About · CW-RAS

System Description

CW-RAS (Contextual Water Risk Assessment System) is a panchayat-level environmental risk evaluation tool designed for Kollam District, Kerala. It assesses two critical water-related risks — flood and water scarcity — by analyzing real-world hydrological, geological, and land-use data for each panchayat.

The system accepts a location name or panchayat, geocodes it if necessary using OpenStreetMap, matches it to the nearest panchayat in the dataset, and computes a composite risk score (0–100) along with a qualitative risk level (Low / Moderate / High).

                CW-RAS covers 74 regions across Kollam District,
                with each region record containing rainfall, groundwater,
                land-use, and water body coverage data.
            

Data Sources

CW-RAS relies on authoritative, publicly available environmental datasets to ensure scientific validity and reproducibility.

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WRIS Kerala

Water Resources Information System — provides long-term normal rainfall and current observed rainfall data at the panchayat level. Used for rainfall deviation analysis.

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CGWB

Central Ground Water Board — supplies groundwater level measurements (meters below ground level) for monitoring wells across Kerala. Used for groundwater fluctuation assessment.

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Land-use Data

Urban coverage and forest cover percentages derived from satellite-based land-use classification data, used to assess surface runoff and infiltration characteristics.

Algorithm Summary — SR-SA v2

CW-RAS uses the SR-SA v2 (Simplified Risk–Score Aggregation, Version 2) algorithm — a deterministic, weighted scoring model that converts raw environmental observations into a single composite risk score.

Rainfall Deviation: Computes the percentage deviation between long-term normal and current observed rainfall. Higher deviation → higher risk.
Groundwater Fluctuation: Measures the absolute change in groundwater depth (mbgl), normalized against a 3m reference maximum. For flood risk, only rising water levels contribute.
Land-use Parameters: Combines urban coverage and forest deficit into a single score. More urbanization and less forest cover → higher runoff risk.
Weighted Scoring Model: Parameters are weighted differently for flood (40% rain, 40% land-use, 20% GW) vs. scarcity (40% rain, 40% GW, 20% land-use). A Surface Water Factor (SWF) further moderates scarcity in lake-adjacent areas.
Risk Classification: The final score (0–100) is mapped to Low (<30), Moderate (30–59), or High (≥60) risk levels.

For a detailed technical breakdown with equations and sample calculations, visit the Algorithm Documentation →

Team

CW-RAS is developed as a Mini Project by Group 5.

Hritik Krishna

PRN23CS071

Flask Backend Architecture · System Integration · About System Page

Nandu M V

PRN23CS099

SWF · Flood & Drought Risk Calculation · Result Page

Sruthi S

PRN23CS121

OSM API Geocoding & Location Fetch · Algorithm Page

Ivan John Benny

PRN23CS074

Rainfall Deviation · Groundwater Score · Land-use · Landing Page

Under the guidance of:

Siji Mol K
Assistant Professor
Department of Computer Science & Engineering
College of Engineering, Perumon

About CW-RAS