Wetland health assessment using DPSI framework: a case study in Kolkata Metropolitan Area

Wetlands are among the most valuable components of the ecosystem, playing an important role in preventing floods, maintaining the hydrological cycle, protecting against natural hazards, and controlling local weather conditions and ecological restoration. The Kolkata Metropolitan Area (KMA) is considered one of the most ecologically valuable regions in terms of wetland ecosystem, but due to haphazard development and human activities, the wetlands of the city are under constant threat of degradation. Therefore, this study aims to assess the factors responsible for wetland health and their dynamics using Driving Force-Pressure-State-Impact (DPSI) framework. To assess wetland health during 2011–2020, seventeen indicators and four sub-indicators were selected to calculate weights using the analytic hierarchy process (AHP). The results showed that most of the municipalities in the healthy category were in the pressure (P) section in 2011, while fluctuations were observed in the impact (I) section in several wards during 2011–20. The condition section (S) showed the overall change in the water, vegetation, and built-up categories from 2011 to 2020, so the most dominant category was “healthy,” followed by “unhealthy” and “poor.” The highly significant factors worsening wetland health were population density (B1), road density (B3), per capita wastewater generation (B5), per capita solid waste generation (B7), biological oxygen demand (D1a), dissolved oxygen (D1b), pH (D1c), and total coliform (D1d). The results of the study can help develop sustainable conservation and management of the wetland ecosystem in the KMA urban area and at the global level with similar geographical conditions.


Introduction
Wetlands are the areas of peatland or water, swamps, marsh, fen, whether permanent or temporary, natural or artificial, with standing or flowing, brackish or saline water, fresh water, including marine water areas whose depth at low tide is less than 6 m (Gumbricht et al. 2017).Wetlands are an important part of an ecosystem, both for plant and animal habitat (Mitsch et al. 2015;Mallick et al. 2021).They regulate local climate, prevent floods and droughts, maintain nutrient cycling, alter water flow, reduce pollution, sequester carbon and create value for local people, provide recreation, and maintain environmental stability (Talukdar and Pal 2020).Wetlands provide an important link to the hydrosphere, lithosphere, biosphere, and atmosphere (Talukdar et al. 2021a).Wetlands (freshwater, marshes, and swamps) produce about 2.5 kg/m 2 /year of net primary production, which is the highest among all ecosystems on Earth (Strahler and Strahler 2007).However, both coastal and inland wetlands are disappearing at an alarming rate due to urban expansion, over-exploitation of resources, and climate change in various parts of the world (Zhao et al. 2016;Islam et al. 2021a).In developing countries such as India, wetland degradation in urban areas is a common problem due to discharge of domestic and industrial wastewater, climate change, chemically mixed water from agriculture topped up with solid waste, and unplanned urban growth damaging the overall wetland environment (Gopal 2013).
Numerous studies have been conducted on wetland health across various micro and macro environmental regions such as in tropical (Vittorio and Georgakakos 2018), temperate (Owers et al. 2018), plateau (Cui et al. 2012), highlands (Sharma and Rawat 2009), coastal (Zhao et al. 2016), river basin (Talukdar et al. 2021b), and lakes (Sun et al. 2020).There are different techniques for assessing the wetland health such as fuzzy logic (Alilou et al. 2019), reliability, resilience, and vulnerability paradigm (Hoque et al. 2014), Vigor-Organization-Resilience pattern (Li et al. 2013), pressure-state-response model and the AHP approach (Das et al. 2022a, b), fuzzy Delphi analytic hierarchy process (Ocampo et al. 2018), Single pollution index, Geo-accumulation index, Nemerow's synthetical contamination index, Potential ecological risk index, and principal component analysis (Torbick and Becker 2009;Huang et al. 2020) and metal pollution index, heavy metal evaluation index, degree of contamination index, and water quality index (Tokatli and Fikret 2020).Past studies have adopted different indicators to assess the health of wetland such as aquatic macro invertebrates as bio-indicator (Sharma and Rawat 2009), amphibian (Dupler et al. 2020), flora and fauna (Irfan et al. 2020), soil and water indicator (Montgomery and Eames 2008), heavy metals (Zhang et al. 2014), eutrophication concentration, and toxic release from agriculture activities (Wang et al. 2020).
The interior part of KMA is surrounded by acclaimed wetlands such as East Kolkata wetland, Hooghly River, Rabindra Sarovar Lake, several ponds, and other small water bodies (Mondal et al. 2017).Several studies have been carried out to assess the wetland health by using multiple indicators and approaches (Jafary et al. 2018;Sun et al. 2019;Xu et al. 2020).Alilou et al. (2019) have employed the fuzzy logic theory for the assessment of health and considered erosion of rock surface, slope, topography, morphometric indicators, climatic vulnerability, and nonpoint pollution sources are the indicators for health assessment.Hoque et al. (2014) explore the effects of land use and climate change scenarios on watershed health measurement.Researchers have also used the reliability, resilience, and vulnerability paradigm and vigor-organization-resilience (VOR) pattern to assess ecosystem health (Peng et al. 2017a, b).
Wetland degradation is a common phenomenon in the process of urban expansion which has been noted in different cities of the world (An et al. 2013;Huang et al. 2017;Ma et al. 2021).In KMA, wetlands have been deteriorating rapidly owing to large-scale urban expansion coupled with the multiple anthropogenic activities.Therefore, this study aims to assess the wetland health status in the KMA during 2011-2020 using drivers-pressure-state-impact (DPSI) and analytic hierarchy process (AHP) technique as well as to examine the numerous elements that contribute to wetland health degradation and assess the health under various pressure factors.The significance of this study is that these techniques and the associated concept are anticipated to be support for wetland health assessment on a regional to large area level and to provide scientifically sound decisions regarding the preservation, evaluation, and utilization of wetlands.Although, studies have been done to examine the wetland health in KMA, all these studies were primarily focused on ecosystem problems and consequences, but there was lack of exploration in studying the wetland health and identifying the different pressures and pattern associated with wetland degradation (Ghosh and Das 2020).In this research, we have used the maximum number of diversified indicators which were not used by any other existing research to quantitatively measure the wetland health as well as none had assessed the wetland health municipality-wise in KMA.

