scholarly journals Analysis and Practice of Urban Wetland Construction Technology in Mining Subsidence Water Area

2020 ◽  
Vol 194 ◽  
pp. 05037
Author(s):  
Xueliang Li
Keyword(s):  
Surface Water ◽  
Water Area ◽  
Mining Subsidence ◽  
Construction Technology ◽  
Urban Service ◽  
Wetland Construction ◽  
Urban Wetland ◽  
Tourism Image ◽  
Coal Mining Subsidence ◽  
Wetland Resources

The mining of underground coal resources has a great impact on the ecological environment, especially in the high groundwater level area in the East, the mining subsidence has a more severe impact on the surface water, resulting in serious surface water, and the feasibility of restoring the original land function is poor. Based on the analysis of the characteristics of mining subsidence water, this paper puts forward the key technology of urban wetland construction, and analyzes it combined with engineering examples. The results show that: in the mining subsidence water area around the city, relying on the geographical advantages and abundant secondary wetland resources of coal mining subsidence, we can shape the regional tourism image, focus on the construction of Urban Wetland Park and ecological wetland, expand the urban service function of wetland in the aspects of leisure, tourism, education and tourism, as well as the rainwater storage and water purification function of wetland. This study provides a reference for the construction of similar mining cities.

scholarly journals Surface Water Extraction and Dynamic Analysis of Baiyangdian Lake Based on the Google Earth Engine Platform Using Sentinel-1 for Reporting SDG 6.6.1 Indicators

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 138
Author(s):  
Zijie Jiang ◽  
Weiguo Jiang ◽  
Ziyan Ling ◽  
Xiaoya Wang ◽  
Kaifeng Peng ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Surface Water ◽  
Essential Element ◽  
Water Area ◽  
Google Earth ◽  
Water Extraction ◽  
Natural Ecosystem ◽  
The Sustainable Development ◽  
Baiyangdian Lake ◽  
Google Earth Engine

Surface water is an essential element that supports natural ecosystem health and human life, and its losses or gains are closely related to national or local sustainable development. Monitoring the spatial-temporal changes in surface water can directly support the reporting of progress towards the sustainable development goals (SDGs) outlined by the government, especially for measuring SDG 6.6.1 indicators. In our study, we focused on Baiyangdian Lake, an important lake in North China, and explored its spatiotemporal extent changes from 2014 to 2020. Using long-term Sentinel-1 SAR images and the OTSU algorithm, our study developed an automatic water extraction framework to monitor surface water changes in Baiyangdian Lake at a 10 m resolution from 2014 to 2020 on the Google Earth Engine cloud platform. The results showed that (1) the water extraction accuracy in our study was considered good, showing high consistency with the existing dataset. In addition, it was found that the classification accuracy in spring, summer, and fall was better than that in winter. (2) From 2014 to 2020, the surface water area of Baiyangdian Lake exhibited a slowly rising trend, with an average water area of 97.03 km2. In terms of seasonal variation, the seasonal water area changed significantly. The water areas in spring and winter were larger than those in summer and fall. (3) Spatially, most of the water was distributed in the eastern part of Baiyangdian Lake, which accounted for roughly 57% of the total water area. The permanent water area, temporary water area, and non-water area covered 49.69 km2, 97.77 km2, and 171.55 km2, respectively. Our study monitored changes in the spatial extent of the surface water of Baiyangdian Lake, provides useful information for the sustainable development of the Xiong’an New Area and directly reports the status of SDG 6.6.1 indicators over time.

