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The present study represents the impact of marble mining and processing units on the quality of ground water in the Rajasamand district of Rajasthan state. For this work various water sampleswere collected from surrounding areas of the mining hub covering all the tehsil namely- Rajasmand, Amet, Bhim, Deogarh, Khamnor,Kumbhalgarh, and RailmangraofRajasamd district. The sample were analysed for various Physio- chemical parameters like-Electrical Conductivity(EC), pH, Total Hardness (TH), Dissolved Solids-Total (TDS), Sodium (Na+1) Potassium(K+1), Calcium (Ca+2), Magnesium (Mg+2), Chloride (Cl-1), Sulphate (SO4-2), Carbonate (CO3-2 ), Bicarbonate (HCO32), Nitrate(NO3-1) , Fluoride (F), the result of water quality parameters was compared with IS:10500-2012 drinking water specification. The finding of results indicates that the level of the certain parameters like TDS, TH, Ca, Mg, Na, K, Cl, NO3, andF exceed the limits of ground water stipulated by Bureau of Indian Standards (BIS). As per the observations, we must say that it may be possible that one of the egregious sourcesto polluting ground water in the region is marble mining and its allied activities. The present study is based on the sample collected and tested in the laboratory and it is an attempt to determine the physio- chemical characteristics of ground water in the marble mining area of the Rajasamand district in Rajasthan state of India.

Wildfire is one of the complex and damaging natural phenomena in the world. Wildfires pose an enormous challenge to predict and monitor complicated integration chemistry with the physical aspects of solid-gas stage combustion and heat transmission spatially diverse vegetations, topography, and detailed time and space conditions at various spatial and time scales. The research community has greatly enhanced its efforts in the last 25 years to better understand wildfires by improving observation, measurement, analysis and modelling. The fast development of spatial data analysis and computer technology has been facilitated. This combination allowed new decision promotion systems, information collection, analysis methods, growth, and existing fire management instruments. In several countries, despite this activity, forest fires remain a serious problem. Factors that raise the world risk of wildfires are climate change, urban-rural migration and the creation of the interface between urban and wildlands. These events demonstrate the tremendous destructive force of wildfires of great magnitude, sometimes well beyond our concrete containment and control capability. In addition to firefighters, foresters and other organised systems, the scientific community is key to addressing the problems of fire recognition in the countryside. Advances in our understanding of fire-fighting mechanisms and the relationship between fire activity and the natural and constructed environment can lead to successful fire risk decision support systems, the predictions for fire propagation and the reduction of fire risk. The convergence of forest ecosystems and forest fires has become the growing threat posed by human influences and other factors to ecosystems, resources and even human lives. Climate change will change forest fire regimes to enhance forest fire understanding and to build strategies for mitigation and adaptation. The study highlights broad aspects of forest fire in combination with

The effects of climate change are causing large scale human displacements over the past few decades. Climate refugees are putting the biggest challenges to the geophysical biological and social system all over the world. This paper attempts to assess and compare the vulnerability of the climate-induced migrants and regular settlers of selected mouzas of Sagar Island, south 24parganas, India. People are witnessing their lands vanishing under their feet in these constantly sinking and shrinking deltaic estuaries of Sundarban. Findings of LVI and LVI-IPCC analysis indicate that the climate-induced migrant communities are more exposed to climatic variability due to the poor adaptive capacity. Moreover, poor access to food, water, health facilities is making them extremely vulnerable with lower resilience as these mouzas are facing frequent flooding, severe coastal erosion, embankment breaching and higher storm surge on annual basis. The outcomes of this study could be beneficial ineffective on-site risk management and planning propositions.

