Carrying capacity and strategic planning for sustainable tourism practices in the Char Dham from the Western Himalaya, India

The Char Dham Yatra (journey) significantly contributes to the economy of Uttarakhand state, generating approximately USD 888 million annually and employing 50,000 people⁴². However, the increasing number of visitors in Char Dham, reaching over 4 million pilgrims in 2022⁴³ and an estimation approximately 6 million in 2025 raise prime environmental and management concerns. Kedarnath, alone producing 1.5-2.0 tonnes of daily waste during peak season^44,45, aims at launching different waste to energy initiatives like microbial biocomposting from biowaste, reuse of non-biodegradables for developing small waste eco-parks, etc. for promoting sustainable tourism, and balancing economic benefits with ecological preservation. To manage tourism in the area sustainably, the most effective scientific methods is “nip in the bud” approach that needs to be practised at the source of waste or any other pollution generation, together with stringent enforcement of current regulations. The findings of the present study depict the vital interaction mechanism among geospatial analysis, impacts of climate change, socioeconomic elements, and carrying capacity analysis for sustainable tourism development in the Char Dham area. The study region shows varying degrees of tourism compatibility based on vegetation cover, slope, and elevation. Lower elevations, omitting valley bases on either side with a minimum of 100 m, and moderate slopes with best fit approach are included for developing future spots. The Char Dham areas are facing significant challenges associated to climate change as a result of rapidly retreating glaciers, rising temperatures and extreme weather events as cloudbursts that endanger landscapes, human settlements, water resources and biodiversity. Weather radars and other weather forecasting mechanism need to be made available on priority in order to accurately predict extreme weather events in these high-altitude regions, especially in view of the devastating experiences of the tragedies in Kedarnath (16–17 June 2013), Reni village (7 February, 2021), Dharali (5 August 2025), Tharali (23 August 2025), Sahastradhara and Tapkeshwar Mahadev in Dehradun (15 September, 2025) and many others caused by cloudbursts and flash floods. So the results of the study collectively highlight the need for climate driven disaster adaptive tourism action plans for increasing sustainability of these areas.

Sustainable tourism and action plan for the decentralization of tourism

The Department of Economic and Social Affairs defines ‘sustainable tourism’ as ‘a form of tourism that addresses the concerns of visitors, the industry, the environment, and host communities while considering its present and future economic, social, and environmental impacts’. Tourism addresses multiple sections of the 2030 Agenda for Sustainable Development. For instance, SDG 8.9 pertains to the formulation and execution of policies that encourage sustainable tourism, which not only creates employment opportunities but also supports local culture and its products. Similarly, SDG targets 12.b. and 14.7 are focused on creating jobs through sustainable tourism that will give economic benefits to the people. In view of the above objectives, customized actions are required to be implemented in the Char Dham area including development of mountaineering villages for planning of home stays, infrastructural services like adequate car/vehicle parks, and amenities prior to develop a spot or its satellite spot, promotion of adventure tourism destinations, development of community-based responsible tourism and launching sustainable travel mobile App for secure travel. Specific implementation plan for the mentioned strategies is provided in Table 5 and Fig. 7. Further, minimizing the adverse impact of concentrated and localized tourism, decentralization of tiny spots surrounding major spots may be alternate options for planners³. Keeping this in view, potential tourist spots were also identified with classified zones for future development of satellite tourist spots in and around the Char Dham area. Implementing such plan as well as establishment of ecofriendly tourism initiatives will be beneficial for managing the overwhelming tourist rush in the areas by decentralizing them in the suggested satellite spots. This approach will not only reduce continuous pollution loads at a spot or shrine but will also minimize seasonality of tourism in view of changing available tourist resources in different seasons in these locations. Here, available infrastructure, and income of the local communities will suit to all-weather tourism with all-weather roads being under construction to reduce travel time, increase transportation efficiency, less emissions, smooth transit of goods and services, uninterrupted movement of visitors and minimizing congestions. However, regulatory measures like maintenance of carrying capacity, proper management of solid waste^46,47, bringing ambient air pollution emissions under prescribed norms through introducing electric rickshaws, car, vehicles, ropeways, etc. also need to be introduced in the Char Dham as well as proposed alternative tourist places surrounding to them. The Hon’ble Prime Minister of India, Mr. Narendra Modi, suggested the idea of “Gham Tapo” (basking in the sunshine) tourism, which Uttarakhand Tourism is also pursuing. The term “Gham” in the local Garhwali language means “sunlight,” while “Tapo” means “basking”. In the Himalayan region, where the sky is clear, local communities typically warm up under bright sunlight during the winter months. On the other hand, smog and other transported aerosol emissions from both inside and outside the region throughout the winter keep the Indo-Gangetic Plain and other adjoining Punjab Plain regions obscure. This noble idea of “basking in the sunshine” may therefore be beneficial from the perspective of tourist health recovery in the form of body warming and ‘vitamin D’, as well as reducing seasonality during the winter months when there are not enough recreational resources available except winter sports like “snow” or “skiing.”

