Relationship between North Pacific atmospheric pressure variations and Indian Monsoon rainfall

Summary Analysis of mean sea level pressure (1925 to 1988) over the North Pacific Ocean (NPP) for the winter period (November to March) revealed a significant correlation with Indian Monsoon rainfall during the later period. Its correlation coefficients (CC) for different periods (during 1951–1988) are significant at the 1% to 5% levels. The temporal stability of these CCs is examined using 11, 21 and 31 year sliding windows. NPP is seen to play an important role in the regression models as revealed by the relative significance of its partial regression coefficients. The regression models developed are seen to perform well for the independent period.With 5 Figures     

Drought hotspot analysis and risk assessment using probabilistic drought monitoring and severity–duration–frequency analysis

Drought hotspot identification requires continuous drought monitoring and spatial risk assessment. The present study analysed drought events in the agriculture‐dominated mid‐Mahanadi River Basin in Odisha, India, using crop water stress as a drought indicator. This drought index incorporated different factors that affect crop water deficit such as the cropping pattern, soil characteristics, and surface soil moisture. The drought monitoring framework utilized a relevance vector machine model‐based classification that provided the uncertainty associated with drought categorization. Using the proposed framework, drought hotspots are identified in the study region and compared with indices based on precipitation and soil moisture. Further, a bivariate copula is employed to model the agricultural drought characteristics and develop the drought severity–duration–frequency (S–D–F) relationships. The drought hotspot maps and S–D–F curves are developed for different locations in the region. These provided useful information on the site‐specific drought patterns and the characteristics of the devastating droughts of 2002 and 2012, characterized by an average drought duration of 7 months at several locations. The site‐specific risk of short‐ and long‐term agricultural droughts are then investigated using the conditional copula. The results suggest that the conditional return periods and the S–D–F curves are valuable tools to assess the spatial variability of drought risk in the region.     

MODFLOW based groundwater resource evaluation and prediction in Mendha sub-basin,NE Rajasthan

A direct approach to designing MODFLOW finite difference model is tedious and less intuitive, specifically for complex boundary and initial conditions. Therefore, a MODFLOW model can be developed either using a grid or conceptual model approach. The conceptual model is created using Geographic Information System (GIS) objects including points, arcs and polygons so that it can more accurately represent real world condition. It is a simplified representation of the site to be modelled including the model domain, boundary conditions, sources, sinks and material zones. Advantage of conceptual model is that most of the input can be in terms of physical objects, such as wells, lakes, recharge zones etc which can then be converted to a grid based mathematical model with the help of preprocessor software. This paper presents the results of a mathematical groundwater model developed for the northern part of Mendha sub-basin in the semi arid region of northeastern Rajasthan, employing conceptual groundwater modelling approach. For this purpose, Groundwater Modelling Software (GMS) was used which supports the MODFLOW-2000 code. For the purpose of modelling the Source/ Sink Coverage, Recharge Coverage, Extraction Coverage, Return Flow Coverage and Soil Coverage were considered. The model was calibrated against the historical and observed water level data for periods 1998 to 2003 and 2003 to 2005 respectively.     

Prioritisation of sub-watersheds based on earth observation data of agricultural dominated northern river basin of India

The Upper Tons River Basin of North India has been selected for prioritisation of sub-watersheds (SW) based on morphometric parameters with respect to groundwater derived from topographic sheets and CARTOSAT data. There are 10 SW have been delineated in the region, high stream frequency (F_s) values of SW (1–5) and SW-9 indicated the occurrence of steep slopes, less permeable rocks, greater runoff, less infiltration possibility. Further, these regions have been predicted as poor groundwater potentialities. SW-2 has been identified as poorest groundwater potential zone, whereas SW-4 and SW (6–8) regions possess good permeable bed rocks. The Drainage density (D_d) map demonstrated that the middle south-west region possesses higher D_d whereas northeastern regions contain lower D_d. Further, the areal parameters indicate elongated shape of the basin, hilly region has moderate to steeper ground slope. The outcomes of work have potential to manage groundwater and to ameliorate the flash flood and droughts.     

Evaluation of linear regression methods as downscaling tools in temperature projections over the Pichola Lake Basin in India

In this paper, downscaling models are developed using various linear regression approaches, namely direct, forward, backward and stepwise regression, for obtaining projections of mean monthly maximum and minimum temperatures (Tmax and Tmin) to lake‐basin scale in an arid region in India. The effectiveness of these regression approaches is evaluated through application to downscale the predictands for the Pichola lake region in the state of Rajasthan in India, which is considered to be a climatically sensitive region. The predictor variables are extracted from (i) the National Centers for Environmental Prediction (NCEP) reanalysis dataset for the period 1948–2000 and (ii) the simulations from the third‐generation Canadian Coupled Global Climate Model (CGCM3) for emission scenarios A1B, A2, B1 and COMMIT for the period 2001–2100. The selection of important predictor variables becomes a crucial issue for developing downscaling models as reanalysis data are based on a wide range of meteorological measurements and observations. A simple multiplicative shift was used for correcting predictand values. Direct regression was found to yield better performance among all other regression techniques for the training data set, while the forward regression technique performed better in the validation data set, explored in the present study. For trend analysis, the Mann–Kendall non‐parametric test was performed. The results of downscaling models show that an increasing trend is observed for Tmax and Tmin for A1B, A2 and B1 scenarios, whereas no trend is discerned with the COMMIT scenario by using predictors. Copyright © 2010 John Wiley & Sons, Ltd.     