Study area
Kolkata Metropolitan Area (KMA) is located in deltaic part of the Ganga-Brahmaputra-Meghna delta (Fig. 1) with the latitudinal and longitudinal extension between 22°00′17″ N to 23°00′03″ N and 88°00′06″ E to 88°00′52″ E, respectively.The Hooghly River flows through KMA that prompted to make it the largest agglomeration region in eastern India and the third-largest in India.It is spread over 38 municipalities and 4 municipal corporations: Kolkata Municipal Corporation, Howrah Municipal Corporation, Chandannagar Municipal Corporation, and Bidhan Nagar Municipal Corporation (Census of India 2011).It additionally contains 77 census towns or non-municipal towns, 16 outgrowths as well as 446 villages.The KMA is administered by Kolkata Municipal Development Authority (KMDA) that incorporates the part of Howrah, Hooghly, North 24 Parganas, South 24 Parganas, and Nadia districts which spreads over 1886.67 km 2 of geographical area.It has tropical monsoon climate, with rainy summers, dry winters, and the average monthly temperature reaches to 27.2 °C, while the average monthly rainfall is 165 cm (Ghosh et al. 2021).The entire population of the study region was 14.2 million in 2011, projected to be 20 million in 2021 and 21.1 million by 2025, with a density of 7950 people per square kilometer and an annual growth rate of 1.8% in 2011 (KMDA 2011; Census of India 2011).After the creation of KMA, various facilities such as infrastructure, cheap living costs, transit, industrial growth, economic development, commercial activity, and employment opportunities all have stimulated potential migration that has been inducing increase in unplanned urban expansion, slum population, poverty, and environmental pollution (Gazi and Mondal 2018;Ghosh et al. 2021).In the KMA, fast growth of urban population has resulted in Fig. 1 Location map of Kolkata Metropolitan Area a number of environmental issues, such as decrease green space, climate change, encroached wetlands, increase water and soil pollution, heat island in city region, and habitat damage (Dutta et al. 2021;Ghosh et al. 2021).

Databases
The present research work has both primary and secondary databases.The indicators of DPSI framework were taken into consideration based on their relative importance as per the literature survey and formal analysis by researchers.To get the indicators of water quality, data was collected from the twelve water sampling stations located in the KMA.Out of these 12 stations, four stations did not have the data of dissolved oxygen (DO), while three did not have the data of total coliform (TC).Hence, to fill this gap, water samples were collected for these stations.The water samples were collected from the same depth (15 cm) for each station.The samples were then tested for two physical indicators, i.e., DO and TC, using standard procedures method (APHA 2005;Wanda et al. 2016).The secondary data were available on published articles, government annual reports, and different organizations (Table 4).The demographic information such as population density, municipality wise households was obtained from the Census of India.  1 and Fig. 2).