Sites recommended for establishment of ecotourism circuits and sustainable tourism development plan in and around the Char Dham area (generated using ArcGIS software (ESRI, CA, USA), https://www.esri.com/en-us/arcgis/products/arcgis-online/trial).

SDGs and policy directions towards promotion of green tourism

While working towards achieving the SDGs, appropriate policy and planning processes are crucial for local, regional, and national levels. Destinations are likely to be benefitted from the positive effects of tourism components⁴⁹. At present, the state has launched “Uttarakhand Tourism Policy 2030”, which proposes to develop tourism industry in the state by including 5 sectors, such as, nature and adventure tourism, health and wellness tourism, religious and cultural tourism, heritage tourism and meetings, Incentives, Convention and Exhibitions (MICE) tourism. Further, several other schemes and projects that are presently operational in the areas include, ‘Swadesh Darshan (SD)’ and ‘Pilgrimage Rejuvenation and Spiritual, Heritage Augmentation Drive (PRASHAD)’ and ‘Scheme for Special Assistance to States for Capital Investment (SASCI) 2024-25’. The SD and PRASHAD mainly focuses on sustainable and theme specific development of tourism that aligns with the geoscientific, bioscientific, socioeconomic, and cultural-historical indicators of the present study. Whereas, the SASCI is focused on infrastructure development and iconic tourist centres. The current study adequately describes the development of nature-based tourism while addressing the challenges of over tourism and carrying capacity within limit, which are important aspects of sustainable tourism. Here, a concept is important that carrying capacity approach is required for tourist influx as well as with vehicular influx in the areas and equines used for the trek routes. As unlimited vehicles cause air pollution and unhealthy equines are used in trek routes and even their dead bodies are associated with soil and water pollution. Also, policies focused on entry of vehicles only with Bharat Stage VI (BS VI) and/or electric vehicles, empowering nomadic tribes through ecotourism (Radampa and Bhotia in Mana village, Badrinath; Jaad-Bhotiyas in Gangotri) are suggested for the area. Further, infrastructure facilities reading proper monitoring of air, water and soil quality of these pristine areas are urgently needed. Investments are also required for a development of infrastructure in remote mountain regions, particularly in the digitalization of tourism services tapping the local food network and promote sustainable tourism. In addition, a comprehensive tourism marketing strategy is essential. This strategy focuses on creating and expanding markets for tourism while simultaneously developing the necessary infrastructure to support the growth of the industry. It also emphasizes the importance of collaboration between the public and private sectors to leverage resources and expertise. Also, effective promotion of the destination is a key component to attract tourists and maximize revenue generation. By implementing a well-rounded tourism marketing strategy, the aim is to create sustainable economic benefits for the destination and its local communities (Table 6). The small and medium-sized enterprises (SMEs) of travel and tourist industry have the ability to positively influence the environment, economy, and society. In emerging nations, SMEs are crucial for advancing socioeconomic well-being. Micro-entrepreneurship in the tourism sector has been demonstrated to assist socioeconomic growth and conservation goals in the destinations that prioritize nature-based tourism. Given the important role of travel, particularly small-scale travel, plays in the expansion of SMEs, entrepreneurship can help to promote the long-term growth of the tourist industry. A number of SDGs, including SDG 1 on reducing poverty, SDG 4 on improving education, SDG 8 on promoting economic growth and decent work, SDG 12 on responsible production and consumption, and SDG 13 on combating climate change, ought to be undertaken by the commercial sector⁵⁰. Nonetheless, tourism is a key factor in all 17 goals (Fig. 8).

Potentiality assessment of green tourism and strategy for sustainable tourism in the Char Dham area.

Database and methodology

This study employed a multidisciplinary approach to assess the Char Dham pilgrim circuits in Uttarakhand, India, integrating geoscientific, bioscientific, socioeconomic, and cultural-historical analyses for the assessment of site suitability. A spatial assessment of tourism resources used 10 main indices encompassing 21 sub-indices, with a distribution emphasizing geological and ecological factors due to their relevance to the pilgrimage routes. The methodology incorporated field surveys, GIS mapping, cartographic analysis, archival research, and literature review. Field evaluations, conducted between 2019 and 2023 at regional and local scales, are focused on selected geosites. This comprehensive approach enabled a systematic evaluation of tourism potential of the region, considering both current conditions and future prospects for sustainable development.

