Pravat Kumar Shit

Morphometric Analysis of Kangshabati-Darkeswar Interfluves Area in West Bengal, India using ASTER DEM and GIS Techniques

The aim of the study is to delineate the morphometric characteristics of Kangshabati-Darkeswar Interfluves Area using remote sensing and GIS technology. 10 km2 grids were elaborate to delineate the relief characteristics using Advance Space Thermal Emission and Radiometer (ASTER) data. Drainage networks were automatically extracted from digital aster elevation models. Second order local polynomial (LP) interpolation technique was used to estimate the surface characteristics of the study area using ArcGIS 9.3. The absolute elevation of the study region is extended between 4.0-949.29 m with an average elevation of 484.50 m. The highest relative relief resulted 833.69 m, whereas the average ruggedness index of the study area is recorded as 0.09 per 10 km2 area. The average drainage density of the study area was computed 0.73/sq. km and the highest drainage intensity are recorded as 9.58/10 km2 grid area. The average length of overland flow of the study area was 2.56/10 km2 grid areas. The result of the study highlights an about the spatial distribution of relief and hydrological characteristics which may provide the knowledge to devise and accomplish an appropriate plan to progress agriculture and others allied activities. Hence, from the study, it can be concluded that remote sensing data (ASTER –DEM) coupled with GIS techniques prove to be a competent tool in morphometric analysis and the data can be used for basin or interfluves area management and other hydrological studies in future.

Spatial variability of groundwater quality of Sabour block, Bhagalpur district (Bihar, India)

This paper examines the quality of groundwater of Sabour block, Bhagalpur district of Bihar state, which lies on the southern region of Indo-Gangetic plains in India. Fifty-nine samples from different sources of water in the block have been collected to determine its suitability for drinking and irrigational purposes. From the samples electrical conductivity (EC), pH and concentrations of Calcium (Ca2+), Magnesium (Mg2+), Sodium (Na+), Potassium (K+), carbonate ion (CO32−), Bicarbonate ion (HCO3-), Chloride ion (Cl−), and Fluoride (F−) were determined. Surface maps of all the groundwater quality parameters have been prepared using radial basis function (RBF) method. RBF model was used to interpolate data points in a group of multi-dimensional space. Root Mean Square Error (RMSE) is employed to scrutinize the best fit of the model to compare the obtained value. The mean value of pH, EC, Ca2+, Mg2+, Na+, K+, HCO3−, Cl−, and F− are found to be 7.26, 0.69, 38.98, 34.20, 16.92, 1.19, 0.02, and 0.28, respectively. Distribution of calcium concentration is increasing to the eastern part and K+ concentrations raise to the downstream area in the southwestern part. Low pH concentrations (less than 6.71) occur in eastern part of the block. Spatial variations of hardness in Sabour block portraying maximum concentration in the western part and maximum SAR (more than 4.23) were recorded in the southern part. These results are not exceeding for drinking and irrigation uses recommended by World Health Organization. Therefore, the majority of groundwater samples are found to be safe for drinking and irrigation management practices.

Spatial analysis of soil properties using GIS based geostatistics models

Accurate assessment of the spatial variability of soil properties is key component of the agriculture ecosystem and environment modeling. The main objective of the present study is to measure the soil properties and their spatial variability. A combination of conventional analytical methods and geostatistical methods were used to analyze the data for spatial variability. In November 2014 a total of 32 soil samples were collected in the field through random sampling in Medinipur Sadar block of Paschim Medinipur district in West Bengal (India). Soil properties of pH, electric conductivity (EC), phosphorus (P), potassium (K), and organic carbon (OC) were estimated using the standard analytical methods. A classical ordinary kriging (OK) interpolation was used for direct visualization of soil properties. The spatial distribution of EC, pH, and OC in soil are influenced by structural factors, such as climate, parent material, topography, soil properties and other natural factors. The semivariograms of the six soil properties were fit with exponential curve and root mean square error value is near about zero (0). Finally, spatial distribution and correlation between OC and other soil properties is shown by overlay of maps in GIS environment. The present study suggest that the OK interpolation can directly reveal the spatial distribution of soil properties and the sample distance in this study is sufficient for interpolation.

Vegetation Influence on Runoff and Sediment Yield in the Lateritic Region: An Experimental Study

The lateritic badland topography (Western part of West Bengal, India) is prone to severe erosion, caused by heavy rainfall events of short duration and high intensities. Five catchments were instrumented in order to study the rainfall– runoff process and soil management impact on runoff and/or sediment yield. In the five micro catchments (Rangamati, Medinipur), characterized by a homogeneity of surface geology, a data set of about 43 rainfall–runoff events covering the January 2012 to Sept, 2012 period was generated by field monitoring. Multiple regression analysis is done to define the role of rainfall volume vis-a-vis vegetation cover on sediment yield. The physical and chemical properties of soil were estimated at the initial and final stage of the gully development in the lower gully basin area. Temporal assessment of soil erosion indicated that increase of rainfall volume protracted the whole process of sediment production, and vegetation on the slope delayed that process. Results indicated that the highest spatial coverage of vegetation (73.5%) yield very low amount of soil [basin-I experimental site (Adjusted R2 = 0.56)] whereas, the lowest spatial coverage (5.9%) leads to severe soil loss [(basin-IV experimental site (Adjusted R2 = 0.33)]. Results illustrated that at the initial stage, the percent of sand was maximum in the upper catchment of each gully basin and the concentration of silt and clay is less. Gradually as vegetation starts trapping the sediment, composition of soil changes registering higher percentage of finer particles. Again, the nutrients detached from the upper catchment were arrested by check dams that induced nutrients supply and water storage, which in turn, increased the growth of vegetation. This result proved the significance of vegetation cover to curb soil erosion and it may help the planners and managers to take proper decision for the conservation of soil.

