WebGIS decision support tool helps Bhutan manage landslide risks

In the mountainous kingdom of Bhutan, where steep Himalayan slopes, intense monsoon rainfall, and rapidly expanding road networks combine to make landslides one of the nation’s most persistent natural hazards, a team of Bhutanese researchers has unveiled a new web-based decision support system designed to transform how the country assesses and manages landslide risk. The platform, described in a study published in the journal Natural Hazards, is a two-dimensional WebGIS-based decision support system that brings together hazard, exposure, and vulnerability information at the level of the Gewog, Bhutan’s smallest territorial and administrative unit. By placing this information on an accessible online interface rather than in isolated, locally stored files, the researchers aim to give government agencies, planners, and disaster managers a single, consistent, and current source of truth about landslide risk across the country.

The new study builds directly on a substantial body of earlier work by the same research group. In previous publications, the team demonstrated the performance of statistical models including the Frequency Ratio, Information Value, and Shannon Entropy methods for producing landslide susceptibility maps of Bhutan. These models quantify how strongly factors such as slope, lithology, land cover, proximity to roads and rivers, and rainfall correlate with observed landslide occurrences, and they convert those correlations into spatial predictions of where future slides are most likely. The researchers then extended the susceptibility work into a full landslide risk index, adopting the widely used conceptual framework in which risk is the product of three dimensions: hazard, meaning the likelihood and intensity of landslide occurrence; exposure, meaning the people, buildings, infrastructure, and assets located in hazard-prone areas; and vulnerability, meaning the social and physical susceptibility of those exposed elements to harm. That national-level risk index was computed using an indicator-based approach for every Gewog in the country, and it is precisely this risk framework that the new web platform now makes operational and interactive.

Technically, the platform is constructed from a modern, service-oriented geospatial architecture. ArcGIS Enterprise serves as the backbone, hosting the spatial layers that depict hazard zones, exposure datasets, and vulnerability indicators as map services that can be streamed to any web browser. Tabular data, including the indicator values and attribute information associated with each Gewog, are stored in a PostgreSQL relational database, which provides a robust and open-source backend for querying and managing structured records. The front end is developed with standard web technologies: HTML provides the document structure, CSS controls the visual presentation and layout, and JavaScript drives the interactivity, with the ArcGIS JavaScript API supplying the mapping widgets, layer controls, and client-side rendering that allow users to pan, zoom, toggle layers, and interrogate features directly within a browser. This combination means that no specialized GIS software or expert training is required to use the system; anyone with an internet connection and a standard web browser can access the country’s landslide risk information.

What distinguishes the platform from a static risk map is its emphasis on contextual information and analysis. Users can explore each of the three risk dimensions separately or view them integrated into a composite risk picture at the Gewog level. Beyond the headline risk classification, the system offers contextual analysis of a range of social, physical and infrastructural, and environmental indicators, allowing a decision maker to understand not just that a particular Gewog is at high risk, but why. A planner might discover, for example, that a Gewog’s elevated risk score stems from a combination of highly susceptible slopes and a dense network of roads and settlements cutting across them, or that a moderate hazard level is amplified by a vulnerable population with limited access to services. This layered, interrogable presentation of evidence is precisely what indicator-based risk frameworks are intended to support, and the platform operationalizes that intent for a national audience.

The collaborative dimension of the system is as important as its analytical content. The authors argue that a collaborative effort and an open information platform are crucial for enhancing long-term landslide risk reduction, particularly at the micro-level, and for effective land-use planning. By integrating efforts from multiple government departments with relevant expertise, rather than relying on isolated, locally stored datasets, the platform ensures that landslide-related information remains consistent and up to date. In many countries, disaster risk information is fragmented across agencies that maintain their own copies of overlapping datasets, leading to inconsistencies that undermine planning decisions. A centralized web service architecture addresses this problem directly: when a contributing department updates a dataset, the revised information flows through the same hosted services to every user of the platform, eliminating version conflicts and redundant data maintenance.

