Impacts of Climate Change and Human Activities on Runoff Variation of the Intensive Phosphate Mined Huangbaihe River Basin, China

Bo, Huijuan; Dong, Xiaohua; Li, Zhonghua; Hu, Xiaonong; Reta, Gebrehiwet; Wei, Chong; Su, Zhongbo

doi:10.3390/w11102039

Cited by 8 publications

(4 citation statements)

References 56 publications

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“…Climate impacts on secondary sources in the terrestrial environment Greater extremes in precipitation and drought patterns and intensification of extreme precipitation events 147,148 , along with increasing use of freshwater for human and industrial uses 149,150 , will lead to changes in runoff patterns 3 . Such changes will alter the rate and magnitude of washout of any radionuclides and organic and inorganic material from affected watersheds.…”

Section: Review Articlementioning

confidence: 99%

The effect of climate change on sources of radionuclides to the marine environment

Gwynn,

Hatje,

Casacuberta

et al. 2024

Commun Earth Environ

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Climate change interacts with the sources and cycling of contaminants, such as radionuclides, in the environment. In this review, we discuss the implications of climate change impacts on existing and potential future sources of radionuclides associated with human activities to the marine environment. The overall effect on operational releases of radionuclides from the nuclear and non-nuclear sectors will likely be increased interference or prevention of normal operations due to weather-related events. For certain radioactive waste dumped at sea and sunken nuclear submarines, the impact of climate change and ocean acidification on the release of radionuclides and their subsequent fate in the marine environment should be considered further. Fluxes from secondary sources of radionuclides in the marine and terrestrial environment and cryosphere will change in response to climate change impacts such as sea level rise, warming and changes in precipitation patterns. In addition, climate change impacts may increase the risk of releases of radionuclides from operational and legacy wastes on land to the marine environment. Overall, our synthesis highlights that there is a need to understand and assess climate change impacts on sources of radionuclides to the marine environment to meet environmental and management challenges under future climate scenarios.

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Section: Review Articlementioning

confidence: 99%

The effect of climate change on sources of radionuclides to the marine environment

Gwynn,

Hatje,

Casacuberta

et al. 2024

Commun Earth Environ

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“…The runoff, sediment, nutrients, and other processes can be simulated by inputting the terrain, land cover, soil type, weather, pollution source, and other information. The SWAT model has been widely used in runoff simulation, sediment transport simulation, and non-point source pollution prediction since the advantages of easy access to parameters, high calculation efficiency, and continuous simulation [6,53,54]. A schematic diagram of the SWAT model is shown in Figure A1 of Appendix A.…”

Section: Swat Modelmentioning

confidence: 99%

“…Therefore, hydrological models have become the key way to solve such problems [3]. Commonly used hydrological models include the SHE model, SWAT model [4][5][6][7], TOPMODEL model [8][9][10], and the Xinanjiang model [11,12], etc. With further research, various coupling models have been widely used.…”

Section: Introductionmentioning

confidence: 99%

Accuracy Analysis of IMERG Satellite Rainfall Data and Its Application in Long-term Runoff Simulation

Zhang

Ruan

et al. 2020

Water

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Frequent flood disasters have caused serious damage to karst areas with insufficient measured rainfall data, and the analysis of the applicability of satellite rainfall data in runoff simulation is helpful to the local water management. Therefore, the purpose of this study is to analyze the accuracy of IMERG satellite rainfall data and apply it to long-term runoff simulations in a karst area—the Xiajia River basin, China. First, R (correlation coefficient) and POD (probability of detection) are applied to analyze the accuracy of the IMERG data, and the SWAT model is used for runoff simulation. The results show that the accuracy of the original IMERG data is poor (R range from 0.412 to 0.884 and POD range from 47.33 to 100), and the simulation results are “Unsatisfactory” (NSE (Nash-Sutcliffe efficiency coefficient) ranged from 0.17 to 0.32 and RSR (root mean square standard deviation ratio) ranged from 0.81 to 0.92). Therefore, the GDA correction method is used to correct the original IMERG data, and then the accuracy analysis and runoff simulation are carried out. The results show that the accuracy of the corrected IMERG data is better than that of the original data (R range from 0.886 to 0.987 and POD range from 94.08 to 100), and the simulation results of the corrected IMERG data are “Satisfactory” (NSE is over 0.55 and RSR is approximately 0.65). Therefore, the corrected data have a certain applicability in long-term continuous runoff simulations.

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“…The challenge lies in the fact that runoff is influenced not only by the physical elements of watersheds and rainfall regimes but also by various spatial and temporal changes (Song 2020). Climate change and anthropogenic activities are considered as two major factors driving changes in the hydrological process, especially infiltration and runoff (Bo et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Predicting LULC changes and assessing their impact on surface runoff with machine learning and remote sensing data.

Riche,

Drias,

Ricci

et al. 2023

Preprint

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This study employs an approach to examine the influence of urbanization-induced land use changes on surface runoff. The research leverages the SCS-CN method, integrating remote sensing and machine learning, to analyze land use and cover (LULC) changes over the years 2000 to 2040. Initial land use classification (2000–2020) utilizes the SVM algorithm, while a novel temporal approach is applied to predict LULC for the years 2025, 2030, and 2040. The accuracy of the LULC prediction model is demonstrated to be 85.05% using the Random Forest (RF) algorithm. Notably, built-up areas increase from 11.73% (2000) to 32.96% (2040), whereas cultivated land and grassland decrease from 46.50–26.67%. The study further utilizes the SCS-CN method to model runoff for precipitation return periods of 5, 10, and 20 years, calculating Curve Number (CN) values. The results reveal variations in runoff patterns across different LULC classes and time periods. Higher return periods are associated with expanded runoff areas, with built-up areas contributing to runoff, while forests mitigate it. The study identifies that land factors, such as interception and permeability, exhibit limited influence during intense rainfall events, primarily due to capacity and saturation constraints. These findings have important implications for water resource management and strategies related to flood risk mitigation, benefiting governmental officials, planners, environmental experts, and hydraulic engineers. It's worth noting that a case study in Algeria was selected for its data availability.

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Impacts of Climate Change and Human Activities on Runoff Variation of the Intensive Phosphate Mined Huangbaihe River Basin, China

Cited by 8 publications

References 56 publications

The effect of climate change on sources of radionuclides to the marine environment

The effect of climate change on sources of radionuclides to the marine environment

Accuracy Analysis of IMERG Satellite Rainfall Data and Its Application in Long-term Runoff Simulation

Predicting LULC changes and assessing their impact on surface runoff with machine learning and remote sensing data.

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