Deepesh Machiwal

Central Arid Zone Research Institute

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Madan K. Jha

Indian Institute of Technology Kharagpur

Sanjay Kumar

Dr. Rajendra Prasad Central Agriculture University

Devi Dayal

Post Graduate Institute of Medical Education and Research

Hari Mohan Meena

Central Arid Zone Research Institute

Wim Cornelis

Ghent University

Sabine Reinsch

UK Centre for Ecology & Hydrology

Zhongbo Su

University of Twente

Brent Clothier

Plant & Food Research

Evangelos Hatzigiannakis

National Public Health Organization

Yijian Zeng

University of Twente

Cooperative Institutions

The University of Texas at Austin

Universidade Federal de Santa Maria

Central Arid Zone Research Institute

Indian Institute of Soil and Water Conservation

Indian Council of Agricultural Research

ICAR Research Complex for NEH Region

Centre National de la Recherche Scientifique

Forschungszentrum Jülich

Tarbiat Modares University

Soil Conservation and Watershed Management Research

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Trends and homogeneity of monthly, seasonal, and annual rainfall over arid region of Rajasthan, India

Theoretical and Applied Climatology (2018)

Hari Mohan Meena Deepesh Machiwal Priyabrata Santra P. C. Moharana Deepak Singh

Trend analysis

10.1007/s00704-018-2510-9

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Citations (44)

Identifying sources of groundwater contamination in a hard-rock aquifer system using multivariate statistical analyses and GIS-based geostatistical modeling techniques

Journal of Hydrology Regional Studies (2015)

Deepesh Machiwal Madan K. Jha

The study area is Udaipur district, which is situated in hard-rock hilly terrain of Rajasthan, India. In this study, spatio-temporal variations of fifteen groundwater quality parameters are explored by box–whisker plots, trends are detected and quantified, and GIS-based groundwater quality index (GQI) is computed. For the first time, scores of principal component analysis (PCA) are combined with GIS-based geostatistical modeling by following a sound methodology in comprehensive manner to identify sources of groundwater contamination. Box–whisker plots revealed linkages between rainfall and groundwater quality, which were further verified by GQI ranging from 69 to 76 in Cluster I and from 73 to 78 in Cluster II. Cluster analysis identified two clusters of sites based on groundwater contamination controlled by geology. Significantly increasing trends are indicated (p < 0.05) at most sites in fluoride, sodium, EC and TDS, but significantly decreasing trends in silica at 40% sites indicate a possibility of replacement of older groundwater with recent rainfall recharge. Spatial distribution of increasing trends is affected by anthropogenic processes. Sen's method indicated increasing rates for calcium, magnesium, sodium, iron, bicarbonate, sulphate, fluoride, TDS, hardness and EC. PCA results indicated occurrence of groundwater contamination in Cluster I by anthropogenic sources and presence of natural/geogenic processes in Cluster II. Significant PCs, viz. major ion and soil leaching pollution factors, govern overall evolution of geochemical processes.

Geostatistics

10.1016/j.ejrh.2014.11.005

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Citations (190)

Comparison of Hybrid LSTAR-GARCH Model with Conventional Stochastic and Artificial-Intelligence Models to Estimate Monthly Streamflow

Water Resources Management (2024)

Priyanka Sharma Farshad Fathian Deepesh Machiwal S. R. Bhakar Survey D. Sharma

10.1007/s11269-024-03834-8

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Citations (2)

Assessment and mapping of groundwater vulnerability to pollution: Current status and challenges

Earth-Science Reviews (2018)

Deepesh Machiwal Madan K. Jha Vijay P. Singh Chinchu Mohan

Vulnerability

10.1016/j.earscirev.2018.08.009

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Citations (228)

Clustering of rainfall stations and distinguishing influential factors using PCA and HCA techniques over the western dry region of India

Meteorological Applications (2018)

Deepesh Machiwal Sanjay Kumar Hari Mohan Meena Priyabrata Santra R. K. Singh

This study used hierarchical cluster analysis (HCA) to delineate the spatial patterns of monthly, seasonal and annual rainfall by clustering 62 stations in the western arid region of India based on a 55 year (1957–2011) data set. The statistical properties of clusters were computed and box–whisker plots plotted. Furthermore, the relative influence of three geographical factors (longitude, latitude and altitude) and five statistical parameters (the mean, standard deviation (SD), co‐efficient of variation (CV), and maximum and minimum rainfall) on mean rainfall was investigated using principal component analysis (PCA). The use of HCA resulted in four rainfall clusters geographically located at a distinct position. Cluster I, characterized by the lowest mean rainfall and highest CV, was located in the western portion, whereas mean rainfall was the highest for cluster IV situated in the eastern portion. Box–whisker plots revealed a slight skewness, although the monsoon and annual rainfall followed a normal distribution. The PCA results indicted two to three significant principal components (PCs) with eigenvalues > 1. In four clusters, two PCs explained the major variance, ranging from 69.41% (June) to 91.83% (August) in monthly rainfall, from 63.62% (monsoon) to 93.30% (post‐monsoon) in seasonal rainfall, and from 71.48% to 90.73% in annual rainfall. In monthly and seasonal rainfall, first PC 1 is termed the “mean rainfall component”, which has strong to moderate associations with longitude, and is equally opposed by the CV. These findings are vital for planners and decision‐makers to formulate strategies to manage unusual rainwater quantities.

