Evaluation Wetlands Ecosystem Health using Geospatial Technology: Evidence from Lower Gangetic Flood Plain in India

The lower Gangetic ood plain of West Bengal occupies diversied riverine and oodplain wetlands. These wetlands played a signicant role maintain ecosystem health and supports for human wellbeing. This paper presents the health of wetland ecosystem by comprising the wetland ecosystem health index (WEHI) in 2011 and 2018 at block level of Malda district, as a part of lower Gangetioc ood plain using pressure – state – response model (PSR model) and AHP method. A total number of six Landsat satellite images and statistical census data were used to determine the wetland. Wetlands are classied as very healthy, healthy, sub-healthy, unhealthy and sick category on the basis of wetland ecosystem health index score. Results showed the health of wetland ecosystem has slightly decreased from 2011 to 2018. 13.33% of blocks are fall under sick category in 2011. 26.67% block are comes under very healthy category in 2011 but it decrease to 20% in 2018. The heath of wetland ecosystem in Harischandrapur – II, Ratua-II, Maldah (Old), English Bazar, Bamongola, Habibpur, Chanchal-I and Kaliachak – II blocks are degrading from 2011 to 2018. This may be attributed to the increasing urbanization rate and associated growth of infrastructure. Developing local level institutions is useful measures to manage wetland resource; and protect biodiversity should be guided by the Government organization and NGOs for its mitigation measure.


Introduction
The River Ganga (The Ganges) basin, which covers 26.2 percent of India's total geographical space, has been designated as the country's largest river basin. The Government of India declared it a National River on November 4, 2008, in recognition of its immense signi cance to the people's economic, spiritual, and cultural lives (Mukherjee et al., 1993;Mukherjee 2020). It has a complex wetland ecosystem, ranging from high-altitude oligotrophic lakes in the Himalayas, Terai region's marshes and swamps, oodplain and riverine wetlands in the Gangetic and Brahmaputra alluvial plains, and coastal wetlands in the deltaic tracts. The Gangetic Plains are a vast swath of highly fertile alluvium that serves as the Ganga Basin's agricultural backbone. The Ganga River and its tributaries' ood pulses are intricately related to riverine and oodplain wetlands. Here, signi cant exchange of water, sediments, nutrients, and species occur between river channel and linking wetlands. Thus, the process and interconnected system related with biodiversity and ecosystem services. Nonetheless, natural ow regimes are being disrupted, agriculture and settlements are expanding and intensifying, deforestation, uncontrolled tourism, and invasive species are all putting pressure on the wetland landscape.
Globally, there are over 1,275 m ha wetland habitats (Finlayson and Spiers 1999) with an annual economic value of about USD15 trillion a year (MEA 2005). The population growth has continued to be a cause of wetland depletion and degradation across the globe, placing tremendous strain on water supplies and undeveloped land settlements, increased agricultural and industrial development and expansion of infrastructure (IUCN, 1990). The ine cient use of wetland services can be called a mixture of de ciencies of intelligence, business and policy de ciencies or action failures and other social and nancial factors. The factors are over shing, irrigation, erosion, invasive plants, climate change, depletion of water, land invasion and urbanization. Rapport et al. (1985) promoted the concept of 'ecosystem health' to describe the type of natural framework reliability and viability to keep up its hierarchical structure, normal controlling and recovery limit after versatility.
India is a gifted with a various dynamics of wetland landscape, covering nearly 18.4% of the land surface (MoEF, 1990) and they provide useful natural assets services to human. As per ISRO (2011), India has 69.23% of the area under inland wetland and 30.77% of the region are has a place with coastal wetland.
We lose 2-3 percent of the wetlands each year. The numerous wetlands environmental system has seen a quick derogation, including reducing area, fading in water quality, and loss of biodiversity (Foote et al. 1996). But the sustainable and stable system wetlands ecosystems are essential in India for supply food to humans and consumable water accessibility for people and domesticated animals. The researchers  tried to determine the loss of wetland area and resultant consequences. These studies (Das et al. 2015) also address that how the wetlands were bene ts to households. But, the researchers of India as well as the world were mainly concern about the wetland biological system wellbeing and  (Paul and Pal, 2020;Alanna et al., 2017). With the help of these data, we can analyse wetland ecosystem health at different spatio -temporal scale. Most the studies in China (Sun et al., 2017;Jia et al., 2015) have targeted the wetlands located the river basin or coastal region and they used remote sensing data. But the studies related to health conditions in inland wetlands were disregarded day by day.
In this speci c context, there is a need to examine precise evaluations of the health status in the Gangetic ood plain of West Bengal. This study focus on Malda district as an evidence of wetland ecosystem health by comprise wetland ecosystem health index (WEHI) in 2011 and 2018 at block level of Malda district, using pressure -state -response (PSR) model. The PSR model was very common to analysed health risk of wetland ecosystem (Das et al., 2020;Mai et al., 2005;Sun et al., 2017). Based on wetland ecosystem health index (WEHI) score, we categorized the health level and differentiate the blocks where the health condition is decreasing or increasing from 2011 to 2018. The ndings from this paper could helpful for the establishment and evaluation of ecological restoration policies and environmental management techniques in Malda district.

