Application of frequency ratio and logistic regression models for assessing physical wetland vulnerability in Punarbhaba river basin of Indo-Bangladesh

References

• Acreman M, Harding R, Sullivan C, et al. 2009. Review of Hydrological Issues on Water Storage in International Development. Report to Centre for Ecology and Hydrology & British Geological Survey, Wallingford, UK
   Google Scholar
• Bastawesy ME, Gabr S, and White K. 2013. Hydrology and geomorphology of the Upper White Nile lakes and their relevance for water resources management in the Nile basin. Hydrol Process 27(2):196–205. https://doi.org/10.1002/hyp.9216
   Web of Science ®Google Scholar
• Basu T and Pal S. 2017a. Exploring landslide susceptibility zones by analytical hierarchy process (AHP) for the Gish River basin, West Bengal, India. Spat Inf Res 25:665–675. doi:10.1007/s41324-017-0134-2
   Web of Science ®Google Scholar
• Basu T and Pal S. 2017b. Identification of Landslide Susceptibility Zones in Gish River Basin. Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, West Bengal, India. Available at https://doi.org/10.1080/17499518.2017.1343482
   Google Scholar
• Brandt SA. 2000. Classification of geomorphological effects downstream of dams. Catena 40(4):375–401. https://doi.org/10.1016/S0341-8162(00)00093-X
   Web of Science ®Google Scholar
• Borro M, Morandeira N, Salvia  , et al. 2014. Mapping shallow lakes in a large South American floodplain: A frequency approach on multitemporal Landsat TM/ETM data. J Hydrol 512:39–52. https://doi.org/10.1016/j.jhydrol.2014.02.057
   Web of Science ®Google Scholar
• Chatterjee K, Bandyopadhyay A, Ghosh A, et al. 2015. Assessment of environmental factors causing wetland degradation using Fuzzy Analytic Network Process: A case study on Keoladeo National Park, India. Ecol Model 316:1–13. https://doi.org/10.1016/j.ecolmodel.2015.07.029
   Web of Science ®Google Scholar
• Chung CJ and Fabbri AG. 1999. Probabilistic prediction models for landslide hazard mapping. Photogrammetric Eng Remote Sensing 65(12):1389–99
   Web of Science ®Google Scholar
• CLEAR. 2002. Forest Fragmentation in Connecticut: 1985–2006. Center for Land Use Education and Research. University of Connecticut, Middlesex County Extension Centre, USA. http://clear.uconn.edu/projects/landscape/forestfrag. Accessed May 5, 2015
   Google Scholar
• Cong PT, Manh DH, Huy HA, et al. 2016. Livelihood vulnerability assessment to climate change at community level using household survey: A case study from Nam Dinh province, Vietnam. Mediterr J Soc Sci 7:358–66
   Google Scholar
• Cutter SL and Finch C. 2008. Temporal and spatial changes in social vulnerability to natural hazards. PNAS 105:2301–6. https://doi.org/10.1073/pnas.0710375105
   PubMed Web of Science ®Google Scholar
• Das RT and Pal S. 2017a. Exploring geospatial changes of wetland in different hydrological paradigms using water presence frequency approach in Barind Tract of West Bengal. Spat Inf Res https://doi.org/10.1007/s41324-017-0114-6
   Web of Science ®Google Scholar
• Das RT and Pal S. 2017b. Investigation of the principal vectors of wetland loss in Barind tract of West Bengal. Geo J 82:1–16. doi:10.1007/s10708-017-9821-8
   Google Scholar
• de Chazal J, Quétier F, Lavorel S, et al. 2008. Including multiple differing stakeholder values into vulnerability assessments of socio-ecological systems. Glob Environ Change 18:508–20. Available at https://doi.org/10.1016/j.gloenvcha.2008.04.005. https://doi.org/10.1016/j.gloenvcha.2008.04.005
