Climate Change Impacts on Land Surface, Hydrological Processes and Water Management

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water and Climate Change".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 20123

Special Issue Editors

China Institute of Water Resources and Hydropower Research, Beijing, China
Interests: modelling of water cycle in watersheds; climate change and hydrological response to human activities; land use change impact on hydrology; hydroclimate; ecohydrology
School of Geographical Sciences, Southwest University, Chongqing 400715, China
Interests: hydrological modeling; climate change and land use/land cover change impact on water resources; eco-hydrology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the context of the increasing climate variability and anthropogenic stresses, changes to the water cycle and the underlying land surface have widespread vast concern regarding water resources security and the corresponding ecological evolution. Investigations into the changes and driving mechanisms of the water cycle and water resources at the catchment or regional scales have become one of the most basic issues for global sustainable development.

In recent years, with the development of computer science, remote sensing technology, and climatic models, climate change impacts on land surface, hydrological processes, and water management have been further studied, alongside the emegence of new perspectives and understandings. Therefore, this Special Issue aims to represent the latest advances of this scientific topic. We welcome contributions in all fields relevant to climate change, hydrometeorological modeling, and water resources management, as well as emerging technologies and models. The specific topics of interest include, but are not limited to, the following:

  • Climate change impacts on land surface;
  • Hydrological modeling of the effects of land use/land cover change;
  • Hydrological response to climate change;
  • Water resources management;
  • Application of regional climate model;
  • Catchment flood and drought;
  • Remote sensing hydrology;
  • Ecological response to hydrological change;
  • Vegetation–atmosphere interaction.

Dr. Chuanzhe Li
Dr. Xuchun Ye
Guest Editors

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Keywords

  • climate change
  • land use/land cover change
  • hydrologic and ecologic modeling
  • hydrometeorology
  • ecohydrology
  • hydrological processes
  • water management

Published Papers (13 papers)

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Research

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18 pages, 12817 KiB  
Article
The Spatial and Temporal Variability of the Blue–Green Spatial Structures of the South Dongting Lake Wetland Areas Amidst Climate Change, including Its Relationship with Meteorological Factors
Water 2024, 16(2), 209; https://doi.org/10.3390/w16020209 - 06 Jan 2024
Viewed by 666
Abstract
In recent years, the water level of the Dongting Lake (DTL) has been continuously low, and the wetland area and landscape pattern have changed significantly. Considering the obvious spatial heterogeneity of water regime changes in different waters of the DTL, this paper takes [...] Read more.
In recent years, the water level of the Dongting Lake (DTL) has been continuously low, and the wetland area and landscape pattern have changed significantly. Considering the obvious spatial heterogeneity of water regime changes in different waters of the DTL, this paper takes two core areas of the South Dongting Lake Nature Reserve (SDLNR) as study areas and analyzes the spatial distribution characteristics of the wetland blue–green landscape patterns by using remote sensing image data and hydrological and meteorological data. The multi-scale correlation between runoff, precipitation, temperature, and evapotranspiration in the SDLNR was studied via cross-wavelet transform analysis. The results show the following: (1) The change in the blue–green spatial patterns in different regions in different periods is inconsistent, and this inconsistency is related to the topography, climate, and human activities in each region; (2) there are seasonal fluctuations in precipitation, air temperature, and evapotranspiration in the SDLNR. Among them, the annual mean temperature shows a rising trend and passes the significance test with 95% confidence, while the annual mean precipitation and annual mean evapotranspiration show no significant change trend; and (3) our Pearson correlation analysis and cross-wavelet change results show that precipitation and temperature are strongly correlated with runoff, with a resonance period of 8–16 months, while the correlation between evapotranspiration and runoff is not significant. We recommend that policymakers establish an effective early warning system and make plans to store water through micro-terrain transformation in possible climate change treatments and strategies. Full article
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14 pages, 11723 KiB  
Article
Changes in the Urban Hydrological Cycle of the Future Using Low-Impact Development Based on Shared Socioeconomic Pathway Scenarios
Water 2023, 15(22), 4002; https://doi.org/10.3390/w15224002 - 17 Nov 2023
Viewed by 846
Abstract
Representative Concentration Pathway (RCP) scenarios have been used for various studies in the field of climate change. In this regard, the Shared Socioeconomic Pathway (SSP) scenario has been newly introduced to examine climate change impacts, but relevant research is still insufficient. For this [...] Read more.
