Browsing by Author "Gunathilake, M. B"

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Open Access
Analysis of Meandering River Morphodynamics Using Satellite Remote Sensing Data—An Application in the Lower Deduru Oya (River), Sri Lanka
(MDPI, 2022-07-16) Basnayaka, V; Samarasinghe, J. T; Gunathilake, M. B; Muttil, N; Hettiarachchi, D. C; Abeynayaka, A; Rathnayake, U
River meandering and anabranching have become major problems in many large rivers that carry significant amounts of sediment worldwide. The morphodynamics of these rivers are complex due to the temporal variation of flows. However, the availability of remote sensing data and geographic information systems (GISs) provides the opportunity to analyze the morphological changes in river systems both quantitatively and qualitatively. The present study investigated the temporal changes in the river morphology of the Deduru Oya (river) in Sri Lanka, which is a meandering river. The study covered a period of 32 years (1989 to 2021), using Landsat satellite data and the QGIS platform. Cloud-free Landsat 5 and Landsat 8 satellite images were extracted and processed to extract the river mask. The centerline of the river was generated using the extracted river mask, with the support of semi-automated digitizing software (WebPlotDigitizer). Freely available QGIS was used to investigate the temporal variation of river migration. The results of the study demonstrated that, over the past three decades, both the bend curvatures and the river migration rates of the meandering bends have generally increased with time. In addition, it was found that a higher number of meandering bends could be observed in the lower (most downstream) and the middle parts of the selected river segment. The current analysis indicates that the Deduru Oya has undergone considerable changes in its curvature and migration rates.
Open Access
Analysis of recent trends and variability of temperature and relative humidity over Sri Lanka
(India Meteorological Department, 2022-07-01) Rathnayake, U; Gunathilake, M. B; Senatilleke, U; Alyousifi, Y
The world is experiencing adverse consequences of climate change and shifts in climate regimes. Hence, studying the trends and patterns of meteorological variables is of major importance for many parties, including meteorologists, climatologists, agriculturists and hydrologists. Although several researchers have examined the trends and patterns in historical rainfall, only a few have examined the trends in atmospheric temperature. Noteworthy none of the previous studies have attempted to investigate trends in relative humidity over Sri Lanka. Therefore, identifying this existing research gap, this present paper presents a trends and variability analysis of atmospheric temperature and relative humidity of Sri Lanka. The long-term variations of minimum and maximum temperature and relative humidity records at 18 stations distributed in the three climatic zones namely, the dry zone, the intermediate zone and the wet zone in Sri Lanka were investigated for 30 years from 1990 to 2019. Annual and monthly trends were assessed using non-parametric statistical tests, including the Mann Kendall test (MK), Sen’s slope and Spearman’s rho test, while the changing points of temperature and humidity were determined using the Pettit test. In addition, the variability of climate parameters was estimated using the Coefficient of Variation (CoV). Interesting and encouraging results were obtained from the present analysis. Badulla in the intermediate climatic zone was identified with unexpected decreasing temperature trends, while several other areas were identified with expected increasing temperature and relative humidity trends. The adaptation practices based on these results would be interesting to incorporate in achieving sustainable development goals for the country
Open Access
Appraisal of Satellite Rainfall Products for Malwathu, Deduru, and Kalu River Basins, Sri Lanka
(MDPI, 2022-10-20) Perera, H; Senaratne, N; Gunathilake, M. B; Mutill, N; Rathnayake, U
Satellite Rainfall Products (SRPs) are now in widespread use around the world as a better alternative for scarce observed rain gauge data. Upon proper analysis of the SRPs and observed rainfall data, SRP data can be used in many hydrological applications. This evaluation is very much necessary since, it had been found that their performances vary with different areas of interest. This research looks at the three prominent river basins; Malwathu, Deduru, and Kalu of Sri Lanka and evaluates six selected SRPs, namely, IMERG, TRMM 3B42, TRMM 3B42-RT, PERSIANN, PERSIANNCCS, PERSIANN-CDR against 15+ years of observed rainfall data with the use of several indices. Four Continuous Evaluation Indices (CEI) such as Root Mean Square Error (RMSE), Percentage Bias (PBIAS), Pearson’s Correlation Coefficient (r), and Nash Sutcliffe Efficiency (NSE) were used to evaluate the accuracy of SRPs and four Categorical Indices (CI) namely, Probability of Detection (POD), Critical Success Index (CSI), False Alarm Ratio (FAR) and Proportion Correct (PC) was used to evaluate the detection and prediction accuracy of the SRPs. Then, the Mann–Kendall Test (MK test) was used to identify trends in the datasets and Theil’s and Sens Slope Estimator to quantify the trends observed. The study of categorical indicators yielded varying findings, with TRMM-3B42 performing well in the dry zone and IMERG doing well in the wet zone and intermediate zone of Sri Lanka. Regarding the CIs in the three basins, overall, IMERG was the most reliable. In general, all three basins had similar POD and PC findings. The SRPs, however, underperformed in the dry zone in terms of CSI and FAR. Similar findings were found in the CEI analysis, as IMERG gave top performance across the board for all four CEIs in the three basins. The three basins’ overall weakest performer was PERSIANN-CCS. The trend analysis revealed that there were very few significant trends in the observed data. Even when significant trends were apparent, the SRP projections seldom captured them. TRMM-3B42 RT had the best trend prediction performance. However, Sen’s slope analysis revealed that while the sense of the trend was properly anticipated, the amplitude of the prediction significantly differed from that of the observed data.
