| Sanction Date: | 20.03.2025 | |||
| Project Category | MG | |||
| Year | 2024-2025 | |||
| Project Duration | 3 Years | |||
| BTA : | WRM | |||
| Project Site/ State/ Districts/ Villages Covered: |
Shimla, Kinnaur and Kullu in Himachal and Almora and Nainital in Uttarakhand |
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| Organization/ Implementation Agency: | Indian Institute of Technology IIT-Bombay | |||
| Project Partners: | S.No. | Name | ||
| 1. | GBPNIHE | |||
| 2. | NIT Hamirpur | |||
| Lead Proponent: | Prof. S. Ravichandran |
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| Project Brief Description: | The footprints of global warming on North West Himalayan (NWH) region’s climate are already visible not only in terms of warming trends in surface temperature but also in local amplifications of warming as well as erratic and contrasting changes in precipitation in recent decades in different parts of NWH (Sen Roy and Balling, 2005; Singh and Mal, 2014; Basistha et al.,2009; Jaiswal et al., 2015; Bharti and Singh 2015; Bharti et al., 2016 and references therein). In addition, the NWH region of the Indian subcontinent has the largest numbers of glaciers and hence has been identified as one of the most eco-hydro-climatologically sensitive regions (Saha et al. 2019). Recent systematic documentation clearly suggests that the local climate change poses serious climate risks to the millions of vulnerable inhabitants of this region. The natural variability in the region is modulated by the anthropogenic climate change of the system, driving socioeconomic vulnerability and risk across sectors including water, food, energy, health and transportation. The remote forcings and local amplifications make this an ideal site for a pilot implementation of an end-to-end Decision-Support System. Sectoral decision-support systems (DSSs) utilising subseasonal-to-season (S2S) forecasts with location-specific risk maps and early warnings to enable state and local authorities to prepare for extreme weather events and to issue timely advisories is thus the urgent need of the hour. In this pilot project, we propose to implement a DSS in Himachal and Uttarakhand with apple orchards as the pilot focus sector. The multi-institutional, multi-disciplinary team will deliver an end-to-end solution for this specific sector. The basic framework can, in the future, be applied to other sectors and to other regions. | |||
| Beneficiaries/ Stakeholders: |
Local Farmers agricultural / horticultural agencies.
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| Activity Chart | ||||
| Total Grants (in Rs.) | Rs. 32,319,200/- (Rupees Three Crore Twenty-Three Lakh Nineteen Thousand Two Hundred Only ) | |||
| Project Objectives | Quantifiable Deliverables | Monitoring Indicators |
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• To set up a decision support system that will take as inputs local data and produce risk maps and early warnings to be supplied to local agencies • To ensure that the decision support system is people-centric and actionable at the community level • To act as proof of concept of the use of downscaled forecasts and data assimilation in such a decisionsupport system for future deployment in other locations and/or sectors • To generate detailed vulnerability and risk maps at the village scale for the target areas to quantify the effects of climate change. • Human resource training through educational modules, training workshops, etc. |
• Development of a real-time farm-scale decision support system • High-resolution vulnerability and risk maps for selected districts • Library of kilometre-scale downscaled forecasts for the Western Himalayan region, focusing on past extreme events. • Hazard/ risk maps for 05 districts (Shimla, Kinnaur, Kullu in HP and Almora & Nainital in UK). • Statistical/ AI-ML-based downscaling methods for farmscale downscaled forecasts. • Advisories for local agencies,training of representativesfrom local agencies. |
• No. of risk maps and early warnings issued. • No. of community interactions. • Level of user engagement and adoption. • No. of training sessions conducted. • No. of beneficiaries trained. • Accuracy and efficiency of AI-ML models • Integration with Decision Support system. • No. of advisories issued. • No. of agency representatives trained |
| S.No. | Name (Sanctioned) | Salary (Sanctioned) |
| 1. | 8 SRF | @ Rs.42,000/- + 09 to 28% HRA |
| 2. | 7 JRF | @ Rs.37,000/- + 09 to 28% HRA |
| 3. | 3 Field Assistant | @ Rs.20,000/- + 9% HRA |
| S.No. | Name of Equipment (Sanctioned) | Cost (in INR) |
| 1. | 01 Computer Node for existing HPC @15 Lac, 04 Desktop Computers @1.5 Lac, 01 High-ended Server @10Lac, 04 Desktop Workstation @0.75, 02 AWS @8.5 Lac, 01 Open-path H/CO2 gas analyzer with accessories @20 Lac, 02 Laptops @1 Lac, 01 Printer @0.2 Lac, 02 Hard drives, Recorder @0.15 Lac, Printer supplies/ Miscellaneous @3 Lac. | 6,750,000 |
