Pub Date : 2025-02-08DOI: 10.1016/j.jhydrol.2025.132827
Dawei Cheng , Hongbin Zhan , Xi Chen , Shengke Yang , Dongyong Sun , Xiuyu Liang
The capillarity effect, which refers to the movement of liquid in narrow spaces without the aid of external forces like gravity, plays a crucial role in water movement within soils and is often underrepresented in previous models. In cases where the capillary fringe is always below the soil surface, a new analytical model for saturated flow is developed, with the upper boundary located at the air-entry plane (), to simulate groundwater dynamics under a single angular frequency harmonic forcing. This new analytical solution agrees well with previous experimental results and a specifically designed saturated–unsaturated flow finite element numerical model. The new model also addresses the assumptions regarding the upper boundary condition in previous models. The oscillatory behavior of the ha plane are explored based on a simplified approximation of the new solution. The increase in hydraulic conductivity or time-averaged recharge rate will lead to an increase in phase lag and a decrease in amplitude decay. The increase of the initial ha plane elevation, the average specific yield or the angular frequency of the harmonic forcing will lead to the decrease of the phase lag and the increase of the amplitude decay.
{"title":"Capillarity effect on groundwater dynamics during periodic forcing","authors":"Dawei Cheng , Hongbin Zhan , Xi Chen , Shengke Yang , Dongyong Sun , Xiuyu Liang","doi":"10.1016/j.jhydrol.2025.132827","DOIUrl":"10.1016/j.jhydrol.2025.132827","url":null,"abstract":"<div><div>The capillarity effect, which refers to the movement of liquid in narrow spaces without the aid of external forces like gravity, plays a crucial role in water movement within soils and is often underrepresented in previous models. In cases where the capillary fringe is always below the soil surface, a new analytical model for saturated flow is developed, with the upper boundary located at the air-entry plane (<span><math><msub><mi>h</mi><mi>a</mi></msub></math></span>), to simulate groundwater dynamics under a single angular frequency harmonic forcing. This new analytical solution agrees well with previous experimental results and a specifically designed saturated–unsaturated flow finite element numerical model. The new model also addresses the assumptions regarding the upper boundary condition in previous models. The oscillatory behavior of the <em>h<sub>a</sub></em> plane are explored based on a simplified approximation of the new solution. The increase in hydraulic conductivity or time-averaged recharge rate will lead to an increase in phase lag and a decrease in amplitude decay. The increase of the initial <em>h<sub>a</sub></em> plane elevation, the average specific yield or the angular frequency of the harmonic forcing will lead to the decrease of the phase lag and the increase of the amplitude decay.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132827"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403316","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}
Pub Date : 2025-02-08DOI: 10.1016/j.jhydrol.2025.132832
Yasaman Kazemnadi, Mahta Nazari, Reza Kerachian
In recent years, due to the effects of climate change and the non-stationarity of hydrological data, the operation of reservoirs has shifted towards adaptive operation utilizing inflow forecasting data. Accurate long-term predictions of inflow to reservoirs are crucial for the adaptive operation of dams. By extending the prediction timeframe, we can incorporate more information about expected inflows over the coming months; however, this also leads to increased uncertainty in those predictions. Therefore, it is necessary to evaluate the effect of the lead time of predictions on the reliability of reservoir operating policies. This problem becomes even more challenging in multi-reservoir systems with objectives related to water quantity and quality (WQQ). This adds computational complexities and poses challenges regarding the run-time of simulation and optimization models. This paper presents an adaptive operation framework for operating a two-reservoir system taking into account both the amount and quality of allocated water to demands, along with the water quality within the reservoirs. Precipitation forecasts for lead times spanning from one to six months are obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF). These precipitation figures are then post-processed and transformed into runoff using a calibrated Soil and Water Assessment Tool (SWAT) model. The adaptive optimization model (AOM) is connected to a two-dimensional CE-QUAL-W2-based water quality simulation model (WQSM), allowing for an effective evaluation of the outflow quality from each gate and a thorough assessment of in-reservoir water quality throughout the optimization process. To reduce the computational cost of the adaptive simulation–optimization model, we use a combination of Parallel Cellular Automata and Local Search optimization algorithms, referred to as PCA-LS. To assess the effectiveness of the proposed methodology, it is implemented in the Karkheh watershed in Iran, which includes two significant reservoirs, Seimare and Karkheh. After comparing the outputs of the models with various rainfall forecast lead times, we found that a two-month lead time yields the most accurate results. The results of the AOM, which predicts rainfall with a two-month lead time, are compared to those of a model that uses perfect (observed) input data. This comparison reveals that the objective functions of the perfect and adaptive models differ by only 0.4%, demonstrating that the adaptive operation policies maintain a high level of accuracy when utilizing optimal rainfall prediction lead time.