Representative Concentration Pathway (RCP) scenarios have been used for various studies in the field of climate change. In this regard, the Shared Socioeconomic Pathway (SSP) scenario has been newly introduced to examine climate change impacts, but relevant research is still insufficient. For this reason, new SSP scenarios with a combination of Low-Impact Development (LID) techniques are applied to predict rainfall-runoff efficiency and hydrological variation. The inter-model variability in the monthly average precipitation for each GCM according to new SSP scenarios under future climate was investigated. Based on the RCP 4.5 and RCP 8.5 scenarios, the results show precipitation changes with an increase of 4.8% and 12.3%, respectively. Furthermore, precipitation projections under SSP2-4.5 and SSP5-8.5 scenarios are predicted to increase by 13.9% and 20.6%, respectively, indicating that the magnitude of precipitation increases with new climate change scenarios. The Storm Water Management Model (SWMM) during the future period indicated that LID applications will reduce runoff compared with scenarios with no LID application. In particular, the introduction of permeable pavement and infiltration trenches revealed the best runoff reduction performance among the combinations of LID techniques considered. In addition, this study projected changes in the urban hydrological cycle for the climate over the next 30 years to reflect the implementation of urban hydrological cycle plans, which take approximately 10 years. Overall, it was found that, in the future, LID applications will contribute to improving the sustainability of the urban hydrological cycle of the study area. The results of our study can provide future directions for water management strategies in Korea. Full article
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26 pages, 5717 KiB  
Article
Simulation of the Potential Impacts of Projected Climate and Land Use Change on Runoff under CMIP6 Scenarios
Water 2023, 15(19), 3421; https://doi.org/10.3390/w15193421 - 28 Sep 2023
Cited by 12 | Viewed by 1400
Abstract
Assessing the impacts of climate change and land use/land cover changes on water resources within a catchment is essential because it helps us understand how these dynamic factors affect the quantity, quality, and availability of freshwater. This knowledge is crucial for making informed [...] Read more.
Assessing the impacts of climate change and land use/land cover changes on water resources within a catchment is essential because it helps us understand how these dynamic factors affect the quantity, quality, and availability of freshwater. This knowledge is crucial for making informed decisions about water management, conservation, and adaptation strategies, especially in regions facing increasing environmental uncertainties and challenges to water resource sustainability. In Pakistan’s Kunhar River Basin (KRB), this investigation explores the potential effects of shifting land use/land cover (LULC), and climate on stream flows. The SWAT (Soil and Water Assessment Tool), a semi-distributed hydrological model, and the most recent Coupled Model Intercomparison Project phase 6 (CMIP6) dataset from multiple global climate models (GCMs) were used to evaluate these effects. The temperature and precipitation data were downscaled using the CMhyd software; for both shared socioeconomic pathways (SSP2 and SSP5), the top-performing GCM out of four was required to produce downscaled precipitation and temperature predictions while taking future land use characteristics into account. The output from the chosen GCM indicated that by the conclusion of the 21st century, relative to the reference period (1985–2014), the study area’s average monthly precipitation, highest temperature, and lowest temperature will be increasing. Precipitation is anticipated to increase between 2015 and 2100 by 20.5% and 29.1% according to the SSP2 and SSP5 scenarios, respectively. This study’s findings, which emphasize the need for project planners and managers taking into account the effects of climate and land cover changes in their management techniques, show that climate change can have a significant impact on the changing seasons of flows in the Kunhar River basin. Full article
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23 pages, 4208 KiB  
Article
The Improved Reservoir Module of SWAT Model with a Dispatch Function and Its Application on Assessing the Impact of Climate Change and Human Activities on Runoff Change
Water 2023, 15(14), 2620; https://doi.org/10.3390/w15142620 - 19 Jul 2023
Cited by 1 | Viewed by 1135
Abstract
Climate change and human activities significantly impact the hydrological cycle, particularly in regions with numerous large-scale reservoirs. Recognizing the limitations of the reservoir module in the original SWAT model, this study presents an improved reservoir module based on a dispatch function to enhance [...] Read more.
