A note on the possibility of saline water invasion around the Jaldha coast, West Bengal (India)

1967 ◽  
Vol 5 (2) ◽  
pp. 95-101 ◽  
Author(s):  
H.P. Patra
Keyword(s):  
Author(s):  
Roberto González-De Zayas ◽  
Liosban Lantigua Ponce de León ◽  
Liezel Guerra Rodríguez ◽  
Felipe Matos Pupo ◽  
Leslie Hernández-Fernández

The Cenote Jennifer is an important and unique aquatic sinkhole in Cayo Coco (Jardines del Rey Tourist Destination) that has brackish to saline water. Two samplings were made in 1998 and 2009, and 4 metabolism community experiments in 2009. Some limnological parameters were measured in both samplings (temperature, salinity, pH, dissolved oxygen major ions, hydrogen sulfide, nutrients and others). Community metabolism was measured through incubated oxygen concentration in clear and dark oxygen bottles. Results showed that the sinkhole limnology depends on rainfall and light incidence year, with some stratification episodes, due to halocline or oxycline presence, rather than thermocline. The sinkhole water was oligotrophic (total nitrogen of 41.5 ± 22.2 μmol l−1 and total phosphorus of 0.3 ± 0.2 μmol l−1) and with low productivity (gross primary productivity of 63.0 mg C m−2 d−1). Anoxia and hypoxia were present at the bottom with higher levels of hydrogen sulfide, lower pH and restricted influence of the adjacent sea (2 km away). To protect the Cenote Jennifer, tourist exploitation should be avoided and more resources to ecological and morphological studies should be allocated, and eventually use this aquatic system only for specialized diving. For conservation purposes, illegal garbage disposal in the surrounding forest should end.


Planta Medica ◽  
2007 ◽  
Vol 73 (09) ◽  
Author(s):  
M Gangopadhyay ◽  
R Bhattacharya ◽  
D Chakraborty ◽  
S Bhattacharya ◽  
A Mitra ◽  
...  

2020 ◽  
Vol 12 (1) ◽  
pp. 60-69 ◽  
Author(s):  
Pijush Basak

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.


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

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