1
|
Li X, Zhang F, Shi J, Chan NW, Cai Y, Cheng C, An C, Wang W, Liu C. Analysis of surface water area dynamics and driving forces in the Bosten Lake basin based on GEE and SEM for the period 2000 to 2021. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:9333-9346. [PMID: 38191729 DOI: 10.1007/s11356-023-31702-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 12/20/2023] [Indexed: 01/10/2024]
Abstract
As an inland dryland lake basin, the rivers and lakes within the Lake Bosten basin provide scarce but valuable water resources for a fragile environment and play a vital role in the development and sustainability of the local societies. Based on the Google Earth Engine (GEE) platform, combined with the geographic information system (GIS) and remote sensing (RS) technology, we used the index WI2019 to extract and analyze the water body area changes of the Bosten Lake basin from 2000 to 2021 when the threshold value is -0.25 and the slope mask is 8°. The driving factors of water body area changes were also analyzed using the partial least squares-structural equation model (PLS-SEM). The result shows that in the last 20 years, the area of water bodies in the Bosten Lake basin generally fluctuated during the dry, wet, and permanent seasons, with a decreasing trend from 2000 to 2015 and an increasing trend between 2015 and 2019 followed by a steadily decreasing trend afterward. The main driver of the change in wet season water bodies in the Bosten Lake basin is the climatic factors, with anthropogenic factors having a greater influence on the water body area of dry season and permanent season than that of wet season. Our study achieved an accurate and convenient extraction of water body area and drivers, providing up-to-date information to fully understand the spatial and temporal variation of surface water body area and its drivers in the basin, which can be used to effectively manage water resources.
Collapse
Affiliation(s)
- Xingyou Li
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830017, China
| | - Fei Zhang
- College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, 321004, China.
| | - Jingchao Shi
- Department of Earth Sciences, The University of Memphis, Memphis, TN, 38152, USA
| | - Ngai Weng Chan
- GeoInformatic Unit, Geography Section, School of Humanities, Universiti Sains Malaysia, 11800, Penang, USM, Malaysia
| | - Yunfei Cai
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830017, China
| | - Chunyan Cheng
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830017, China
| | - Changjiang An
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830017, China
| | - Weiwei Wang
- College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, 830017, China
| | - Changjiang Liu
- College of Geographic Science and Tourism, Xinjiang Normal University, Urumqi, 830054, China
| |
Collapse
|
2
|
Wei C, Wang X, Cai J, Liao Z, Li C, Liu Q. A new framework combining hydrological connectivity metrics and morphological spatial pattern analysis for the hydrological connectivity evaluation of wetlands. INTEGRATED ENVIRONMENTAL ASSESSMENT AND MANAGEMENT 2022. [PMID: 36314691 DOI: 10.1002/ieam.4708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Revised: 10/21/2022] [Accepted: 10/24/2022] [Indexed: 06/16/2023]
Abstract
The quantitative evaluation of wetland hydrological connectivity is essential to the hydrological connectivity restoration-oriented ecological conservation and environmental management of wetlands. We proposed a framework to evaluate wetland hydrological connectivity with a combination of hydrological connectivity metrics and morphological spatial pattern analysis and recognized potential sites and links that had been generally overlooked in previous studies. Variations in hydrological connectivity revealed a decreasing trend followed by a gradual recovery from the critical time node of 2005 in Baiyangdian Lake. The core, one of the most important landscape types, played a dominant role in maintaining wetland hydrological connectivity at both temporal and spatial scales, and its variations matched those of hydrological connectivity. More importantly, we redressed the conventional ignorance of peripheral patches and links and recognized their importance in improving the hydrological connectivity of wetlands. The proposed framework provides an effective and practical tool for the hydrological connectivity evaluation of wetlands, expanding new insights into maintaining the health and integrity of wetland ecosystems. Integr Environ Assess Manag 2022;00:1-15. © 2022 SETAC.
