Browsing by Author "Samarasinghe, T"

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Open Access
Hydrological models and Artificial Neural Networks (ANNs) to simulate streamflow in a tropical catchment of Sri Lanka
(10.1155/2021/6683389, 2021-05) Gunathilake, M. B; Karunanayake, C; Gunathilake, A. S; Samarasinghe, T; Bandara, I. M; Rathnayake, U. S
Accurate streamflow estimations are essential for planning and decision-making of many development activities related to water resources. Hydrological modelling is a frequently adopted and a matured technique to simulate streamflow compared to the data driven models such as artificial neural networks (ANNs). In addition, usage of ANNs is minimum to simulate streamflow in the context of Sri Lanka. Therefore, this study presents an intercomparison between streamflow estimations from conventional hydrological modelling and ANN analysis for Seethawaka River Basin located in the upstream part of the Kelani River Basin, Sri Lanka. The hydrological model was developed using the Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS), while the data-driven ANN model was developed in MATLAB. The rainfall and streamflows’ data for 2003–2010 period have been used. The simulations by HEC-HMS were performed by four types of input rainfall data configurations, including observed rainfall data sets and three satellite-based precipitation products (SbPPs), namely, PERSIANN, PERSIANN-CCS, and PERSIANN-CDR. The ANN model was trained using three well-known training algorithms, namely, Levenberg–Marquadt (LM), Bayesian regularization (BR), and scaled conjugate gradient (SCG). Results revealed that the simulated hydrological model based on observed rainfall outperformed those of based on remotely sensed SbPPs. BR algorithm-based ANN algorithm was found to be superior among the data-driven models in the context of ANN model simulations. However, none of the above developed models were able to capture several peak discharges recorded in the Seethawaka River. The results of this study indicate that ANN models can be used to simulate streamflow to an acceptable level, despite presence of intensive spatial and temporal data sets, which are often required for hydrologic software. Hence, the results of the current study provide valuable feedback for water resources’ planners in the developing region which lack multiple data sets for hydrologic software.
Open Access
Impact of Climate Change and Variability on Spatiotemporal Variation of Forest Cover; World Heritage Sinharaja Rainforest, Sri Lanka
(Forest and Society, 2022-03-24) Samarasinghe, T; Gunathilake, M. B; Makumbura, R. K; Arachchi, S; Rathnayake, U
Rainforests are continuously threatened by various anthropogenic activities. In addition, the ever-changing climate severely impacts the world’s rainforest cover. The consequences of these are paid back to human at a higher cost. Nevertheless, little or no significant attention was broadly given to this critical environmental issue. The World Heritage Sinharaja Rainforest in Sri Lanka is originating news on its forest cover due to human activities and changing climates. The scientific analysis is yet to be presented on the related issues. Therefore, this paper presents a comprehensive study on the possible impact on the Sinharaja Rainforest due to changing climate. Landsat images with measured rainfall data for 30 years were assessed and the relationships are presented. Results showcased that the built-up areas have drastically been increased over the last decade in the vicinity and the declared forest area. The authorities found the issues are serious and a sensitive task to negotiate in conserving the forest. The rainfall around the forest area has not shown significant trends over the years. Therefore, the health of forest cover was not severely impacted. Nevertheless, six cleared-up areas were found inside the Singaraja Rainforest under no human interactions. This can be due to a possible influence from the changing climate. This was justified by the temporal variation of Land Surface Temperature (LST) assessments over these six cleared-up areas. Therefore, the World Heritage rainforest is threatened due to human activities and under the changing climate change. Hence, the conservation of the Sinharaja Rainforest would be challenging in the future.
Open Access
Multidecadal Land Use Patterns and Land Surface Temperature Variation in Sri Lanka
(Hindawi, 2022-05-16) Samarasinghe, T; Rathnayake, U; Makumbura, R. K
Agricultural land conversion due to urbanization, industrialization, and many other factors is one of the significant concerns to food production. Therefore, analyzing the temporal and spatial variation of agricultural lands is an emerging topic in the research world. However, an agrarian country like Sri Lanka was given weaker attention to the temporal and spatial variation of the land use, including the agricultural lands. This study presents an extended analysis of temporal and spatial variation of land use patterns in Sri Lanka, specifically looking at the agricultural land conversion and land surface temperature (LST) change. Remote sensing techniques and geographic information system (GIS) were used for the presented work. The satellite images from three Landsat’s were analyzed for 2000, 2010, and 2020 to identify the potential land use conversions. In addition, LSTs were extracted for the same period. Significant and continuous increases can be seen in the agricultural lands from 33.94% (of total area) in 2000 to 43.2% in 2020. In contrast, the forest areas showcase a relative decrease from 38.51% to 33.82% (of total area) during the analyzed period. In addition, the rate of conversion from agriculture to settlements is higher in the latter decade (2010–2020) compared to the earlier decade (2000–2010). Only general conclusions were drafted based on the LSTs results as they were not extracted in the same months of the year due to high cloud cover. Therefore, the results and conclusions of this study can be effectively used to improve the land use policies in Sri Lanka and lead to a sustainable land use culture.
Open Access
Projected Moisture Index (MI) for tropical Sri Lanka
(Hindawi, 2021-12) Wickramarachchi, C; Samarasinghe, T; Alyousifi, Y; Rathnayake, U. S
Atmospheric moisture loading can cause a great impact on the performance and integrity of building exteriors in a tropical climate. Buildings can be highly impacted due to the changing climate conditions over the world. Therefore, it is important to incorporate the projected changes of moisture loads in structural designs under changing climates. The moisture index (MI) is widely used in many countries as a climate-based indicator to guide the building designs for their durability performance. However, this was hardly considered in structural designs in Sri Lanka, even though the country is one of the most affected countries under climate change. Therefore, this study investigates future climate change impacts on the environmental moisture in terms of MI, which can be used in climate zoning, investigating indoor air quality, understanding thermal comfort and energy consumption, etc. The moisture index was found as a function of the drying index (DI) and wetting index (WI) to the whole country for its four rainfall seasons. The temporal and spatial distributions were plotted as MI maps and showcased under two categories; including historical MI maps (1990–2004) and future projected MI maps (2021–2040, 2041–2070, and 2071–2100). Future projected MI maps were constructed using bias-corrected climatic data for two RCP climatic scenarios (RCP4.5 and RCP8.5). Results showed that the temporal and spatial variations of MIs are justifiable to the country’s rainfall patterns and seasons. However, notable increases of MIs can be observed for future projected MIs in two seasons, and thus a careful investigation of their impacts should be assessed in terms of the construction of buildings and various agricultural activities. Therefore, the outcome of this research can be essentially used in policy implementation in adapting to the ongoing climate changes in Sri Lanka.