Assessing subsidence susceptibility to coal mining using frequency ratio, statistical index and Mamdani fuzzy models: evidence from Raniganj coalfield, India
Creators
- 1. Jamia Milia Islamia. Department of Geography (India)
- 2. University of Manchester. School of Environment, Education and Development (SEED) (United Kingdom)
- 3. The University of Burdwan. Department of Geography (India)
- 4. University of Tokyo. Spatial Information Science (Japan)
- 5. CSJM University. Department of Geography (India)
- 6. Nagaoka University of Technology (Japan)
Description
Raniganj, an important coalfield in India, is susceptible to mining subsidence, ejection of toxicants in the environment and huge subsurface destruction. Mining with opencast method poses a great risk to the surrounding areas of this coalfield. Anthropogenic and natural activities have caused ground movement leading to subsidence in Raniganj coalfield. Existing knowledge on subsidence susceptibility to coal mining in Raniganj coalfield is scant. The study makes an attempt to analyze mining subsidence susceptibility in Raniganj coalfield using site-specific parameters. We first prepared subsidence inventory map to identify old subsidence locations and to construct the model. It was later utilized for validating the models. Fifteen site-specific parameters related to subsidence were chosen to analyze coal mining subsidence. Frequency ratio (Fr), statistical index (SI) and Mamdani fuzzy (Mf) models were utilized to assess their effectiveness in preparing susceptibility map. Findings of the study revealed very high susceptibility in the central part, high susceptibility in north-western part and moderate susceptibility in the eastern part of Raniganj coalfield. Low and very low susceptibility was found in those parts having largest area under vegetation and water bodies. The models were validated through ROC curve, seed cell area index (SCAI) and spatially agreed area approach. Mamdani fuzzy model with highest success rate (87%) and prediction accuracy (85%) was found the best fit model for analyzing mining subsidence susceptibility. The framework of the methodology will be instructive for analyzing susceptibility at different geographical locations.
Additional details
Identifiers
Publishing Information
- Journal Title
- Environmental Earth Sciences
- Journal Volume
- 79
- Journal Issue
- 16
- Journal Page Range
- vp.
- ISSN
- 1866-6280
INIS
- Country of Publication
- Germany
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 55064156
- Subject category
- S01: COAL, LIGNITE, AND PEAT; S54: ENVIRONMENTAL SCIENCES;
- Descriptors DEI
- ACCURACY; ANTHRACITE; COAL MINES; COAL MINING; COAL SEAMS; FORECASTING; FUZZY LOGIC; GROUND SUBSIDENCE; HAZARDS; INDIA; MAGNETIC SUSCEPTIBILITY; STATISTICAL MODELS; SURFACE MINING
- Descriptors DEC
- ASIA; BLACK COAL; CARBONACEOUS MATERIALS; COAL; COAL DEPOSITS; DEVELOPING COUNTRIES; ENERGY SOURCES; FOSSIL FUELS; FUELS; GEOLOGIC DEPOSITS; MAGNETIC PROPERTIES; MATERIALS; MATHEMATICAL LOGIC; MATHEMATICAL MODELS; MINERAL RESOURCES; MINES; MINING; PHYSICAL PROPERTIES; RESOURCES; UNDERGROUND FACILITIES
Optional Information
- Copyright
- Copyright (c) 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020