Climate change and human activities significantly impact the hydrological cycle, particularly in regions with numerous large-scale reservoirs. Recognizing the limitations of the reservoir module in the original SWAT model, this study presents an improved reservoir module based on a dispatch function to enhance runoff simulation. Its performance is validated by simulating daily runoff in the Jinsha River Basin, China. The scenario simulation approach is employed to quantitatively analyze the influences of climate change and human activities on runoff. And downscaled Global Climate Models (GCMs) are utilized to predict runoff for the next three decades. The results show that (1) the improved SWAT model outperforms the original model in runoff simulation; (2) during the test period, reservoir regulations caused a reduction of 26 m3/s in basin outlet runoff, while climate change led to an increase of 272 m3/s; and (3) future changes in basin outlet runoff over the next 30 years exhibit a high level of uncertainty, ranging from −5.6% to +11.0% compared to the base period. This study provides valuable insights into the hydrological impacts of climate change and human activities, highlighting the importance of incorporating an improved reservoir module in hydrological modeling for more accurate predictions and assessments. Full article
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16 pages, 2517 KiB  
Article
Spatial Equilibrium Evaluation of the Water Resources in Tai’an City Based on the Lorenz Curve and Correlation Number
Water 2023, 15(14), 2617; https://doi.org/10.3390/w15142617 - 19 Jul 2023
Cited by 3 | Viewed by 821
Abstract
Water resource spatial equilibrium evaluations provide the bases for water resource utilization and allocation. To analyze the regional spatial water resource matching balance, this study constructed a water resource spatial matching model based on the Gini coefficient and Lorenz curve methods. To further [...] Read more.
Water resource spatial equilibrium evaluations provide the bases for water resource utilization and allocation. To analyze the regional spatial water resource matching balance, this study constructed a water resource spatial matching model based on the Gini coefficient and Lorenz curve methods. To further reflect the influence of each subregion on the whole region, we combined the correlation number and Gini coefficient methods to propose the water resource spatial balance evaluation method. Herein, we constructed nine Lorenz curve pairs that matched the total water resources and total water use with cultivated land area, population, GDP (Gross Domestic Product) of the secondary industry, GDP (Gross Domestic Product) of the tertiary industry, and agricultural irrigation water consumption. Set pair analysis theory was applied to calculate sample correlation numbers and determine equilibrium levels, which were then compared to Gini coefficient method-based results for Tai’an city evaluation. The results showed that the total water consumption spatial equilibrium in Tai’an city from 2011 to 2020 was favorable, while the total water resource results for Tai’an city greatly differed, especially the balance between total water resources and GDPs of the secondary and tertiary industries, which should be further improved. In practice, quantitative analysis of the water resource spatial equilibrium state in Tai’an city is important for efficient water resource utilization and coordinated development of water resources and economic and social environments. Full article
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25 pages, 4942 KiB  
Article
Investigating the Effects of Climate and Land Use Changes on Rawal Dam Reservoir Operations and Hydrological Behavior
Water 2023, 15(12), 2246; https://doi.org/10.3390/w15122246 - 15 Jun 2023
Cited by 6 | Viewed by 1892
Abstract
In order to assess the effects of climate change and land use change on Rawal Dam, a major supply of water for Rawalpindi and Islamabad, this study uses hydrological modeling at the watershed scale. The HEC-HMS model was used to simulate the hydrological [...] Read more.