Open Access
Climate Variation and Hydropower Generation in Samanalawewa Hydropower Scheme, Sri Lanka
(Institution of Engineers, Sri Lanka, 2020-07) Laksiri, K; Rathnayake, U. S; Dabare, G; Gunathilake, M. B; Miguntanna, N
Climate variation is a challenging scenario on water resources. Therefore, runoffbased hydropower development stations are at an alarming situation across the world and the hydropower industry has significantly been affected. Therefore, it would be interesting to understand the impact of climate change on hydropower development in a country, where a significant energy contribution takes place by the renewable hydropower. However, such studies in Sri Lanka are limited mainly due to data scarcity. Nevertheless, this study was carried out to understand the relationships between the rainfall and the hydropower development in one of the major hydropower developments in Sri Lanka, Samanalawewa hydropower station. Non-parametric statistical trend analyses were carried out to the monthly rainfall over 26 years for the catchment rainfall. As the initial step, the link between rainfall and hydropower development was tested using the Pearson’s correlation coefficient. Interestingly, results revealed positive rainfall trends over the catchment. The correlation coefficient suggests that there is an acceptable correlation between the rainfall and the hydropower development. However, non-linear analysis is proposed to achieve more sound conclusions. Initial results revealed that there is no adverse impact to the inflow of the reservoir due to the on-going climate change
Open Access
Comparing Combined 1D/2D and 2D Hydraulic Simulations Using High-Resolution Topographic Data: Examples from Sri Lanka—Lower Kelani River Basin
(MDPi, 2022-02-17) Samarasinghe, J. T; Basnayaka, V; Gunathilake, M. B; Azamathulla, H. M; Rathnayake, U
The application of numerical models to understand the behavioural pattern of a flood is widely found in the literature. However, the selection of an appropriate hydraulic model is highly essential to conduct reliable predictions. Predicting flood discharges and inundation extents are the two most important outcomes of flood simulations to stakeholders. Precise topographical data and channel geometries along a suitable hydraulic model are required to accurately predict floods. Onedimensional (1D) hydraulic models are now replaced by two-dimensional (2D) or combined 1D/2D models for higher performances. The Hydraulic Engineering Centre’s River Analysis System (HECRAS) has been widely used in all three forms for predicting flood characteristics. However, comparison studies among the 1D, 2D to 1D/2D models are limited in the literature to identify the better/best approach. Therefore, this research was carried out to identify the better approach using an example case study of the Kelani River basin in Sri Lanka. Two flood events (in 2016 and 2018) were separately simulated and tested for their accuracy using observed inundations and satellite-based inundations. It was found that the combined 1D/2D HEC-RAS hydraulic model outperforms other models for the prediction of flows and inundation for both flood events. Therefore, the combined model can be concluded as the better hydraulic model to predict flood characteristics of the Kelani River basin in Sri Lanka. With more flood studies, the conclusions can be more generalized.
