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Author: search.filters.author.Rathnayake, U. SSubject: search.filters.subject.discharge

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    PublicationOpen Access
    Flood modeling in the Mahaweli River reach from Kothmale to Polgolla
    (University of Peradeniya, 2007) Rathnayake, U. S; Weerakoon, S. B; Nandalal, K. D. W; Rathnayake, U
    The occurrence of floods and inundation of the low lands adjacent to the Mahaweli River reach from Gampola to Polgolla were very frequent prior to the Kotmale reservoir project in mid 1980s. However, during last two decades with the construction of the Kotmale dam, the regulation of flow by the reservoir has reduced the inundation risk of these lands, which were vulnerable to frequent flooding. As a result, these lands are developed at an increasing rate and more people have started to live in them. This fact gives an alarming signal to the authorities, as the damage that might be caused due to an extreme flood event could be significant. It is therefore of paramount importance that comprehensive flood modeling and inundation analysis of the Mahaweli River reach between Kotmale and Polgolla is carried out. This paper presents the flood modeling and inundation analysis in the Mahaweli river reach from the Kotmale dam to Polgolla barrage using the HECRAS model. The HECRAS model was set up for the river reach using the river cross-sections at 200 m intervals from Kotmale dam to Polgolla barrage. The model was applied to estimate the water stages along the river reach for the floods of different return periods. Though the Kotmale reservoir acts as a flood control reservoir for floods of medium return periods, it becomes ineffective to reduce the flood levels in the downstream flood plains due to floods of high return periods when it has to release high discharge. Inundation areas in the downstream of the dam due to several flood discharges are presented.
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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.