In order to assess the effects of climate change and land use change on Rawal Dam, a major supply of water for Rawalpindi and Islamabad, this study uses hydrological modeling at the watershed scale. The HEC-HMS model was used to simulate the hydrological response in the Rawal Dam catchment to historical precipitation. The calibrated model was then used to determine how changes in land use and climate had an impact on reservoir inflows. The model divided the Rawal Dam watershed into six sub-basins, each with unique features, and covered the entire reservoir’s catchment area using data from three climatic stations (Murree, Islamabad Zero Point and Rawal Dam). For the time spans of 2003–2005 and 2006–2007, the model was calibrated and verified, respectively. An excellent fit between the observed and predicted flows was provided by the model. The GCM (MPI-ESM1-2-HR) produced estimates of temperature and precipitation under two Shared Socioeconomic Pathways (SSP2 and SSP5) after statistical downscaling with the CMhyd model. To evaluate potential effects of climate change and land use change on Rawal Dam, these projections, along with future circumstances for land use and land cover, were fed to the calibrated model. The analysis was carried out on a seasonal basis over the baseline period (1990–2015) and over future time horizon (2016–2100), which covers the present century. The findings point to a rise in precipitation for both SSPs, which is anticipated to result in an increase in inflows throughout the year. SSP2 projected a 15% increase in precipitation across the Rawal Dam catchment region until the end of the twenty-first century, while SSP5 forecasted a 17% increase. It was determined that higher flows are to be anticipated in the future. The calibrated model can also be utilized successfully for future hydrological impact assessments on the reservoir, it was discovered. Full article
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21 pages, 7306 KiB  
Article
Wavelet Analysis and the Information Cost Function Index for Selection of Calibration Events for Flood Simulation
Water 2023, 15(11), 2035; https://doi.org/10.3390/w15112035 - 27 May 2023
Viewed by 1278
Abstract
Globally, floods are a prevalent type of natural disaster. Simulating floods is a critical component in the successful implementation of flood management and mitigation strategies within a river basin or catchment area. Selecting appropriate calibration data to establish a reliable hydrological model is [...] Read more.
Globally, floods are a prevalent type of natural disaster. Simulating floods is a critical component in the successful implementation of flood management and mitigation strategies within a river basin or catchment area. Selecting appropriate calibration data to establish a reliable hydrological model is of great importance for flood simulation. Usually, hydrologists select the number of flood events used for calibration depending on the catchment size. Currently, there is no numerical index to help hydrologists quantitatively select flood events for calibrating the hydrological models. The question is, what is the necessary and sufficient amount (e.g., 10 events) of calibration flood events that must be selected? This study analyses the spectral characteristics of flood data in Sequences before model calibration. The absolute best set of calibration data is selected using an entropy-like function called the information cost function (ICF), which is calculated from the discrete wavelet transform (DWT) decomposition results. Given that the validation flood events have already been identified, we presume that the greater the similarity between the calibration dataset and the validation dataset, the higher the performance of the hydrological model should be after calibration. The calibration datasets for the Tunxi catchment in southeast China were derived from 21 hourly flood events, and the calibration datasets were generated by arranging 14 flood events in sequences from 3 to 14 (i.e., a Sequence of 3 with 12 sets (set 1 = flood events 1, 2, 3; set 2 = flood events 2, 3, 4, …, and so on)), resulting in a total of 12 sequences and 78 sets. With a predetermined validation set of 7 flood events and the hydrological model chosen as the Hydrologic Engineering Center (HEC–HMS) model, the absolute best calibration flood set was selected. The best set from the Sequence of 10 (set 4 = S10′) was found to be the absolute best calibration set of flood events. The potential of the percentile energy entropy was also analyzed for the best calibration sets, but the ICF was the most consistent index to reveal the ranking based on similarity with model performance. The proposed ICF index in this study is helpful for hydrologists to use data efficiently with more hydrological data obtained in the new era of big data. This study also demonstrates the possibility of improving the effectiveness of utilizing calibration data, particularly in catchments with limited data. Full article
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26 pages, 5873 KiB  
Article
A WRF/WRF-Hydro Coupled Forecasting System with Real-Time Precipitation–Runoff Updating Based on 3Dvar Data Assimilation and Deep Learning
Water 2023, 15(9), 1716; https://doi.org/10.3390/w15091716 - 28 Apr 2023
Viewed by 1861
Abstract
This study established a WRF/WRF-Hydro coupled forecasting system for precipitation–runoff forecasting in the Daqing River basin in northern China. To fully enhance the forecasting skill of the coupled system, real-time updating was performed for both the WRF precipitation forecast and WRF-Hydro forecasted runoff. [...] Read more.