Longitude

Seasonality

Geographic coordinate system

10.1002/met.1763

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Citations (26)

Assessment of Groundwater Potential in a Semi-Arid Region of India Using Remote Sensing, GIS and MCDM Techniques

Water Resources Management (2010)

Deepesh Machiwal Madan K. Jha Bimal C. Mal

Groundwater resources

10.1007/s11269-010-9749-y

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Citations (484)

Analysis of trend in temperature and rainfall time series of an Indian arid region: comparative evaluation of salient techniques

Theoretical and Applied Climatology (2018)

Deepesh Machiwal Ankit Gupta Madan K. Jha Trupti Kamble

Trend analysis

10.1007/s00704-018-2487-4

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Citations (77)

Exploring temporal dynamics of spatially-distributed groundwater levels by integrating time series modeling with geographic information system

Geocarto International (2019)

Deepesh Machiwal P. C. Moharana Sanjay Kumar Vandita Srivastava Subhash Bhandari

This study developed a novel framework for integrating time series modeling with geographic information system (GIS). For the first time, procedures of four statistical tests, i.e., t-test of stationarity, cumulative deviation test of homogeneity, autocorrelation technique of persistence, and variance-corrected Mann–Kendall test of trend, are implemented in GIS platform to enable use of raster dataset. Application of developed framework is demonstrated by exploring time series characteristics of pre- and post-monsoon groundwater levels in an Indian arid region. Raster dataset of 22-year (1996–2017) groundwater levels are generated using four best-fit geostatistical models, according to mean absolute error, root mean square error, correlation coefficient and modified index of agreement. Increasing groundwater level trends in central and southern parts are attributed to abrupt change-points in annual rainfall that enhanced groundwater recharge. The developed framework can be adopted in other parts of the world to explore groundwater-level dynamics in spatially-distributed manner.

10.1080/10106049.2019.1648561

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Citations (3)

Estimating aquifer properties and distributed groundwater recharge in a hard-rock catchment of Udaipur, India

Applied Water Science (2016)

Deepesh Machiwal Pradeep Kumar Singh Kamal Kishore Yadav

The present study determined aquifer parameters in hard-rock aquifer system of Ahar River catchment, Udaipur, India by conducting 19 pumping tests in large-diameter wells. Spreadsheet programs were developed for analyzing pumping test data, and their accuracy was evaluated by root mean square error (RMSE) and correlation coefficient (R). Histograms and Shapiro–Wilk test indicated non-normality (p value <0.01) of pre- and post-monsoon groundwater levels at 50 sites for years 2006–2008, and hence, logarithmic transformations were done. Furthermore, recharge was estimated using GIS-based water table fluctuation method. The groundwater levels were found to be influenced by the topography, presence of structural hills, density of pumping wells, and seasonal recharge. The results of the pumping tests revealed that the transmissivity (T) ranges from 68–2239 m2/day, and the specific yield (S y) varies from 0.211 to 0.51 × 10−5. The T and S y values were found reasonable for the hard-rock formations in the area, and the spreadsheet programs were found reliable (RMSE ~0.017–0.339 m; R > 0.95). Distribution of the aquifer parameters and recharge indicated that the northern portion with high ground elevations (575–700 m MSL), and high S y (0.08–0.25) and T (>600 m2/day) values may act as recharge zone. The T and S y values revealed significant spatial variability, which suggests strong heterogeneity of the hard-rock aquifer system. Overall, the findings of this study are useful to formulate appropriate strategies for managing water resources in the area. Also, the developed spreadsheet programs may be used to analyze the pumping test data of large-diameter wells in other hard-rock regions of the world.

Aquifer properties

10.1007/s13201-016-0462-8

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Citations (17)

Evaluating effect of cover crops on runoff, soil loss and soil nutrients in an Indian arid region

Communications in Soil Science and Plant Analysis (2021)

Deepesh Machiwal Sushil Kumar Adlul Islam Sanjay Kumar Sita Ram Jat

Estimates of the soil and nutrient losses are essential for design and planning of soil conservation measures in Indian arid region. This study aims at estimating rainfall-runoff, soil and nutrient losses from different cover crops, and to identify the best cover for checking soil loss. The study is conducted for 2013–2015 in research farm of the Central Arid Zone Research Institute, Regional Station, Bhuj, Gujarat, India. Ten treatments comprising four sole-crop, that is, sorghum (Sorghum bicolor), pearl millet (Pennisetum glaucum), green gram (Vigna radiata), and cluster bean (Cyamopsis tetragonoloba) and four cereal-legume intercropping with two controls (cultivated and unplowed fallows) are undertaken in randomized block design with three replications. Multi-slot divisors are fabricated and installed. Analysis of variance (ANOVA) is performed, and their interrelationships are explored. The highest soil loss is recorded from cultivated fallow (108.03 ± 49.95 kg.ha−1.yr−1) and unplowed fallow (78.95 ± 28.42 kg.ha−1.yr−1). Green gram is found effective in controlling soil loss as sole-crop (event-wise soil loss ~0.54–33.94 kg.ha−1) as well as intercropping with sorghum (event-wise soil loss ~0.60–23.37 kg.ha−1) and pearl millet (event-wise soil loss ~2.45–31.11 kg ha−1). ANOVA revealed significance (p < .05) of runoff-generating rainfall, crop cover, and their sole- and intercropping practices. Values of coefficient of determination (R2) indicated highly correlated (R2 ≥ 0.75) relationships of rainfall-runoff for all treatments, rainfall-soil loss for sole cereals and cultivated fallow, and runoff-soil loss for pearl millet and intercropping with green gram. This study concludes that cereal-legume intercropping diminishes the adverse impact of raindrops on soil erosion and crop production.

Intercropping

Pennisetum

Alfisol

10.1080/00103624.2021.1892726

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Citations (14)