{"title":"Evaluating how inflow forecast lead time affects the operating policies of cascade reservoirs with a focus on water quality issues","authors":"Yasaman Kazemnadi, Mahta Nazari, Reza Kerachian","doi":"10.1016/j.jhydrol.2025.132832","DOIUrl":"10.1016/j.jhydrol.2025.132832","url":null,"abstract":"<div><div>In recent years, due to the effects of climate change and the non-stationarity of hydrological data, the operation of reservoirs has shifted towards adaptive operation utilizing inflow forecasting data. Accurate long-term predictions of inflow to reservoirs are crucial for the adaptive operation of dams. By extending the prediction timeframe, we can incorporate more information about expected inflows over the coming months; however, this also leads to increased uncertainty in those predictions. Therefore, it is necessary to evaluate the effect of the lead time of predictions on the reliability of reservoir operating policies. This problem becomes even more challenging in multi-reservoir systems with objectives related to water quantity and quality (WQQ). This adds computational complexities and poses challenges regarding the run-time of simulation and optimization models. This paper presents an adaptive operation framework for operating a two-reservoir system taking into account both the amount and quality of allocated water to demands, along with the water quality within the reservoirs. Precipitation forecasts for lead times spanning from one to six months are obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF). These precipitation figures are then post-processed and transformed into runoff using a calibrated Soil and Water Assessment Tool (SWAT) model. The adaptive optimization model (AOM) is connected to a two-dimensional CE-QUAL-W2-based water quality simulation model (WQSM), allowing for an effective evaluation of the outflow quality from each gate and a thorough assessment of in-reservoir water quality throughout the optimization process. To reduce the computational cost of the adaptive simulation–optimization model, we use a combination of Parallel Cellular Automata and Local Search optimization algorithms, referred to as PCA-LS. To assess the effectiveness of the proposed methodology, it is implemented in the Karkheh watershed in Iran, which includes two significant reservoirs, Seimare and Karkheh. After comparing the outputs of the models with various rainfall forecast lead times, we found that a two-month lead time yields the most accurate results. The results of the AOM, which predicts rainfall with a two-month lead time, are compared to those of a model that uses perfect (observed) input data. This comparison reveals that the objective functions of the perfect and adaptive models differ by only 0.4%, demonstrating that the adaptive operation policies maintain a high level of accuracy when utilizing optimal rainfall prediction lead time.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132832"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396236","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}
Pub Date : 2025-02-08DOI: 10.1016/j.jhydrol.2025.132850
Yookyung Jeong , Dongkyun Kim , Kyuhyun Byun
Climate change presents a significant challenge, impacting both the environment and society. Addressing this challenge effectively necessitates in-depth analysis of climate trends and extreme events, relying on long-term, high-resolution meteorological data. However, such data is often lacking in many regions globally, with dense observation networks only recently becoming available. To tackle this issue, our study proposes a novel framework utilizing deep learning to reconstruct high-quality gridded meteorological data for historical periods. Specifically, our approach involves training deep learning models to bridge the gap between gridded products derived from sparse networks, which have existed from the past to the present, and gridded products from dense networks representing recent periods. This training enables us to simulate a gridded product for historical periods of interest using the trained deep learning model. To demonstrate and test our approach, we reconstruct the gridded daily meteorological data for the historical period (1973–1997) over South Korea, where a dense network has been in operation since the late 1990s. The simulated daily datasets by the developed models can capture complex geographic and topographic effects reasonably well, providing a realistic depiction of resulting climate variability. Furthermore, the extreme analysis suggests that the models accurately represent detailed variations between grid cells, contrasting with the limitations of the one derived from sparse observation network, which suffers from gridding artifacts. These findings emphasize the capability of the framework developed in this study to reconstruct high-resolution, high-quality datasets for historical periods without dense observation networks. This indicates the potential of our approach to produce long-term, high-quality gridded meteorological data crucial for hydrological models and climate change analyses, including extreme events.