This study established a WRF/WRF-Hydro coupled forecasting system for precipitation–runoff forecasting in the Daqing River basin in northern China. To fully enhance the forecasting skill of the coupled system, real-time updating was performed for both the WRF precipitation forecast and WRF-Hydro forecasted runoff. Three-dimensional variational (3Dvar) multi-source data assimilation was implemented using the WRF model by incorporating hourly weather radar reflectivity and conventional meteorological observations to improve the accuracy of the forecasted precipitation. A deep learning approach, i.e., long short-term memory (LSTM) networks, was adopted to improve the accuracy of the WRF-Hydro forecasted flow. The results showed that hourly data assimilation had a positive impact on the range and trends of the WRF precipitation forecasts. The quality of the WRF precipitation outputs had a significant impact on the performance of WRF-Hydro in forecasting the flow at the catchment outlet. With the runoff driven by precipitation forecasts being updated by 3Dvar data assimilation, the error of flood peak flow was decreased by 3.02–57.42%, the error of flood volume was decreased by 6.34–39.30%, and the Nash efficiency coefficient was increased by 0.15–0.52. The implementation of LSTM can effectively reduce the forecasting errors of the coupled system, particularly those of the time-to-peak and peak flow volumes. Full article
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17 pages, 3103 KiB  
Article
Streamflow Simulation with High-Resolution WRF Input Variables Based on the CNN-LSTM Hybrid Model and Gamma Test
Water 2023, 15(7), 1422; https://doi.org/10.3390/w15071422 - 06 Apr 2023
Cited by 3 | Viewed by 1710
Abstract
Streamflow modelling is one of the most important elements for the management of water resources and flood control in the context of future climate change. With the advancement of numerical weather prediction and modern detection technologies, more and more high-resolution hydro-meteorological data can [...] Read more.
Streamflow modelling is one of the most important elements for the management of water resources and flood control in the context of future climate change. With the advancement of numerical weather prediction and modern detection technologies, more and more high-resolution hydro-meteorological data can be obtained, while traditional physical hydrological models cannot make full use of them. In this study, a hybrid deep learning approach is proposed for the simulation of daily streamflow in two mountainous catchments of the Daqing River Basin, northern China. Two-dimensional high-resolution (1 km) output data from a WRF model were used as the model input, a convolutional neural network (CNN) model was used to extract the physical and meteorological characteristics of the catchment at a certain time, and the long short-term memory (LSTM) model was applied to simulate the streamflow using the time-series data extracted by the CNN model. To reduce model input noise and avoid overfitting, the Gamma test method was adopted and the correlations between the input variables were checked to select the optimal combination of input variables. The performance of the CNN-LSTM models was acceptable without using the Gamma test (i.e., with all WRF input variables included), with NSE and RMSE values of 0.9298 and 9.0047 m3/s, respectively, in the Fuping catchment, and 0.8330 and 1.1806 m3/s, respectively, in the Zijingguan catchment. However, it was found that the performance of the model could be significantly improved by the use of the Gamma test. Using the best combination of input variables selected by the Gamma test, the NSE of the Fuping catchment increased to 0.9618 and the RMSE decreased to 6.6366 m3/s, and the NSE of the Zijingguan catchment increased to 0.9515 and the RMSE decreased to 0.6366 m3/s. These results demonstrate the feasibility of the CNN-LSTM approach for flood streamflow simulation using WRF-downscaled high-resolution data. By using this approach to assess the potential impacts of climate change on streamflow with the abundant high-resolution meteorological data generated by different climate scenarios, water managers can develop more effective strategies for managing water resources and reducing the risks associated with droughts and floods. Full article
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24 pages, 8867 KiB  
Article
Appraisal of Land Cover and Climate Change Impacts on Water Resources: A Case Study of Mohmand Dam Catchment, Pakistan
Water 2023, 15(7), 1313; https://doi.org/10.3390/w15071313 - 27 Mar 2023
Cited by 8 | Viewed by 2270
Abstract
Land cover change (LCC) and climate change (CC) impacts on streamflow in high elevated catchments are a great challenge to sustainable management and the development of water resources. This study evaluates the possible future impacts of both land cover and climate change on [...] Read more.
