Application of numerical models to simulate the charland area from Rajmahal to Farakka barrage of the Ganga river of eastern India

2020 ◽  
Vol 28 (6) ◽  
pp. 683-698
Author(s):  
Rajsekhar Chakraborty ◽  
Swades Pal
2021 ◽  
Author(s):  
Gaurav Kailash Sonkar ◽  
Kumar Gaurav

<p>The Ganga-Brahmaputra river system in the Himalayan Foreland supports diverse aquatic fauna. Decades of flow regulation through dams and barrages have affected their habitat suitability. To evaluate the impacts of large barrages on the morphology and habitat ecology we studied two different reaches (middle and lower) of the Ganga River. These reaches are the habitat of the endangered Ganga River dolphin (<em>Platanista gangetica</em>). In a reach in the middle Ganga between Bijnor and Narora barrage, a reported rise in dolphin population has been documented. In contrast, near the Farakka barrage in the lower reach of the Ganga River, a significant decline in the dolphin population has been observed.</p><p>We use Corona and time-series Landsat satellite images along with flow discharge data to assess the morphological and ecological impact of the barrages. In middle Ganga, the dolphin habitat is isolated between the Bijnor and Narora barrage where the minimum flow is available throughout the year for the dolphins to thrive.  On the other hand, in the lower Ganga, contrasting impacts are observed in the proximity (upstream/downstream) of the Farakka barrage. In the downstream, reduction in water (by one-third in the pre-monsoon discharge) and sediment discharge has decoupled the channel belt to its floodplain resulting in a loss of lateral connectivity. The presence of minimum flow between the Bijnor and Narora barrage has aided the dolphin population rise while the loss of lateral connectivity and excess siltation at the Farakka barrage has made the river reach unsuitable for habitation.   </p>


2020 ◽  
Vol 82 ◽  
pp. 149-160
Author(s):  
N Kargapolova

Numerical models of the heat index time series and spatio-temporal fields can be used for a variety of purposes, from the study of the dynamics of heat waves to projections of the influence of future climate on humans. To conduct these studies one must have efficient numerical models that successfully reproduce key features of the real weather processes. In this study, 2 numerical stochastic models of the spatio-temporal non-Gaussian field of the average daily heat index (ADHI) are considered. The field is simulated on an irregular grid determined by the location of weather stations. The first model is based on the method of the inverse distribution function. The second model is constructed using the normalization method. Real data collected at weather stations located in southern Russia are used to both determine the input parameters and to verify the proposed models. It is shown that the first model reproduces the properties of the real field of the ADHI more precisely compared to the second one, but the numerical implementation of the first model is significantly more time consuming. In the future, it is intended to transform the models presented to a numerical model of the conditional spatio-temporal field of the ADHI defined on a dense spatio-temporal grid and to use the model constructed for the stochastic forecasting of the heat index.


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