Multi-Temporal Geospatial Assessment of Bathymetric Characteristics, Water Storage Capacity Dynamics, and Hydro-Climatic Variability of Senanayake Samudraya, Sri Lanka (2000–2025)

This research proposal presents a geospatial framework for assessing the bathymetric characteristics, water storage capacity, and hydro-climatic variability of Senanayake Samudraya, Sri Lanka's largest reservoir. The study integrates Geographic Information Systems (GIS), Remote Sensing (RS), Digital Elevation Models (DEMs), and rainfall datasets to reconstruct reservoir bathymetry, estimate storage capacity, and evaluate long-term storage dynamics. Multi-temporal Landsat and Sentinel-2 imagery, SRTM and ALOS PALSAR DEMs, and CHIRPS rainfall data will be utilized to analyze changes in reservoir extent and water storage between 2000 and 2025. The methodology includes water body extraction using NDWI and MNDWI, bathymetric reconstruction through DEM integration and interpolation, elevation-area-volume modelling, and rainfall-storage relationship analysis. The expected outcomes include bathymetric maps, depth distribution models, storage-capacity estimates, hydro-climatic assessments, and recommendations for sustainable reservoir management. This proposal aims to establish a replicable geospatial methodology for reservoir assessment in tropical environments where conventional bathymetric data are limited.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-09
DOI
https://doi.org/10.5281/zenodo.20613879
Primary Topic
Groundwater and Watershed Analysis
Type
article
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article

Multi-Temporal Geospatial Assessment of Bathymetric Characteristics, Water Storage Capacity Dynamics, and Hydro-Climatic Variability of Senanayake Samudraya, Sri Lanka (2000–2025)

Sahan Dayarathna
Zenodo (CERN European Organization for Nuclear Research)
Groundwater and Watershed Analysis
article

Multi-Temporal Geospatial Assessment of Bathymetric Characteristics, Water Storage Capacity Dynamics, and Hydro-Climatic Variability of Senanayake Samudraya, Sri Lanka (2000–2025)

Sahan Dayarathna
article en

Abstract

This research proposal presents a geospatial framework for assessing the bathymetric characteristics, water storage capacity, and hydro-climatic variability of Senanayake Samudraya, Sri Lanka's largest reservoir. The study integrates Geographic Information Systems (GIS), Remote Sensing (RS), Digital Elevation Models (DEMs), and rainfall datasets to reconstruct reservoir bathymetry, estimate storage capacity, and evaluate long-term storage dynamics. Multi-temporal Landsat and Sentinel-2 imagery, SRTM and ALOS PALSAR DEMs, and CHIRPS rainfall data will be utilized to analyze changes in reservoir extent and water storage between 2000 and 2025. The methodology includes water body extraction using NDWI and MNDWI, bathymetric reconstruction through DEM integration and interpolation, elevation-area-volume modelling, and rainfall-storage relationship analysis. The expected outcomes include bathymetric maps, depth distribution models, storage-capacity estimates, hydro-climatic assessments, and recommendations for sustainable reservoir management. This proposal aims to establish a replicable geospatial methodology for reservoir assessment in tropical environments where conventional bathymetric data are limited.

Zenodo (CERN European Organization for Nuclear Research)
Sabaragamuwa University of Sri Lanka (LK)
Openalex Percentile: Top 10%
Groundwater and Watershed Analysis
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