative) as well as transpiration fraction and error (positive). We found the point at which errors are smallest (<i>x</i>-intercept of the multi-site regression) is at a higher transpiration fraction than is currently specified in the models. Which means that transpiration fraction is underestimated on average. Stable isotope tracers offer an additional tool for model evaluation and identifying areas for improvement, potentially enhancing LSM simulations and our understanding of land-surface hydrologic processes.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"84 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142788551","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 Multi-Radar Multi-Sensor (MRMS) product incorporates radar, quantitative precipitation forecasts, and gage data at a high spatiotemporal resolution for the United States and southern Canada. MRMS is subject to various sources of measurement error, especially in complex terrain. The goal of this study is to provide a framework for understanding the uncertainty of MRMS in mountainous areas with limited observations. We evaluate 8-hr time series samples of MRMS 15-min intensity through a comparison to 204 gages located in the mountains of Colorado. This analysis shows that the MRMS surface precipitation rate product tends to overestimate rainfall with a median normalized root mean squared error (RMSE) of 42% of the maximum MRMS 15-min intensity. For each time series sample, various features related to the physical characteristics influencing MRMS performance are calculated from the topography, surrounding storms, and rainfall observed at the gage location. A gradient-boosting regressor is trained on these features and is optimized with quantile loss, using the RMSE as a target, to model nonlinear patterns in the features that relate to a range of error. This model was used to predict a range of error throughout the mountains of Colorado during warm months, spanning 6 years, resulting in a spatiotemporally varying error model of MRMS for sub-hourly precipitation rates. Mapping of this data set by aggregating normalized RMSE over time reveals that areas further from radar sites in higher elevation terrain show consistently greater error. However, the model predicts larger performance variability in these regions compared to alternative error assessments.
{"title":"Evaluation of Sub-Hourly MRMS Quantitative Precipitation Estimates in Mountainous Terrain Using Machine Learning","authors":"Phoebe White, Peter A. Nelson","doi":"10.1029/2024wr037437","DOIUrl":"https://doi.org/10.1029/2024wr037437","url":null,"abstract":"The Multi-Radar Multi-Sensor (MRMS) product incorporates radar, quantitative precipitation forecasts, and gage data at a high spatiotemporal resolution for the United States and southern Canada. MRMS is subject to various sources of measurement error, especially in complex terrain. The goal of this study is to provide a framework for understanding the uncertainty of MRMS in mountainous areas with limited observations. We evaluate 8-hr time series samples of MRMS 15-min intensity through a comparison to 204 gages located in the mountains of Colorado. This analysis shows that the MRMS surface precipitation rate product tends to overestimate rainfall with a median normalized root mean squared error (RMSE) of 42% of the maximum MRMS 15-min intensity. For each time series sample, various features related to the physical characteristics influencing MRMS performance are calculated from the topography, surrounding storms, and rainfall observed at the gage location. A gradient-boosting regressor is trained on these features and is optimized with quantile loss, using the RMSE as a target, to model nonlinear patterns in the features that relate to a range of error. This model was used to predict a range of error throughout the mountains of Colorado during warm months, spanning 6 years, resulting in a spatiotemporally varying error model of MRMS for sub-hourly precipitation rates. Mapping of this data set by aggregating normalized RMSE over time reveals that areas further from radar sites in higher elevation terrain show consistently greater error. However, the model predicts larger performance variability in these regions compared to alternative error assessments.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"24 5 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142788522","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}
Samaneh Vahid Dastjerdi, Nikolaos Karadimitriou, S. Majid Hassanizadeh, Holger Steeb
Including specific interfacial area and saturation of the percolating phase into two-phase porous media flow models, on the Darcy scale, enhances our ability to capture the physical properties of porous media flow more effectively. Using optical microscopy and microfluidic devices, we perform sequential drainage and imbibition experiments. The relevant processes, images, and boundary pressures are monitored, recorded, and logged at all times. For comparative purposes, two PDMS micromodels are used, one with an ortho-canonical, homogeneous, and the other with a periodic heterogeneous pore network, with similar macro- but different pore-scale properties. After processing the images, parameters like interfacial area belonging to percolating and non-percolating phases and the corresponding phase saturations are determined. Our experimental results show that the relation between specific interfacial area and saturation of the percolating invading phase is a linear relationship with interesting properties. Additionally, after a number of fluid displacement processes (drainage and imbibition), and for both pore networks, unique flow paths for both phases are formed. We speculate that this happens due to the establishment of an effective porous medium, meaning a hydro-dynamically active region within the pore space where the corresponding phase remains connected and flowing, where the capillary forces act as the guide for creating the “path of least resistance” in a highly viscous flow regime by keeping the non-percolating phases in place. As the results can be specific to our experiments, more work needs to be done toward the potential generalization of these findings, especially in 3D flow domains.