Conceptual index model for health assessment
Numerous techniques are used globally to assess the wetland health such as principal component analysis (PCA), Delphi method, artificial neural network (ANN), fuzzy AHP, ecosystem services, ecological integrity, logistic regression model, fuzzy logic approaches, andcellular automata (Camilleri et al. 2015;Walters et al. 2021).Here, two modelling approaches DPSI and AHP are used.This is one of the important flexible and suitable methodologies to determine the wetland health.DPSI is crucial for understanding the cause-and-effect relationships between various environmental challenges.The earlier studies endorsed the DPSI framework as the most appropriate tool for evaluating and managing various environmental issues.Its assessment process is comparatively simple to use, which is efficient for scientists (Banerjee et al. 2020;Shao et al. 2020;Khan et al. 2021).However, there is still a shortage of assessments that incorporate both new and sophisticated conceptual models and weighting techniques at the same time.Another fascinating issue related to wetland ecosystems is that complicated ecological and socioeconomic conditions are often overlooked in studies of health assessment (Jafary et al. 2018).
The DPSI framework is the dynamic and significant methods to assess the wetland health by using multiple indicators.The DPSI framework manifests the association between anthropogenic issues and its ramifications on ecology and socio-economic activities (Camilleri et al. 2015).The DPSI model was applied by researchers, planners, decision-makers, and policy-makers across the globe for the better sustainable planning (Pullanikkatil et al. 2016).DPSI indicators were created after the in-depth scrutiny from scientists and experts in different domains.
The DPSI framework was first developed by the Organization of Economic Co-operation and Development and later accepted by the European Environmental Agency (OECD 1993;EEA 2003).It is particularly applied to determine various issues of environmental concern from district to country level (Tscherning et al. 2012).The framework originated and developed in different stages, i.e., from pressurestate-response (PSR) and driving force-state-response (DSR) models which covered consistency, adaptability, robustness, and understanding sources and causes of environment

Weight determination
The wetland health index (WHI) is one of the most effective techniques for obtaining the present quality of the wetland (Sahu and Sikdar 2008).There are the following steps for calculating the WHI.Each of the 17 indicators and 4 sub-indicators has been given a weight based on its significance in the overall quality.The collected municipalities, municipal corporations, and station-wise raw data from secondary sources (Table 4) were normalized using the following equation: The range of values can vary from 0 to 1.In the next step, AHP calculated through following stage by giving the weight of each indicator with help of expert assistance using the 1 to 9 scale of Saaty's, and then pairwise comparisons were carried out for 17 indicators under the DPSI method (Table 2) (Saaty 1987).Saaty (2003) developed the AHP method, a healthy multi-objective mathematical technique that helps to rate indicators by doing pairwise comparisons of indicators.
In the next stage the consistency test was passed by all matrices (Eq.( 2)) and then calculated the consistency rate (Eq.( 3)).The random index depends on the number of pairwise comparison matrices which is shown in Table 3.Finally, consistency was verified; if the value was less than 0.1, it is confirmed that the result is consistent, and then the AHP weight has been determined.
In the next step, final weight is measured by the AHP weight of each indicator multiplied by the normalized value of municipalities, municipal corporations, and station-wise data (Eq.(4)).For example (B 1 ), in population density cases, (1) AHP weight is 0.084, and the normalized weight of Kolkata MC is 0.5918, and the final weight should be 0.0497 (Table 4).
where, F W = final weight; AHP W = analytic hierarchy process; weight N W = normalized weight.Lastly, the wetland health index (WHI) is calculated by the sum of final weight/number of indicators (Eq.5): where, WF i = the final weight of all indicators in ith municipalities, municipal corporations, and stations, n i = the number of indicators in ith municipalities, municipal corporations, and stations.
The final value of WHI is classified into five categories.

Indicator analysis related to wetland health assessment
The DPSI framework is a tool to measure the different environmental problems and their management techniques.DPSI begins with driving forces (D) which involves human induced activities.Drivers indicator may affect wetland ecosystem which could lead to pressure (P) and changes the state (S) of wetland through driver's impact (I) which if immediate would affect the quantity and quality of fishes and foods (Table 5).

