Research Papers - Department of Civil Engineering

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Author: search.filters.author.Wanniarachchi, SHas files: Yes

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Now showing 1 - 5 of 5
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    Enhancing the effectiveness of satellite precipitation products with topographic and seasonal bias correction
    (Elsevier B.V., 2026-02) Wanniarachchi, S; Sarukkalige, R; Hapuarachchi, H.A. P; Gomes, P.I.A; Rathnayake, U
    Estimating precipitation distribution across large regions is crucial for understanding water availability, planning infrastructure, and forecasting flood hazards. Traditional gauge-based methods face challenges, particularly with sparse gauge networks. In response, satellite-based, near-real-time (NRT) precipitation data has gained popularity, especially in poorly gauged watersheds. However, satellite precipitation data quality is often compromised by latency, atmospheric complexities, and topographic effects, resulting in nonlinear errors. To overcome the research gap, this study introduces the Heavy Rain Peak Adjustment (HRPA) method alongside the well-established Seasonal Autoregressive Integrated Moving Average (SARIMA) model for satellite precipitation bias correction. The analysis utilised Global Satellite Mapping of Precipitation (GSMaP-NRT) data and hourly precipitation records from 31 rain gauges in the Ovens River region of Australia. On average, the mean residual of observed and GSMaP-NRT precipitation was −0.02 mm. Additionally, the HRPA method yielded better linear regression R2(0.911), NSE (log) (−0.847), and RMSE (0.628) compared to SARIMA. The results indicate that HRPA outperforms SARIMA, particularly at lower elevations, whereas SARIMA struggles at higher elevations, underscoring its limitations in those areas. Additionally, autocorrelation and partial autocorrelation plots for some stations in hilly areas show significant wave-like patterns, indicating greater uncertainty in satellite precipitation estimates over complex terrain. For several stations, autocorrelations at 24 and 48-hour lags suggest a systematic influence of past residuals on future ones, emphasizing the need for further refinement in satellite precipitation correction methods for these regions.
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    PublicationOpen Access
    A Review on Evapotranspiration Estimation in Agricultural Water Management: Past, Present, and Future
    (MDPI, 2022-07) Wanniarachchi, S; Sarukkalige, R
    Evapotranspiration (ET) is a major component of the water cycle and agricultural water balance. Estimation of water consumption over agricultural areas is important for agricultural water resources planning, management, and regulation. It leads to the establishment of a sustainable water balance, mitigates the impacts of water scarcity, as well as prevents the overusing and wasting of precious water resources. As evapotranspiration is a major consumptive use of irrigation water and rainwater on agricultural lands, improvements of water use efficiency and sustainable water management in agriculture must be based on the accurate estimation of ET. Applications of precision and digital agricultural technologies, the integration of advanced techniques including remote sensing and satellite technology, and usage of machine learning algorithms will be an advantage to enhance the accuracy of the ET estimation in agricultural water management. This paper reviews and summarizes the technical development of the available methodologies and explores the advanced techniques in the estimation of ET in agricultural water management and highlights the potential improvements to enhance the accuracy of the ET estimation to achieve precise agricultural water management.
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    PublicationOpen Access
    A Review on Evapotranspiration Estimation in Agricultural Water Management: Past, Present, and Future
    (maps and institutional affiliations., 2022-07-08) Wanniarachchi, S; Sarukkalige, R
    Evapotranspiration (ET) is a major component of the water cycle and agricultural water balance. Estimation of water consumption over agricultural areas is important for agricultural water resources planning, management, and regulation. It leads to the establishment of a sustainable water balance, mitigates the impacts of water scarcity, as well as prevents the overusing and wasting of precious water resources. As evapotranspiration is a major consumptive use of irrigation water and rainwater on agricultural lands, improvements of water use efficiency and sustainable water management in agriculture must be based on the accurate estimation of ET. Applications of precision and digital agricultural technologies, the integration of advanced techniques including remote sensing and satellite technology, and usage of machine learning algorithms will be an advantage to enhance the accuracy of the ET estimation in agricultural water management. This paper reviews and summarizes the technical development of the available methodologies and explores the advanced techniques in the estimation of ET in agricultural water management and highlights the potential improvements to enhance the accuracy of the ET estimation to achieve precise agricultural water management
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    PublicationOpen Access
    Rainfall analysis in Uma Oya basin, Sri Lanka
    (Faculty of Engineering, Sri Lanka Institute of Information Technology, 2016) Senadeera, D; Wanniarachchi, S; Rathnayake, U. S
    Climate change is believed to be a critical issue and there is enough evidence to identify the impact of climate change. Sri Lanka is expected to be one of the most affected countries from adverse impact of climate change. Various climatic models propose a rise of rainfall intensity to south Asian region while the number of rainy days are to be reduced. Therefore, the necessity is raised to find the clear trends in climatic factors in the region. However, a very few research work was carried out to see the climatic changes over the last few decades in Sri Lanka. Temporal variation of precipitation (rainfall) can be a good indicator to identify the trends in climate. In addition, these rainfall variations are used in many engineering aspects, including design of massive civil engineering structures like dams, design of water supply networks, etc. Furthermore, the rainfall variations are not only important in engineering aspects but also heavily in agriculture. Therefore, this research paper presents an analysis of temporal variation of rainfall in Uma Oya basin, Sri Lanka. Initial results show some interesting trends in rainfall over a period of 24 years. Furthermore, research is being conducted using advanced statistical data analysis techniques to present comprehensive trends in rainfall in Uma Oya basin
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    PublicationOpen Access
    Importance of Hydrologic Simulation for Lids and BMPs Design Using HEC-HMS: A Case Demonstration
    (MedCrave, 2017-11-16) Khaniya, B; Wanniarachchi, S; Rathnayake, U. S
    Best management practices (BMPs) and the Low impact development (LIDs) is water management tools used to mitigate hydrological impact resulting from unpremeditated urbanization. For the proper functioning of the LID and BMP features the volume of the runoff generated, peak runoff rate before and after the installation, need to be accessed. Modeling by comparing different developmental scenarios helps to characterize the impact of BMPs and LIDs practices on the surface runoff. Therefore, this paper describes a modeling approach to predict the performance of these BMPs and LIDs in an existing hydrological model. This type of modeling approach is important to understand the long-term operation of the watershed post-development plan. A single rainfall event in May 2013 has been modeled and the characteristics graphs such as outflow, precipitation, runoff, infiltration have been analyzed. Run-off volume after retrofitting infiltration trench has decreased by 351m3 at the outlet with an increase of 39 L/s in peak discharge. Time series study of reservoirs depicts low performance of infiltration trench at latter phase of rainfall event. This leads with a rational that infiltration trench cannot result favorable for longer rainfall events unless underlying soil has superior geo-technical properties with low level water table. Results manifest the benefits of using hydrologic modeling software to understand the watershed hydrology.