Emeshi J Warusavitharana

Wetlands provide critical ecosystem services by regulating hydrological processes and moderating flood risks. However, gradual wetland degradation often occurs through small-scale land conversions that remain below regulatory thresholds, leading to cumulative impacts on watershed stability. Despite growing recognition of these pressures, most hydrological assessments evaluate wetlands using simplified “with–without” comparisons, which fail to capture nonlinear responses associated with incremental loss and restoration. This study develops a watershed-scale modelling framework to investigate how progressive wetland degradation and restoration influence flood attenuation services within a complex hydrological system. A calibrated SWAT+ modelling framework was used to simulate a series of wetland loss and restoration scenarios ranging from 5% to 90% of existing wetland extent. The results show a strong nonlinear relationship between wetland loss and flood response. Peak discharge increases progressively with wetland loss, with a clear acceleration beyond approximately 25–30% loss, suggesting the existence of a critical threshold beyond which watershed stability deteriorates rapidly. In contrast, restoration scenarios reveal significant hysteresis behaviour. Equivalent restoration efforts recover only a limited portion of the lost flood attenuation capacity, demonstrating that hydrological systems exhibit path dependency and memory effects. Quantitative assessment shows that less than half of the cumulative hydrological impacts generated during degradation can be reversed through comparable restoration measures.

Coastal erosion poses a persistent and intensifying threat to Sri Lanka’s eastern shoreline, affecting both ecological systems and socio-economic infrastructure. This study combines remote sensing techniques, historical shoreline data, and machine learning models to analyze shoreline dynamics from 1990 to 2024 across six key coastal segments. Shoreline changes were assessed using the Digital Shoreline Analysis System (DSAS), supported by NDWI and vegetation index layers to map land cover transitions. A range of machine learning models was tested to predict future shoreline positions at erosion hotspots, with the Random Forest model yielding the highest accuracy (R² = 0.93). Projections show significant shoreline retreat across several vulnerable locations by 2035. Additionally, the study evaluates coastal setback policies outlined in Sri Lanka’s Coastal Zone Management Plans (2018–2024), highlighting a critical misalignment between increasing erosion risk and reduced setback distances. A site-specific setback model is proposed for the Reservation Area, incorporating historical erosion rates and safety margins to support more adaptive and risk-responsive coastal planning. These findings emphasize the importance of data-driven strategies for enhancing long-term coastal resilience.

Parameters are the key element in any hydrological model which govern the processes of water cycle. However, determining the most influential parameters and their ranges has certainly a challenging task for an ungauged river basin, where measurements related to hydrometeorological data and parameters are either too few or too poor in quality or not available at all. In this context, the aim of this research is to demonstrate a semi-distributed modelling approach and to optimize uncertainty assessment of model parameters in part of an ungauged river basin belongs to Deduru Oya Basin. Satellite retrieved weather data was used as input data and the model was run using SWAT water resources modelling tool. The parameters were optimized for the period of 2007–2011, using SUFI-2 inverse modelling approach. In local sensitivity analysis, out of the 43 parameters 14 were received as significant and out of them 4 were received as most sensitive with reference to the selected catchment. The model showed acceptable P values greater than 70% for 2007, 2008 and 2010 and lower R values that indicate lesser parameter uncertainty. The calibrated parameter ranges are also similar for the above 3 years. The key feature noticed in the final result was that the above 3 years have relatively similar seasonal rainfall pattern. Conversely, the model showed moderately acceptable P values, lesser than 60% for 2009 and 2011 where the annual rainfall pattern of the 2 years was comparatively different than its usual seasonal pattern. Moreover, the significant parameters identified by SUFI-2 have shown direct and indirect relationship with the physical properties and characteristics of the soil in the watershed.

Despite the advances in low cost open hardware and open software IoT (Internet of Things) enabled devices, their application in regional scale environmental monitoring has not been explored until the launch of 4ONSE (4 times Open and Non-conventional technology for Sensing the Environment) project, which is an ongoing research project between University of Moratuwa, Sri Lanka and University of Applied Sciences and Arts of Southern Switzerland (SUPSI). The project has paved the path for deploying low cost, open technologies based, non-conventional environmental monitoring systems in Deduru Oya river basin area of Sri Lanka. This research presents the selection process of appropriate sensors suitable for tropical climatic condition of Sri Lanka, issues encountered and remedies taken during the design and deployment phases.

Despite the advances in low cost open hardware and open software IoT (Internet of Things) enabled devices, their application in regional scale environmental monitoring has not been explored until the launch of 4ONSE (4 times Open and Non-conventional technology for Sensing the Environment) project, which is an ongoing research project between University of Moratuwa, Sri Lanka and University of Applied Sciences and Arts of Southern Switzerland (SUPSI). The project has paved the path for deploying low cost, open technologies based, non-conventional environmental monitoring systems in Deduru Oya river basin area of Sri Lanka. This research presents the selection process of appropriate sensors suitable for tropical climatic condition of Sri Lanka, issues encountered and remedies taken during the design and deployment phases.

Urbanization tends bring out a number of problems, such as inadequate housing and urban services, increase land prices and construction costs, propagation of slums, pollution and deterioration of the urban environment. Currently, spatial development activities focusing on major cities of Sri Lanka are demanding urban infrastructure and services where municipalities are facing challenges on provision of the infrastructure and proper urban management too. This study seeks to identify the relevant criteria, indicators and a method for assessing the urban management performance of municipalities in Sri Lanka since specific measurement criteria and related indicators are not yet identified to evaluate urban management by the central government or local government levels. Based on Literature review, five criteria and 25 indicators were selected considering their applicability for the context of Sri Lanka. The Full Permutation Polygon Synthetic Indicator Method (FPPSI) was applied to synthesize indicators and the Synthetic indicator has been used to show the performance of each criterion in terms of urban service delivery. Colombo Municipal Council (CMC), Sri Jayawardenapura Kotte Municipal Council (SJKMC) and Moratuwa Municipal Council (MMC) have been selected as the case studies for this research. Although selected cases are within Colombo Metropolitan Region, none of the municipalities were achieved the “High” or “Very High” level of synthetic indicator (SR>= 0.50) that shows the standard of municipal service delivery of Sri Lanka as a whole. This research lays the platform to evaluate the functional performance of Municipal Councils to guide the future scenario and to make decisions at the grass root level for managing the urbanization related issues in the country. Also this research helps the government to know the current trends of development impact and to take necessary policy level decisions to guide the economic growth in a correct direction with the political manifestoes.