Drivers
Demography (A 1 ) Demography incorporates urban and rural population, density, and sex ratio.According to the 2011 Census, West Bengal's total urban population was around 29 million, while KMA consisted of 15.87 million people.In 2025, the population of KMA is expected to reach 21.1 million with approximate density of 8500 people per square kilometer (KMDA) which is creating pressure on land resources.

Agriculture (A 2 )
In West Bengal as well as surrounding rural areas of Kolkata urban agglomeration in particular, agriculture is one of the most important sources of income.Agriculture intensity has changed the land use pattern significantly, and uses of chemicals and pesticides runoff from the agricultural field into the wetlands causes the deterioration (4)  cities, cities into metropolis, and megacities.As Kolkata city grew with population and developmental activities, people required efficient transport system for the spread of roads and to carry the loads of increasing number of vehicles.
According to Kolkata Metropolitan Development Authority (KMDA), the vehicles that deliver goods would increase from 41,000 to 71,000 (73%), motorized vehicles 10 to 30 lakhs (300%), and river traffic range from 1.43 to 3.12 lakhs/ day (118%) from 2001 to 2025.Though, the dense transport system reduces the time from one place to another, but the unintended growth and expansion of connectivity also have negative impact on environment, as automobiles and roads are maintained poorly and causing land and air pollution (Joseph et al 2009).
Water (A 5 ) Wetlands play a major role in balancing environmental equilibrium with economic activities such as agriculture, industrial, recreational, but on the other hand, the agricultural waste and industrial effluent degrade the habitat of wetlands.This problem is more severe in developing countries than in developed countries.The water quality indicators to measure the wetland health are pH, dissolved oxygen, biological oxygen demand, and total coliform.The water in the KMA was found contaminated with dissolved particles, concentration of algae and bacteria, eutrophication, iron, chromium, and arsenic concentration that deteriorated the wetland health.

Pressure (P)
Population density (B 1 ) and number of households (B 2 ) The population density, total population, per capita income, and households can be regarded as social anthropogenic activities (Pinto et al. 2013) Total income (B 8 ) Primary, secondary, tertiary economy of any country may govern positive and negative impact on wetlands (Castiglione et al. 2015).The most predominant economic activities in KMA are agriculture, fishing, manufacturing, and services.Kolkata MC has the highest total income (Rs 266,684 lakhs), followed by Bhatpara (Rs 1 3 30,289 lakhs), and Howrah MC (Rs 18,034 lakhs).Naihati (533 lakhs Rs), Kanchrapara (Rs 634 lakhs), and Bally (Rs 724 lakhs) municipalities have the lowest total income.However, the investment on environmental sector, policy implication to protect the ecology is highly profitable.
Others: urbanization growth According to the United Nations 2011 report, the Kolkata urban agglomeration is the third in the country and the tenth place in terms of population in the world that constituted around 14.72 million people (UN 2011).This growth occurred owing to birth rate, migration, employment opportunities, education, medical facilities, and economic investment.But in KMA, the major concerning issue is environmental degradation due to the high pace of unplanned urbanization (Peng et al. 2017a, b;Ghosh et al. 2021).The urban population growth rate is highly correlated with loss of cultivable areas, loss of biodiversity, and degradation of water bodies.

Use of fertilizer
Mostly fertilizer and pesticides used to produce vegetables, grains, and fish in a short-time period.But excessive usage of these chemicals, as well as poor management, has a negative influence on the wetland environment (Carey et al. 2011;Islam et al. 2021b).

Number of registered industries
Rapid industrialization has put a severe strain on the environment which is a matter of great concern (Parveen et al. 2021;Rihan et al. 2021).In West Bengal, the major pollution contribution to environment is from the industrial sector.The red category industries such as dyeing and bleaching industries were restricted within Kolkata Metropolitan Area because these were producing excess toxic material.Six districts (Kolkata, Howrah, Hooghly, South 24 Parganas, North 24 Parganas, and Nadia) are included in the Kolkata Metropolitan Area, and maximum registered industries are found in North 24 Parganas, followed by Kolkata and Howrah.The waste discharge by industrial activities cause pollution in water bodies and changes the land use pattern in the study area.