Study Area
The current study was carried out in lower Gangetic ood plain of West Bengal using geospatial technology, where wetland ecosystem is vulnerable. We selected Malda district is also a part of Diara region, where the wetlands play a vital role for maintaining landscape stability. Geomorphologically, the study area belongs to the active oodplain as it occupies more than half of the region's area occupies marsh, inactive oodplain, and levee and river islands. The Malda district lies between 24° 40 20 N to 25° 30 08 N and 87° 45 50 E to 88° 28 10 E ( Figure 1). It includes 15 blocks and 2 sub-divisions, such as Chanchal and Malda Sadar. The total geographical area of Malda district is nearly 3652.75 km 2 . The total population of the district is 3699312 with a population density of 1013 persons per sq kilometer in 2011. The major rivers in the district are Ganga, Punarbhaba, Mahananda, Pagla, Kalindri, Tangon, Fulahar etc. The river Ganga has enough evidence of lateral migration (Mukherjee and Pal, 2017). With the shifting of river course, it creates numerous ox-bow lake, cut-off channels, beels, etc. which are no longer direct link with parent river (Singh et al., 2019). Such water bodies have evolved into riparian wetlands that are vital to the oodplain ecosystem as well as the human wellbeing. Such dynamics physical and socio-economic aspects were the main attraction of researchers and that's why we selected Malda district as our study area.

Data resources and processing procedures
Systematic procedures were done to demonstrate the health conditions of wetland ecosystem in Malda district. The systematic procedures involve-preparation of block level vector map of Malda district and tabulation of the health indicator data. The block level administrative map of Malda district was prepared by using the administrative atlas of West Bengal; the statistical data incorporates population density, percentage of cultivation area, urbanization rate is gathered from the Census of India 2001 and 2011. The road network map was prepared from the Survey of India topographical sheet and same has to be updated with the satellite data. Finally, the digital database of road network is used for the calculation of road density. The patch richness (PR), patch density (PD), largest patch index (LPI), landscape diversity index (LDI), wetland degradation rate was calculated by using a total number of six Landsat satellite images in the year 2001, 2011 and 2018. The Landsat pace borne satellite images were downloaded via the web site https://earthexplorer.usgs.gov/. The description of satellite data has been given in Table 1. The ecosystem function value index was used for the economic valuation of ecosystem services provided by the wetlands (Zhang et al., 2015).

Wetlands ecosystems health assessment system
The PSR model was common and popular method along the numerous research studies ( NDVI is commonly used for determining different aspects of plant characteristics. The NDVI is rst de ned by Rouse in 1973 (Rouse et al., 1974). In this study, we have found that the NDVI value ranges between -0.674 to 0.658. Basically, the positive value of NDVI represents green vegetation and the negative value formed from clouds, water and snow.
Modi ed Normalized Difference Water index (MNDWI) has been calculated based on the Eq.2 The MNDWI has been used where the water bodies are mixed with built-up area (Xu, 2006). In this study, we have found that the MNDWI value ranges between -0.566 to 0.893. The positive values of MNDWI denote water features and the negative values indicated the non-water feature.
Normalized Difference Pond index (NDPI) has been calculated based on the Eq.3 Lacaux (2006) rst described Normalized Difference Pond index (NDPI) for the identi cation of ponds. In this study, we have found that the NDPI value ranges between -0.986 to 0.566.
After the calculation of above indices, MNDWI is greater than zero from this maximum water features.
Next, we have combined NDVI value of greater than zero and NDPI value of less than zero. This condition can separate water features from vegetation. The hybrid image provides better result.
Based on the extracted surface waterbodies, the wetlands are classi ed as natural lakes, natural ponds, ox-bow type or cut-off meander, natural waterlogged, natural riverine and man-made ponds. The classi cation scheme was considered based on the Indian Space Research Organization (ISRO) National Wetland Atlas report in the year 2011.