   Web of Science ®Google Scholar
• Fickas KC, Cohen WB, and Yang Z. 2016. Landsat-based monitoring of annual wetland changein the Willamette Valley of Oregon, USA from 1972 to 2012. Wetlands Ecol Manage 24:73. Available at https://doi.org/10.1007/s11273-015-9452-0. https://doi.org/10.1007/s11273-015-9452-0
   Web of Science ®Google Scholar
• Finlayson C. 2006. Vulnerability assessment of important habitats for migratory species: examples from eastern Asia and northern Australia. In: Vagg R, Hepworth H. (eds.), Migratory Species and Climate Change: Impacts of a Changing Environment on Wild Animals, 3rd ed, pp 18–25. UNEP/CMS Secretariat, Bonn, Germany
   Google Scholar
• Fuchs S, Birkmann J, and Glade T. 2012. Vulnerability assessment in natural hazard and risk analysis: current approaches and future challenges. Nat Hazards 64(3):1969–75. https://doi.org/10.1007/s11069-012-0352-9
   Web of Science ®Google Scholar
• Graf WL. 2006. Downstream hydrologic and geomorphic effects of large dams on American rivers. Geomorphology 79:336–60. https://doi.org/10.1016/j.geomorph.2006.06.022
   Web of Science ®Google Scholar
• Gain AK and Giupponi C. 2015. A dynamic assessment of water scarcity risk in the Lower Brahmaputra River Basin: An integrated approach. Ecol Indicators 48:120–31. https://doi.org/10.1016/j.ecolind.2014.07.034
   Web of Science ®Google Scholar
• Gao J. 2016. Wetland and its degradation in the yellow river source zone. In: Brierley G, Li X, Cullum C, and Gao J. (eds), Landscape and Ecosystem Diversity, Dynamics and Management in the Yellow River Source Zone, pp. 209–232. Springer Geography. Springer. https://link.springer.com/chapter/10.1007/978-3-319-30475-5_10
   Google Scholar
• García-Artola A, Cearreta A, and Irabien MJ. 2017. Recent agricultural occupation and environmental regeneration of salt marshes in Northern Spain. In: Finkl C and Makowski C. (eds), Coastal Wetlands: Alteration and Remediation. Coastal Research Library, vol 21. 1 ed., pp 47–79. Springer, Cham
   Google Scholar
• Hiestermann J and Rivers-Moore NA. 2015. Predictive modelling of wetland occurrence in KwaZulu-Natal, South Africa. S Afr J Sci 111:1–10. https://doi.org/10.17159/sajs.2015/20140179
   Web of Science ®Google Scholar
• Jiang W, Lv J, Wang C, et al. 2017. Marsh wetland degradation risk assessment and change analysis: A case study in the Zoige Plateau, China. Ecolog Indicators 82:316–26. https://doi.org/10.1016/j.ecolind.2017.06.059
   Web of Science ®Google Scholar
• Karim F, Petheram C, Marvanek S, et al. 2016. Impact of climate change on floodplain inundation and hydrological connectivity between wetlands and rivers in tropical river catchment. Hydrol Process 30:1574–93. https://doi.org/10.1002/hyp.10714
   Web of Science ®Google Scholar
• Khatun S and Pal S. 2017. Categorization of morphometric surface through morphometric diversity analysis in Kushkarani river basin of Eastern India. Asian J Phys Chem Sci 2(1):1–19. doi:10.9734/AJOPACS/2017/31098
   Google Scholar
• Mahmud MS, Masrur A, Ishtiaque A, et al. 2011. Remote sensing & GIS based spatio temporal change analysis of wetland in Dhaka City, Bangladesh. J Water Resour Prot 3:781–7. https://doi.org/10.4236/jwarp.2011.311088
   Google Scholar