{"title":"A novel deep learning-based approach for reconstruction of historical long-term high-quality gridded meteorological dataset","authors":"Yookyung Jeong , Dongkyun Kim , Kyuhyun Byun","doi":"10.1016/j.jhydrol.2025.132850","DOIUrl":"10.1016/j.jhydrol.2025.132850","url":null,"abstract":"<div><div>Climate change presents a significant challenge, impacting both the environment and society. Addressing this challenge effectively necessitates in-depth analysis of climate trends and extreme events, relying on long-term, high-resolution meteorological data. However, such data is often lacking in many regions globally, with dense observation networks only recently becoming available. To tackle this issue, our study proposes a novel framework utilizing deep learning to reconstruct high-quality gridded meteorological data for historical periods. Specifically, our approach involves training deep learning models to bridge the gap between gridded products derived from sparse networks, which have existed from the past to the present, and gridded products from dense networks representing recent periods. This training enables us to simulate a gridded product for historical periods of interest using the trained deep learning model. To demonstrate and test our approach, we reconstruct the gridded daily meteorological data for the historical period (1973–1997) over South Korea, where a dense network has been in operation since the late 1990s. The simulated daily datasets by the developed models can capture complex geographic and topographic effects reasonably well, providing a realistic depiction of resulting climate variability. Furthermore, the extreme analysis suggests that the models accurately represent detailed variations between grid cells, contrasting with the limitations of the one derived from sparse observation network, which suffers from gridding artifacts. These findings emphasize the capability of the framework developed in this study to reconstruct high-resolution, high-quality datasets for historical periods without dense observation networks. This indicates the potential of our approach to produce long-term, high-quality gridded meteorological data crucial for hydrological models and climate change analyses, including extreme events.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132850"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437663","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}
Pub Date : 2025-02-08DOI: 10.1016/j.jhydrol.2025.132839
Yi Nan , Fuqiang Tian , Zongxing Li
Hydrological simulations bear large uncertainties in mountainous basins due to complex water sources and runoff pathways. Tracer-aided modelling is useful for improving hydrological simulation and reducing uncertainties. The mixing assumption is an important issue for tracer-aided hydrological models. Although numerous studies have shown that partial mixing phenomena are common in small-scale catchments and groundwater storages, no research has yet adopted the partial mixing assumption in distributed tracer-aided hydrological models, and the impact of the mixing assumption on distributed models has not been fully understood. This study developed a two-reservoir method to simulate the partial mixing processes in the groundwater storage for the tracer-aided hydrological model THREW-T. Adopting the model in a typical large mountainous basin on the Tibetan Plateau, we analyzed the influence of mixing assumption on the estimated contribution of subsurface runoff. Results showed that: (1) The model with the partial mixing assumption (THREW-PM) can effectively simulate the isotopic variation of subsurface runoff. The calibrated parameters related to partial mixing indicated a small active storage controlling hydrological response and (∼0.05) a long time required for complete mixing between active and passive storages (∼100 days). (2) The mixing assumption and isotope data had an important influence on the subsurface runoff estimated by the THREW-T model. Adopting the partial mixing assumption and calibrating the model toward the subsurface runoff isotope resulted in a 10 % difference in the estimated contribution. (3) The mixing assumption affected the models by influencing the isotope variation of subsurface runoff. As the temporal variation in the simulated isotope composition of subsurface runoff increased, the estimated contribution of subsurface runoff also increased. This study conducted the first analysis on how mixing assumptions influence distributed tracer-aided hydrological models, and highlighted the importance of tracer data from various water bodies in verifying the simulations of the tracer composition in runoff components, and, the consequently the separation among them.
{"title":"How does the mixing assumption influence the distributed tracer-aided hydrological model?","authors":"Yi Nan , Fuqiang Tian , Zongxing Li","doi":"10.1016/j.jhydrol.2025.132839","DOIUrl":"10.1016/j.jhydrol.2025.132839","url":null,"abstract":"<div><div>Hydrological simulations bear large uncertainties in mountainous basins due to complex water sources and runoff pathways. Tracer-aided modelling is useful for improving hydrological simulation and reducing uncertainties. The mixing assumption is an important issue for tracer-aided hydrological models. Although numerous studies have shown that partial mixing phenomena are common in small-scale catchments and groundwater storages, no research has yet adopted the partial mixing assumption in distributed tracer-aided hydrological models, and the impact of the mixing assumption on distributed models has not been fully understood. This study developed a two-reservoir method to simulate the partial mixing processes in the groundwater storage for the tracer-aided hydrological model THREW-T. Adopting the model in a typical large mountainous basin on the Tibetan Plateau, we analyzed the influence of mixing assumption on the estimated contribution of subsurface runoff. Results showed that: (1) The model with the partial mixing assumption (THREW-PM) can effectively simulate the isotopic variation of subsurface runoff. The calibrated parameters related to partial mixing indicated a small active storage controlling hydrological response and (∼0.05) a long time required for complete mixing between active and passive storages (∼100 days). (2) The mixing assumption and isotope data had an important influence on the subsurface runoff estimated by the THREW-T model. Adopting the partial mixing assumption and calibrating the model toward the subsurface runoff isotope resulted in a 10 % difference in the estimated contribution. (3) The mixing assumption affected the models by influencing the isotope variation of subsurface runoff. As the temporal variation in the simulated isotope composition of subsurface runoff increased, the estimated contribution of subsurface runoff also increased. This study conducted the first analysis on how mixing assumptions influence distributed tracer-aided hydrological models, and highlighted the importance of tracer data from various water bodies in verifying the simulations of the tracer composition in runoff components, and, the consequently the separation among them.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132839"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143386720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-08DOI: 10.1016/j.jhydrol.2025.132802
