Evaluating the performance of MIKE NAM model on rainfall–runoff in lower Gangetic floodplain, West Bengal, India

2022 ◽  
Author(s):  
Arnab Ghosh ◽  
Malabika Biswas Roy ◽  
Pankaj Kumar Roy
Keyword(s):  
West Bengal ◽  
Rainfall Runoff

A Mathematical Modelling System for Flood Forecasting

1984 ◽  
Vol 15 (4-5) ◽  
pp. 305-316 ◽  
Author(s):  
T. Jønch-Clausen ◽  
J. Chr. Refsgaard
Keyword(s):  
Mathematical Modelling ◽  
Real Time ◽  
West Bengal ◽  
Simulation Models ◽  
Flood Routing ◽  
Rainfall Runoff ◽  
Reservoir Operations ◽  
River Catchment ◽  
Damodar River ◽  
Modelling System

In this paper comprehensive simulation models are presented which can forecast the streamflow in real time at various points in river systems and provide a tool for identifying improvements of the reservoir operations during flood situations while taking into consideration the conditions downstream. The mathematical modelling has involved rainfall-runoff predictions as well as flood routing. The application of the modelling system to a part of the 22,000 square kilometres Damodar River Catchment located in Bihar and West Bengal in India, is described.

An investigation on in vitro propagation of Colchicum luteum and its evaluation of colchicine for the economic benefit of rural people in West Bengal

Planta Medica ◽  
2007 ◽  
Vol 73 (09) ◽  
Author(s):  
M Gangopadhyay ◽  
R Bhattacharya ◽  
D Chakraborty ◽  
S Bhattacharya ◽  
A Mitra ◽  
...  
Keyword(s):  
Economic Benefit ◽  
In Vitro Propagation ◽  
West Bengal ◽  
Rural People

Forecasting of Summer Monsoon Rainfall over Gangetic West Bengal, India Utilising Intrinsic Mode Functions, Linear and Neural Regression

2020 ◽  
Vol 12 (1) ◽  
pp. 60-69 ◽  
Author(s):  
Pijush Basak
Keyword(s):  
Neural Network ◽  
West Bengal ◽  
Monsoon Rainfall ◽  
Linear Part ◽  
Intrinsic Mode Functions ◽  
Quasi Biennial Oscillation ◽  
Nonlinear Part ◽  
South West ◽  
South West Monsoon ◽  
West Monsoon

The South West Monsoon rainfall data of the meteorological subdivision number 6 of India enclosing Gangetic West Bengal is shown to be decomposable into eight empirical time series, namely Intrinsic Mode Functions. This leads one to identify the first empirical mode as a nonlinear part and the remaining modes as the linear part of the data. The nonlinear part is modeled with the technique Neural Network based Generalized Regression Neural Network model technique whereas the linear part is sensibly modeled through simple regression method. The different Intrinsic modes as verified are well connected with relevant atmospheric features, namely, El Nino, Quasi-biennial Oscillation, Sunspot cycle and others. It is observed that the proposed model explains around 75% of inter annual variability (IAV) of the rainfall series of Gangetic West Bengal. The model is efficient in statistical forecasting of South West Monsoon rainfall in the region as verified from independent part of the real data. The statistical forecasts of SWM rainfall for GWB for the years 2012 and 2013 are108.71 cm and 126.21 cm respectively, where as corresponding to the actual rainfall of 93.19 cm 115.20 cm respectively which are within one standard deviation of mean rainfall.

Congress Defeat in West Bengal

1949 ◽  
Vol 18 (15) ◽  
pp. 178-179
Author(s):  
Richard L. Park
Keyword(s):  
West Bengal

Inequality and Radical Land Reform: Some Notes from West Bengal

Asian Survey ◽  
1979 ◽  
Vol 19 (7) ◽  
pp. 718-727 ◽  
Author(s):  
Jnanabrata Bhattacharyya
Keyword(s):  
Land Reform ◽  
West Bengal
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