Bhilwara District Research Articles

A new geographic record of rare artillery fungus, Sphaerobolus jaysukhianus Vasava, Patel & Rajput, 2020, from Bhilwara District, Rajasthan, India

A new geographic record of rare artillery fungus, Sphaerobolus jaysukhianus Vasava, Patel & Rajput, 2020, from Bhilwara District, Rajasthan, India

Description and Comparative Analysis of Status of Soil Fertility in Suwana Block of Bhilwara District of Rajasthan, India

Description and Comparative Analysis of Status of Soil Fertility in Suwana Block of Bhilwara District of Rajasthan, India

Constraints faced by the farmers of Kisan farm pond scheme in Bhilwara district

Constraints faced by the farmers of Kisan farm pond scheme in Bhilwara district

A simplistic approach for monitoring meteorological drought over arid regions: a case study of Rajasthan, India

The commonly used precipitation-based drought indices typically rely on probability distribution functions that can be suitable when the data exhibit minimal discrepancies. However, in arid and semi-arid regions, the precipitation data often display significant discrepancies due to highly irregular rainfall patterns. Consequently, imposing any probability distributions on the data for drought analysis in such regions may not be effective. To address this issue, this study employs a novel drought index called the Discrepancy Precipitation Index (DPI), specifically designed for arid regions. Unlike traditional methods, the DPI does not impose a probability distribution on the precipitation data; instead, it relies on the discrepancy between the data and the mean value. Drought severity classifications (i.e., Drought-I, Drought-II, and Drought-III) are proposed based on the DPI values. The DPI is used to characterize and assess the meteorological drought years based on annual and monsoonal precipitation over nineteen districts in Western Rajasthan, India, during 1901–2019. Additionally, a novel statistic called Discrepancy Measure (DM) is employed to assess the degree of discrepancy in the precipitation climatology of the districts for annual and monsoon precipitation time series. Based on annual precipitation, Jaisalmer district exhibited the highest number of historical drought years (35), whereas three districts, i.e., Jhunjhunu, Dausa, and Bhilwara exhibited the lowest number of drought years (11). Similarly, based on monsoon precipitation, Jaisalmer and Bhilwara encountered the highest (34) and the lowest (11) number of drought years, respectively. The return period of Drought-II is lower for monsoon precipitation-based DPI as compared to that of the annual precipitation-based DPI for all the districts. The DM and DPI-based total number of droughts are found to be strongly correlated for both annual and monsoon precipitation. The DM value is highest for Jaisalmer and lowest for Bhilwara district. The findings reveal DPI as an efficient tool for assessing drought years, particularly in arid climatic conditions. Moreover, as the DM value increases for a precipitation series, the DPI becomes more effective in capturing drought events.

Attitude of farmers towards kisan farm pond scheme in Bhilwara district of Rajasthan

Attitude of farmers towards kisan farm pond scheme in Bhilwara district of Rajasthan

Comparative evaluation of airborne AVIRIS-NG and spaceborne PRISMA hyperspectral data in identification and mapping of altered/weathered minerals in Jahazpur, Rajasthan

The present study addresses a comparative evaluation of airborne AVIRIS-NG and spaceborne PRISMA hyperspectral datasets for mapping hydrothermally altered minerals in Jahazpur town (25°25′23.37″N; 75°06′23.17″E) of Bhilwara district in southeastern Rajasthan. This area is located in Aravalli Craton which host notable base metal mineralization namely Rampura-Agucha, Pur-Banera and Rajpura-Dariba. The hyperspectral datasets were classified using spectral angle mapper which identified talc, soapstone, and kaolinite clay minerals in the study area. The samples were collected from the identified areas. Their spectral signature was compared with AVIRIS-NG, PRISMA, and USGS mineral spectral library and showed greater similarity in spectral absorption features. Conventional geological techniques such as thin section studies and XRD diffraction pattern analysis were carried out to validate the presence of minerals in the study area. Comparative analysis shows AVIRIS-NG and PRISMA sensor capability to identify altered/weathered minerals. The PRISMA dataset did not identify small surface exposure of talc deposit at the Padampura location due to its low spatial resolution (30 m) and SNR values. In contrast, AVIRIS-NG imagery successfully maps this exposure in the classified mineral map. The types of alteration in the area show formation of talc mineral from dolomite and argillic alteration resulting in kaolinite and montmorillonite formation. Therefore, airborne AVIRIS-NG proves its efficiency in mapping of relatively small surface exposure of altered minerals compared with the spaceborne PRISMA hyperspectral dataset.