Open Access
Comparison of Calibration Approaches of the Soil and Water Assessment Tool (SWAT) Model in a Tropical Watershed
(MDPI, 2022-10-22) Makumbura, R. K; Gunathilake, M. B; Samarasinghe, J. T; Confesor, R; Muttil, N; Rathnayak, U
Hydrologic models are indispensable tools for water resource planning and management. Accurate model predictions are critical for better water resource development and management decisions. Single-site model calibration and calibrating a watershed model at the watershed outlet are commonly adopted strategies. In the present study, for the first time, a multi-site calibration for the Soil and Water Assessment Tool (SWAT) in the Kelani River Basin with a catchment area of about 2340 km2 was carried out. The SWAT model was calibrated at five streamflow gauging stations, Deraniyagala, Kithulgala, Holombuwa, Glencourse, and Hanwella, with drainage areas of 183, 383, 155, 1463, and 1782 km2 , respectively, using three distinct calibration strategies. These strategies were, utilizing (1) data from downstream and (2) data from upstream, both categorized here as single-site calibration, and (3) data from downstream and upstream (multi-site calibration). Considering the performance of the model during the calibration period, which was examined using the statistical indices R 2 and NSE, the model performance at Holombuwa was upgraded from “good” to “very good” with the multi-site calibration technique. Simultaneously, the PBIAS at Hanwella and Kithulgala improved from “unsatisfactory” to “satisfactory” and “satisfactory” to “good” model performance, while the RSR improved from “good” to “very good” model performance at Deraniyagala, indicating the innovative multi-site calibration approach demonstrated a significant improvement in the results. Hence, this study will provide valuable insights for hydrological modelers to determine the most appropriate calibration strategy for their large-scale watersheds, considering the spatial variation of the watershed characteristics, thereby reducing the uncertainty in hydrologic predictions.
Open Access
Comparison of different analyzing techniques in identifying rainfall trends for Colombo, Sri Lanka
(Hindawi, 2020-08) Perera, A; Ranasinghe, T; Gunathilake, M. B; Rathnayake, U. S
Identifying rainfall trends in highly urbanized area is extremely important for various planning and implementation activities, including designing, maintaining and controlling of water distribution networks and sewer networks and mitigating flood damages. However, different available methods in trend analysis may produce comparable and contrasting results. Therefore, this paper presents an attempt in comparing some of the trend analysis methods using one of the highly urbanized areas in Sri Lanka, Colombo. Recorded rainfall data for 10 gauging stations for 30 years were tested using the MannKendall test, Sen’s slope estimator, Spearman’s rho test, and innovative graphical method. Results showcased comparable findings among three trend identification methods. Even though the graphical method is easier, it is advised to use it with a proper statistical method due to its identification difficulties when the data scatter has some outliers. Nevertheless, it was found herein that Colombo is under a downward rainfall trend in the month of July where the area receives its major rainfall events. In addition, the area has several upward rainfall trends over the minor seasons and in the annual scale. Therefore, the water management activities in the area have to be revisited for a sustainable use of water resources.
Open Access
Ecosystem-Based Adaptation for the Impact of Climate Change and Variation in the Water Management Sector of Sri Lanka
(Hindawi, 2021-02-25) Khaniya, B; Gunathilake, M. B; Rathnayake, U. S
The climate of Sri Lanka has been fluctuating at an alarming rate during the recent past. These changes are reported to have pronounced impacts on the livelihoods of the people in the country. Water is central to the sustainable functioning of ecosystems and wellbeing of mankind. It is evident that pronounced variations in the climate will negatively impact the availability and the quality of water resources. The ecosystem-based adaptation (EbA) approach has proved to be an effective strategy to address the impact of climate change on water resources in many parts of the world. The key aim of this paper is to elaborate the wide range of benefits received through implementation of EbAs in field level, watershed scale, and urban and coastal environments in the context of Sri Lanka. In addition, this paper discusses the benefits of utilizing EbA solutions over grey infrastructure-based solutions to address the issues related to water management. The wide range of benefits received through implementation of EbAs can be broadly classified into three categories: water supply regulation, water quality regulation, and moderation of extreme events. This paper recommends the utilization of EbAs over grey infrastructure-based solutions in adaptation to climate change in the water management sector for the developing region due its cost effectiveness, ecofriendliness, and multiple benefits received on long-term scales. The findings of this study will unequivocally contribute to filling existing knowledge and research gaps in the context of EbAs to future climate change in Sri Lanka. The suggestions and opinions of this study can be taken into account by decision makers and water resources planning agencies for future planning of actions related to climate change adaptation in Sri Lanka.