Indicator system establishment
The systematic studies involve selection of the indicator and standardize them for the computation of a score which is described the actual continuity of the study area on a speci c topic. Development of wetland ecosystem health index of Malda district, we select ten health indicators, where four pressure, four state and two response indicators. Table 2 shows the detailed list of indicators. Max -min normalization method has been followed to unify the indicators. The scale of the data ranges between 0 to 1. impact an assortment of natural processes. Patch density (PD) decrease when the wetland fragmentation occurs frequently. The higher value of Largest patch index (LPI) denotes greater impact for maintain environmental process. Shannon diversity index (SHDI) helped to understand the wetland diversity in a speci c area. SHDI value of '0' indicates that in the study area, only one patch class exists and has no decent variety. The above indices were calculated by using Arc GIS 10.3.1.
Apart from the state indicator, we have selected two response indicators i.e., wetland degradation rate (WDR) and ecosystem service value (ESV). WDR is determined how much wetlands area has decreased within a particular period of time. Based on the previous research paper (Xie et al. 2001) we calculated ESV of the wetland classes in the study area.

Calculation of indicator weights and assessment methods
Saaty's AHP technique is used for the determination of weight of the indicators (Saaty, 2008). The AHP priority was calculated via the website (https://bpmsg.com), which is freely accessible. Table 3 shows the correlation matrix and weight of each indicator used in AHP technique. For the construction of WEHI, the weight of the indicators is multiplied by respective standardized value of the indicators.
where, WEHI is the wetland ecosystem health index, W i is the weight of the i th indicator, and C i is the standardized value of the i th indicator.

Wetlands ecosystem pressure
The ecosystem pressure factors have gradually brought down the forward succession processes of the wetland ecological system. Therefore, it is di cult to implement effective management policies to sustain the natural system in wetland ecosystem. But the pressure indicators can alarm us to rethink the about wetlands deterioration process. Urbanization is an inescapable pattern of human culture and fundamental advance of a nation's modernization; simultaneously it affects on wetland ecological system and health. The researchers (Zheng et al., 2008) determined that the effects of urbanization can change the wetland ecosystem in three aspects-hydrological change, water quality change and climate change. Results of our analysis showed that the English Bazar and Old Maldah Municipality has most urbanized where 6.825 percent and 8.57 percent population are residing in 2001 and 2011 respectively. Figure 4 shows that urbanization rate from 2011 and 2018 is high in Kaliyachak-I block, followed by English Bazar and Maldah (Old) block.
The researchers (Findlay and Bourdages, 2001;Wang et al., 2003) observed that road construction can degraded wetland ecosystem in many ways like-pollutants the environment, fragments the wetland, shrinking the area and signi cant loss in bio-diversity etc. The paper shows that road density is high in Kaliyachak-I, English Bazar and Maldah (Old) block in 2001 and 2011. But the road connectivity is poor in Habibpur and Manikchak blocks (Figure 4).

Wetlands ecosystem health state
Present study showed four state indicator of wetland ecosystem to explore the health status. The indicators have direct in uences to sustain the wetland structure and help to maintain ecosystem function and services.
The patch density is an important indicator because greater patch density has greater signi cance of ecosystem health. Our results showed that English Bazar block has highest patch density followed by Kaliachak-III and Harishchandrapur-II block in 2011 and 2018 and the patch density is low in Bamangola, Gazole and Malda (Old) block (Figure 7).
Patch richness in the study area has decreased from 2001 to 2018. In 2011 and 2018, the patch richness is high in English Bazar and Harishchandrapur-II block and low in the block Kaliachak-III and Bamangola ( Figure 6).
The diversity of wetland landscape is highlighted by Shannon diversity index. If the types of wetland class increase then the Shannon diversity index (SDI) may increase. The highest value of SDI means the landscape has diversi ed wetlands and SDI value decreases if wetland diversity decreases. The highest SDI value is observed in English Bazar, Ratua II and Ratua-I block.