• Malekmohammadi B and Jahanishakib F. 2017. Vulnerability assessment of wetland landscape ecosystem services using driver-pressure-state-impact-response (DPSIR) model. Ecol Indic 82:293–303. Available at https://doi.org/10.1016/j.ecolind.2017.06.060. https://doi.org/10.1016/j.ecolind.2017.06.060
   Web of Science ®Google Scholar
• Marti-Cardona B, Dolz-Ripolles J, and Lopez-Martinez C. 2013. Wetland inundation monitoring by the synergistic use of ENVISAT/ASAR imagery and ancilliary spatial data. Remote Sensing Environ 139:171–84. https://doi.org/10.1016/j.rse.2013.07.028
   Web of Science ®Google Scholar
• McFeeters SK. 1996. The use of the normalized difference water index (NDWI) in the delineation of open water features. Int J Remote Sensing 17:1425–32. https://doi.org/10.1080/01431169608948714
   Web of Science ®Google Scholar
• Meten M, PrakashBhandary N, and Yatabe R. 2015. Effect of landslide factor combinations on the prediction accuracy of landslide susceptibility maps in the blue Nile gorge of central Ethiopia. Geoenviron Disasters 12:1355–72. Available at https://doi.org/10.1186/s40677-015-0016-7
   Google Scholar
• Mitsch WJ. 2010. Conservation, restoration and creation of wetlands: A global perspective. In Comin F. (ed), Ecological Restoration: A Global Challenge, pp 175–88. Cambridge University Press, Cambridge
   Google Scholar
• Mitsch WJ and Gosselink JG. 2000. Wetlands, 3rd ed. John Wiley and Sons, New York
   Google Scholar
• Mondal D and Pal S. 2017. Evolution of wetlands in lower reaches of Bagmari–Bansloi–Pagla rivers: A study using multidated images and maps. Curr Sci 112(11):2263–72. https://doi.org/10.18520/cs/v112/i11/2263-2272
   Web of Science ®Google Scholar
• Mondal S and Mandal S. 2017. Application of frequency ratio (FR) model in spatial prediction of landslides in the Balason river basin, Darjeeling Himalaya. Spat Inf Res 25:337–350. doi. 10.1007/s41324-017-0101-y
   Web of Science ®Google Scholar
• Monserud RA and Leemans R.1992. Comparing global vegetation maps with the Kappa statistic. Ecol Model 62:275–93. https://doi.org/10.1016/0304-3800(92)90003-W
   Web of Science ®Google Scholar
• NOAA. 1999. Community Vulnerability Assessment Tool CD – ROOM. NOAA Coastal Services Center. 2234 South Hobson Ave., Charleston, USA
   Google Scholar
• Oishi M. 2016. Can ASEAN cope with “Human Insecurity” in Southeast Asia? In search of a new ASEAN way. Hum Insecurities Southeast Asia 5:103–19. https://doi.org/10.1007/978-981-10-2245-6_7
   Google Scholar
• Pal S. 2015. Impact of Massanjore dam on hydro-geomorphological modification of Mayurakshi river, Eastern India. Environ Dev Sustainability, 17(3):1573–2975
   Google Scholar
• Pal S. 2016a. Impact of Tilpara barrage on backwater reach of Kushkarni River: A tributary of Mayurakshi River. Environ Dev Sustain 19:2115–2142. doi:10.1007/s10668-016-9833-4
   Web of Science ®Google Scholar
• Pal S. 2016b. Impact of water diversion on hydrological regime of Atreyee river of Indo-Bangladesh. Int J River Basin Manage 14:459–475. https://doi.org/10.1080/15715124.2016.1194282
   Web of Science ®Google Scholar
• Pal S and Akoma OC. 2009. Water scarcity in wetland area within Kandi block of West Bengal: A hydro-ecological assessment. Ethiop J Environ Stud Manag 2:1–17
   Google Scholar
