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035 _a.b12179243
099 9 _aAIT Thesis no.WM-15-05
100 1 _aSandilya, Sneha
245 1 0 _aFlood forecasting using hydrologic and hydrodynamic modeling :
_ba case of Kosi River Basin, Nepal and India
260 _aPathum Thani, Thailand :
_bAsian Institute of Technology,
_c2015
300 _a66 leaves :
_bill. (some col.)
490 1 _aThesis ;
_vno. WM-15-05
500 _aA thesis report submitted in partial fulfillment of the requirements for the Degree of Master of Engineering in Water Engineering and Management
520 _aFloods have become more frequ ent and devastating disaster in recent times. Bihar is India's most flood - prone State, with 76% of the population in the north living under the recurring threat of flood devastation. T raditional efforts at flood management have focused on structural measur es , such as the buil ding of a system of embankments, but the threat of floods remains as high as ever to the economy and livelihoods in Bihar. The Kosi River is one of the premier tributaries of the Ganges. In this study th e basin wide approach for Kosi R iver is used to achi eve better forecasting results and lead time. The upper catchment of Kosi lying in Nepal is divided into 3 sub catchments ( Arun, Tamor and Sun k osi ) with a common outlet point Chatra and rainfall runoff Modeling approach using MIKE 11 NAM models is used to simulate the Discharge at Chatra . The Model results show about 80 to 90% co rrelation between observed and s imulated values. The downstre am of Kosi basin lying in Bihar i s Jackated with embankments in late 1950{u2019}s and Kosi Barrage was constructed 53 Km. downstream to Chatra to channelize its flow Because of its peculiar nature of changing morphology. Hydrodynamic Modeling approach is used with MIKE 11 HD models to simulate the flow of the river from Chatra to Kursela (last forecasting s tation). Several analysis such as the difference in discharge between Chatra and Kosi Barrage and effect of rainfall in Nepal and water level at Basua is also done. The inflow from Bagmati is also considered for Model Calibration at Baltara. Flood forecas ting with a lead time of 72 hours (3 days) is done using forecasted rainfall data from RIMES. The data assimilation (DA) technique is used in forecasting of flood in this Rese arch and the forecasting result is taken for 7 days in the Month of July, 2013 at Baltara station. The coefficient of correlation varies from 75 to 85% for the forecast.
502 _aThesis (M.Eng.) - Asian Institute of Technology, 2015
650 0 _aFlood forecasting
_zKosi River Basin (Nepal and India)
700 0 _aSomchai Chonwattana,
_eExamination Committee
700 1 _aPaudyal, Guna Nidhi,
_eExamination Committee
700 1 _aShrestha, Sangam,
_eExamination Committee
700 1 _aBabel, Mukand Singh,
_eChairperson
710 2 _aAIT Fellowship,
_eScholarship donor
810 2 _aAsian Institute of Technology.
_tThesis ;
_vno. WM-15-05
856 _3Full-Text
_uhttp://203.159.5.9/ait-thesis/detail.php?q=B04395
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