Land cover change (LCC) and climate change (CC) impacts on streamflow in high elevated catchments are a great challenge to sustainable management and the development of water resources. This study evaluates the possible future impacts of both land cover and climate change on the streamflows in the Mohmand Dam catchment, Pakistan, by utilizing the semi-distributed hydrological model known as the Soil and Water Assessment Tool (SWAT), along with the latest Coupled Model Intercomparison Project phase 6 (CMIP6) dataset of different global climate models (GCMs). The downscaling of the precipitation and temperature data was performed by the CMhyd software. The downscaled precipitation and temperature projections from the best performing GCM, out of four GCMs, under two shared socioeconomic pathways (SSP2 and SSP5) and future land cover conditions were forced in a calibrated hydrological model (SWAT model). Compared to the baseline period (1990–2015), the outputs from the selected GCM indicated an increase in the average monthly precipitation, and the maximum and minimum temperature in the study area under both the SSP2 and SSP5 scenarios, by the end of the 21st century. It is expected that the increase in precipitation for the period 2016–2100 is 10.5% and 11.4% under the SSP2 and SSP5 scenarios, respectively. Simulated results from the SWAT model showed significant impacts from the projected climate and land cover changes on Mohmand Dam flows that include: (a) an increase in the overall mean annual flow ranging from 13.7% to 34.8%, whereas the mean monthly flows of June, July and August decreased, and (b) a shift in the peak flows in the Mohmand catchment from July to June. It is concluded that the projected climate changes can substantially influence the seasonality of flows at the Mohmand Dam site. Climate and land cover change impacts are significant, so project planners and managers must include CC and LCC impacts in the proposed operational strategy. Full article
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20 pages, 8375 KiB  
Article
Evaluation of Water Resources Utilization Efficiency Based on DEA and AHP under Climate Change
Water 2023, 15(4), 718; https://doi.org/10.3390/w15040718 - 11 Feb 2023
Cited by 7 | Viewed by 2007
Abstract
In the context of climate change, the problem of water scarcity is becoming increasingly serious, and improving the efficiency of water resources use is an important measure to alleviate this problem. The evaluation of water resources utilization efficiency has become the basis of [...] Read more.
In the context of climate change, the problem of water scarcity is becoming increasingly serious, and improving the efficiency of water resources use is an important measure to alleviate this problem. The evaluation of water resources utilization efficiency has become the basis of water resource management. Data envelopment analysis (DEA) and analytic hierarchy process (AHP) are widely used in the evaluation of water resources utilization efficiency. However, one of these methods is mostly used for evaluation, which cannot reflect the influence of both objective and subjective factors. Therefore, in this study, we propose a water resources utilization efficiency index (WEI) to evaluate the water resources utilization efficiency of each region in the Tumen River Basin (TRB), combining both DEA and AHP methods. Firstly, the DEA-CCR model was used to quantify domestic, agricultural and industrial water use efficiency in the TRB. The DEA-BCC model was used to analyze the main influences on water use efficiency in each sector. Secondly, the WEI was constructed by assigning weights using the AHP model based on the importance of each water use sector. The results show that the WEI values for most areas within the TRB trended upwards between 2014 and 2019. In particular, domestic water use efficiency ranged from 0.294 to 0.775, while agricultural and industrial water use efficiency ranged from 0.039 to 0.054 and 0.031 to 0.375, respectively. Technical efficiency is the main factor influencing water use efficiency in TRB. This study could provide a basis for water resource management and mitigation of water scarcity in the context of climate change. Full article
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15 pages, 4355 KiB  
Article
Study on Interaction between Surface Water and Groundwater in Typical Reach of Xiaoqing River Based on WEP-L Model
Water 2023, 15(3), 492; https://doi.org/10.3390/w15030492 - 26 Jan 2023
Cited by 2 | Viewed by 2500
Abstract
Surface water and groundwater (SW-GW) are an inseparable whole, having a tightly coupled hydraulic relationship and frequent inter-transformation. As such, the quantitative calculation of water exchange between SW-GW is a difficult challenge. To address this issue, we propose the use of a physically [...] Read more.
