Monitoring and Evaluation of Hydrology and Ecology in Mining Areas

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

Deadline for manuscript submissions: closed (10 May 2024) | Viewed by 2108

Special Issue Editors


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Guest Editor
1. Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region, Ministry of Education, Chang’an University, Xi’an, China
2. School of Water and Environment, Chang’an University, Xi’an, China
Interests: soil environmental quality; soil erosion; hydrology ecology; geological disaster
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
1. Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region, Ministry of Education, Chang’an University, 710064 Xi’an, China
2. School of Water and Environment, Chang’an University, 710064 Xi’an, China
Interests: urban flood; flood management; hydrological modeling; water quality analysis; statistical analysis; sustainable water resource management; ecohydrology
Special Issues, Collections and Topics in MDPI journals

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Guest Editor Assistant
School of Architecture, Chang’an University, Xi'an 710064, China
Interests: landscape architecture; urban planning and design; urban ecological environment

Special Issue Information

Dear Colleagues,

In the past few decades, different indicators and models for evaluating ecosystem service function have emerged in order to solve the problems of species loss and habitat fragmentation. Under the influence of natural factors and human activities, land use transformation directly affects the material circulation and energy flow of the ecosystem and changes habitat quality. Understanding the temporal and spatial evolution characteristics of LUCC and assessing habitat quality are aid the effectiveness of ecological environment management, ecological health protection, and green sustainable development. However, the factors affecting the spatial-temporal evolution of the ecological environment and the degree of influence human activities have need to be further quantitatively analyzed. In these cases, simulating and analyzing the changes and driving factors of ecosystem service functions, realizing spatial visualizations of simulation results, and evaluating the quality of the ecological environment are reliable methods to maintain the sustainable development of ecosystems.

Given this scientific framework, we would like to invite scientists involved in this research field to contribute to this Special Issue, which will focus broadly on the analysis, assessment, and/or prediction of changes in the ecological environment caused by natural factors, human activities, or other driving factors, as well as the temporal and spatial transformation of land use, mine-related geological environment monitoring, and ecological restoration. Therefore, manuscripts in the form of case studies on land use change simulation and prediction, habitat quality analysis and assessment, large-scale or regional ecological planning, and landscape pattern optimization strategies, as well as studies that assess trends in ecological environment change and explore temporal and spatial variation in ecosystem service functions at different scales, will be welcomed.

Prof. Dr. Aidi Huo
Prof. Dr. Pingping Luo
Dr. Chunli Zheng
Guest Editors

Assoc. Prof. Lili Liu
Guest Editor Assistant

Manuscript Submission Information

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Keywords

  • habitat quality assessment
  • ecological restoration
  • land use change
  • ecological environment monitoring

Published Papers (3 papers)