Evaluation of machine learning techniques with AVIRIS-NG dataset in the identification and mapping of minerals

Identifying valuable mineral resources is obligatory for human development and survival due to their scientific and economic implications. Hyperspectral Remote Sensing (HRS) is an efficient technique that empowers us to precisely identify and map altered minerals based on spectral absorption curves in the VNIR and SWIR range of the electromagnetic spectrum. Machine Learning Algorithms (MLAs) are a subclass of Artificial Intelligence (AI) that improves and automate HRS based lithological mapping using spectra based classification approach. The present study evaluates various MLAs in identifying and mapping hydrothermally altered and weathered minerals such as kaolinite, talc, kaosmec, and montmorillonite. The study was performed with the Airborne Visible Infrared Imaging Spectrometer- Next Generation (AVIRIS-NG) hyperspectral dataset of Jahazpur town of Bhilwara district in the state of Rajasthan, India (75° 9′ 57′' E, 25° 32′ 24″ N). The Spectral Angle Mapper (SAM) algorithm was applied to create a reference mineral distribution map for the target mineral classes. Further, the reference map has been verified with the field validation survey. A total of 828 pixels were identified as end member pixels. The obtained endmember pixels were further used for developing predictive machine learning based models for mapping the mineral resources using eight supervised classifiers, namely Support Vector Machine, k-Nearest Neighbor, Decision Tree, Random Forest, Logistic Regression, Artificial Neural Network, Linear Discriminant Analysis, and Naïve Bayes. The performance of the classifiers was measured using the kappa coefficient, overall accuracy, precision, recall, F1-score, Matthews’s correlation coefficient, and ROC curve. It was observed in the study that the Support Vector Machine outperformed all the classifiers in terms of overall accuracy and AVIRIS-NG data poses an excellent potential for mineral mapping using machine learning based models in a diverse mountainous area.

Cost and Return Analysis of Kharif Sorghum (Sorghum bicolor) in Bhilwara District, Rajasthan

Background: Sorghum is a heat and drought resistant crop that is widely grown in arid and semi-arid regions for food, feed and bio-energy. The sorghum crop is important to the majority of farmers for income, nutritional security and environmental sustainability. They grow sorghum not for profit, but because it is the only crop that can withstand the harsh climatic conditions that exist. The present study aimed to investigate the economics of sorghum in the Bhilwara district of Rajasthan during the year 2020-21 using primary data from 60 sample households from four different villages. Methods: The standard cost concept method of the Commission for Agricultural Cost and Price (CACP) was used to calculate the cost of cultivation (COC) of sorghum crop. It includes Cost A1, Cost A2, Cost B1, Cost B2, Cost C1, Cost C2 and Cost C3. Farm income measures, which include gross income, farm business income, family labour income and net income, are used to determine crop profitability and return on investment. Result: The results of study revealed that total cost (Cost C2) of sorghum cultivation per ha was found to be ₹ 25149.69. The cost of producing one quintal of sorghum was calculated to be ₹ 1383.18. Sorghum cultivation generated a net income, farm business income and family labour income of ₹ 23658.44, ₹ 30680.32 and ₹ 26527.74 per ha, respectively.

Epigenetic Copper Mineralization in Raipur-Mokhampura Area, Mangalwar Complex, Bhilwara District, Rajasthan

Abstract Rocks of the Mangalwar and Sandmata Complex of the Bhilwara Supergroup of Archaean age host copper mineralization in the form of chalcopyrite-bornite in Raipur-Mokhampura and Rajaji ka Karera areas of Bhilwara district, Rajasthan. The area forms a part of the dismembered granite-greenstone sequence of the Bhilwara Supergroup. Chalcopyrite and bornite form the dominant copper sulphides along with pyrite, digenite, chalcocite and some accessory Bi-telluride and Bi-Cu sulphide phases. These sulphides occur along the S2 foliation planes, veins and fractures within the amphibolites and calc-gneiss. Presence of Bi indicates hydrothermal epigenetic nature of the mineralization developed under highly acidic reducing condition and high sulphur fugacity.

Indicator-Based Assessment of Drought in Bhilwara District, Rajasthan

Management of water resources helps to sustain even in drastic conditions resulted due to unprecedented disruption in rainfall patterns. Change and irregularity in the pattern of the Indian monsoon are the outcomes of human-induced activities. Inadequate water availability affecting various sectors namely domestic, industrial, and agricultural sectors that are dependent upon it. To cope under such drastic conditions adaptability and planning prior to its occurrence plays a significant role. It is under this context, the present study investigated drought characteristics which include drought frequency and severity caused by prolonged dry spells in Bhilwara district, Rajasthan. The district falls in the water-scarce regions with arid to semi-arid conditions and with an average annual rainfall of 658.03 mm. Due to high rainfall variability, the region is frequently subsumed under drought-like conditions. Comprehensive analysis using daily rainfall data from 1973-2018 for 12 rain gauge stations in Bhilwara district has been carried out. Most of the stations were drought-prone assessed by probability analysis using Weibull’s plotting position formula. The departure analysis showed that Kotri station has a maximum drought frequency of 1 in 2 years while other stations were having a drought frequency of 1 in 3 to 4 years. Prioritization of drought-prone stations based on rainfall departure analysis helps to initiate an immediate mitigation process based on the ranking of its proneness. Asind and Bhilwara station with RDI 0.91 has maximum proneness and its calls for effective planning for drought management. Based on seasonal departure analysis it is found that 1980, 1981, 1985, 1987, 2000, 2002, 2008, 2015, and 2017 are drought years. The result has been supplemented using NDVI so that the vegetation condition can also be assessed during water stress conditions. The study highlighted that the frequency of drought has increased owing due to climate change and thus, poses serious challenges if not tackle adequately.