Change of water area (NDWI, MNDWI, NDPI, and NDTI) (C 1 ), change of vegetation area (NDVI) (C 2 ), and change of built-up area (NDBI) (C 3 )
The land use land cover in KUA is changing rapidly owing to the urban and industrial development (Sahana et al. 2018;Makwinja et al. 2021).It has significant impact on vegetation cover and water bodies.In this study, the major components to assess health of water bodies and vegetation cover are NDWI, MNDWI, NDPI, NDTI, NDVI, and NDBI.The values of all index ranges vary from + 1 to − 1.
The KMA wetland ecosystem changed enormously from 2011 to 2020 due to intensive agriculture and encroachment by built-up cover (Mondal et al. 2022).The NDWI was used to calculate the area of water and non-water bodies and differentiate water from terrestrial vegetation and soil cover (McFeeters 1996).In 2011 and 2020, the result showed NDWI range from 0.714 to − 0.704 and 0.122 to − 0.386, respectively (Table 6 and Fig. 3).MNDWI determines water and non-water areas particularly where water bodies and built-up areas intermix (Sagar et al. 2017).The MNDWI value in KUA ranged from 0.695 to − 0.678 and 0.288 to − 0.617 for the years 2011 and 2020, respectively (Table 6 and Fig. 3).In 2011 and 2020, the NDWI and MNDWI positive values were noticed majorly in the Hooghly River, east Kolkata wetland, and minor values were observed in small extent in the entire KMA.While, NDWI and MNDWI was immensely found in negative values in Gayeshpur, Kalyani, Maheshtala, Uluberia, Barasat municipality and central part of north-west, and extreme south direction of KMA.Therefore, the result implies that the natural wetland has been encroached by built-up, agriculture, and other land uses.
Sometimes, NDVI could not make a clear difference of vegetation in water bodies and on the ground between the natural vegetation cover and agriculture (Lacaux et al. 2007).It might give the distorted result of the same spectral reflectance.Hence, NDPI fills in to detect the vegetation even in a very small pond without any spectral reflectance distortion, and the presence of water turbidity helps in assessing the pond cover (Mondal and Bandyopadhyay 2014).In 2011 and 2020, the NDPI values were ranged from 0.678 to 0.695 and from 0.617 to 0.288, respectively (Table 6 and Fig. 5).In 2011, the highest concentration of NDPI was noticed along the Hooghly River, North of Panihati, North Dum Dum, south of East Kolkata Wetland (EKW), Kalyani, Gayeshpur, Barasat, and Uluberia municipalities.In 2020, it got   decreased and was majorly found in Uluberia, south of EKW and sparsely seen in the KMA areas.
The NDTI is mainly used to detect varying degrees of turbidity and muddy concentration in water (Lacaux et al. 2007).A turbidity index is applied for wetland water quality assessment (Singh et al. 2020).It is used for inland wetlands including ponds, reservoirs, ox-bowlakes, and rivers (Panigrahy 2017).The NDTI results showed the turbidity value of 0.287 and − 0.666 in 2011 and 0.097 to − 0.081 in 2020.The NDTI values of KMA's wetland manifest that the very high turbidity found in Bidhannagar, Madhyamgram, North and South Dum Dum region for the years 2011 and 2020 (Table 6 and Fig. 4).In 2011, maximum small water bodies or higher NDTI values were observed in the north-west, middlewest and south-east of KMA but in 2020, it encroached by built-up areas (Fig. 4).
In this study, NDVI is employed to estimate the green surface of the region.Greater NDVI value represents green vegetation presence in the region.The range of NDVI was from 0.809 to 565 and from 0.446 to 0.115 in the year 2011 and 2020, respectively.The maximum vegetation was found along the margin of KMA in 2011 and west and north-east of KMA in 2020 (Table 6 and Fig. 5). Figure 5 shows that the disturbed vegetation areas are from Rajpur-Sonarpur to Baruipur, along the NH 12, south of EKW which transformed from vegetation area to settlement or agriculture area.
Wetland habitats in urban areas are under threat from rapidly growing urban population specially in developing nations (Ehrenfeld 2000;).Uncontrolled built-up growth has a significant problem to the natural ecosystem (Shahfahad et al. 2022;Ghosh et al. 2019).Therefore, built-up area change is shown using the NDBI indices of the study area (Fig. 5 and Table 6).The values of NDBI range from − 1 to + 1, with vegetation cover surface being 0; water cover and built-up indicate negative and positive values.The result of NDBI varies from 0.771 to − 0.5 in 2011 and from 0.447 to − 0.388 in 2020.The maximum extension of the built-up was noticed along the highways, outskirt of cities, most of municipalities have higher concentration of urban areas in KMA both in 2011 and 2020.The built-up area encroached the water bodies, green space, and agricultural areas resulting in municipal wastes, and posing a threat to ecological security (Dutta et al. 2020).