Analysis of thematic layer

The selection of elements or thematic layers constitutes the initial phase of the present investigation^51,52,53. Thematic layers mainly taken under consideration were slope, elevation, vegetation, proximity to drainage, retreat of snow cover, climate, biodiversity (including national park or wildlife sanctuary), natural geosites over surface, sub-surface (caves, hot springs), unique natural sites (alipne pastures, lakes, hill villages), cultural places (temples), socio-economic index (rural and urban MPCE, BPL families %, monthly income of highest earning members), and tourist facility (tourist carrying capacity and proximity to road) have been taken into consideration (Fig. 9) for the identification of potential ecotourism sites. Influence of these mentioned layers with the tourism sector is described in Table 7.

Generation of data base

Geospatial characteristics analysis

While planning ecotourism locations, elevation was considered to be a key factor. The sites around the Char Dham were categorized into three elevation classes: low (< 2400 m), moderate (2400–4200 m), and high (> 4200 m). Further, slope of the land surface also influences the construction of potential ecotourism sites. The slope layer was classified into three classes: low (0–16°), moderate (16–33°), and high (> 33°).

Vegetation: This is an essential component for the development of ecotourism sites. Vegetation layer was derived from global map of land use land cover (LULC) dataset which is acquired from ESA Sentinal − 2 imagery at 10 m resolution⁵⁴.

Proximity to road: Proximity is a spatial analysis tool being used to determine specified distance in view of other factors like road, drainage, settlement, etc⁵⁵.

Destinations with well-developed transportation systems and convenient access are generally more appealing to tourists^56,57. In order to identify suitable ecotourism sites in the Char Dham, ArcGIS software was used to establish three buffer zones from the existing road network spanning distances of 1000 m, 1000–3000 m, and 3000–5000 m.

Proximity to drainage: In view of determining the distance between drainage networks and ecotourism sites, reclassification process was used. Areas with reasonable distance from drainage were given a higher preference to be considered as a potential ecotourism site. Hence, sites within 100–800 m distance⁵⁸ are suitable, while 800–1600 m are moderately suitable and 1600–3200 m are less suitable.

Proximity to trek: Trekking is such an activity through which one analyses nature at close whether it is pristine or polluted. Char Dham also let tourists to explore its nature through pristine treks and trails⁵⁹. Based on proximity buffer analysis, trek routes were classified into three buffer zones; 100–600 m, 600–1200 m and 1200–2400 m.

Snow cover change analysis

Snow cover retreat rate of the glacier areas of each Dham was analysed using MODIS aqua (MODIS/006/MYD10A1) and terra (MODIS/006/MOD10A1) daily snow cover datasets (500 m) in the google earth engine’s integrated development environment (IDE), code editor platform⁶⁰.

The normalized difference snow index (NDSI) algorithm, effective for binary (i.e., delineating between “snow” and “no snow”) monitoring of snow cover, used both datasets. NDSI is defined as the difference in reflectance between wavelengths of visible (green) and shortwave infrared (SWIR) light:

The surface reflectance in the green and SWIR bands, denoted as rgreen and rSWIR, respectively. The range of the index varies − 1 to + 1. Pure snow pixels have a non-destructive strength index (NDSI) that is significantly higher than pixel compositions which contain combined elements (e.g., snow, water, vegetation, bare ground, etc.).

Climate analysis

Since meteorological observation for the study regions started recently, so in view of assessing long-term climate variability, we have used Climate Research Unit (CRU) climate data ( These have been in well agreement between observed climate data in the mountain terrains. Monthly temperature and precipitation data for the period 1990–2020 were used for the study in all the study sites. Linear regression analysis showed significant growing or decreasing trends in the time series. The significant trend was assessed using coefficient of determination (R2) and p-value < 0.05. In view of discovering seasonal changes in climatic data, the research was carried out for each season: winter (December-February), pre-monsoon (March-May), monsoon (June-September), and post-monsoon (October-November).

Biodiversity & geodiversity analysis

Thereafter, Natural & cultural heritages (peaks, glaciers, etc.), sub-surface (caves, hot springs, etc.) unique sites (alipne pastures, lakes, hill villages, etc.) and location of temples are digitized using high-resolution satellite imageries like Airbus and Maxar technologies through the Google Earth Pro platform and field surveys.

National Park and Wildlife Sanctuary acquired from BHUVAN NRSC site and later their per cent area was computed in ArcGIS.

Socio-economic conditions: District level analysis was carried out using secondary data under review. Parameters like rural MPCE of the district, urban MPCE of the district, % of BPL families in the district, monthly income of the highest earning members in the district (rural households %) were considered for analysis.