Jingyi Hu , Wei Ouyang , Congyu Hou , Kaiyue Ji , Zhifeng Yang
High-quality stormwater management is crucial for sustainable urban development and the protection of aquatic ecosystems, particularly because urbanization and climate-induced extreme events intensify runoff and pollution risks. Although urban stormwater pollution and its potential impacts have been addressed, its impacts on diffuse pollutant loads under compound climate have not been well evaluated. Our study focused on the Bahe River Basin and two river sections at the inlet and outlet of Xi’an city and quantified the impacts of extreme climate and high load risk. The contributions of different precipitation events to pollutant losses were explored using the Soil and Water Assessment tool (SWAT). Cropland was the main source of total nitrogen (TN) and total phosphorus (TP), accounting for 94 % and 91 % of the total pollution during single extreme precipitation events, respectively. However, during compound drought and extreme precipitation events, more than 50 % of the TP pollution originated from urban land. Attribution analysis showed that the heavy precipitation amount (R95P) and frequency (R20MM) were the main factors affecting TN and TP loads, accounting for 65–78 % and 83–88 % of the total impact. In addition, these factors have a greater impact downstream of the city, indicating that urban stormwater pollution increases the response of diffuse loads to climate extremes. The SWAT and copula function were combined to quantify the high-load probabilities under different climatic conditions. The probabilities of the TN and TP load exceeding the top 5 %–30 % were 4 %–19 % and 3 %–21 %, respectively, when the precipitation exceeded the top 20 %, and the probabilities of the TP load downstream of the city were more susceptible to high precipitation. Our study highlights the role of urban stormwater pollution on watershed diffuse loads in addition to point source pollution, with urban development potentially leading to more pollutants being transported to the receiving rivers.
{"title":"Effects of urban stormwater pollution on watershed diffuse loads under extreme precipitation conditions","authors":"Jingyi Hu , Wei Ouyang , Congyu Hou , Kaiyue Ji , Zhifeng Yang","doi":"10.1016/j.jhydrol.2025.132802","DOIUrl":"10.1016/j.jhydrol.2025.132802","url":null,"abstract":"<div><div>High-quality stormwater management is crucial for sustainable urban development and the protection of aquatic ecosystems, particularly because urbanization and climate-induced extreme events intensify runoff and pollution risks. Although urban stormwater pollution and its potential impacts have been addressed, its impacts on diffuse pollutant loads under compound climate have not been well evaluated. Our study focused on the Bahe River Basin and two river sections at the inlet and outlet of Xi’an city and quantified the impacts of extreme climate and high load risk. The contributions of different precipitation events to pollutant losses were explored using the Soil and Water Assessment tool (SWAT). Cropland was the main source of total nitrogen (TN) and total phosphorus (TP), accounting for 94 % and 91 % of the total pollution during single extreme precipitation events, respectively. However, during compound drought and extreme precipitation events, more than 50 % of the TP pollution originated from urban land. Attribution analysis showed that the heavy precipitation amount (R95P) and frequency (R20MM) were the main factors affecting TN and TP loads, accounting for 65–78 % and 83–88 % of the total impact. In addition, these factors have a greater impact downstream of the city, indicating that urban stormwater pollution increases the response of diffuse loads to climate extremes. The SWAT and copula function were combined to quantify the high-load probabilities under different climatic conditions. The probabilities of the TN and TP load exceeding the top 5 %–30 % were 4 %–19 % and 3 %–21 %, respectively, when the precipitation exceeded the top 20 %, and the probabilities of the TP load downstream of the city were more susceptible to high precipitation. Our study highlights the role of urban stormwater pollution on watershed diffuse loads in addition to point source pollution, with urban development potentially leading to more pollutants being transported to the receiving rivers.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132802"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143386725","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}
Pub Date : 2025-02-08DOI: 10.1016/j.jhydrol.2025.132833
Yanxiao Liu , Zheng Li , Jinbo Zhang , Huaicheng Guo , Xia Jiang , Shuhang Wang , Yang Zhang , Zhenghui Fu
With increasingly significant climate change trends in the next three decades, the ecological security of lake basins is of great significance to the sustainability of biospheres and human societies, and it is requisite to quantify their evolution in the future to evaluate possible impacts and risks. Here, we propose a measurement framework for the response of specific regions to climate change, and make predictions for the future situation of the Qinghai Lake basin, which plays a significant ecological role in northwestern China under three RCP (Representative Concentration Pathways) scenarios by means of machine learning model prediction, geographical identification and experimental simulation. Unlike studies that focus on isolated aspects such as historical data analysis or simple predictions, this framework provides a more comprehensive and dynamic analysis of the entire chain of causes and effects underlying a specific region’s response to climate change, enhancing the overall understanding of this process. Our results show that under the predicted scenarios, water level changes in Qinghai Lake over the next 30 years may lead to land cover changes affecting nearly 200 km2, with the largest exposure of underwater land (∼163.79 km2) occurring under the RCP 4.5 scenario, predominantly meadows and deserts. Nutrient fluxes into the lake are highest under the RCP 4.5 scenario, with up to ∼ 4,141 tons of total nitrogen (TN) and ∼ 276 tons of total phosphorus (TP) expected by 2050, posing risks such as lakeside ecological transformation, water pollution, and eutrophication. The significant influx of nutrients highlights that preventive strategies are necessary to mitigate potential threats and ensuring ecological security and sustainable development for the Qinghai Lake basin and similar sensitive lake systems.