Research and Application on Technology of Flood-Storage and Flood-Detention of Coal Mining Subsidence Area of Suzhou Coal Mine

2014 ◽  
Vol 641-642 ◽  
pp. 80-83
Author(s):  
Jia Zhong Zheng ◽  
Mei Zhu ◽  
Zheng Long Wang
Keyword(s):  
Coal Mining ◽  
Dynamic Change ◽  
Storage Conditions ◽  
Flood Routing ◽  
Mining Subsidence ◽  
Subsidence Area ◽  
The Status ◽  
Suzhou City ◽  
Change Trend ◽  
Coal Mining Subsidence

The artical is based on the investigation of the basis of the status quo of Zhuxianzhuang and Luling coal mining subsidence area in Anhui province Suzhou city(hereinafter referred to as the "Zhu Lu subsidence area"), a preliminary analysis of the dynamic change trend of detention space in Zhu Lu subsidence area, and based on the hysteresis storage conditions of subsidence area, use the flood routing model to simulate the hysteresis effect of storage at different subsidence scenarios of different frequency flood. Finally, using the experience type channel evolution model and peak delay routing model further revealed storage effect on flood process of Zhu Lu subsidence area.

scholarly journals Downscaling MODIS Surface Reflectance to Improve Water Body Extraction

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Xianghong Che ◽  
Min Feng ◽  
Hao Jiang ◽  
Jia Song ◽  
Bei Jia
Keyword(s):  
Surface Water ◽  
Water Body ◽  
Terrestrial Ecosystems ◽  
Water Area ◽  
Water Bodies ◽  
Tibet Plateau ◽  
Surface Reflectance ◽  
Discrimination Ability ◽  
Automated Method ◽  
Landsat 7

Inland surface water is essential to terrestrial ecosystems and human civilization. Accurate mapping of surface water dynamic is vital for both scientific research and policy-driven applications. MODIS provides twice observation per day, making it perfect for monitoring temporal water dynamic. Although MODIS provides two bands at 250 m resolution, accurately deriving water area always depends on observations from the spectral bands with 500 m resolution, which limits its discrimination ability over small lakes and rivers. The paper presents an automated method for downscaling the 500 m MODIS surface reflectance (SR) to 250 m to improve the spatial discrimination of water body extraction. The method has been tested at Co Ngoin and Co Bangkog in Qinghai-Tibet plateau. The downscaled SR and the derived water bodies were compared to SR and water body mapped from Landsat-7 ETM+ images were acquired on the same date. Consistency metrics were calculated to measure their agreement and disagreement. The comparisons indicated that the downscaled MODIS SR showed significant improvement over the original 500 m observations when compared with Landsat-7 ETM+ SR, and both commission and omission errors were reduced in the derived 250 m water bodies.

scholarly journals Monitoring monthly surface water dynamics of Dongting Lake using Sentinal-1 data at 10 m

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4992 ◽  
Author(s):  
Liwei Xing ◽  
Xinming Tang ◽  
Huabin Wang ◽  
Wenfeng Fan ◽  
Guanghui Wang
Keyword(s):  
Surface Water ◽  
Water Distribution ◽  
Remote Sensing Data ◽  
Water Area ◽  
Dongting Lake ◽  
Water Dynamics ◽  
High Temporal Resolution ◽  
Backscattering Coefficient ◽  
Distribution Maps ◽  
Lower Accuracy

High temporal resolution water distribution maps are essential for surface water monitoring because surface water exhibits significant inner-annual variation. Therefore, high-frequency remote sensing data are needed for surface water mapping. Dongting Lake, the second-largest freshwater lake in China, is famous for the seasonal fluctuations of its inundation extents in the middle reaches of the Yangtze River. It is also greatly affected by the Three Gorges Project. In this study, we used Sentinel-1 data to generate surface water maps of Dongting Lake at 10 m resolution. First, we generated the Sentinal-1 time series backscattering coefficient for VH and VV polarizations at 10 m resolution by using a monthly composition method. Second, we generated the thresholds for mapping surface water at 10 m resolution with monthly frequencies using Sentinel-1 data. Then, we derived the monthly surface water distribution product of Dongting Lake in 2016, and finally, we analyzed the inner-annual surface water dynamics. The results showed that: (1) The thresholds were −21.56 and −15.82 dB for the backscattering coefficients for VH and VV, respectively, and the overall accuracy and Kappa coefficients were above 95.50% and 0.90, respectively, for the VH backscattering coefficient, and above 94.50% and 0.88, respectively, for the VV backscattering coefficient. The VV backscattering coefficient achieved lower accuracy due to the effect of the wind causing roughness on the surface of the water. (2) The maximum and minimum areas of surface water were 2040.33 km2in July, and 738.89 km2in December. The surface water area of Dongting Lake varied most significantly in April and August. The permanent water acreage in 2016 was 556.35 km2, accounting for 19.65% of the total area of Dongting Lake, and the acreage of seasonal water was 1525.21 km2. This study proposed a method to automatically generate monthly surface water at 10 m resolution, which may contribute to monitoring surface water in a timely manner.