The research team behind the system reflects an institutional cross-section of Bhutanese geospatial and engineering expertise. Lead author Indra Bahadur Chhetri of the Department of Civil Engineering and Surveying at Jigme Namgyel Engineering College, Royal University of Bhutan, conceived the core idea, developed the methodology framework, analyzed the spatial content, and led application development and manuscript preparation. Co-authors Tshering Dorji Sherpa of Druk Green Power Corporation Limited, Menuka Rai of the National Land Commission Secretariat, and Sonam Jamtsho and Yonten Jamtsho of Rigsar-Vajra JV Private Limited contributed to data collection and the coding of the application. The spread of affiliations, spanning academia, a state power utility, the national land administration, and a private surveying firm, mirrors the multi-stakeholder philosophy embedded in the platform’s design, in which different organizations supply and consume risk information through a shared infrastructure.

Bhutan’s landslide problem provides the urgent context for this work. The country’s terrain is among the most landslide-prone in the Himalayan region, and the hazard intersects directly with national development priorities, since roads, hydropower infrastructure, and growing settlements must all be planned and maintained in steep, geologically young, and tectonically active landscapes. Previous research by other groups has documented the extent of the challenge, including spatial landslide risk assessments at Phuentsholing, susceptibility mapping along the Asian highway corridor, landslide identification using the index of entropy technique, and UAV-based localization of specific failure sites such as the Rinchending Goenpa landslide. Studies of roadblock events caused by geohazards have highlighted the disruption that slope failures inflict on transportation and the economy. Against this backdrop, a national, Gewog-level, web-accessible risk platform fills a clear operational gap between academic risk modelling and the day-to-day decisions of land-use planners and emergency responders.

The Bhutanese platform also enters a well-established international conversation about the role of web-based GIS in disaster risk management. Prior systems have demonstrated the value of the approach in other hazard contexts: dynamic web-GIS landslide early warning systems have been developed for the Chittagong metropolitan area in Bangladesh; web-based GIS platforms have been used to manage and assess landslide data in Peace River, Canada; collaborative web mapping applications built on REST API services and open data have been deployed for landslides and floods in Italy; and integrated two- and three-dimensional WebGIS platforms have been proposed for landslide hazard management more broadly. Systematic reviews of Web-GIS for natural hazard management confirm a growing consensus that web services are the most scalable way to deliver geospatial risk information to non-specialist users. The Bhutanese system contributes a national-scale, indicator-based, three-dimensional risk framework to this landscape, tailored to the administrative structure and institutional realities of a small mountain kingdom.

The design choices embedded in the system also align with international policy frameworks. The United Nations Office for Disaster Risk Reduction’s Sendai Framework for Disaster Risk Reduction 2015–2030 calls for understanding disaster risk as the first priority for action, and emphasizes the role of accessible, disaggregated, and up-to-date risk information in supporting evidence-based policy. Multi-stakeholder platforms have long been recognized in the disaster risk reduction literature as mechanisms for adaptive governance and resilience. By providing a shared informational foundation on which multiple organizations can coordinate, the Bhutanese WebGIS platform functions as a practical instrument of such governance, translating the abstract goals of risk-informed development into a concrete tool that can be consulted before a road is realigned, a settlement expanded, or a monsoon-season response planned.

The authors report no competing interests and note that the research received no external funding. The data supporting the findings can be provided by the corresponding author upon reasonable request. While the platform as described is a two-dimensional system, the broader trajectory of WebGIS development, including three-dimensional visualizations of seismic and landslide risk demonstrated elsewhere, suggests possible avenues for future extension. For now, the significance of the work lies in its demonstration that a country with limited resources can assemble a modern, standards-based geospatial decision support system from open web technologies, a relational database, and hosted GIS services, and that doing so can change the institutional economics of disaster risk information. Instead of each agency maintaining its own brittle collection of files, the risk knowledge becomes a living, shared service. In a region where climate change is expected to intensify the rainfall triggering mechanisms behind landslides, and where every monsoon season brings new slope failures, the value of such a shared, current, and analytically rich picture of risk is difficult to overstate. The platform represents a step toward making landslide risk management in Bhutan proactive, collaborative, and continuously informed by the best available evidence, offering a model that other hazard-prone nations in the Himalayas and beyond may find instructive.