{"title":"Nutrient release to Qinghai Lake from buffer zone evolution driven by climate change","authors":"Yanxiao Liu , Zheng Li , Jinbo Zhang , Huaicheng Guo , Xia Jiang , Shuhang Wang , Yang Zhang , Zhenghui Fu","doi":"10.1016/j.jhydrol.2025.132833","DOIUrl":"10.1016/j.jhydrol.2025.132833","url":null,"abstract":"<div><div>With increasingly significant climate change trends in the next three decades, the ecological security of lake basins is of great significance to the sustainability of biospheres and human societies, and it is requisite to quantify their evolution in the future to evaluate possible impacts and risks. Here, we propose a measurement framework for the response of specific regions to climate change, and make predictions for the future situation of the Qinghai Lake basin, which plays a significant ecological role in northwestern China under three RCP (Representative Concentration Pathways) scenarios by means of machine learning model prediction, geographical identification and experimental simulation. Unlike studies that focus on isolated aspects such as historical data analysis or simple predictions, this framework provides a more comprehensive and dynamic analysis of the entire chain of causes and effects underlying a specific region’s response to climate change, enhancing the overall understanding of this process. Our results show that under the predicted scenarios, water level changes in Qinghai Lake over the next 30 years may lead to land cover changes affecting nearly 200 km<sup>2</sup>, with the largest exposure of underwater land (∼163.79 km<sup>2</sup>) occurring under the RCP 4.5 scenario, predominantly meadows and deserts. Nutrient fluxes into the lake are highest under the RCP 4.5 scenario, with up to ∼ 4,141 tons of total nitrogen (TN) and ∼ 276 tons of total phosphorus (TP) expected by 2050, posing risks such as lakeside ecological transformation, water pollution, and eutrophication. The significant influx of nutrients highlights that preventive strategies are necessary to mitigate potential threats and ensuring ecological security and sustainable development for the Qinghai Lake basin and similar sensitive lake systems.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132833"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378727","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}
Pub Date : 2025-02-08DOI: 10.1016/j.jhydrol.2025.132812
Siqi Gao , Yihe Lü , Xiaohui Jiang
Water resources are the primary limiting factor in restoring vegetation, particularly in dryland regions. Evapotranspiration (ET) is an important link among earth systems, and changes in ET affect water resources’ spatial and temporal distribution as well as the characteristics of changes in vegetation cover. After vegetation restoration projects were implemented in the middle reaches of the Yellow River Basin (MRYRB), issues such as how the ET process has been affected and how the terrestrial available water resources have changed remain largely unknown. To address this knowledge gap, we analyzed the spatial and temporal variability and influencing factors in ET and its components (transpiration (T), interception evaporation loss (EI), and bare-soil evaporation (EB)) in the MRYRB, and thus explored changes in the terrestrial water resources’ effectiveness and availability there. The results showed that from 2000 to 2020, ET showed an increasing trend at the rate of 2.11 mm yr−1. T, EI, and T/ET showed an increasing trend of 3.88 mm yr−1, 0.63 mm yr−1, and 0.0054 yr−1, respectively, and EB showed a decreasing trend of −2.58 mm yr−1. The increase in T was found to be the main reason for the increased ET in the MRYRB. As an effective water resource used in the process of increasing vegetation cover in the MRYRB, T was affected primarily by precipitation (P) (path coefficient of 0.502) and normalized difference vegetation index (NDVI) (path coefficient of 0.409), and the T/ET was affected mainly by NDVI (path coefficient of 0.524). In addition, the principal factor that affected EB and EI was also NDVI, with path coefficients of −0.631 and 0.381, respectively. Except for the direct influence, all factors promote or inhibit ET components indirectly by influencing vegetation growth. It was also found that the increase in P determined the increase in terrestrial available water resources (P-ET) at a rate of 2.44 mm yr−1. Therefore, increased precipitation and vegetation cover synergistically enhanced water resources’ availability and effectiveness. However, it was still necessary to direct attention to the risk of vegetation’s water use under future precipitation changes and promote vegetation restoration subject to water resource limits. The results of the study have important implications for vegetation restoration and water resource management in dryland regions such as the MRYRB under future changing environments.
