Journal ArticleDOI
Machine learning algorithm-based risk assessment of riparian wetlands in Padma River Basin of Northwest Bangladesh
Abu Reza Md. Towfiqul Islam,Swapan Talukdar,Susanta Mahato,Sk Ziaul,Kutub Uddin Eibek,Shumona Akhter,Quoc Bao Pham,Babak Mohammadi,Firoozeh Karimi,Nguyen Thi Thuy Linh +9 more
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TLDR
In this paper, the authors explored the spatiotemporal dynamics of wetlands, prediction of wetland risk assessment, and showed that wetland areas at present are declining less than one-third of those in 1988 due to the construction of the dam at Farakka, which is situated at the upstream of the Padma River.Abstract:
Wetland risk assessment is a global concern especially in developing countries like Bangladesh. The present study explored the spatiotemporal dynamics of wetlands, prediction of wetland risk assessment. The wetland risk assessment was predicted based on ten selected parameters, such as fragmentation probability, distance to road, and settlement. We used M5P, random forest (RF), reduced error pruning tree (REPTree), and support vector machine (SVM) machine learning techniques for wetland risk assessment. The results showed that wetland areas at present are declining less than one-third of those in 1988 due to the construction of the dam at Farakka, which is situated at the upstream of the Padma River. The distance to the river and built-up area are the two most contributing drivers influencing the wetland risk assessment based on information gain ratio (InGR). The prediction results of machine learning models showed 64.48% of area by M5P, 61.75% of area by RF, 62.18% of area by REPTree, and 55.74% of area by SVM have been predicted as the high and very high-risk zones. The results of accuracy assessment showed that the RF outperformed than other models (area under curve: 0.83), followed by the SVM, M5P, and REPTree. Degradation of wetlands explored in this study demonstrated the negative effects on biodiversity. Therefore, to conserve and protect the wetlands, continuous monitoring of wetlands using high resolution satellite images, feeding with the ecological flow, confining built up area and agricultural expansion towards wetlands, and new wetland creation is essential for wetland management.read more
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Applications of various data-driven models for the prediction of groundwater quality index in the Akot basin, Maharashtra, India.
TL;DR: In this paper, four standalone methods such as additive regression (AR), M5P tree model (M5P), random subspace (RSS), and support vector machine (SVM) were employed to predict WQI based on variable elimination technique.
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Classification of Zambian grasslands using random forest feature importance selection during the optimal phenological period
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Journal ArticleDOI
Impact of wetland fragmentation due to damming on the linkages between water richness and ecosystem services.
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References
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Novel hybrid models between bivariate statistics, artificial neural networks and boosting algorithms for flood susceptibility assessment.
Romulus Costache,Quoc Bao Pham,Mohammadtaghi Avand,Nguyen Thi Thuy Linh,Matej Vojtek,Jana Vojteková,Sunmin Lee,Dao Nguyen Khoi,Pham Thi Thao Nhi,Tran Duc Dung +9 more
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Journal ArticleDOI
Delineating wetland catchments and modeling hydrologic connectivity using LiDAR data and aerial imagery
Qiusheng Wu,Charles R. Lane +1 more
TL;DR: The graph-theory-based contour tree method was used to delineate hierarchical wetland catchments and characterize their geometric and topological properties and demonstrated that the proposed framework is promising for improving overland flow simulation and hydrologic connectivity analysis.
Journal ArticleDOI
Exploring physical wetland vulnerability of Atreyee river basin in India and Bangladesh using logistic regression and fuzzy logic approaches
Tamal Kanti Saha,Swades Pal +1 more
TL;DR: In this paper, the authors explored the nature of the physical vulnerability of wetland using logistic regression (LR) and fuzzy logic (FL) approaches for both pre and post-dam periods.
Journal ArticleDOI
Model tree approach for prediction of pile groups scour due to waves
Amir Etemad-Shahidi,Negin Ghaemi +1 more
TL;DR: New formulas are given that are easy to use, accurate and physically sound for estimating the pile group scour depth, which can be so useful for engineers.
Journal Article
Morphometric Relationships of Length-Weight and Length-Length of Four Cyprinid Small Indigenous Fish Species from the Padma River (NW Bangladesh)
TL;DR: This study describes the length-weight (LWR) and length-length (LLR) relationships of four cyprinid important small indigenous fish species (SIS) from the Padma River, Bangladesh and indicated that LLRs were highly correlated.
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