Open Access
Evaluation of Ecosystem-Based Adaptation Measures for Sediment Yield in a Tropical Watershed in Thailand
(MDPI, 2021-10-06) Babel, M. S; Gunathilake, M. B; Jha, M. K
Ecosystem-based adaptation (EbA) can potentially mitigate watershed degradation problems. In this study, various EbA measures were evaluated using a bio-physical model called the Soil and Water Assessment Tool (SWAT), in a small, forested watershed named Hui Ta Poe, in the northeastern region of Thailand. The developed watershed model was first used to investigate the effect of various degraded watersheds due to land-use changes on the sediment yield in the study area. The most degraded watershed produced an annual average sediment yield of 13.5 tons/ha. This degraded watershed was then used to evaluate the effectiveness of various EbA measures such as reforestation, contouring, filter strips, and grassed waterways in reducing the sediment yield. Under all individual and combined EbA scenarios analyzed, there was a significant reduction in sediment yield; however, the maximum reduction of 88% was achieved with a combined scenario of reforestation, grassed waterways, and filter strips. Reforestation alone was found to be the second-best option, which could reduce the sediment yield by 84%. Contouring alone was the least effective, with a reduction in sediment yield of only 23%. This study demonstrates the usefulness of implementing EbA measures for sediment management strategies to address watershed degradation, which is a severe problem across the globe.
Open Access
Evaluation of future climate and potential impact on streamflow in the Upper Nan River basin of Northern Thailand
(Hindawi, 2020-10) Rathnayake, U. S; Gunathilake, M. B; Amaratunga, V; Perera, A
Water resources in Northern Thailand have been less explored with regard to the impact on hydrology that the future climate would have. For this study, three regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment (CORDEX) of Coupled Model Intercomparison Project 5 (CMIP5) were used to project future climate of the upper Nan River basin. Future climate data of ACCESS_CCAM, MPI_ESM_CCAM, and CNRM_CCAM under Representation Concentration Pathways RCP4.5 and RCP8.5 were bias-corrected by the linear scaling method and subsequently drove the Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS) to simulate future streamflow. This study compared baseline (1988–2005) climate and streamflow values with future time scales during 2020–2039 (2030s), 2040–2069 (2050s), and 2070–2099 (2080s). The upper Nan River basin will become warmer in future with highest increases in the maximum temperature of 3.8°C/year for MPI_ESM and minimum temperature of 3.6°C/year for ACCESS_CCAM under RCP8.5 during 2080s. The magnitude of changes and directions in mean monthly precipitation varies, with the highest increase of 109 mm for ACESSS_CCAM under RCP 4.5 in September and highest decrease of 77 mm in July for CNRM, during 2080s. Average of RCM combinations shows that decreases will be in ranges of −5.5 to −48.9% for annual flows, −31 to −47% for rainy season flows, and −47 to −67% for winter season flows. Increases in summer seasonal flows will be between 14 and 58%. Projection of future temperature levels indicates that higher increases will be during the latter part of the 20th century, and in general, the increases in the minimum temperature will be higher than those in the maximum temperature. The results of this study will be useful for river basin planners and government agencies to develop sustainable water management strategies and adaptation options to offset negative impacts of future changes in climate. In addition, the results will also be valuable for agriculturists and hydropower planners.
Open Access
Evaluation of Future Streamflow in the Upper Part of the Nilwala River Basin (Sri Lanka) under Climate Change
(MDPI, 2022-03-16) Chathuranika, I. M; Gunathilake, M. B; Azamathulla, H. M; Rathnayake, U
Climate change is a serious and complex crisis that impacts humankind in different ways. It affects the availability of water resources, especially in the tropical regions of South Asia to a greater extent. However, the impact of climate change on water resources in Sri Lanka has been the least explored. Noteworthy, this is the first study in Sri Lanka that attempts to evaluate the impact of climate change in streamflow in a watershed located in the southern coastal belt of the island. The objective of this paper is to evaluate the climate change impact on streamflow of the Upper Nilwala River Basin (UNRB), Sri Lanka. In this study, the bias-corrected rainfall data from three Regional Climate Models (RCMs) under two Representative Concentration Pathways (RCPs): RCP4.5 and RCP8.5 were fed into the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model to obtain future streamflow. Bias correction of future rainfall data in the Nilwala River Basin (NRB) was conducted using the Linear Scaling Method (LSM). Future precipitation was projected under three timelines: 2020s (2021–2047), 2050s (2048–2073), and 2080s (2074–2099) and was compared against the baseline period from 1980 to 2020. The ensemble mean annual precipitation in the NRB is expected to rise by 3.63%, 16.49%, and 12.82% under the RCP 4.5 emission scenario during the 2020s, 2050s, and 2080s, and 4.26%, 8.94%, and 18.04% under RCP 8.5 emission scenario during 2020s, 2050s and 2080s, respectively. The future annual streamflow of the UNRB is projected to increase by 59.30% and 65.79% under the ensemble RCP4.5 and RCP8.5 climate scenarios, respectively, when compared to the baseline scenario. In addition, the seasonal flows are also expected to increase for both RCPs for all seasons with an exception during the southwest monsoon season in the 2015–2042 period under the RCP4.5 emission scenario. In general, the results of the present study demonstrate that climate and streamflow of the NRB are expected to experience changes when compared to current climatic conditions. The results of the present study will be of major importance for river basin planners and government agencies to develop sustainable water management strategies and adaptation options to offset the negative impacts of future changes in climate.