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Research

16 pages, 3223 KiB  
Article
Time-Domain Transfer Learning for Accurate Heavy Metal Concentration Retrieval Using Remote Sensing and TrAdaBoost Algorithm: A Case Study of Daxigou, China
by Yun Yang, Qingzhen Tian, Han Bai, Yongqiang Wei, Yi Yan and Aidi Huo
Water 2024, 16(10), 1439; https://doi.org/10.3390/w16101439 - 17 May 2024
Viewed by 401
Abstract
Traditionally, the assessment of heavy metal concentrations using remote sensing technology is sample-intensive, with expensive model development. Using a mining area case study of Daxigou, China, we propose a cross-time-domain transfer learning model to monitor heavy metal pollution using samples collected from different [...] Read more.
Traditionally, the assessment of heavy metal concentrations using remote sensing technology is sample-intensive, with expensive model development. Using a mining area case study of Daxigou, China, we propose a cross-time-domain transfer learning model to monitor heavy metal pollution using samples collected from different time domains. Specifically, spectral indices derived from Landsat 8 multispectral images, terrain, and other auxiliary data correlative to soil heavy metals were prepared. A cross time-domain sample transfer learning model proposed in the paper based on the TrAdaBoost algorithm was used for the Cu content mapping in the topsoil by selective use of soil samples acquired in 2017 and 2019. We found that the proposed model accurately estimated the concentration of Cu in the topsoil of the mining area in 2019 and performed better than the traditional TrAdaBoost algorithms. The goodness of fit (R2) of the test set increased from 0.55 to 0.66; the relative prediction deviation (RPD) increased from 1.37 to 1.76; and finally, the root-mean-square deviation (RMSE), decreased from 8.33 to 7.24 mg·kg−1. The proposed model is potentially applicable to more accurate and inexpensive monitoring of heavy metals, facilitating remediation-related efforts. Full article
(This article belongs to the Special Issue Monitoring and Evaluation of Hydrology and Ecology in Mining Areas)
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21 pages, 8342 KiB  
Article
Environmental Regulation and Stormwater Management Strategies for an Urban River in Northwest China: A Sustainable Approach
by Chen Lu, Jiqiang Lyu, Wang Yan, Peng Guo, Xianghang Fu, Dengrui Mu, Pingping Luo, Yueyan Zhang and Aidi Huo
Water 2024, 16(8), 1115; https://doi.org/10.3390/w16081115 - 14 Apr 2024
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Abstract
Low-impact developments (LIDs) have emerged as effective strategies for mitigating the adverse impacts of urbanization on river environments. This study aims to enhance river environment quality by examining the effects of LIDs and land use/cover change (LUCC) in the context of river environment [...] Read more.
Low-impact developments (LIDs) have emerged as effective strategies for mitigating the adverse impacts of urbanization on river environments. This study aims to enhance river environment quality by examining the effects of LIDs and land use/cover change (LUCC) in the context of river environment and hydrological conditions. Using the Stormwater Management Model (SWMM) in an urban river setting, the study investigates the impact of LIDs on urban river water volume. An analysis of river runoff quality and quantity is conducted, followed by the development of an optimal river water regulation scheme through a multi-objective ecological scheduling model. The results reveal that the incorporation of LIDs can substantially decrease river runoff yield for varying recurrence periods of design rainstorms. Consequently, the flood peak reduction rate ranged from 10% to 18%, and the flood volume experienced a reduction of 10–29% in the study area. The combination of river water regulation, LIDs and LUCC leads to a decrease in river water volume within the lower river channel by up to 47% especially in a typical dry year and dry season, accompanied by a decline in river flow velocity and water self-purification capacity. A risk-based multi-objective stochastic optimization model is employed to ensure sustainable management of urban river runoff in terms of both quantity and quality. This research contributes to the advancement of knowledge in sustainable basin management practices and offers practical insights for policymakers involved in the management of water resources and environmental conservation in semi-arid basins. Full article
(This article belongs to the Special Issue Monitoring and Evaluation of Hydrology and Ecology in Mining Areas)
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12 pages, 3886 KiB  
Article
Habitat Quality Assessment and Driving Factor Analysis of Xiangyu in Feng River Basin Based on InVEST Model
by Aidi Huo, Qi Liu, Zhixin Zhao, Ahmed Elbeltagi, Mohamed EL-Sayed Abuarab and Hossein Ganjidoust
Water 2023, 15(23), 4046; https://doi.org/10.3390/w15234046 - 22 Nov 2023
Viewed by 792
Abstract
Analyzing the evolution of regional habitat quality is an important means to assess the impact of engineering activities on ecosystems. Taking Xiangyu in the Feng River Basin as the study area, the land use change in 1985 and 2022 was analyzed, and the [...] Read more.
Analyzing the evolution of regional habitat quality is an important means to assess the impact of engineering activities on ecosystems. Taking Xiangyu in the Feng River Basin as the study area, the land use change in 1985 and 2022 was analyzed, and the habitat quality and degradation degree were evaluated by using the Integrated Assessment and Tradeoff of Ecosystem Services (InVEST) model. The results showed that from 1985 to 2022, the transfer of land use types in Xiangyu mainly occurred on dry land, bare land, forest land, and industrial land. The area of dry land and bare land converted into industrial land is 10,825.15 m2 and 249,123.09 m2, respectively, and affected by the measures of returning farmland to forest and grassland in Shaanxi Province, the area transferred to forest land reached 371,471.87 m2, mainly from dry land and bare land. The continuous expansion of industrial land led to a significant decline in habitat quality, and the areas with high habitat degradation were concentrated in forest land in a large range, which indicated that forest land was vulnerable to industrial land expansion. Land use change and human engineering activities are the main factors affecting the ecological environment, and limiting the expansion rate of industrial land is the key to protecting the ecological environment. Full article
(This article belongs to the Special Issue Monitoring and Evaluation of Hydrology and Ecology in Mining Areas)
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