scholarly journals A new approach to increase land reclamation rate in coal mining subsidence area: A case study of Guqiao Coal Mine, China

2021 ◽  
Author(s):  
Gensheng LI ◽  
Jianxuan Shang ◽  
Zhenqi Hu ◽  
Dongzhu Yuan ◽  
Pengyu Li ◽  
...  
Keyword(s):  
Coal Mining ◽  
Coal Mine ◽  
Land Reclamation ◽  
Water Area ◽  
Land Area ◽  
Reclaimed Land ◽  
Land Protection ◽  
Mining Areas ◽  
Concurrent Mining And Reclamation ◽  
Coal Mining Subsidence

Underground coal mining will inevitably cause land ponding in high groundwater table, which will affect the land sustainable development. However, the traditional reclamation (TR) is poor in land rate. Thus, finding a suitable reclamation approach is crucial to alleviate the conflicts between coal exploitation and land protection. In this paper, taking Guqiao Coal Mine of China was seriously affected by mining-induced ponding as an example. Firstly, dynamic distribution of surface subsidence and land damage from 2007 to 2017 was revealed base on concurrent mining and reclamation (CMR). Second, the land-water layout of five reclamation schemes (no reclamation, TR, CMR I, CMR II and CMR III) were simulated. Then, and the dynamic filling elevation model and filling thickness model were constructed. Finally, the sequence of earthwork allocation was optimized. The results revealed that: 1) reclaimed land area: CMR III > CMR II > CMR I > TR > no reclamation; 2) The digging depth is directly proportional to earthwork volume and land area, and inversely proportional to water area, but with increase of digging depth, the increase in the reclaimed land area relatively slowed down; 3) CMRs had reclaimed 426.31~637.82 ha and 259.62~471.13 ha more than the no reclamation and TR respectively. Compared with the no reclamation and TR, CMRs can increase the proportion of reclaimed land by 33.77~50.52% and 20.57~37.32% respectively. The research results provide a reference to increase the reclamation rate of mining areas in the high phreatic table.

scholarly journals A New Method to Monitor the Coal Mining Subsidence by Gravimetry

2015 ◽  
Vol 8 (1) ◽  
pp. 304-308 ◽  
Author(s):  
Jinyun Guo ◽  
Hongjuan Yu ◽  
Yi Shen ◽  
Wang Li ◽  
Bin Guo
Keyword(s):  
Coal Mining ◽  
Mining Subsidence ◽  
New Method ◽  
Coal Mining Subsidence

Remote Sensing of Surface Water Dynamics Between 2015 and 2020 in the Prairie Pothole Region 

2021 ◽  
Author(s):  
Stefan Schlaffer ◽  
Marco Chini ◽  
Wouter Dorigo
Keyword(s):  
Surface Water ◽  
Prairie Pothole Region ◽  
Water Area ◽  
Water Bodies ◽  
Water Dynamics ◽  
Drought Indices ◽  
Prairie Pothole ◽  
Small Water ◽  
Wide Range ◽  
Small Water Bodies