Open Access
Evaluation of Satellite Rainfall Products over the Mahaweli River Basin in Sri Lanka
(Hindawi, 2022-04) Perera, H; Fernando, S; Gunathilake, M. B; Sirisena, J; Rathnayake, U
e availability of accurate spatiotemporal rainfall data is of utmost importance for reliable predictions from hydroclimatological studies. Challenges and limitations faced due to the absence of dense rain gauge (RG) networks are seen especially in the developing countries. erefore, alternative rainfall measurements such as satellite rainfall products (SRPs) are used when RG networks are scarce or completely do not exist. Noteworthy, rainfall data retrieved from satellites also possess several uncertainties. Hence, these SRPs should essentially be validated beforehand. e Mahaweli River Basin (MRB), the largest river basin in Sri Lanka, is the heart of the country’s water resources contributing to a signi cant share of the hydropower production and agricultural sector. Given the importance of the MRB, this study explored the suitability of SRPs as an alternative for RG data for the basin. Daily rainfall data of six types of SRPs were extracted at 14 locations within the MRB. ereafter, statistical analysis was carried out using continuous and categorical evaluation indices to evaluate the accuracy of SRPs. Nonparametric tests, including the Mann-Kendall and Sen’s slope estimator tests, were used to detect the possibility of trends and the magnitude, respectively. Integrated MultisatellitE Retrievals for Global Precipitation Measurement (IMERG) outperformed among all SRPs, while Precipitation Estimation from Remotely Sensed Information using Arti cial Neural Networks (PERSIANN) products showed dire performances. However, IMERG also demonstrated underestimations when compared to RG data. Trend analysis results showcased that the IMERG product agreed more with RG data on monthly and annual time scales while Tropical Rainfall Measurement Mission Multisatellite Precipitation Analysis–3B42 (TRMM-3B42) agreed more on the seasonal scale. Overall, IMERG turned out to be the best alternative among the SRPs analyzed for MRB. However, it was clear that these products possess signi cant errors which cannot be ignored when using them in hydrological applications. e results of the study will be valuable for many parties including river basin authorities, agriculturists, meteorologists, hydrologists, and many other stakeholders.
Open Access
Evaluation of the Impact of Land Use Changes on Soil Erosion in the Tropical Maha Oya River Basin, Sri Lanka
(MDPI, 2023-01) Palliyaguru, C; Basnayake, V; Makumbura, R. K; Gunathilake, M. B; Muttil, N; Wimalasiri, E. M; Rathnayake, U
Soil degradation is a serious environmental issue in many regions of the world, and Sri Lanka is not an exception. Maha Oya River Basin (MORB) is one of the major river basins in tropical Sri Lanka, which suffers from regular soil erosion and degradation. The current study was designed to estimate the soil erosion associated with land use changes of the MORB. The Revised Universal Soil Loss Equation (RUSLE) was used in calculating the annual soil erosion rates, while the Geographic Information System (GIS) was used in mapping the spatial variations of the soil erosion hazard over a 30-year period. Thereafter, soil erosion hotspots in the MORB were also identified. The results of this study revealed that the mean average soil loss from the MORB has substantially increased from 2.81 t ha−1 yr−1 in 1989 to 3.21 t ha−1 yr−1 in 2021, which is an increment of about 14.23%. An extremely critical soil erosion-prone locations (average annual soil loss > 60 t ha−1 yr−1) map of the MORB was developed for the year 2021. The severity classes revealed that approximately 4.61% and 6.11% of the study area were in high to extremely high erosion hazard classes in 1989 and 2021, respectively. Based on the results, it was found that the extreme soil erosion occurs when forests and vegetation land are converted into agricultural and bare land/farmland. The spatial analysis further reveals that erosion-prone soil types, steep slope areas, and reduced forest/vegetation cover in hilly mountain areas contributed to the high soil erosion risk (16.56 to 91.01 t ha−1 yr−1) of the MORB. These high soil erosional areas should be prioritized according to the severity classes, and appropriate land use/land cover (LU/LC) management and water conservation practices should be implemented as recommended by this study to restore degraded lands.