Surface water and groundwater (SW-GW) are an inseparable whole, having a tightly coupled hydraulic relationship and frequent inter-transformation. As such, the quantitative calculation of water exchange between SW-GW is a difficult challenge. To address this issue, we propose the use of a physically based and distributed hydrological model, called WEP-L, in order to analyze the effects of the SW-GW interaction and its spatiotemporal variation characteristics in the Xiaoqing River basin. We demonstrate that the SW-GW interaction is significantly affected by season. The simulated annual average exchange volume of SW-GW above the control section of Huangtaiqiao Station from 1980 to 2020 is found to be 54.79 m3/s. The exchange volumes of SW-GW in the wet and dry season are 28.69 m3/s and 13.46 m3/s, respectively, accounting for 48.75% and 22.87% of the whole year. In addition, considering two types of climate change scenarios, the exchange capacity of SW-GW increases by 0.42m3/s when the rainfall increases by 5%, while the exchange capacity decreases by only 0.2 m3/s when the temperature increases by 0.2 °C. This study provides insights for the quantification of the SW-GW interaction at the regional scale, which will benefit our understanding of the water cycle and evolution of water resources in Xiaoqing River basin. Full article
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Review

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16 pages, 3254 KiB  
Review
Review on Zinc Isotopes in River Systems: Distribution and Application
Water 2024, 16(1), 87; https://doi.org/10.3390/w16010087 - 25 Dec 2023
Viewed by 805
Abstract
Zinc (Zn) is an essential trace element widely present in rivers and plays a crucial role in ecosystems. Human activities have led to the extensive migration and dissemination of Zn in the environment. When the accumulation of Zn in rivers reaches excessive levels, [...] Read more.
Zinc (Zn) is an essential trace element widely present in rivers and plays a crucial role in ecosystems. Human activities have led to the extensive migration and dissemination of Zn in the environment. When the accumulation of Zn in rivers reaches excessive levels, it transforms into a potentially harmful contaminant. Consequently, tracing Zn’s origin by its isotope ratios (δ66Zn) from natural and anthropogenic sources is essential for the management of and safeguarding against river pollution and comprehending Zn behavior in rivers as well. This review presents the advancements in Zn isotope research in river environments, including a summary of Zn isotope measurement, the distribution and controlling factors (mineral adsorption, precipitation, and biological effects) of Zn isotopes, and the applications of Zn isotopes in rivers. The median δ66Zn values for uncontaminated river water and suspended particulate matter (SPM) were 0.37‰ and 0.22‰, respectively, close to the bulk silicate Earth (BSE) value of 0.28 ± 0.05‰. With respect to the contaminated river, δ66Zn falls within −0.73‰ to 1.77‰, with it being heavily influenced by anthropogenic sources, such as the electroplating and metal processing industries. Apart from contamination identification, this review summarizes the river material exchange process and the δ66Zn values of rainwater (−0.2‰~0.38‰), groundwater (−0.13‰~1.4‰), lake water (−0.66‰~0.21‰), and seawater (−1.1‰~0.9‰), which facilitates a holistic understanding of the Zn cycle and isotope fractionation in the river system. In conclusion, Zn isotopes are an effective tool for tracing pollution sources and Zn migration processes, with enormous unexplored potential. Therefore, this review finally summarizes some challenges and future directions in current research on Zn isotopes. Full article
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