Tourist facilities assessment

The areas were analysed by two sub-categories, namely, tourist carrying capacity of the main areas, and road density. Physical Carrying Capacity (PCC), which refers to the utmost number of tourists who could be physically accommodated in or onto a designated area during a specific period of time, was computed in view of the tourist carrying capacity analysis⁶¹. Estimations for the PCC were as follows:

Where, PCC denotes physical carrying capacity; A = Area available for tourist use. Between 15% and 20% of the total geographical area is considered for the present tourist activity in accordance with Urban and Regional Development Plans Formulation Implementation (URDPFI) guidelines⁶² along with expert opinion given that the economy and employment of the region are exclusively rely on tourism. The census data pertaining to Badrinath and Kedarnath regions was taken into account for subsequent analysis. The region encompassing Gangotri and Yamunotri shrines is computed using LISS-IV data from 2017.

Au = required area per tourist, or 3 m; Rf = Daily operating time divided by average visit duration.

Also, the Real Carrying Capacity (RCC), which refers to the highest allowable number of visitors to a particular site, can be ascertained once it becomes feasible to calculate the Correction Factors (CF) based on prevailing unique attributes of a site. Consequently, CF is implemented in the PCC as shown below.

RCC represents actual carrying capacity; PCC denotes physical carrying capacity; and Cf signifies correction factors. The formula for determining correction factors is as follows.

The variables Cfx, Lmx, and Tmx represent the correction factors, limiting magnitude, and total magnitude of variable x, respectively.

Methodological approach used for framing sustainable tourism action plan for the Char Dham.

Driving the normalized weight using AHP

Analytical hierarchy process (AHP) weighting of the subcategories was performed in the subsequent phases. AHP, an approach to multiple criteria decision analysis (MCDA) used in a variety of scientific fields, is a widely recognized methodology. The AHP framework provides a systematic approach to quantifying the pairwise comparison of various decision elements and criteria. In order to rank the value of a criterion map for a pairwise matrix using Saaty’s scale^63,64, the opinions of experts were taken into account.

Further, consistency ratio (CR) and normalized weight of different thematic layers were also calculated (Table 8). CR predicts (acceptable value should be < 0.1), the inconsistency of judgments mathematically and calculated by the following equations.

Where, CI = Consistency ratio, RI = Random Index.

Where ⋋ = The largest Eigen value of the matrix, n = represents the number of sub-categories.

Site suitability assessment

Further, site suitability assessment score “Si” in the final stage was evaluated for each Dham based on the linear combination of each used factor’s suitability score as shown in the following equation.

Where ‘n’ indicates number of sub-categories, ‘Wi’ shows multiplication of all associated weights in the hierarchy of “i^th” sub-category and ‘Ri’ is a rating given for the defined class of the “i^th” sub-category found from the direct assessment. When weighted linear combination is used for Multi Criteria Evaluation (MCE), the sum of assigned weights should be 1 for a defined each category/subcategory. Each factor sub-category layer was classified into 3 suitability classes (i.e., S1, S2, and S3) and their suitability scores were presented in the standardized format ranging from marginally suitable to high suitable. Finally, the total suitability score from each factor was assembled to create site suitability map for ecotourism. The land suitability map for ecotourism created based on the linear combination of suitability score of every index. The GIS-based model for multi-criteria land suitability evaluation for ecotourism is shown in Fig. 2.

However, there have been some of the limitations of the work which mainly include the estimation of carrying capacity which is based on physical parameters and may inadequately accounts for spiritual significance and real experience of the visitors. Though perceptive, the estimates of carrying capacity in the Char Dham area have significant limits that need to be noted. Here, strict geographical limits and LULC analysis only to the temple associated areas form the basis of most estimation. These do not fully consider dynamic elements as seasonal fluctuations, infrastructure adaptation, or socio-cultural impacts. For example, development in tourism infrastructure, better waste management systems, and better crowd control policies might raise the real carrying capacity in use. In addition, behaviour of the visitors and ability of the local ecosystems to withstand human activities are not specifically considered, which could lead to an underestimation of the actual capacity. Moreover, the calculations neglect psychological or economic carrying capabilities reflecting visitors’ contentment or profitability of tourism operations. Seasonal influxes during times of maximum pilgrimage also provide difficulties in matching theoretical capacities with real world situations. The study ignores adaptive tactics that could improve accessibility and usability in less favourable terrain, even while it sets fixed standards for elevation and slope suitability. Therefore, even if the results offer a basic framework for sustainable tourist planning, dynamic assessments and adaptive management techniques should be added to properly address these restrictions. Further, the suggested sustainable tourism strategies in spite of being comprehensive may face implementation challenges due to limited resources and institutional capacities in these remote areas. For future endeavours, extensive engagement of the stakeholders and local participatory approaches are suggested for addressing the present limitations.