http://repository.ou.ac.lk/handle/94ousl/3431 Mon, 31 Aug 2026 01:36:22 GMT 2026-08-31T01:36:22Z http://repository.ou.ac.lk/handle/94ousl/3467 Restoring Sri Lanka’s Central Highland Cloud Forests in Bopaththalawa: A Nature-Based Fiscal Strategy for Climate Adaptation and Water Security Perera, P.M.; Gamage, I.D.B.; De Silva, S. Wed, 01 Jan 2025 00:00:00 GMT http://repository.ou.ac.lk/handle/94ousl/3467 2025-01-01T00:00:00Z http://repository.ou.ac.lk/handle/94ousl/3466 Feasibility Study on Forecasting Water Level Fluctuation of the Senanayaka Samudra Reservoir Nifras, Mohammed; Weerabangsa, M.Z.; Iresh, A.D.S.; Athapattu, B.C.L. The Senanayake Samudraya Reservoir in Ampara District of Sri Lanka is a crucial piece of water management infrastructure. It supports various sectors, including agriculture, industry, and domestic water needs. The country experiences variable rainfall patterns throughout the year due to its tropical climate and diverse topography. Catchment area of the reservoir is 994.22 sq.km and command area is 120,254 ac (488.66 sq.km). Data for the reservoir was collected from irrigation department, Ampara and 26-year (1990-2015) rainfall and temperature data collected from Department of Meteorology and Irrigation department. This study developed a comprehensive water level forecasting system for the Reservoir to improve water resources management system. Both Hydrologic Engineering Centre-Hydrologic Modelling System (HECHMS) and Soil Conservation Service-Curve number (SCSCN) methods were used to simulate the surface inflow and compared, with SCS-CN proving more reliable for this study. Then, the base flow of the reservoir was determined. The Long Short-Term Memory (LSTM) recurrent neural network (RNN) was employed to forecast water level fluctuations. The model performance was evaluated based on the computed statistical parameters. The performance of model is very good with Coefficient of Determination (R2) = 0.998, Mean Square Error (MSE)= 0.0357 and Root Mean Squared Error (RMSE)= 0.189. Finally, it can be concluded that the model can be used effectively in forecasting water level fluctuations, providing valuable insights for reservoir management. Wed, 01 Jan 2025 00:00:00 GMT http://repository.ou.ac.lk/handle/94ousl/3466 2025-01-01T00:00:00Z http://repository.ou.ac.lk/handle/94ousl/3465 Extending the European Union Deforestation-free Regulation to Sri Lanka’s Land-Based Shrimp Aquaculture: Environmental, Regulatory and Trade Justifications Madumali, K.G.I.; Perera, P.M.; Dahanayake D.D.G.L The European Union Deforestation-free Regulation (EUDR), adopted in 2023, seeks to guarantee that commodities entering the EU are free from deforestation after 31 December 2020, with strict requirements for traceability and due diligence. While aquaculture is not yet included, this study evaluates the environmental and regulatory dimensions of Sri Lanka’s land-based shrimp farming to assess its suitability for future inclusion. Evidence from coastal districts shows that shrimp farming contributes to mangrove loss, carbon emissions, biodiversity decline and reduced coastal ecosystem services; impacts comparable to those of EUDRregulated commodities. Regulatory analysis reveals gaps in geolocation-based traceability, legality verification and land-use monitoring. Even though the Sri Lanka’s marine resource governance framework offers some protection, the provisions fall short of addressing the conversion of critical habitats for aquaculture and centralized Monitoring, Reporting and Verification (MRV) systems are lacking. Voluntary certifications such as ASC and BAP remain underutilized. The study recommends aligning national governance with EUDR principles through legal reforms, MRV implementation, certification expansion. It also highlights ecological risks from converting regenerating mangroves on abandoned saltern lands, advocating for their consideration within deforestation-free compliance frameworks. Wed, 01 Jan 2025 00:00:00 GMT http://repository.ou.ac.lk/handle/94ousl/3465 2025-01-01T00:00:00Z http://repository.ou.ac.lk/handle/94ousl/3464 Integrating Biodiversity Assessments as a Complementary Framework for EUDR Implementation in High-Risk Commodity Landscapes Perera, P.M.; Madumali, K.G.I. Wed, 01 Jan 2025 00:00:00 GMT http://repository.ou.ac.lk/handle/94ousl/3464 2025-01-01T00:00:00Z