{"title":"Increased precipitation and vegetation cover synergistically enhanced the availability and effectiveness of water resources in a dryland region","authors":"Siqi Gao , Yihe Lü , Xiaohui Jiang","doi":"10.1016/j.jhydrol.2025.132812","DOIUrl":"10.1016/j.jhydrol.2025.132812","url":null,"abstract":"<div><div>Water resources are the primary limiting factor in restoring vegetation, particularly in dryland regions. Evapotranspiration (ET) is an important link among earth systems, and changes in ET affect water resources’ spatial and temporal distribution as well as the characteristics of changes in vegetation cover. After vegetation restoration projects were implemented in the middle reaches of the Yellow River Basin (MRYRB), issues such as how the ET process has been affected and how the terrestrial available water resources have changed remain largely unknown. To address this knowledge gap, we analyzed the spatial and temporal variability and influencing factors in ET and its components (transpiration (T), interception evaporation loss (EI), and bare-soil evaporation (EB)) in the MRYRB, and thus explored changes in the terrestrial water resources’ effectiveness and availability there. The results showed that from 2000 to 2020, ET showed an increasing trend at the rate of 2.11 mm yr<sup>−1</sup>. T, EI, and T/ET showed an increasing trend of 3.88 mm yr<sup>−1</sup>, 0.63 mm yr<sup>−1</sup><sub>,</sub> and 0.0054 yr<sup>−1</sup>, respectively, and EB showed a decreasing trend of −2.58 mm yr<sup>−1</sup>. The increase in T was found to be the main reason for the increased ET in the MRYRB. As an effective water resource used in the process of increasing vegetation cover in the MRYRB, T was affected primarily by precipitation (P) (path coefficient of 0.502) and normalized difference vegetation index (NDVI) (path coefficient of 0.409), and the T/ET was affected mainly by NDVI (path coefficient of 0.524). In addition, the principal factor that affected EB and EI was also NDVI, with path coefficients of −0.631 and 0.381, respectively. Except for the direct influence, all factors promote or inhibit ET components indirectly by influencing vegetation growth. It was also found that the increase in P determined the increase in terrestrial available water resources (P-ET) at a rate of 2.44 mm yr<sup>−1</sup>. Therefore, increased precipitation and vegetation cover synergistically enhanced water resources’ availability and effectiveness. However, it was still necessary to direct attention to the risk of vegetation’s water use under future precipitation changes and promote vegetation restoration subject to water resource limits. The results of the study have important implications for vegetation restoration and water resource management in dryland regions such as the MRYRB under future changing environments.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132812"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419516","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}
Pub Date : 2025-02-08DOI: 10.1016/j.jhydrol.2025.132822
Yuan Yuan , Yaoming Ma , Chenyi Yang , Jinlei Chen , Gang Xiao , Min Xu
The surface roughness length is important in the parameterization of turbulence in the atmospheric boundary layer for land surface modeling. The accuracy of this parameter directly affects the calculation of momentum and heat exchange between the surface and lower atmosphere, thus affecting simulation performance. Dynamic changes of vegetation have a great impact on roughness length; however, they are rarely considered in parameterization schemes. In this study, a spatial distance index (SDI) scheme which normalizes the LAI, surface temperature, and precipitation into a comprehensive term to describe the vegetation dynamics changes is proposed for the Community Land Model version 5.0 (CLM5.0). It was tested through comparison with the classical schemes and in-situ observations in four typical underlying surfaces (Gobi desert, alpine meadows, alpine grasslands, and alpine wetlands) on the Tibetan Plateau. Several advantages are identified in the SDI scheme, especially in areas of low and high vegetation coverage (Gobi desert and alpine wetlands, respectively). Application of the SDI scheme can help future studies, especially for surface temperature. The deviation of sensible heat flux is reduced by half in the Gobi desert, alpine grassland, and alpine wetlands. Furthermore, water transfer is also better simulated on the Gobi desert and alpine grassland. The future application of the SDI scheme has unique characteristics for the water and the heat exchange at the land–atmosphere interface in the Tibetan Plateau.