Potentials of Airborne Hyperspectral AVIRIS-NG Data in the Exploration of Base Metal Deposit—A Study in the Parts of Bhilwara, Rajasthan

In this study, we have processed the spectral bands of airborne hyperspectral data of Advanced Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) data for delineating the surface signatures associated with the base metal mineralization in the Pur-Banera area in the Bhilwara district, Rajasthan, India.The primaryhost rocks of the Cu, Pb, Zn mineralization in the area are Banded Magnetite Quartzite (BMQ), unclassified calcareous silicates, and quartzite. We used ratio images derived from the scale and root mean squares (RMS) error imagesusing the multi-range spectral feature fitting (MRSFF) methodto delineate host rocks from the AVIRIS-NG image. The False Color Composites (FCCs) of different relative band depth images, derived from AVIRIS-NG spectral bands, were also used for delineating few minerals. These minerals areeither associated with the surface alteration resulting from the ore-bearing fluid migration orassociated with the redox-controlled supergene enrichments of the ore deposit.The results show that the AVIRIS-NG image products derived in this study can delineate surface signatures of mineralization in 1:10000 to 1:15000 scales to narrow down the targets for detailed exploration.This study alsoidentified the possible structural control over the knownsurface distribution of alteration and lithocap minerals of base metal mineralizationusing the ground-based residual magnetic anomaly map. This observationstrengthens the importance of the identified surface proxiesas an indicator of mineralization. X-ray fluorescence analysis of samples collectedfromselected locations within the study area confirms the Cu-Pb-Zn enrichment. The sulfide minerals were also identified in the microphotographs of polished sections of rock samples collected from the places where surface proxies of mineralization were observed in the field. This study justified the investigation to utilize surface signatures of mineralization identified using AVIRIS-NG dataand validated using field observations, geophysical, geochemical, and petrographical data.

India Fighting COVID-19: Experiences and Lessons Learned From the Successful Kerala and Bhilwara Models.

The COVID-19 pandemic marks its emergence in China in December 2019. India reported its first case on January 30th 2020 which happened to be epidemiologically linked to China. On March 24, India went into nationwide lockdown. The number of cases increased in the country and a few hotspots were identified. Cluster containment strategy seemed to be effective in containing the disease and breaking the chain of transmission. Two models (Kerala and Bhilwara) emerged as a lesson for other states. Kerala government implemented a "triple-lock containment strategy" and Bhilwara district administration followed "all down curfew" with massive sample testing. The experiences from these successful field models can be implemented in other districts and states to flatten the COVID-19 curve.

Geotechnical Studies of World Largest Lead-Zinc Producing- Rampura AguchaMines, Bhilwara District, Rajasthan

The Paleoproterozoic age of the Aravalli Supergroup bears most complex deposit of economically important strata bound base metal- lead and zinc. The Rampura Aguchamine which is located in the Bhilwara district of Rajasthan, NW India has a SEDEX-type of deposit with its highly deformed nature. The basement ensemble represented by the graphite-mica sillimanite gneiss shows an intricate tectonic evolutionary history. The potentially hazardous nature of this large open-pit mine requires a proper geotechnical studies for mine designing and general operating procedure to allow safe and economic mining. The inherent geotechnical complexity parameters incorporates the physical and mechanical properties like porosity, swelling,moisturecontent, degree of saturation, anisotropy, durability, elasticity, and plasticity.If appropriately analyzed, these traits can convey valuable information by using advanced techniques. Slope Stability Radar (SSR), Inclinometer, prism, piezometer, rock bolting, rock stitching have been manoeuvre to oversee the RQD, RMR, Q system and variant geological criterion.