The present study addresses the objective of mapping the Water Quality Index (WQI) using a geospatial method to ensure availability of healthy drinking water in parts of Madhya Pradesh Guna district. One thousand nine hundred seventy-two water samples were obtained in the presented study and tested in a laboratory to estimate the Physico-chemical and microbial contamination of drinking water. The GIS techniques were used for spatial analysis of WQI for all the blocks of Guna district to classify in very poor, poor, good and very good water quality categories. In the present study, eight parameters, i.e. pH, Turbidity, Total Dissolve Solid (TDS), Fluoride, Chloride, Iron, total Coliform, were taken into consideration in assigning weights. Higher weightage was assigned according to its water quality and vice versa. The overall assessment of the WQI shows that very good category covers 21.69% of the total area exhibited good category covers 5.57%, moderate category covers 7.3% poor category covers 12.53% and very poor WQI category covers 52.91%.

Rainfall and runoff are the significant hydrologic component in the water resources assessment. Numerous methods are available to estimate runoff from rainfall; however, the SCS-CN method remains the most popular and frequently used method as runoff curve number (CN) is a crucial factor of the SCS-CN method and depends on land use/land cover (LULC), soil type, and antecedent soil moisture (AMC). Besides this, various parameters, such as Hydrological Soil Characteristics (HSG), precipitation (P), Potential Maximum Retention (PMR), Antecedent Moisture Condition (AMC), Weighted Curve Number (WCN), are the mandatory inputs to the SCS-CN model. In the results, the daily runoff from the Sind river basin for ten years, i.e., 2005 to 2014, has been used. As a result, the average annual surface runoff calculated for the Sind river basin is 133.71 mm. The total average volume of runoff is 35.04 × 10 8 m 3, representing 17.21% of the total average annual rainfall.

Harvests distinguishing proof from remotely detected pictures is fundamental because of utilization of remote identifying images as a contribution for rural and monetary arranging by the government and private offices. Accessible satellite sensors like IRS AWIFS, LISS, SPOT 5 and furthermore LANDSAT, MODIS are great wellsprings of multispectral information with various spatial resolutions and Hyperion, Hy-Map, AVIRIS are great wellsprings of hyper-Spectral. The technique for current research is choice of satellite information; utilization of appropriate strategy for arrangement and checking the accuracy. From most recent four decades different specialists have been taking a shot at these issues up to some degree yet at the same time a few difficulties are there like numerous products distinguishing proof, separation of harvests of the same sort this paper gives a general survey of the work done in this vital zone. Multispectral and hyper-spectral images contain spectral data about the crops. Good delicate registering and examination aptitudes are required to order and distinguish the class of enthusiasm from that datasets. Various specialists have worked with supervised and unsupervised arrangement alongside hard classifiers and also delicate processing strategies like fuzzy C mean, support vector machine and they have been discovered distinctive outcomes with various datasets.

The rainfall-runoff modeling was carried out using Lacey's and rational formulas to identify the possible locations for surplus precipitation to the groundwater regime with Rain Water Harvesting (RWH) systems, evaluate total recharge potential, and impact on the groundwater regime. Our results found that the total recharge potential created by these artificial recharge systems with injection well is to the tune of 72.07 × 10 4 m3 /annum. These recharge measures will help to improve the groundwater levels as well as control the declining water levels, helps in maintain/improve the existing quality of groundwater, and the quantity of groundwater also increase. While recharging rainfall-runoff water through these RWH systems to the groundwater regime, the overall impact on the groundwater regime will be a positive effect. Groundwater reserves will improve as per the water level fluctuation method; these effects will change the area's replenishable reserves. This phenomenon of continuous recharge of runoff water to groundwater regime, those blocks are in critical/semi-critical/overexploited maybe help to renovate them into the safe category. It may add an excellent source to the groundwater for excess water consumption for irrigation/domestic/industries/mining users. Moreover, considering the cost of installation and maintenance expenses, these systems are effective and economical. This research provides a scientific approach to arrest the extreme possibility of precipitation runoff during different rainfall events, water conservation with groundwater recharge the studied area and helps to ensure the availability of surface and subsurface water in sustainable in long-term uses even in drought period/deficit rainfall events and help mitigate the flood risk hazards.