{"title":"A new roughness parameterization scheme based on vegetation dynamics and its applicability on the Tibetan Plateau","authors":"Yuan Yuan , Yaoming Ma , Chenyi Yang , Jinlei Chen , Gang Xiao , Min Xu","doi":"10.1016/j.jhydrol.2025.132822","DOIUrl":"10.1016/j.jhydrol.2025.132822","url":null,"abstract":"<div><div>The surface roughness length is important in the parameterization of turbulence in the atmospheric boundary layer for land surface modeling. The accuracy of this parameter directly affects the calculation of momentum and heat exchange between the surface and lower atmosphere, thus affecting simulation performance. Dynamic changes of vegetation have a great impact on roughness length; however, they are rarely considered in parameterization schemes. In this study, a spatial distance index (SDI) scheme which normalizes the LAI, surface temperature, and precipitation into a comprehensive term to describe the vegetation dynamics changes is proposed for the Community Land Model version 5.0 (CLM5.0). It was tested through comparison with the classical schemes and in-situ observations in four typical underlying surfaces (Gobi desert, alpine meadows, alpine grasslands, and alpine wetlands) on the Tibetan Plateau. Several advantages are identified in the SDI scheme, especially in areas of low and high vegetation coverage (Gobi desert and alpine wetlands, respectively). Application of the SDI scheme can help future studies, especially for surface temperature. The deviation of sensible heat flux is reduced by half in the Gobi desert, alpine grassland, and alpine wetlands. Furthermore, water transfer is also better simulated on the Gobi desert and alpine grassland. The future application of the SDI scheme has unique characteristics for the water and the heat exchange at the land–atmosphere interface in the Tibetan Plateau.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132822"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395830","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}
Pub Date : 2025-02-08DOI: 10.1016/j.jhydrol.2025.132844
Qian Yang , Jun Fan , Yuzhu Xing , Boya Tong , Zhanbin Luo
Climate change and drought events pose significant challenges to the water use strategies of forest species in semi-arid regions. This study combined stable isotope and sap flow methods to investigate interspecies differences in effective water uptake among Pinus tabuliformis, Populus simonii, and Ulmus pumila and determine the relationships of these processes to environmental variables and vegetation traits. The species exhibited distinct differences in water uptake. P. tabuliformis and U. pumila primarily absorbed water from the 0–40 cm soil layer, accounting for 53 % and 55 % of total uptake, while P. simonii mainly extracted from 0-80 cm, accounting for 69 %. Based on relative (RWUP) and absolute (AWUP) water uptake, differences in water uptake constraints were observed among species during dry periods in June 2022 and August 2023. P. tabuliformis absorbed an average of 49 % of its water from the 0–40 cm soil layer with an 18 % reduction in transpiration, whereas P. simonii extracted an average of 79 % from the 40–400 cm soil layer with a 37 % reduction and U. pumila accessed average 48 % from the 40–200 cm soil layer with a 43 % reduction. The constrained water uptake in P. tabuliformis was mainly due to less deep fine root biomass, while P. simonii and U. pumila faced constraints from deeper soil moisture availability. After heavy precipitation in the early wet periods, trees absorbed water predominantly from the 0–40 cm soil layer (62 %-81 %), which is crucial for restoring effective water uptake. Notably, the recovery potential for effective water uptake was greater in P. simonii after drought release compared to P. tabuliformis and U. pumila. These findings on species-specific precipitation utilization offer valuable insights for water source management in afforestation efforts.