Impact (I)
Water quality change (D 1 ): BOD (D 1a ), DO (D 1b ), pH (D 1c ), and total coliform (TC) (D 1d ) The water bodies offer ground to fishes and vegetables which become the source of local livelihood.The quality of surface water in urban areas is challenging, particularly with the rise of population and climate change (Miller and Hutchins 2017).Therefore, partially treated sewage, dumping on wetlands, insufficient solid waste collection, and chemical usage in agricultural and manufacturing factories are the predominant concerns in KMA (Ellis 1991).The standard limit for biological oxygen demand (BOD) is 3.0 mg/l.In comparison to upstream, the downstream in the Hooghly River had crossed the limit.In 2011, the Kharda canal had the highest BOD (79 mg/l), followed by Noai Canal and East Kolkata Wetland (EKW), while in 2020 the EKW, mainly in the Nalban Bheries, had the highest (80.32 mg/l) during monsoon since garbage in cities drains into the fisheries or bheries.
The dissolved oxygen (DO), pH, and total coliform acceptable limits are 4.0 mg/l, 6.5-8.5, and 5000 MPN/100 ml, respectively.For the years 2011 and 2020, the greatest DO levels were observed in Serampore locations and the Rabindra Sarovar Lake.In 2011, EKW (8.4) had the highest pH, followed by Palta (8.15) in 2020.In both periods, the TC was greatest in the Khardah Canal.
Others: total fish production in wetlands and area under cereal production The demand for fish and food in the megacities of Asia is rapidly increasing which is putting pressure on fish stocks.In KMA also, the demand for fish and grains is high.According to recent studies, East Kolkata Wetland Management Authority (EKWMA) and Wetland International South Asia reported that 20,000 metric tons (MT) of fish and 50,000 MT of vegetables along with huge rice farming are produced in KMA wetland farming areas.The surrounding districts of KMA, the highest production of fish found in North 24 Parganas, i.e., 1502176.5 quintals.But fishes and foods in KMA are often found contaminated with heavy metals, chemicals, and pesticides, and the area of cereals is shrinking due to the grave impact of industrialization and urbanization (Nadella and Sen 2021).

Wetland health analysis
In the Kolkata Metropolitan region, the wetland health index (WHI) results were based on the municipality and station-level data assessment (Appendix Table 8, Table 7, and Fig. 6).Five categories were used to examine the status of the driver, forces, pressure, state, and impact sub-systems.The wetland health conditions in different municipalities were explored using the DPSI framework model.In WHI, the results of each municipality were ranked and then divided into five categories, 1 3 i.e., healthy, sub-healthy, unhealthy, poor, and very poor (Table 5).Wetlands with very poor health were observed in Howrah MC, Garulia and Hooghly-Chinsura from B1 to B8 under pressure (P) indicator.Kolkata and Kalyani are part of the poor category.Bally, Bansberia, Basirhat, Bhatpara, Dum Dum, Kamarhati, and Khardaha were in the unhealthy category; Chandannagar MC, Baidyabati, and Baranagar are sub-healthy groups; whereas all municipalities are included in the healthy wetland category (Appendix Table 8).
The impact (I) indicator of DPSI model revealed a clear health condition of water.The weight of 2011 and 2020-year data was used for a better understanding of wetland health in the "Impact (I)" section.In 2011, the KMA wetland health status index found no stations in the healthy and very poor categories.Tribeni in Bansberia and the water reservoir St. Helens School in Howrah MC were in the sub-healthy category; Howrah-Shivpur (Howrah MC) was in the unhealthy category, and the remaining stations were in the poor category.In 2020, the D1a to D1d indicators found the dynamicity of wetland health that is improved, declined, and showed a moderate trend in the value of WHI under the impact (I) indicator of the DPSI model.The health of the Nalban Bheries in the east Kolkata wetland has improved from poor to healthy, and the Garden Reach of Kolkata MC has also improved from poor to sub-healthy.Palta (North Barrackpur Municipality), Rabindra Sarovar Lake, and Noai Canal (Madhyagram) were all changed from poor to sub-healthy.The sole Kharda Canal in Khardah Municipality was in very poor health, while the other stations are part of the wetland's poor health category (Table 7 and Fig. 6).