Trend analysis of tall crop reference evapotranspiration (ETr) for Bhilwara district

Trend analysis of tall crop reference evapotranspiration (ETr) for Bhilwara district

English

English

Spectral characteristics of talc and mineral abundance mapping in the Jahazpur Belt of Rajasthan, India using AVIRIS-NG data

ABSTRACT Spaceborne data with Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Short Wave Infrared (SWIR) bands have been used worldwide in discriminating different clay minerals. However, due to wide bandwidth of ASTER sensors, it is difficult to distinguish between pure and impure variety of talc mineral. The present study highlights the efficacy of airborne hyperspectral data Airborne Visible/Infrared Imaging Spectrometer – Next Generation (AVIRIS-NG) for spectral analysis in talc mineral in the Jahazpur Belt of Bhilwara district in Rajasthan, India. Due to its better spectral and spatial resolution, AVIRIS-NG is found to be extremely useful in identifying talc mineral in SWIR region. Talc is characterized by doublet shaped spectral pattern in AVIRIS-NG image with strong absorption dips at 2289.75 nm and 2314.80 nm which could not be picked up in ASTER image. Spectral matching of talc pixels is verified with the field spectra of samples and available spectral library of United States Geological Survey, Jet Propulsion Laboratory, and International Geological Correlation Programme. Variation in reflectance percentage of different talc pixels is attributed to variation in chemical composition of talc. However, a large number of mixed pixels with spectral pattern of both talc and kaolinite minerals have been identified in AVIRIS-NG image which are found to be an impure variety of talc. Whole-pixel to sub-pixel classification techniques with Spectral Angle Mapper, Spectral Feature Fitting, Mixture Tuned Matched Filtering, and Linear Spectral Unmixing (LSU) techniques have been applied for talc abundance mapping in Jahazpur area. LSU is found to be the most useful and accurate technique in classifying spectrally pure to impure variety of talc.

Psychological effect on corona pandemic in suspected and positive cases in Bhilwara district in Rajasthan: An observation study

Psychological effect on corona pandemic in suspected and positive cases in Bhilwara district in Rajasthan: An observation study

Insights from COVID-19 cluster containment in Bhilwara District, Rajasthan.

In March 2020, a healthcare professional from a renowned private hospital, in the textile city of Bhilwara, Rajasthan, reported clustering of cases of pneumonia amongst doctors and paramedical staff suspected to be due to COVID-19. The basis of suspicion was clinico-eco-epidemiologic-radiological findings as, by that time, about 20 COVID19 cases were reported from the state of Rajasthan including a big Italian group of tourists who travelled extensively in Rajasthan, including Udaipur city. The current study presents the field experience of the Central and the State Rapid Response Teams (RRTs) in the cluster containment at Bhilwara. Methods: The information regarding the sociodemographic profile of the cases was provided by the Senior Medical Officer In-charge. The containment strategy was modeled under 6 pillars. Google Maps was used for preparing spot map. Immediate public health actions of cluster containment including contact tracing, quarantine, and isolation were initiated using epidemiological approach of mapping the cluster and taking care of reservoir of infection by the District Public Health Team supported by Multidisciplinary Rapid Response Team. This was supplemented by strict enforcement of lock down in the District taking care of daily need of the community by the leadership of administration with very strong intersectoral co-ordination (locally called "ruthless containment"). The forthcoming challenge resides in re-establishment of inter-district and inter-state travel, which can become a risk of re-entry of the new cases, which needs to be taken care of, with the help of stringent administrative measures and screening at all points of entry. The team in Bhilwara needs to remain vigilant to pick up any imported cases early before local transmission establishes.

Pedogenesis and Mineralogy of Alluvial Soils from Semi-arid Southeastern Part of Rajasthan in Aravalli Range, India

Abstract Three representative alluvial soils were studied from Kothari river basin of Bhilwara district in southeast Rajasthan to assess degree of chemical weathering and pedogenesis. Morphological, geochemical, mineralogical and other analytical investigations were carried out. Soils were classified as Entisols and Inceptisols. These soils are mostly sandy with more than 50% of fine and medium sand fractions, silt to clay ratio more than 0.45 and little textural variation suggesting more uniform weathering. These soils are slight to strongly alkaline with high exchangeable sodium (>15%) and cation exchange capacity less than 10 cmol(+)kg-1. Mineralogical investigations showed the dominance of micas and smectites in Pedon 1 (P1) and Pedon 2 (P2) and increase of smectites and micas in Bw3 horizon of P3 under strong alkalinity and high silica activity with limited lessivage. The low chemical index of alteration (CIA) in soils further indicated an incipient pedogenesis with a relative proportion of mica-smectite composition. The A-CNK-FM diagram shows abundance of CaO + Na2O + K2O as against Fe2O3+ MgO components under limited leaching environment and chemical weathering. The results of bivariate plot of SiO2 to (Al2O3 + K2O + Na2O) indicated the past weathering which influenced by prevailing arid climate in the region.

Determination of Land Suitability Using Multi Criteria Approach: A Case Study of Bhilwara District Rajasthan

Determination of Land Suitability Using Multi Criteria Approach: A Case Study of Bhilwara District Rajasthan