• Pal S and Debanshi S. 2017. Influences of soil erosion susceptibility toward overloading vulnerability of the gully head bundhs in Mayurakshi River basin of eastern Chottanagpur Plateau. Environ Dev Sustain, pp 1–37. https://doi.org/10.1007/s10668-017-9963-3
   Google Scholar
• Pal S and Mandal I. 2017. Impacts of stone mining and crushing on streams characters and vegetation health of Dwarka river basin of Jharkhand and West Bengal, Eastern India. J Encironmental Geogr 10(1–2):11–21. doi:10.1515/jengeo-2017-0002
   Google Scholar
• Pal S and Osoundu CA. 2009. Water scarcity in wetland area within Kandi block of West Bengal: A hydro-ecological assessment. Ethiop J Environ Stud Manage 2(3):1–17. https://doi.org/10.4314/ejesm.v2i3.48260
   Google Scholar
• Pal S and Saha TK. 2017a. Identifying dam-induced wetland changes using an inundation frequency approach: The case of the Atreyee River basin of Indo-Bangladesh. Ecohydrology and Hydrobiology, pp 1–17. https://doi.org/10.1016/j.ecohyd.2017.11.001
   Web of Science ®Google Scholar
• Pal S and Saha TK. 2017b. Exploring drainage/relief-scape sub-units in Atreyee river basin of India and Bangladesh. Spat Inf Res 25:685–692. https://doi.org/10.1007/s41324-017-0133-3
   Web of Science ®Google Scholar
• Pal S and Ziaul S. 2016. Detection of land use and land cover change and land surface temperature in English Bazar urban centre. Egypt. J Remote Sens Space Sci 20:125–145. Available at http://dx.doi.org/10.1016/j.ejrs.2016.11.003
   Web of Science ®Google Scholar
• Parent J, Civco D, and Hurd J. 2007. Simulating future forest fragmentation in a Connecticut region undergoing suburbanization. ASPRS 2001 Annual Conference. Tampa, Florida
   Google Scholar
• Pourghasemi HR, Pradhan B, and Gokceoglu C. 2012. Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran. Nat Hazards 63(2):965–96. Available at https://doi.org/10.1007/s11069-012-0217-2. https://doi.org/10.1007/s11069-012-0217-2
   Web of Science ®Google Scholar
• Quiroga MV, Kure S, Udo K, et al. 2016. Application of 2D numerical simulation for the analysis of the February 2014 Bolivian Amazonia flood: Application of the new HEC-RAS version 5. RIBAGUA–Revista Iberoamericana Del Agua 3:25–33
   Web of Science ®Google Scholar
• Rashid B, Islam SU, and Islam B. 2014. Drainage characteristics and evolution of the Barind tract, Bangladesh. Am J Earth Sci 1(4):86–98
   Google Scholar
• Rasyid AR, Bhandary NP, and Yatabe R. 2016. Performance of frequency ratio and logistic regression model in creating GIS based landslides susceptibility map at Lompobattang Mountain, Indonesia. Geoenviron Disasters 3:19. Available at https://doi.org/10.1186/s40677-016-0053-x. https://doi.org/10.1186/s40677-016-0053-x
   Google Scholar
• Richter BD, Baumgartner JV, Wigington R, et al. 1997. How much water does a river need? Freshw. Biol 37:231–49. https://doi.org/10.1046/j.1365-2427.1997.00153.x
   Web of Science ®Google Scholar
• Sahoo S, Dhar A, and Kar A. 2016. Environmental vulnerability assessment using Grey Analytic Hierarchy Process based model. Environ Impact Assess Rev 56:145–54. https://doi.org/10.1016/j.eiar.2015.10.002
   Web of Science ®Google Scholar
• Sami M, Shiekhdavoodi MJ, Pazhohanniya M, et al. 2014. Environmental comprehensive assessment of agricultural systems at the farm level using fuzzy logic: A case study in cane farms in Iran. Environ Model Softw 58:95–108. https://doi.org/10.1016/j.envsoft.2014.02.014
   Web of Science ®Google Scholar
