Climate-resilient water allocation for sustainable irrigation and fisheries in the Nachchaduwa Reservoir of Malwathu Oya River Basin, Sri Lanka | |
| Author | Vasanthakumar, Sareeha |
| Call Number | AIT Diss. no.WM-26-01 |
| Subject(s) | Climatic changes--Environmental aspects--Sri Lanka Urban hydrology--Mathematical models--Sri Lanka Water-supply--Data processing--Sri Lanka |
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Water Engineering and Management |
| Publisher | Asian Institute of Technology |
| Abstract | Climate change is intensifying water stress in Sri Lanka’s dry zone, where multi-purpose reservoirs are vital for sustaining irrigation and inland fisheries. This study develops a climate resilient water allocation framework for the Nachchaduwa Reservoir in the Malwathu Oya River Basin, integrating climate projections, hydrological modeling, fish yield prediction, and multi-objective reservoir optimization in Sri Lanka.An Extreme Bias-adjusted APHRODITE precipitation dataset enhances the reliability of climate inputs for further analysis. Eight GCMs were ranked through compromise programming, with the top three models, MRI-ESM2.0, CNRM-ESM2, and EC-Earth3, selected as the best CMIP6 models. Bias-corrected projections for 2025–2049 and 2050–2075 under SSP2-4.5 and SSP5-8.5 indicate rainfall increases (up to 14.22% under SSP5-8.5) and significant warming, with minimum temperature (Tmin) rising faster than maximum temperature (Tmax). Basin-wide temperature may increase 0.5–2.5 °C from the 1988–2014 baseline. Hydrological simulations with the HEC-HMS model demonstrated satisfactory performance (NSE > 0.50; PBIAS within ±25%) and confirmed its suitability for data-scarce, monsoon-influenced basins. Future inflow projections indicate slight declines under SSP2-4.5 and significant increases and variability under SSP5-8.5. Rising evapotranspiration heightens irrigation water demand from April to October. Reservoir analysis revealed a decline in the sustainability index under future climate scenarios.Fish yield modeling showed that monthly relative reservoir level fluctuation (RRLF) influences fisheries productivity. Empirical polynomial regression performed with the best accuracy (R² = 0.64) and minimal bias compared to other methods. Future projections indicate a 5–50% decrease in fish yield, more variability, and loss of long-term growth trends, especially under SSP5-8.5. A multi-objective optimization using the {u1D700}- constraint method and the Pareto optimal front offer beneficial trade-offs between irrigation supply and fish productivity. The optimized guide curves outperform baseline operations, increasing storage and ecological stability. The study shows that integrated, climate-resilient reservoir operations are vital for sustaining irrigation, fisheries, and livelihoods in Sri Lanka’s dry zone. The framework provides a decision-support tool for adaptive water management amid increasing climate uncertainty. |
| Year | 2026 |
| Type | Dissertation |
| School | Faculty of Civil and Environmental Engineering (2026) |
| Department | Other Field of Studies (No Department) |
| Academic Program/FoS | Water Engineering and Management (WEM) |
| Chairperson(s) | Shanmugam, Mohana Sundaram |
| Examination Committee(s) | Shrestha, Sangam;Babel, Mukand S.;Himanshu, Sushil Kumar;Ho, Huu Loc |
| Scholarship Donor(s) | Organization for Women in Science for the Developing World (OWSD) and Sida;AIT Fellowship |
| Degree | Thesis (Ph.D.) - Asian Insitute of Technology, 2026 |
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