<p>The North American Prairie Pothole Region (PPR) consists of millions of wetlands and holds great importance for biodiversity, water storage and flood management. The wetlands cover a wide range of sizes from a few square metres to several square kilometres. Prairie hydrology is greatly influenced by the threshold behaviour of potholes leading to spilling as well as merging of adjacent wetlands. The knowledge of seasonal and inter-annual surface water dynamics in the PPR is critical for understanding this behaviour of connected and isolated wetlands. Synthetic aperture radar (SAR) sensors, e.g. used by the Copernicus Sentinel-1 mission, have great potential to provide high-accuracy wetland extent maps even when cloud cover is present. We derived water extent during the ice-free months May to October from 2015 to 2020 by fusing dual-polarised Sentinel-1 backscatter data with topographical information. The approach was applied to a prairie catchment in North Dakota. Total water area, number of water bodies and median area per water body were computed from the time series of water extent maps. Surface water dynamics showed strong seasonal dynamics especially in the case of small water bodies (< 1 ha) with a decrease in water area and number of small water bodies from spring throughout summer when evaporation rates in the PPR are typically high. Larger water bodies showed a more stable behaviour during most years. Inter-annual dynamics were strongly related to drought indices based on climate data, such as the Palmer Drought Severity Index. During the extremely wet period of late 2019 to 2020, the dynamics of both small and large water bodies changed markedly. While a larger number of small water bodies was encountered, which remained stable throughout the wet period, also the area of larger water bodies increased, partly due to merging of smaller adjacent water bodies. The results demonstrate the potential of Sentinel-1 data for long-term monitoring of prairie wetlands while limitations exist due to the rather low temporal resolution of 12 days over the PPR.</p>

scholarly journals Construction of the Long-Term Global Surface Water Extent Dataset Based on Water-NDVI Spatio-Temporal Parameter Set

2020 ◽  
Vol 12 (17) ◽  
pp. 2675
Author(s):  
Qianqian Han ◽  
Zhenguo Niu
Keyword(s):  
Surface Water ◽  
Water Area ◽  
Temporal Parameter ◽  
Modis Ndvi ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Spatio Temporal ◽  
Global Surface ◽  
Global Water

Inland surface water is highly dynamic, seasonally and inter-annually, limiting the representativity of the water coverage information that is usually obtained at any single date. The long-term dynamic water extent products with high spatial and temporal resolution are particularly important to analyze the surface water change but unavailable up to now. In this paper, we construct a global water Normalized Difference Vegetation Index (NDVI) spatio-temporal parameter set based on the Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI. Employing the Google Earth Engine, we construct a new Global Surface Water Extent Dataset (GSWED) with coverage from 2000 to 2018, having an eight-day temporal resolution and a spatial resolution of 250 m. The results show that: (1) the MODIS NDVI-based surface water mapping has better performance compared to other water extraction methods, such as the normalized difference water index, the modified normalized difference water index, and the OTSU (maximal between-cluster variance method). In addition, the water-NDVI spatio-temporal parameter set can be used to update surface water extent datasets after 2018 as soon as the MODIS data are updated. (2) We validated the GSWED using random water samples from the Global Surface Water (GSW) dataset and achieved an overall accuracy of 96% with a kappa coefficient of 0.9. The producer’s accuracy and user’s accuracy were 97% and 90%, respectively. The validated comparisons in four regions (Qinghai Lake, Selin Co Lake, Utah Lake, and Dead Sea) show a good consistency with a correlation value of above 0.9. (3) The maximum global water area reached 2.41 million km2 between 2000 and 2018, and the global water showed a decreasing trend with a significance of P = 0.0898. (4) Analysis of different types of water area change regions (Selin Co Lake, Urmia Lake, Aral Sea, Chiquita Lake, and Dongting Lake) showed that the GSWED can not only identify the seasonal changes of the surface water area and abrupt changes of hydrological events but also reflect the long-term trend of the water changes. In addition, GSWED has better performance in wetland areas and shallow areas. The GSWED can be used for regional studies and global studies of hydrology, biogeochemistry, and climate models.

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