Hydrometeorological disasters (HMDs) in the Hindu Kush Himalayan (HKH) area have led to multiple water-related issues that resulted from extreme rainfall, glacial melt, and changing river flows, all of which are made worse by climate change and land use changes. Accurate warnings of these disasters are difficult due to sparse gauging and rugged topography in the Garhwal Himalaya region, which increases the likelihood of disasters during the monsoon.  

The same region experiences water shortage and drought especially during non-monsoon periods. The use of wide coverage remote sensing data from the study region as well as from neighboring countries with access to space-based data can play a significant role in the monitoring and analysing of these challenges. This study applies spatiotemporal clustering and multi-criteria decision-making (MCDM) to map high-risk zones, which will allow policymakers to reinforce infrastructure providing disaster resilience.

There is a need for a solution that uses multi-criteria decision making (MCDM) and spatiotemporal clustering to map areas in Uttarakhand, Himalaya, that are prone to disasters with the help of satellite-based data. To determine which tehsils (smaller administrative units) are vulnerable, it is suggested to examine more than 150 years of recorded disaster data with location and fatalities. Further vulnerable regions can be mapped using high-resolution satellite data (procured through Sentinel, Landsat, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), and Tropical Rainfall Measuring Mission (TRMM)) and analysed in the QGIS platform. This solution could use spatiotemporal clustering and MCDM to map high-risk zones, which will allow policymakers to reinforce infrastructure providing disaster resilience.

Data of the Garhwal Himalayan region (India), which lies in the Hindu Kush Himalayan (HKH) region are needed. The topography of the HKH region is almost the same over eight countries, and all bear similar kinds of disasters and climate patterns. The Garhwal region occupies about 64 per cent of the area of the Uttarakhand state and is also the origin of the river Ganga.

Has this problem been acknowledged in the past?

Numerous government reports (NDMA, IMD), non-governmental organizations (NGOs), international projects (UNDP, World Bank), and scholarly studies have acknowledged the Himalayan region's susceptibility to hydrometeorological disasters (HMDs). These studies have also highlighted the growing frequency and intensity of HMDs in the Hindu Kush Himalayan region. To increase resilience and disaster area mapping, more work is necessary utilising the latest space-based remote sensing data with broader coverage.

Can this challenge be solved using space technologies and data?

The study will need remote sensing and GIS infrastructure to analyse high-resolution satellite data, existing data by the physically gauged hydrometeorological observations for validation of geospatial data, computational resources for processing large datasets and using multi-criteria decision-making tools.

Analysing hydrometeorological disaster issues in rugged, data-scarce, and multi-country border regions with little information has become much easier with the help of space-based data. Information about land use changes, digital elevation models, terrain topography, areal rainfall, and glacial melt can be found in high-resolution satellite data from sources such as Sentinel, Landsat, SRTM DEM, and TRMM. GIS tools like QGIS are used to map risk zones and integrate vulnerability data, and Copernicus, NASA, and ISRO are used for real-time monitoring. For MCDM analysis, global soil datasets, population grids, DEM, LULC, and rainfall data are combined using R and Python, and K-means clustering is carried out in QGIS.

Expected timeframe to develop a solution

The project will likely be completed within three months. Data collection and analysis will take one month, developing the spatiotemporal clustering and MCDM framework will take one month. The last phase will take one month and include validation, risk zone mapping, and policy recommendations.

Potential consequences if no action happens

This shall lead to more loss of lives and livelihoods, damage to infrastructure, and displacement of people. This will burden the government's capacity for recovery and cause harm to the environment, including loss of soil and biodiversity. In the end, those whose livelihoods have been affected will become less resilient in the face of future disasters.

What are additional physical requirements for a solution?

Physical structures such as check dams, retention walls, gabion structures, terracing, drainage channels, and flood barriers are required to conserve soil and water resources and lessen the effects of disasters after vulnerable areas have been identified.