{"title":"Formation of Common Preferential Two-Phase Displacement Pathways in Porous Media","authors":"Samaneh Vahid Dastjerdi, Nikolaos Karadimitriou, S. Majid Hassanizadeh, Holger Steeb","doi":"10.1029/2024wr037266","DOIUrl":"https://doi.org/10.1029/2024wr037266","url":null,"abstract":"Including specific interfacial area and saturation of the percolating phase into two-phase porous media flow models, on the Darcy scale, enhances our ability to capture the physical properties of porous media flow more effectively. Using optical microscopy and microfluidic devices, we perform sequential drainage and imbibition experiments. The relevant processes, images, and boundary pressures are monitored, recorded, and logged at all times. For comparative purposes, two PDMS micromodels are used, one with an ortho-canonical, homogeneous, and the other with a periodic heterogeneous pore network, with similar macro- but different pore-scale properties. After processing the images, parameters like interfacial area belonging to percolating and non-percolating phases and the corresponding phase saturations are determined. Our experimental results show that the relation between specific interfacial area and saturation of the percolating invading phase is a linear relationship with interesting properties. Additionally, after a number of fluid displacement processes (drainage and imbibition), and for both pore networks, unique flow paths for both phases are formed. We speculate that this happens due to the establishment of an effective porous medium, meaning a hydro-dynamically active region within the pore space where the corresponding phase remains connected and flowing, where the capillary forces act as the guide for creating the “path of least resistance” in a highly viscous flow regime by keeping the non-percolating phases in place. As the results can be specific to our experiments, more work needs to be done toward the potential generalization of these findings, especially in 3D flow domains.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"27 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142782803","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}
Yu Zhang, Xiaomang Liu, Kaiwen Wang, Dan Zhang, Weihang Liu
Evapotranspiration (ET), a crucial component of water consumption in the hydrological process, is directly controlled by soil moisture (SM) and vapor pressure deficit (VPD) from the perspectives of water supply and demand. However, SM and VPD are strongly coupled through multiple physical processes, confounding their effects on ET. Here, we decouple the interaction between SM and VPD and then analyze the spatiotemporal pattern of their individual effects on ET based on multiple observation-based data sets. The results show that ET is limited by SM rather than VPD in approximately 63% of global land areas (60°S–60°N), defined as water supply-limited regions. From 1982 to 2014, the effect of SM on ET enhances significantly in 43% of the water supply-limited regions. The trends can be attributed to changes in SM and VPD themselves as well as to changes in vegetation conditions. Using the findings from the observation-based data sets as the benchmark, we show that Earth System Models (ESMs) can overall reproduce the spatial pattern of SM and VPD effects on ET but fail to capture their temporal trends. Our results highlight that the water supply and demand control on ET varies with changing environments, which should be explicitly considered when analyzing the terrestrial water cycle and land-atmosphere interaction.
{"title":"Widespread Increasing Control of Water Supply on Evapotranspiration","authors":"Yu Zhang, Xiaomang Liu, Kaiwen Wang, Dan Zhang, Weihang Liu","doi":"10.1029/2024wr038353","DOIUrl":"https://doi.org/10.1029/2024wr038353","url":null,"abstract":"Evapotranspiration (ET), a crucial component of water consumption in the hydrological process, is directly controlled by soil moisture (SM) and vapor pressure deficit (VPD) from the perspectives of water supply and demand. However, SM and VPD are strongly coupled through multiple physical processes, confounding their effects on ET. Here, we decouple the interaction between SM and VPD and then analyze the spatiotemporal pattern of their individual effects on ET based on multiple observation-based data sets. The results show that ET is limited by SM rather than VPD in approximately 63% of global land areas (60°S–60°N), defined as water supply-limited regions. From 1982 to 2014, the effect of SM on ET enhances significantly in 43% of the water supply-limited regions. The trends can be attributed to changes in SM and VPD themselves as well as to changes in vegetation conditions. Using the findings from the observation-based data sets as the benchmark, we show that Earth System Models (ESMs) can overall reproduce the spatial pattern of SM and VPD effects on ET but fail to capture their temporal trends. Our results highlight that the water supply and demand control on ET varies with changing environments, which should be explicitly considered when analyzing the terrestrial water cycle and land-atmosphere interaction.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"54 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142777457","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}
Hongzheng Zhu, Kieran Khamis, David M. Hannah, Stefan Krause