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
Inflow forecast of Iranamadu reservoir, Sri Lanka under projected climate scenarios using artificial neural networks
(Hindawi 10.1155/2020/8821627, 2020-11) Karunanayake, C; Gunathilake, M. B; Rathnayake, U. S
Prediction of water resources for future years takes much attention from the water resources planners and relevant authorities. However, traditional computational models like hydrologic models need many data about the catchment itself. Sometimes these important data on catchments are not available due to many reasons. Therefore, artificial neural networks (ANNs) are useful soft computing tools in predicting real-world scenarios, such as forecasting future water availability from a catchment, in the absence of intensive data, which are required for modeling practices in the context of hydrology. These ANNs are capable of building relationships to nonlinear real-world problems using available data and then to use that built relationship to forecast future needs. Even though Sri Lanka has an extensive usage of water resources for many activities, including drinking water supply, irrigation, hydropower development, navigation, and many other recreational purposes, forecasting studies for water resources are not being carried out. Therefore, there is a significant gap in forecasting water availability and water needs in the context of Sri Lanka. Thus, this paper presents an artificial neural network model to forecast the inflows of one of the most important reservoirs in northern Sri Lanka using the upstream catchment’s rainfall. Future rainfall data are extracted using regional climate models for the years 2021–2050 and the inflows of the reservoir are forecasted using the validated neural network model. Several training algorithms including Levenberg–Marquardt (LM), BFGS quasi-Newton (BFG), scaled conjugate gradient (SCG) have been used to find the best fitting training algorithm to the prediction process of the inflows against the measured inflows. Results revealed that the LM training algorithm outperforms the other tests algorithm in developing the prediction model. In addition, the forecasted results using the projected climate scenarios clearly showcase the benefit of using the forecasting model in solving future water resource management to avoid or to minimize future water scarcity. Therefore, the validated model can effectively be used for proper planning of the proposed drinking water supply scheme to the nearby urban city, Jaffna in northern Sri Lanka.
Open Access
Planform Changes in the Lower Mahaweli River, Sri Lanka Using Landsat Satellite Data
(MDPI, 2022-10-03) Basnayaka, V; Samarasinghe, J. T; Gunathilake, M. B; Muttil, N; Rathnayake, U
Major development projects along rivers, like reservoirs and other hydraulic structures, have changed not only river discharges but also sediment transport. Thus, changes in river planforms can be observed in such rivers. In addition, river centerline migrations can be witnessed. The Mahaweli River is the longest in Sri Lanka, having the largest catchment area among the 103 major river basins in the country. The river has been subjected to many development projects over the last 50 years, causing significant changes in the river discharge and sediment transport. However, no research has been carried out to evaluate the temporal and spatial changes in planforms. The current seeks to qualitatively analyze the river planform changes of the Lower Mahaweli River (downstream to Damanewewa) over the past 30 years (from 1991 to 2021) and identify the major planform features and their spatiotemporal changes in the lower Mahaweli River. Analyzing the changes in rivers requires long-term data with high spatial resolution. Therefore, in this research, remotely sensed Landsat satellite data were used to analyze the planform changes of Lower Mahaweli River with a considerably high resolution (30 m). These Landsat satellite images were processed and analyzed using the QGIS mapping tool and a semi-automated digitizing tool. The results show that major changes in river Mahaweli occurred mainly in the most downstream sections of the selected river segment. Further, the river curvature was also comparatively high downstream of the river. An oxbow lake formation was observed over time in the most downstream part of the Mahaweli River after 2011. Centerline migration rates were also calculated with the generated river centerlines. It was found that the rates were generally lower than about 30 m per year, except for at locations where river meandering was observed. The main limitations of this study were the possible misclassifications due to the resolution of images and obstructions caused by cloud cover in the Landsat images. To achieve more accurate estimates, this study could be developed further with quantitative mathematical analysis by also considering the sediment dynamics of the Mahaweli River.