Discussion
In association with the execution of the wetland conservation and urban plan, this study provided quantitative data on wetland health deterioration in the Kolkata Metropolitan Area.The wetland provides lots of services such as replenishes groundwater, manages floods, balances the local weather phenomena, and filters pollution and carbon sink (Cao et al. 2017;Gebremedhin et al. 2018).However, globally the status of natural wetlands have been found depraved with inland wetlands being more affected than the coastal wetlands (Xi et al. 2021).Both developed and developing nations have witnessed devolution of wetlands due to multiple factors such as building of dams and barrages, river diversions, poor watershed management, toxic element risk, sedimentation, eutrophication, overfishing, composition of land use, and pesticides used (Banerjee et al. 2017;Jafary et al. 2018;Tokatli and Fikret 2020).In India, wetlands have dramatically decreased on account of declining ecosystem services, urban sprawl, and various other developmental activities (Abraham 2015;Kumar et al. 2020;Parveen et al. 2022).In West Bengal, river habitat suffered greatly as a result of numerous man-made changes (Mishra et al. 2009).Wetland is suffering from various physical and biological concerns due to climate change and scarcity of water during lean season in KMA (Das et al. 2022a, b).The health of the wetland in KMA has also been deteriorating due to industrial and commercial activities which are transforming the landscape and leading to unplanned urban expansion that directly puts a threat on natural ecosystem of a region.The growing population has also a direct impact on amount of municipal solid waste generation and from industries as well which is one of the factors of wetland deterioration (Nabulo et al. 2008).The quality of wetland health changes seasonally in KMA and DO was found to be lowest in monsoon and post-monsoon season and greatest in the winter.
In this study, wetland health index has been prepared using the DPSI and AHP method.In the previous studies, same approaches and indicators were used on wetland health estimation which reported the trend in wetland health deterioration (Camilleri et al. 2015;Shao et al. 2020;Han et al. 2020).The current research work assessed the drivers such as demography in urban area, agriculture in rural area, water in both rural and urban areas, and the transport and industrial indicators in the peri-urban and along the roads in KMA have been affecting the wetland health.The pressure indicators were the main trigger for drastic worsening of wetland status in most of the municipal areas than the rural areas.State factor manifested that the smaller size of wetlands was encroached more rapidly than the bigger one, but it not only downgraded the small ponds but also the large lake, i.e., East Kolkata Wetland in KMA.The majority of municipalities and stations fall into healthy groups, but wetlands of all groups are still suffering from road construction activities, urban area expansion, sewage water, and waste disposal from industry and urban houses, land filling, and water contamination through siltation in KMA (Sahana et al. 2018;Das et al. 2022a, b;Mohibul et al. 2022).The used ranking system in the present research of KMA into municipality and stations determined the wetland health which is associated with social and economic attributes.The significant consequences have leading various detrimental effects on the wetland ecosystem, some of which are already noticeable.In addition, the wetland inside the KMA also maintains the environmental condition.In this study, the result of wetland status and the existing work on wetlands water also witnessed significant deterioration.The similar result have been found in various states of India such as Tripura and Madhya Pradesh, and Karnataka pesticide concentrations varied according to the season and recorded highest dissolved oxygen levels in the winter (Dhananjayan and Muralidharan 2010;Rao et al. 2015).Pollution in static water bodies such as lakes was caused mainly by untreated sewage water, agricultural runoff, and waste from birds.However, there are some limitations of the study that exist in not incorporating the factor wetland health assessment such as paddy production, soil quality, vegetables, fruits, tourism and impact of wetland water on human health, water management strategy, heavy metals in wetland, wetland biodiversity, and others due to lack of resources.
The government has been putting effort to mitigate the wetland degradation such as National Wetland Policy which emphasizes the significance of delineating wetlands, wetland complexes, and zones of affect, documenting short reports, planning and management with the help of government agencies, water users, and other stakeholders (GoI 2018).The government of West Bengal has also passed wetland conservation policy to deal with physico-chemical and biological indicators to estimate the water's quality and prohibit certain activities such as building embankments around wetlands, illegal construction and releasing impurities into wetlands.The West Bengal Housing and Infrastructure Development Corporation (WBHIDCO), EKWMA, and WBPCB, belong under this KMA in order to decrease wetland problems; mapping processes are also utilized to assess the extent, type, location, and ownership of wetlands, and pollution control (Mondal et al. 2017).Despite all these efforts, there has been a persistent matter of wetland devolution in KMA (Bose 2015).The current research work identified the indicators of wetland degradation municipality and the zone wise meticulously.The study will aid in modifying policies to monitor the wetland health and mitigating the disdained issue in the study area and around the globe wherever the same geographical conditions exist.

