Investigating the present status, spatial change, and emerging issues related to riparian wetlands of Bhagirathi–Jalangi Floodplain (BJF) in lower deltaic West Bengal, India

Chatterjee, Sunam; Chakraborty, Kunal; Mura, Shambhu Nath Sing

doi:10.1007/s10668-021-01710-8

Cited by 9 publications

(4 citation statements)

References 60 publications

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“…First, the regions of worst or bad connectivity scenarios match with the presence of diminishing or lost wetlands and vice versa; this demonstrates the direct control of hydrological connectivity on wetland degradation. This direct relation between surface connectivity loss and wetland degradation has also been observed elsewhere in Ganga Basin, e.g., Kaabar Tal [23,27,43], and in the lower Ganga delta region [57], in floodplains of the USA [58], China [59], and Australia [60].…”

Section: Controls Of Wetland Degradation: a Process-response Frameworksupporting

confidence: 75%

Integrating Hydrological Connectivity in a Process–Response Framework for Restoration and Monitoring Prioritisation of Floodplain Wetlands in the Ramganga Basin, India

Singh

Sinha

2022

Water

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Floodplain wetlands are critical for sustaining various ecological and hydrological functions in a riverine environment. Severe anthropogenic alterations and human occupation of floodplains have threatened these wetlands in several parts of the world. A major handicap in designing sustainable restoration and monitoring strategies for these wetlands is the lack of scientific process-based understanding and information on the basin-scale controls of their degradation. Here, we offer a novel approach to integrate the connectivity of the wetlands with the surrounding landscape along with other attributes such as stream density, hydrometeorological parameters, and groundwater dynamics to explain their degradation and then to prioritise them for restoration and monitoring. We hypothesise that the best possible connectivity scenario for the existence of a wetland would be if (a) the wetland has a high connectivity with its upslope area, and (b) the wetland has a low connectivity with its downslope region. The first condition ensures the flow of water into the wetland and the second condition allows longer water residence time in the wetland. Accordingly, we define four connectivity-based wetland health scenarios—good, no impact, bad, and worst. We have implemented the proposed method in 3226 wetlands in the Ramganga Basin in north India. Further, we have applied specific selection criteria, such as distance from the nearest stream and stream density, to prioritise the wetlands for restoration and monitoring. We conclude that the connectivity analysis offers a quick process-based assessment of wetlands’ health status and serves as an important criterion to prioritise the wetlands for developing appropriate management strategies.

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Section: Controls Of Wetland Degradation: a Process-response Frameworksupporting

confidence: 75%

Integrating Hydrological Connectivity in a Process–Response Framework for Restoration and Monitoring Prioritisation of Floodplain Wetlands in the Ramganga Basin, India

Singh

Sinha

2022

Water

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“…The degradation of water quality of river Saraswati finds resemblance to Jalangi River, a tributary of the Ganga River, which is primarily impacted by similar agricultural activities, domestic/municipal waste/wastewater discharges, and land use and land cover (LULC) changes. [72,73] The Yamuna river, considered the dirtiest river in India, showed higher organic loading reflected in its COD and BOD values. [74] The water quality status, nature of pollution, and the drivers and pressures responsible for the degradation of water quality, as revealed in the present study, earn conformity from Gikas et al, [75] who adopted the CCMEWQI model of water quality indexing to show the degraded water quality status of the river resulting from organic loading and sedimentation (Table 5).…”

Section: Discussionmentioning

confidence: 99%

Assessment of the Present State and Future Fate of River Saraswati, India: Water Quality Indices and Forecast Models as Diagnostic and Management Tools

Pramanik

Kaviraj

Saha

2023

CLEAN Soil Air Water

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Water quality assessment is key to the conservation and management of rivers. River Saraswati, a distributary of the river Ganga, serves as a lifeline to many villages in the district Hooghly in West Bengal, India. As the river is gradually dying due to diverse man‐made pollution, ten water quality parameters in two sampling spots (PR‐1 and PR‐2) in the river are monitored month‐wise from March 2017 to February 2020, and these are compared with those from a reference pond. The water quality index (WQI) is determined for the two riverine spots and the reference pond based on the Canadian Council of Ministers of Environment WQI (CCMEWQI) and weighted arithmetic WQI, respectively. In addition to actual observations, three different forecasting methods, exponential smoothing, autoregressive integrated moving average, and artificial neural network, are used to predict WQI for the next two years. This study indicates that free CO2, dissolved oxygen, and turbidity are the key parameters to evaluate this river's anthropogenic stress and health. The actual and forecasted results reflect the precipitous degradation of CCMEWQI in PR‐2. Therefore, the immediate intervention of all stakeholders is required to adopt an integrated and comprehensive river management plan to save the river from utter obliteration.

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“…Difference Water Index (NDWI) are the two most used indices used for measuring the concentration of aquatic plants (Chatterjee et al, 2022), also used in this study. The NDWI index has effectively been used for separating the water areas from the other land covers (Kaplan & Avdan, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…The approach summarises their spectral information in multispectral indices and consequently study the spatio‐temporal variation of these indices (Li et al, 2015). Normalised Difference Vegetation Index (NDVI) and Normalised Difference Water Index (NDWI) are the two most used indices used for measuring the concentration of aquatic plants (Chatterjee et al, 2022), also used in this study. The NDWI index has effectively been used for separating the water areas from the other land covers (Kaplan & Avdan, 2017).…”

Section: Introductionmentioning

confidence: 99%

Dynamics of land use land cover change in an East African inland valley wetland

Gimbo,

Mukundi,

Mburu

et al. 2023

Afr J Ecol

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The dynamics of inland valley wetlands landuse landcover (LULC) changes are of ecological and economical significance hence necessitating up‐to‐date datasets of resource status. Nalwekomba inland valley wetland is highly agriculturally utilised yet ecologically important wetland threatened with conversion. Historical LULC data sets as bench marks justifying wetland conservation are lacking. Therefore, the spatial–temporal LULC changes in Nalwekomba inland valley wetland were analysed through a combination of remote sensing and GIS, using satellite images of 1990, 2000, 2010 and 2020 as reference years. Results revealed variable dominance of grassland and tree cover for the wetland and its catchment over the years; 32.7% and 35.3% and 30.9% and 29.8%, respectively, for 1990 and 41.4% and 30.4% and 26.3% and 29.1% for 2020. The 30‐year analysis revealed increasing area‐shifts for cropland and built‐up/settlement of 265.7% and 76.2%, respectively, reducing cover for shrubland by 78.31% in the wetland. Similar trend emerged for its catchment. Highest net cover gains and losses identified between 1990 and 2000 were for cropland and tree cover respectively. The observed trend points to the need for landuse planning and landcover management to enhance ecosystems' resilience to support sustainable livelihoods dependent on this ecosystem.

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Investigating the present status, spatial change, and emerging issues related to riparian wetlands of Bhagirathi–Jalangi Floodplain (BJF) in lower deltaic West Bengal, India

Cited by 9 publications

References 60 publications

Integrating Hydrological Connectivity in a Process–Response Framework for Restoration and Monitoring Prioritisation of Floodplain Wetlands in the Ramganga Basin, India

Integrating Hydrological Connectivity in a Process–Response Framework for Restoration and Monitoring Prioritisation of Floodplain Wetlands in the Ramganga Basin, India

Assessment of the Present State and Future Fate of River Saraswati, India: Water Quality Indices and Forecast Models as Diagnostic and Management Tools

Dynamics of land use land cover change in an East African inland valley wetland

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