Suspended sediment concentration (SSC) information on the coastal waters is necessary for understanding and management of the estuarine environment. It serves as an indicator of coastal erosion and deposition. It is challenging for a macro-tidal estuary like the Hugli with a complex hydrodynamic condition and depth variations to estimate suspended sediment concentration by field observations only. In the present study, we estimated suspended sediment concentration at different depths of the lower Hugli estuary in the post-monsoon season by using Sentinel-2 satellite data. Since SSC is highest in the monsoon months, the image of October 22, 2019 was selected, which was the earliest available cloud-free data. Furthermore, about forty water samples were collected from different depths on the same date and time of the satellite pass for ground truth verification and data calibration. An empirical multivariate regression algorithm was used to demarcate the SSC zones in the image and correlate them with depth variations. MIKE-21 hydrodynamic model was also used to assess the spatial pattern of sediment flow in the Hugli river estuary. Remote sensing and GIS have proved to be a useful framework to estimate the SSC of any water column’s surface layer to overcome the limitation posed by the field measurements alone.

Waterlogging is a complex phenomenon, the severity of which depends on a number of natural as well as anthropogenic factors. The present study pertains to the evaluation of control exerted by various factors, viz geomorphology, relief, groundwater fluctuation, rainfall, catchment area and canal–road network density, on waterlogging in the north Bihar region of Gangetic Plains. Satellite images IRS P6 LISS III acquired in the years 2005 and 2006 were used to map temporal variability in surface waterlogging which revealed a reduction of 52 % in the waterlogging area during the pre-monsoon. The seasonal groundwater fluctuation was examined using 2005–2006 pre- and post-monsoon water level data. It clearly indicated that a large portion of the area was also under highly critical groundwater level occurring at a depth of less than 1 m belowground surface during the post-monsoon periods. The percentage of waterlogged area per square kilometer in each geomorphological unit clearly depicts that the Kosi megafan (Lower), because of a high density of paleochannels, comprises the highest post-monsoon waterlogged area. The Tropical Rainfall Measuring Mission (TRMM) data were analyzed for the period 1998–2009 to examine the spatial variability of rainfall over the entire catchment during the monsoon period. The high incidence of post-monsoon surface waterlogging delineated through satellite data and high average rainfall (>1,100 mm) in the same area indicates a positive relationship between rainfall and surface waterlogging. Waterlogging is more prominent in the lower relief zones, but anomalous relative rise in waterlogging within 40–50 m of relief zone was attributed to anthropogenic factors primarily related to the development of canal network.

In the present study, the multi-temporal satellite images of IRS P6 LISS III were used to map waterlogging dynamics over different seasons. An area of 594.36 km2 (6.75%) and 4.17 km2 (0.04%) was affected by surface waterlogging during pre and postmonsoon season, respectively. The average annual groundwater level fluctuations were calculated using 18 years (1990–2007) pre and postmonsoon groundwater level data to identify the areas which are under groundwater induced waterlogging conditions. The soil map clearly indicates that salinity and sodicity exhibit the highest severity and occur in areas with shallow groundwater levels. The hydrogeomorphical units mapped using IRS P6 LISS III satellite images are flood plain, alluvial plain, paleochannels, and oxbow lakes. The study revealed that 44.65% areas have very good to excellent groundwater resources. The litholog data clearly indicate an alternating sequence of clay and sand in which deep aquifers made up of coarse sand would be best suited for ad...

Historical to recent spatial variability in surface waterlogging was evaluated using a topographical map of 1925 and satellite images of 1975, 1988, 1999 and 2006. A visual satellite image interpretation technique was used to delineate waterlogged areas and associated infrastructure details. Areas of 31, 73.89, 163.86, 143.61 and 102.59 km2 were found to be affected by surface waterlogging during 1925, 1975, 1988, 1999 and 2006, respectively. A sharp increase in waterlogging from 1925 to 1975 is attributed to the functioning of irrigation projects in the region. The very high areas under waterlogging during 1988 and 1999 reflect intensification of agricultural activity. A substantial decrease in waterlogging during 2006 is attributed to the implementation of government wasteland reclamation measures. The area statistics of waterlogging computed for the buffer zone along select features showed that the maximum waterlogging occurs along canals and railways followed by rivers and the least along roads.