Conclusion
In current research work, DPSI and AHP models were used to examine the health of wetland ecosystem in KMA.The statistical data and remote sensing data with experts' scoring data were used to assess the wetland health.The findings of this study show that most of the municipalities fell into the healthy category of wetland health index in 2020.In the case of water quality of wetland health index, the maximum stations are under the poor category in both 2011 and 2020.Out of 42 municipalities, 27 municipalities fell under the "healthy" category, 3 municipalities "sub-healthy," 7 municipalities "unhealthy," 2 municipalities "poor", and lastly 3 municipalities under "very poor" category of wetland health.Furthermore, there was no station under "healthy" and "very poor" categories in 2011, but there was one station each at "healthy" and "very poor" categories in 2020.Municipalitywise, the most responsible indicators of wetland health were population density (B1), road density (B3), per capita sewerage generation (B5), and per capita solid waste generation (B7).The station-wise data of water quality change such as BOD (D1a), DO (D1b), pH (D1c), and total coliform (D1d) have fluctuated in the wetland from 2011 to 2020.The result implies that KMA's haphazard industrial and urban expansions have inversely affected the wetland habitat.Even though negative pressure on ecosystem has risen but local people's knowledge and their contribution to safeguard wetlands, as well as government investment in wetland monitoring and management, waste management may help to maintain the healthy wetland environment in KMA.Moreover, the present research will also provide insights for the preservation of wetland ecosystem, as it has addressed the critical association of wetland health and anthropogenic issues.

Appendix
damage(Han et al. 2020).The first stage of DPSI model was to determine the driving forces (demography, agriculture, industry, transport, and water) associated with wetland degradations, followed by pressure indicators (population density, road density, sewerage generation, solid waste generation, and income) that leads to the state factors of wetlands (change of water, vegetation, and settlement area) and then stage of impact (water quality change).In the state (S), the Landsat and LISS-III satellite images were used to generate multiscale indices (Fig.2).ERDAS Imagine software version 14 was used to preprocess (layer stack, mosaic, and atmospheric and radiometric correction) the satellite data and extract the area of interest.Multiscale segmentation techniques such as NDWI, MNDWI, NDPI, NDTI, NDVI, and NDBI, were performed in ArcGIS 10.1 for the years 2011 and 2020.

Fig. 6
Fig. 6 Station-wise weights of different assessment indicators in KMA for 2011 and 2020

Table 1
Description of satellite images

Table 2
Relative importance scale of AHP 3 ) West Bengal has been a resource-rich state with great industrial estates in both pre-and post-independence period.The prominent industrial centers in KMA are with leather complexes in South 24 Parganas, where 22 to 24% of India's tanning exports are and also garment park Transport (A 4 ) In Bengal, landscape has been consistently changing.Earlier, the landscape was majorly covered with towns which with time and development transformed into

Table 4
AHP weight of different indicators

of solid waste per day (B 6 ) and per capita solid waste generation (B 7 ) One
(Makoni et al. 2016)1)ld usually have high density of road network and accompanying construction operation(Chenery et al. 2020).Road density is one of the vital components to analyze the wetland health status in urban landscape.The expansion of expressways (Belghoria, Dum Dum and Srerampur-Barrackpur-Barasat expressway), The inappropriate management of huge amount of untreated domestic, agriculture, and and industrial waste poses serious challenges to environment and human health(Nadella and Sen 2021).In West Bengal, total sewage generation in 2008 was about 2345.21 million l/day and 180.42 million l/day in class I cities and II towns(CPCB  2011).The majority of total sewage has been generated from Kolkata MC (172 MLD) and Howrah MC (63.9 MLD).The maximum and lowest per capita sewage was generated from Kalyani (198 MLD/person) and Maheshtala (15.49MLD/ person) municipalities under Kolkata Metropolitan Area (CPCB 2011).Due to untreated waste disposal, poor sewerage, and drainage supply, KMA wetland ecosystem is presently dotted with many big waste-fed areas(Makoni et al. 2016).
(Census of India 2011).Furthermore, pressure factors that determine the wetlands have become unable to offer ground water recharge facility and ecosystem services.Road density (B3)

Table 6
Range of different index values and formulas for wetland

Table 8
Municipality-wise weights of different assessment indicators in KMA