{"title":"Water use strategies for three dominant tree species in pure plantations of the semi-arid Chinese Loess Plateau","authors":"Qian Yang , Jun Fan , Yuzhu Xing , Boya Tong , Zhanbin Luo","doi":"10.1016/j.jhydrol.2025.132844","DOIUrl":"10.1016/j.jhydrol.2025.132844","url":null,"abstract":"<div><div>Climate change and drought events pose significant challenges to the water use strategies of forest species in semi-arid regions. This study combined stable isotope and sap flow methods to investigate interspecies differences in effective water uptake among <em>Pinus tabuliformis</em>, <em>Populus simonii</em>, and <em>Ulmus pumila</em> and determine the relationships of these processes to environmental variables and vegetation traits. The species exhibited distinct differences in water uptake. <em>P. tabuliformis</em> and <em>U. pumila</em> primarily absorbed water from the 0–40 cm soil layer, accounting for 53 % and 55 % of total uptake, while <em>P. simonii</em> mainly extracted from 0-80 cm, accounting for 69 %. Based on relative (RWUP) and absolute (AWUP) water uptake, differences in water uptake constraints were observed among species during dry periods in June 2022 and August 2023. <em>P. tabuliformis</em> absorbed an average of 49 % of its water from the 0–40 cm soil layer with an 18 % reduction in transpiration, whereas <em>P. simonii</em> extracted an average of 79 % from the 40–400 cm soil layer with a 37 % reduction and <em>U. pumila</em> accessed average 48 % from the 40–200 cm soil layer with a 43 % reduction. The constrained water uptake in <em>P. tabuliformis</em> was mainly due to less deep fine root biomass, while <em>P. simonii</em> and <em>U. pumila</em> faced constraints from deeper soil moisture availability. After heavy precipitation in the early wet periods, trees absorbed water predominantly from the 0–40 cm soil layer (62 %-81 %), which is crucial for restoring effective water uptake. Notably, the recovery potential for effective water uptake was greater in <em>P. simonii</em> after drought release compared to <em>P. tabuliformis</em> and <em>U. pumila</em>. These findings on species-specific precipitation utilization offer valuable insights for water source management in afforestation efforts.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132844"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428192","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}
Pub Date : 2025-02-08DOI: 10.1016/j.jhydrol.2025.132843
J.F. Martín-Rodríguez, M. Mudarra, B. Andreo
Evaluation of transient storage in karst aquifers provides critical insights into factors influencing its hydrogeological behavior. This study assesses the applicability of a new approach that combines two key metrics to characterize internal flow constraints within an aquifer located southern Spain: a quantitative index of the hydrodynamic state (TSV) and hydrogeochemical parameters indicative of groundwater transit time (Total Organic Carbon –TOC-, Mg2+, δ13CTDIC). Transient storage volume –TSV- is here defined as the difference between the cumulative functions derived respectively from daily global aquifer recharge and discharge. A common breakpoint of 3.2 hm3 in the relationships between TSV and discharge from two springs (Algarrobal and Garciago) suggests the presence of a geometric constraint (threshold) affecting groundwater flows, which drastically impact on the hydrodynamic functioning of the aquifer. The existence of this threshold is also deduced from hydrogeochemical transit time indicators. Bellow the TSV breakpoint, only Cornicabra spring exhibits natural responses induced proportionally to the magnitude of the recharge. For TSV values above 3.2 hm3 fast flows are activated within the aquifer with the subsequent effects on the natural responses of all springs, due to the mix of recently infiltrated water with previously stored in the saturated zone. Sensitivity analysis of the equations for estimating potential evapotranspiration (one of the key parameters driving recharge) could further enhance the calculations representativeness. At any case, improvements in the conceptualization through such approaches can be integrated into numerical modeling algorithms, thereby enhancing the model plausibility and alignment with the hydrogeological processes.
{"title":"Transient storage volume and transit time vectors to infer geometrical constraints on the hydrogeological functioning of karst aquifers","authors":"J.F. Martín-Rodríguez, M. Mudarra, B. Andreo","doi":"10.1016/j.jhydrol.2025.132843","DOIUrl":"10.1016/j.jhydrol.2025.132843","url":null,"abstract":"<div><div>Evaluation of transient storage in karst aquifers provides critical insights into factors influencing its hydrogeological behavior. This study assesses the applicability of a new approach that combines two key metrics to characterize internal flow constraints within an aquifer located southern Spain: a quantitative index of the hydrodynamic state (TSV) and hydrogeochemical parameters indicative of groundwater transit time (Total Organic Carbon –TOC-, Mg<sup>2+</sup>, δ<sup>13</sup>C<sub>TDIC</sub>). Transient storage volume –TSV- is here defined as the difference between the cumulative functions derived respectively from daily global aquifer recharge and discharge. A common breakpoint of 3.2 hm<sup>3</sup> in the relationships between TSV and discharge from two springs (Algarrobal and Garciago) suggests the presence of a geometric constraint (threshold) affecting groundwater flows, which drastically impact on the hydrodynamic functioning of the aquifer. The existence of this threshold is also deduced from hydrogeochemical transit time indicators. Bellow the TSV breakpoint, only Cornicabra spring exhibits natural responses induced proportionally to the magnitude of the recharge. For TSV values above 3.2 hm<sup>3</sup> fast flows are activated within the aquifer with the subsequent effects on the natural responses of all springs, due to the mix of recently infiltrated water with previously stored in the saturated zone. Sensitivity analysis of the equations for estimating potential evapotranspiration (one of the key parameters driving recharge) could further enhance the calculations representativeness. At any case, improvements in the conceptualization through such approaches can be integrated into numerical modeling algorithms, thereby enhancing the model plausibility and alignment with the hydrogeological processes.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132843"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419513","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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