Research Papers - Department of Civil Engineering

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    PublicationOpen 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.
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    PublicationOpen Access
    Artificial Neural Network based PERSIANN data sets in evaluation of hydrologic utility of precipitation estimations in a tropical watershed of Sri Lanka
    (AIMS Geosciences, 2021-09) Gunathilake, M; Senarath, T; Rathnayake, U. S
    The developments of satellite technologies and remote sensing (RS) have provided a way forward with potential for tremendous progress in estimating precipitation in many regions of the world. These products are especially useful in developing countries and regions, where ground-based rain gauge (RG) networks are either sparse or do not exist. In the present study the hydrologic utility of three satellite-based precipitation products (SbPPs) namely, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), PERSIANN-Cloud Classification System (PERSIANN-CCS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Dynamic Infrared Rain Rate near real-time (PDIR-NOW) were examined by using them to drive the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) hydrologic model for the Seethawaka watershed, a sub-basin of the Kelani River Basin of Sri Lanka. The hydrologic utility of SbPPs was examined by comparing the outputs of this modelling exercise against observed discharge records at the Deraniyagala streamflow gauging station during two extreme rainfall events from 2016 and 2017. The observed discharges were simulated considerably better by the model when RG data was used to drive it than when these SbPPs. The results demonstrated that PERSIANN family of precipitation products are not capable of producing peak discharges and timing of peaks essential for near-real time flood-forecasting applications in the Seethawaka watershed. The difference in performance is quantified using the Nash-Sutcliffe Efficiency, which was >0.80 for the model when driven by RGs, and <0.08 when driven by the SbPPs. Amongst the SbPPs, PERSIANN performed best. The outcomes of this study will provide useful insights and recommendations for future research expected to be carried out in the Seethawaka watershed using SbPPs. The results of this 479 AIMS Geosciences Volume 7, Issue 3, 478–489. study calls for the refinement of retrieval algorithms in rainfall estimation techniques of PERSIANN family of rainfall products for the tropical region.