Collapse
Affiliation(s)
- Chenxi Wei
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China
- Key Laboratory for Water and Sediment Sciences of Ministry of Education, School of Environment, Beijing Normal University, Beijing, China
| | - Xuan Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China
- Key Laboratory for Water and Sediment Sciences of Ministry of Education, School of Environment, Beijing Normal University, Beijing, China
| | - Jianying Cai
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China
- Key Laboratory for Water and Sediment Sciences of Ministry of Education, School of Environment, Beijing Normal University, Beijing, China
| | - Zhenmei Liao
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China
- Key Laboratory for Water and Sediment Sciences of Ministry of Education, School of Environment, Beijing Normal University, Beijing, China
| | - Chunhui Li
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China
- Key Laboratory for Water and Sediment Sciences of Ministry of Education, School of Environment, Beijing Normal University, Beijing, China
| | - Qiang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China
- Key Laboratory for Water and Sediment Sciences of Ministry of Education, School of Environment, Beijing Normal University, Beijing, China
| |
Collapse
|
3
|
Dynamic Analysis in Surface Water Area and Its Driving Factors in Northeast China from 1988 to 2020. WATER 2022. [DOI: 10.3390/w14152296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The spatiotemporal changes in surface water area (SWA) in the basins of Northeast China have far-reaching impacts on their economic, agricultural, and social development and ecological sustainability. However, the long-term variation characteristics of water bodies in the Northeast basin and its main driving factors are still unclear. Based on the global surface water dataset, combined with the Meteorological and Vegetation Normalized Index (NDVI) datasets, this study used linear regression and correlation analysis to investigate the temporal and spatial variation characteristics of surface water in Northeast China and its driving factors from 1988 to 2020. The results show that (1) the seasonal surface water area (SSWA) and permanent surface water area (PSWA) in Northeast China increased at the rates of 58.408 km2/ year and 169.897 km2/ year, respectively, from 1988 to 2020. Taking 2000 as the node, PSWA and SSWA showed a trend of first decreasing and then increasing. (2) Changes in surface water types in each basin have significant space–time differences, and the transition between water bodies is dominated by the addition and reduction of seasonal water bodies. PSWA decreased significantly in western basins such as the Ulagai River Basin, the Otindag Desert, and the Liao River Basin, but increased significantly in the Songhua River Basin. (3) The driving forces of surface water change in different basins are different. Temperature and NDVI play a leading role in the change of SWA in the western arid region; permafrost degradation under the condition of air temperature rise is an indispensable factor affecting SWA change in the Argun River Basin; the eastern basin with a larger surface water area responded more strongly to changes in precipitation and evapotranspiration. Land-use conversion and water conservancy project construction were the main reasons for the increase of SWA in the Songhua River Basin under reduced precipitation. This research provides a reference for the in-depth study of the characteristics of surface water resources in Northeast China and has important practical significance for the scientific management of water resources in the basin.
Collapse
|
4
|
Assessing Surface Water Losses and Gains under Rapid Urbanization for SDG 6.6.1 Using Long-Term Landsat Imagery in the Guangdong-Hong Kong-Macao Greater Bay Area, China. REMOTE SENSING 2022. [DOI: 10.3390/rs14040881] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
As one of the most open and dynamic regions in China, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has been urbanizing rapidly in recent decades. The surface water in the GBA also has been suffering from urbanization and intensified human activities. The study aimed to characterize the spatiotemporal patterns and assess the losses and gains of surface water caused by urbanization in the GBA via long time-series remote sensing data, which could support the progress towards sustainable development goals (SDGs) set by the United Nations, especially for measuring SDG 6.6.1 indicator. Firstly, utilizing 4750 continuous Landsat TM/ETM+/OLI images during 1986–2020 and the Google Earth Engine cloud platform, the multiple index water detection rule (MIWDR) was performed to extract surface water extent in the GBA. Secondly, we achieved surface water dynamic type classification based on annual water inundation frequency time-series in the GBA. Finally, the spatial distribution and temporal variation of urbanization-induced water losses and gains were analyzed through a land cover transfer matrix. Results showed that (1) the average minimal and maximal surface water extents of the GBA during 1986–2020 were 2017.62 km2 and 6129.55 km2, respectively. The maximal surface water extent fell rapidly from 7897.96 km2 in 2001 to 5087.46 km2 in 2020, with a loss speed of 155.41 km2 per year (R2 = 0.86). (2) The surface water areas of permanent and dynamic types were 1529.02 km2 and 2064.99 km2 during 2000–2020, accounting for 42.54% and 57.46% of all water-related areas, respectively. (3) The surface water extent occupied by impervious land surfaces showed a significant linear downward trend (R2 = 0.98, slope = 36.41 km2 per year), while the surface water restored from impervious land surfaces denoted a slight growing trend (R2 = 0.86, slope = 0.99 km2 per year). Our study monitored the long-term changes in the surface water of the GBA, which can provide valuable information for the sustainable development of the GBA urban agglomeration. In addition, the proposed framework can easily be implemented in other similar regions worldwide.
Collapse
|
5
|
Going beyond Global Indicators—Policy Relevant Indicators for SDG 6 Targets in the Context of Austria. SUSTAINABILITY 2022. [DOI: 10.3390/su14031647] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
Bringing forward sustainable transformation as envisioned within the Agenda 2030 requires comprehensive monitoring of the 17 Sustainable Development Goals (SDGs) formulated therein. To monitor and report progress on goal 6 on clean water and sanitation and its eight pertinent targets, 11 indicators were stipulated in an elaborated process. Yet, through continuous scientific and public scrutiny and debate several gaps and weaknesses were identified. Amongst others, these globally defined indicators are found to reflect weakly the diversity of national realities, capacities and levels of development. To translate the targets into national contexts and fully cover all aspects of the SDG 6 targets, the utilization of complementary indicators is recommended. Within this paper, following a critical appraisal of the SDG 6 indicators, possible complementary indicators are collected from literature and screened based on their quality, relevance for the national context and data availability. A deepened status quo of the SDG 6 targets and corresponding problem areas are outlined for the context of Austria, where water and sanitation infrastructure as well as regulation and governance of water bodies are widely established. Despite increasing the monitoring effort, it is concluded that complementary indicators are practicable to support coherent policy-making and ultimately contribute to the Agenda 2030’s aspiration that all countries take action.
Collapse
|