• Sarkar S, Parihar SM, and Dutta A. 2016. Fuzzy risk assessment modelling of East Kolkata Wetland Area: A remote sensing and GIS based approach. Environ Model Softw 75:105–18. https://doi.org/10.1016/j.envsoft.2015.10.003
   Web of Science ®Google Scholar
• Solaimani K, Mousavi SZ, and Kavian A. 2013. Landslide susceptibility mapping based on frequency ratio and logistic regression models. Arab J Geosci 6:2557–69. https://doi.org/10.1007/s12517-012-0526-5
   Web of Science ®Google Scholar
• Süzen ML and Doyuran V. 2004. Data driven bivariate landslide susceptibility assessment using geographical information systems: A method and application to Asarsuyu catchment, Turkey. Eng Geol 71:303–21. Available at http://www.sciencedirect.com/science/article/pii/S0013795203001431
   Web of Science ®Google Scholar
• Talukdar S and Pal S. 2017a. Impact of dam on inundation regime of flood plain wetland of Punarbhaba river basin of Barind tract of Indo-Bangladesh. Int Soil Water Conserv Res. https://doi.org/10.1016/j.iswcr.2017.05.003
   Web of Science ®Google Scholar
• Talukdar S and Pal S. 2017b. Impact of dam on flow regime and flood plain modification in Punarbhaba River Basin of Indo-Bangladesh Barind Tract. Water Conserv Sci Eng 1–19. doi: 10.1007/s41101-017-0025-3
   Google Scholar
• Tockner K, Pusch M, Borchardt D, et al. 2010. Multiple stressors in coupled river–floodplain ecosystems. Feshwater Biol 55(Suppl. 1):131–5
   Google Scholar
• Townshend JR and Justice CO. 1986. Analysis of the dynamics of African vegetation using the normalized difference vegetation index. Int J Remote Sens 7(11):1435–45. https://doi.org/10.1080/01431168608948946
   Web of Science ®Google Scholar
• United States Environmental Protection Agency. 2009. EPA-SAB-09-012, p 121. Washington, DC
   Google Scholar
• Vogt P, Riitters KH, Estreguil C, et al. 2007. Mapping spatial patterns with morphological image processing. Landscape Ecology 22:171–7. https://doi.org/10.1007/s10980-006-9013-2
   Web of Science ®Google Scholar
• WWF. 2006. Conservation of High Altitude Wetlands in the Himalayas. Report of the Fourth Regional Workshop. Capacity building for high altitude wetlands conservation and management. New Delhi, India, 27–29 June 2006. Available at http://www.ramsar.org/pdf/mtg/mtg_himalaya_4th.pdf
   Google Scholar
• Yan B, Wang J, Li S, et al. 2016. Assessment of socio-economic vulnerability under sea level rise coupled with storm surge in the Chongming County, Shanghai. Acta Ecologica Sinica 36:91–8. https://doi.org/10.1016/j.chnaes.2016.01.006
   Google Scholar
• Yang H, Sun H, Jiao L, et al. 2010. Assessment on the Ecological Vulnerability of Wetland of China Irtysh River Valley. In: Environmental Science and Information Application Technology (ESIAT), 2:764–767. doi: 10.1109/ESIAT.2010.5568849
   Google Scholar
• Zedler JB and Kercher S. 2005. Wetland resources: Status, trends, ecosystem services, and restorability. In: Annual Review of Environment and Resources. 30:39–74
   Google Scholar
• Zha Y, Gao J, and Ni S. 2003. Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. Int J Remote Sensing 24(3):583–94. https://doi.org/10.1080/01431160304987
   Web of Science ®Google Scholar
• Ziaul S and Pal S. 2017. Estimating wetland insecurity index for Chatra wetland adjacent English Bazar Municipality of West Bengal. Spat Inf Res 25:813–823. doi: 10.1007/s41324-017-0147-x
   Web of Science ®Google Scholar