In-situ dissolved organic matter (DOM) monitoring frequencies have often been chosen for convenience or based on perceived wisdom, without fully assessing their impact on representation of DOM dynamics. To address this gap, we collected 5-min fluorescence data in an urban headwater and resampled it at coarser intervals to investigate the impact of monitoring frequencies on the detectability of DOM dynamics during storms. Expecting hydrometeorological conditions to modify the impact of monitoring frequency, we categorized 85 storm events into groups: Group A (low intensity, short duration), Group B (high intensity, short duration), and Group C (low intensity, long duration). Surprisingly, our analysis indicated that monitoring frequency has minimal influence on commonly used biogeochemical indexes (e.g., maximum, hysteresis and flushing index), which are employed to characterize solute behavior, regardless of storm type. To facilitate a direct comparison between monitoring frequencies, we back-interpolated coarser data into 5-min intervals and calculated mean squared errors by comparing them with original high-resolution data. Our findings indicated that in colder periods with predominately Type A and C storms, a coarser monitoring frequency (>30 min) can capture DOM dynamics. Conversely, in warmer periods when Type B storms dominate, a finer frequency (≤15 min) is necessary to capture key solute chemograph processes (e.g., first flush and dilution). Generally, we suggest a 15-min monitoring frequency as optimal for similar urban headwater systems, and advocate an adaptive approach based on seasonal variations to improve efficiency, especially when power, data transfer, and storage are constraints.
{"title":"Importance of Monitoring Frequency for Representation of Dissolved Organic Matter Dynamics in Urban Rivers","authors":"Hongzheng Zhu, Kieran Khamis, David M. Hannah, Stefan Krause","doi":"10.1029/2024wr037254","DOIUrl":"https://doi.org/10.1029/2024wr037254","url":null,"abstract":"In-situ dissolved organic matter (DOM) monitoring frequencies have often been chosen for convenience or based on perceived wisdom, without fully assessing their impact on representation of DOM dynamics. To address this gap, we collected 5-min fluorescence data in an urban headwater and resampled it at coarser intervals to investigate the impact of monitoring frequencies on the detectability of DOM dynamics during storms. Expecting hydrometeorological conditions to modify the impact of monitoring frequency, we categorized 85 storm events into groups: Group A (low intensity, short duration), Group B (high intensity, short duration), and Group C (low intensity, long duration). Surprisingly, our analysis indicated that monitoring frequency has minimal influence on commonly used biogeochemical indexes (e.g., maximum, hysteresis and flushing index), which are employed to characterize solute behavior, regardless of storm type. To facilitate a direct comparison between monitoring frequencies, we back-interpolated coarser data into 5-min intervals and calculated mean squared errors by comparing them with original high-resolution data. Our findings indicated that in colder periods with predominately Type A and C storms, a coarser monitoring frequency (>30 min) can capture DOM dynamics. Conversely, in warmer periods when Type B storms dominate, a finer frequency (≤15 min) is necessary to capture key solute chemograph processes (e.g., first flush and dilution). Generally, we suggest a 15-min monitoring frequency as optimal for similar urban headwater systems, and advocate an adaptive approach based on seasonal variations to improve efficiency, especially when power, data transfer, and storage are constraints.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"46 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142763409","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}
Ikechukwu Kalu, Christopher E. Ndehedehe, Vagner G. Ferreira, Sreekanth Janardhanan, Matthew Currell, Russell S. Crosbie, Mark J. Kennard
The Gnangara groundwater system is a highly productive water resource in southwestern Australia. However, it is considered one of the most vulnerable groundwater systems to climate change, due to consistent declines in precipitation and recharge, and regional climate models project further declines into the future. This study introduces a new framework underpinned by machine learning techniques to provide reliable estimates of precipitation-based recharge over the whole Perth Basin (including the Gnangara system). By combining estimates of baseflow, groundwater evaporation, and extraction, groundwater recharge was estimated over the Perth (testing site) and Gnangara (calibration site) systems using downscaled Groundwater Storage Anomalies (GWSA) from the Gravity Recovery and Climate Experiment (GRACE) mission. The random forest regression (RFR) model was used to downscale the spatial resolution of GRACE to 0.05° (approx. 5 km), providing estimable signals over the relatively small calibration site (∼2,200 km2) in order to discern any meaningful signals from the original GRACE resolution. Our study reveals that downscaled signals from GRACE can be used to provide precipitation-based recharge estimates for groundwater systems accurately. However, the growing impacts of climate change, which has led to sporadic precipitation patterns over Western Australia, can limit the efficiency of satellite remote sensing methods in estimating recharge, especially in deep and complex aquifers.
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