Wetlands ecosystem health response
The condition of wetland ecosystem has changed and become more complex due to combined effects of natural and human factor. This process in response to wetland degradation. The table 4 shows progressive changes of wetland area from 2.91% to 1.11% in 2001 to 2018. With the continuous population growth and infrastructure development are the main reason for wetland degradation except English Bazar and Maldah (Old) block, where urbanization is the main controlling factor. The paper determined that highest wetland degradation rate has found in Ratua-I, Chachal-II and Bamangola block from 2001 to 2011 and Gazole and Maldah (Old) block from 2011 to 2018 ( Figure 5).
Moreover, large wetland has provides more ecosystem service to the society. This paper shows that English Bazar and Kaliachak-III block provides highest ecosystem service and Habibpur block has lowest ecosystem service in 2011 ( Figure 10). In 2018, English Bazar and Bamangola block has highest ecosystem service and Kaliachak-II, Maldah (Old) and Bamangola block has lowest ecosystem service (Figure 7).

Spatial -temporal variations and levels in the health status of wetland ecosystem
After the computation of WEHI, we have categorized the WEHI score into ve classes-very healthy, healthy, sub-healthy, unhealthy and sick based on the previous research study (Sun et al., 2016(Sun et al., , 2017Jia et al., 2015). The description of the classes has been given in table 5, where higher value describes wetland landscape has stable and healthy ecosystem status and lower value denotes relatively unstable and poor ecosystem health status. In Malda district, the ecosystem health status has continuously changing with the increase of population pressure. Rapid urbanization and population density are the major factor that degraded the ecosystem health status. The wetland ecosystem health status of Malda district shows 13.33% of blocks fall under sick category in 2011 as well as 2018Table 6). It is also noticed that 26.67% block are residing under very healthy category in 2011 but it decreases to 20% in 2018. Figure 9 shows Our results showed that the average WEHI has been slightly decreased from 0.703 to 0.699 in 2011 and 2018 respectively. It is also noticed that the cultivation area of each block decreased from 2011 to 2018. This observation indicated that conversion of cultivated land to built-up area can regularly occur and has less pressure on wetlands in Malda district. Our results also stated that Harischandrapur -II, Ratua-II, Maldah (Old), English Bazar, Bamongola, Habibpur, Chanchal-I and Kaliachak -II blocks are degraded in terms of ecosystem health from 2011 to 2018. Urbanization rate has signi cant impact for the degradation of wetland ecosystem in case on English Bazar and Maldah (Old) block. Other blocks are in uenced by increase population density and road density.
Moreover, irrigation, high dependency in wetlands by household's use, canalization for conveying water to agricultural lands and continuous shifting of river channels have wrecked wetland landscape. This has driven to decrease in wetland area, decreasing in water holding capacity and change in water quality makes an unfortunate and wiped out situation for widely varied ora and fauna. The habitats -food, shelter and protection of the living organisms are exceptionally in uenced. Therefore, the carrying capacity of the wetlands by supporting the human society of Malda district is making it signi cantly more vulnerable. Therefore, the useful wetlands protection policies and restoration strategies should emphasize and implemented in these regions by the Government or NGOs.

Discussion
Wetland biological systems are viewed as the most ecological diverse and the characteristics of the ecosystems are exceptionally unique and complex. The evaluation of wetland environment wellbeing is ful lled on the grounds that the effects of controlling components are uctuated from spatio-temporal scale. The present research work showed that the status of wetland ecosystem health in Malda district is slightly decreased from 2011 to 2018. Natural as well as the anthropogenic factors were the main thrusts which are responsible to deteriorate wetlands ecosystem health in Malda district. The paper also reveals that change in population, growth in transport network, urbanization and sub-urbanization related infrastructure development is the major in uencing factor for changing wetland ecosystem ( Figure 10

Conclusion
Exploration of wetland ecosystem health index using geospatial technology in Malda district was carried out after the consideration of ten measurable indicators. The block wise variations map was prepared to establish the result. Both the spatial and non-spatial data were accumulated for the development of wetland ecosystem health index. The result of this paper determined that wetland ecosystem health has slightly increasing from 2011 to 2018. The percentage of blocks placed in sick category is 13.33 in 2011 as well as 2018, while the percentage of blocks in very healthy category has decreased from 26.67 to 20.00 from 2011 to 2018.
The wetlands make the environment healthy by maintaining ecological system and making liveable for living organisms. The majority of the people situated nearing wetlands dependent on wetlands by using water resource. Describing the block wise variations of WEHI is taken as subject matter in order. Developing local level institutions is useful measures to manage wetland resource and protect biodiversity should guided by the Government organization and NGOs. The emphasis should go to degraded blocks to protect wetlands environment it for the life and livelihood of a large community. Tables   Table 1 Description of satellite images in the study area.