Heavy metal pollution assessment through comparison of different indices in sewage-fed fishery pond sediments at East Kolkata Wetland,India

The sediments of the raw sewage-fed fishpond system at East Kolkata Wetland (EKW) were analyzed for heavy metal content in a comprehensive way. Various indices of contamination like enrichment factor (EF), geo-chemical index (I _geo), modified degree of contamination (mD_C), and pollution load index (PLI) were assessed. In all cases, instead of literature values, the metal concentrations of less contaminated sites, separated by the statistical approach of the hierarchical cluster analysis, were used as baseline values. In the present study, about 70% of the pond sediments are found uncontaminated, 5% display low degree of contamination and 25% are designated as moderate degree of contamination. Both the EF and I _geo indices highlighted that the metals lead (Pb), cadmium (Cd), and chromium (Cr) are responsible for the contamination while there is little anthropogenic input in cases of Cu, Zn, and Ni. Most of the ponds situated near the main sewage flowing canals as well as the main traffic highway and close to the solid waste dumping areas recorded higher degree of metal contamination as evident from spatial variation of mD_C and PLI indices in the study area. Indices comparison study clearly indicates that although these are calculated using different methods, these may or may not produce the same indices values and hence the values should neither be compared nor be averaged. But all the above indices are directly related to a common term contamination factor (CF). Classification of contamination levels based on these CF values is found to be similar and this classification is only valid up to the level of high degree of contamination. Thus, the use of any one of these indices is sufficient to classify the degree of contamination of an area. However, to evaluate the contamination per metal, both I _geo and EF are effective while, to assess the composite effect of all the metals, PLI is preferable to mD_C.     

Earthquake analysis of intake-outlet towers including tower-water-foundation-soil interaction

The available procedure for earthquake analysis of axisymmetric intake-outlet towers is extended to towers of arbitrary geometry, but with two axes of plan symmetry, and to include the effects of tower-foundation-soil interaction. The total system is represented as four substructures: tower, surrounding water, contained water and the foundation supported on flexible soil. The substructure representation of the system permits use of the most effective idealization for each substructure. An example earthquake response analysis is presented to demonstrate the results obtained from the analysis procedure. Computation times for several cases are included to demonstrate the efficiency of the analysis procedure.     

Remote detection of geological structures: an application to the Aravalli region,western India

Optical and microwave remote sensing data are used in conjunction with a digital elevation model to map lineaments in the central parts of the Aravalli region, Rajasthan, western India. Lineament maps interpreted from each data-set are subsequently combined to derive a composite lineament map of the area. Rose plots are used to identify the prominent trends of the lineaments and compared with published structural map of the study area. Three major trends are identified, namely, the NE–SW, NNE–SSW and EW, which are interpreted to be, related to the DF1, DF2 and DF4 deformation phases identified by the previous workers through field studies. The lineaments are classified as fold axes or faults, and a total of 10-fold axes and 30 faults mapped in the area.     

Impact assessment of textile effluent on groundwater quality in the vicinity of Tirupur industrial area, southern India

Adverse effect of rapid industrialization on groundwater quality and quantity is widely known problem especially in developing countries. Tirupur, which is situated on the bank of Noyyal River in India, is known for intensive textile processing activities. As groundwater is the main water source for drinking water, there is an urgency to assess the groundwater quality. Twenty groundwater samples were collected for each post and pre-monsoon sampling during August 2009 and March 2010, respectively. Chemical and statistical analysis along with numerical modelling has been performed to assess the current status. The hydro-geochemical study revealed that the dominance of Mg–Cl and Na–HCO₃ groundwater type in the upstream region Tirupur industrial hub of Noyyal River basin. Na–Cl groundwater type was found increasing in industrial hub (Kasipalayam) and downstream of the industrial hub (Anaipalayam) sites. The dominance of Na–Cl type of water is mainly due to the impact of salts like NaCl, Na₂SO₄, etc. used in textile processing, which after discharge, percolate and accumulate in the aquifers. Seasonal groundwater quality of Tirupur region as a whole showed the dominance of Ca–HCO₃ ^?, Na–HCO₃ ^? and Na–Cl water types. PHREEQC model output indicates that nearly all the groundwater samples were oversaturated with respect to calcite and dolomite and undersaturated with respect to gypsum and halite. The results obtained in this study were then compared with groundwater quality of the Noyyal River basin for the year 2008–2009. Among the two sites, Kasipalayam was found to be most contaminated due to incessant industrial discharge. But with the advent of new treatment technologies like CETPs having zero liquid discharge system and MBR, there has been slight decline in the concentration of different physicochemical parameters from 2002–2003 to 2008–2009. This study not only makes situation alarming but also calls for immediate attention for sustainable management of water resources.