Open Access
Projection of future hydropower generation in Samanalawewa power plant, Sri Lanka
(Hindawi, 2020-10) Khaniya, B; Karunanayake, C; Gunathilake, M. B
+e projection of future hydropower generation is extremely important for the sustainable development of any country, which utilizes hydropower as one of the major sources of energy to plan the country’s power management system. Hydropower generation, on the other hand, is mostly dependent on the weather and climate dynamics of the local area. In this paper, we aim to study the impact of climate change on the future performance of the Samanalawewa hydropower plant located in Sri Lanka using artificial neural networks (ANNs). ANNs are one of the most effective machine learning tools for examining nonlinear relationships between the variables to understand complex hydrological processes. Validated ANN model is used to project the future power generation from 2020 to 2050 using future projected rainfall data extracted from regional climate models. Results showcased that the forecasted hydropower would increase in significant percentages (7.29% and 10.22%) for the two tested climatic scenarios (RCP4.5 and RCP8.5). +erefore, this analysis showcases the capability of ANN in projecting nonstationary patterns of power generation from hydropower plants. +e projected results are of utmost importance to stakeholders to manage reservoir operations while maximizing the productivity of the impounded water and thus, maximizing economic growth as well as social benefits.
Open Access
Satellite Rainfall Products for analysis of Rainfall trends for Mahaweli River Basin
(SLIIT, 2022-02-11) Perera, H; Gunathilake, M. B; Rathnayakea, U
The presence of accurate and spatiotemporal data is of utmost importance in hydrological studies for river basins. However, limited ground-measured rainfall data restrict the accuracy of these analyses. Data scarcities can often be seen not only in many developing countries but also in the developed world. Therefore, much attention is given to alternative techniques to accomplish the data requirement. Precipitation data extraction from satellite precipitation products is one of the frequently used techniques in the absence of ground-measured rainfall data. The Mahaweli River Basin (MRB) is the largest river basin in Sri Lanka and it covers 1/6th of the total land area of the country. Mahaweli River is the heart of the country and the water of it is being used for many activities, including hydropower development, water supply, irrigation, etc. Therefore, analyzing rainfall trends of MRB is interesting and worthwhile for many stakeholders of the river basin. Therefore, this research investigates the suitability of Satellite Rainfall Products (SRP’s) as an alternative for Rain Gauge measured data in the MRB by performing trend analysis between the two datasets. Six precipitation products, namely PERSIANN, PERSIANNCCS, PERSIANN-CDR, GPM IMERG V06, TRMM-3B42 V7, TRMM-3B42RT V7 were extracted for 10-35 years for 14 locations of the MRB spatially distributed in the three climatic zones of the catchment. Non-parametric tests, including the Mann-Kendall test and Sen’s slope estimator tests, were used to detect the possible rainfall trends in precipitation products. Significant increasing trends were observed for both ground-measured and SRP’s in the annual scale while mixed results were observed in monthly and seasonal scales. The trends from ground-measured rainfall and SRP’s were compared and the suitability of SRP’s as an alternative technique was stated.
Open Access
Statistical evaluation and hydrologic simulation capacity of different satellite-based precipitation products (SbPPs) in the Upper Nan River Basin, Northern Thailand
(Elsevier, 2020-10) Gunathilake, M. B; Amaratunga, V; Perera, A; Karunanayake, C; Gunathilake, A. S; Rathnayake, U. S
Study region: The Upper Nan River Basin, Northern Thailand Study focus: Precipitation is a major component of the hydrological cycle. A large number of remotely sensed precipitation products are used in hydro-meteorological studies. The accuracy of these relies on basin climatology, basin topography, precipitation mechanism and precipitation sampling techniques used in satellites. Hence, the precipitation products should be validated. Numerous studies have evaluated the reliability of satellite-based precipitation products (SbPPs) in the tropical Asia. However, a handful of research has yet examined the reliability of these in Thailand. Therefore, in this study the reliability of six SbPPs namely, PERSIANN, PER- SIANN