• Kishan Singh Rawat

      Articles written in Journal of Earth System Science

    • Appraisal of long term groundwater quality of peninsular India using water quality index and fractal dimension

      Kishan Singh Rawat Sudhir Kumar Singh T German Amali Jacintha Jasna Nemčić-Jurec Vinod Kumar Tripathi

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      A review has been made to understand the hydrogeochemical behaviour of groundwater through statistical analysis of long term water quality data (year 2005–2013). Water Quality Index (WQI), descriptive statistics, Hurst exponent, fractal dimension and predictability index were estimated for each water parameter. WQI results showed that majority of samples fall in moderate category during 2005–2013, but monitoring site four falls under severe category (water unfit for domestic use). Brownian time series behaviour (a true random walk nature) exists between calcium (Ca2+) and electric conductivity (EC); magnesium (Mg2+) with EC; sodium (Na+) with EC; sulphate (SO2−4) with EC; total dissolved solids (TDS) with chloride (Cl) during pre- (2005–2013) and post- (2006–2013) monsoon season. These parameters have a closer value of Hurst exponent (H) with Brownian time series behaviour condition (H=0.5). The result of times series analysis of water quality data shows a persistent behaviour (a positive autocorrelation) that has played a role between Cl and Mg2+, Cl and Ca2+, TDS and Na+, TDS and SO2−4, TDS and Ca2+ in pre- and post-monsoon time series because of the higher value of H (>1). Whereas an anti-persistent behaviour (or negative autocorrelation) was found between Cl and EC, TDS and EC during pre- and post-monsoon due to low value of H. The work outline shows that the groundwater of few areas needs treatment before direct consumption, and it also needs to be protected from contamination.

    • Semi-empirical model for retrieval of soil moisture using RISAT-1 C-Band SAR data over a sub-tropical semi-arid area of Rewari district, Haryana (India)

      Kishan Singh Rawat Vinay Kumar Sehgal Sanatan Pradhan Shibendu S Ray

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      We have estimated soil moisture (SM) by using circular horizontal polarization backscattering coefficient (σoRH), differences of circular vertical and horizontal σooRV− σo RH) from FRS-1 data of Radar Imaging Satellite (RISAT-1) and surface roughness in terms of RMS height (RMSheight). We examined the performance of FRS-1 in retrieving SM under wheat crop at tillering stage. Results revealed that it is possible to develop a good semi-empirical model (SEM) to estimate SM of the upper soil layer using RISAT-1 SAR data rather than using existing empirical model based on only single parameter, i.e., σo. Near surface SM measurements were related to σoRH, σoRV−σoRH derived using 5.35 GHz (C-band) image of RISAT-1 and RMSheight. The roughness component derived in terms of RMSheight showed a good positive correlation with σoRH−σoRH (R2 = 0.65). By considering all the major influencing factors (σoRH, σoRV− σoRH, and RMSheight), an SEM was developed where SM (volumetric) predicted values depend on σoRH, σoRV− σoRH, and RMSheight. This SEM showed R2 of 0.87 and adjusted R2 of 0.85, multiple R=0.94 and with standard error of 0.05 at 95% confidence level. Validation of the SM derived from semi-empirical model with observed measurement (SMObserved) showed root mean square error (RMSE) = 0.06, relative- RMSE (R-RMSE) = 0.18, mean absolute error (MAE) = 0.04, normalized RMSE (NRMSE) = 0.17, Nash–Sutcliffe efficiency (NSE) = 0.91 (≈1), index of agreement (d) = 1, coefficient of determination (R2) = 0.87, mean bias error (MBE) = 0.04, standard error of estimate (SEE) = 0.10, volume error (VE) = 0.15, variance of the distribution of differences (S2d) = 0.004. The developed SEM showed better performance in estimating SM than Topp empirical model which is based only on σo. By using the developed SEM, top soil SM can be estimated with low mean absolute percent error (MAPE) = 1.39 and can be used for operational applications.

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