Freshwater fish resource mapping and conservation strategies of West Bengal, India

Explorations and Germplasm estimation of fish biodiversity in the freshwater bodies of India are being gradually updated and analysed with a number of new discoveries though a well-defined figure of existing freshwater fish species at regional and state level remains to be calculated. The freshwater resources of India are currently experiencing an alarming decline trend in term of piscine biodiversity due to several undesired factors and consequences a considerable portion of freshwater fishes have been categorized as Threatened category. West Bengal is now becomes one of the most significant states of freshwater fish producer in India. The research study workout and divide the West Bengal state into six major physiographic divisions along with the help of modern Geoinformatics techniques (ArcGIS 10.2, Google Earth and Global Mapper software for map making purpose). The present study deals with the freshwater fish resource, distribution and biodiversity assessment of entire part of West Bengal. Occurrence of 251 fish species belonging to 15 orders, 50 families have been noted during the study period of 2012–2016. It is evident that the members belonging to Cyprinifomes constitute 37% of the total fish fauna of the river. Fluctuation in occurrence and abundance of the species are influenced by several anthropogenic activities. The demand of proper management of conservation policy is highlights through our research work.

Soil organic carbon mapping using remote sensing techniques and multivariate regression model

Abstract Soil organic carbon (SOC) is an important aspect of soil quality and plays an imperative role in soil productivity in the agriculture ecosystems. The present study was applied to estimate the SOC stock using space-borne satellite data (Landsat 4–5 Thematic Mapper [TM]) and ground verification in the Medinipur Block, Paschim Medinipur District and West Bengal in India. In total, 50 soil samples were collected randomly from the region according to field surveys using a hand-held Global Positioning System (GPS) unit to estimate the surface SOC concentrations in the laboratory. Bare soil index (BSI) and normalized difference vegetation ndex (NDVI) were explored from TM data. The satellite data-derived indices were used to estimate spatial distribution of SOC using multivariate regression model. The regression analysis was performed to determine the relationship between SOC and spectral indices (NDVI and BSI) and compared the observed SOC (field measure) to predict SOC (estimated from satellite images). Goodness fit test was performed to determine the significance of the relationship between observed and predicted SOC at p ≤ 0.05 level. The results of regression analysis between observed SOC and NDVI values showed significant relationship (R2 = 0.54; p < 0.0075). A significant statistical relationship (r = −0.72) was also observed between SOC and BSI. Finally, our model showed nearly 71% of the variance of SOC distribution could be explained by SOC and NDVI values. The information from this study has advanced our understanding of the ongoing ecological development that affects SOC dissemination and might be valuable for effective soil management.

Evaluation of groundwater quality and its suitability for drinking and irrigation using GIS and geostatistics techniques in semiarid region of Neyshabur, Iran

Groundwater is a vital source for drinking and agricultural purposes in semiarid region of Neyshabur area (Iran). The present study assessed the groundwater quality and mapped the spatial variation of water samples in terms of suitability for drinking and irrigation purposes. A total 402 groundwater samples were collected from the field with global positioning system (GPS) from 2010 to 2013 and analyzed for pH, calcium (Ca2+), magnesium (Mg2+), sodium (Na+), potassium, bicarbonate, sulfate, chloride, sodium adsorption ratio (SAR), electrical conductivity (EC), total dissolved solids, and total hardness (TH). A GIS-based ordinary kriging method with best fit semivariogram models was used for preparation of thematic maps of groundwater quality parameters. The results were evaluated and compared with WHO (2011) recommended water quality standard. Results showed that 68.40% of SAR, 25% of Mg2+, 32.62% of Na+, and 1.74% of TH of the total groundwater samples are suitable for the irrigation purpose. Consequently, 55.57% of EC, 89.19% of TDS, 0.75% of pH, and 6.25% of K+ of the total groundwater samples are suitable for the drinking purpose as per the WHO standard. The groundwater quality in the study area is very hard and slightly alkaline in nature. The spatial distribution map of groundwater quality showed 80% of the area suitable for drinking purpose; whereas, 90% of the area demarcated for irrigation purpose.

Soil crack morphology analysis using image processing techniques

The present paper demonstrated an image processing technique of surface soil crack analysis. The geometric features of cracks, such as width, length, and surface area are estimated. These parameters are important, because they influence both the soil hydraulics and mechanics. The crack intensity factor was introduced as a descriptor of the extent of surficial cracking. The correlation analysis indicates that area-weighted mean ratio of soil-crack area to perimeter and index r has a much closed positive relationship with cracks intensity and the area weighted mean of crack fractal dimension declines continuously as the degree of development of soil cracks increases, indicating that the degree of complexity of the soil cracks also gradually decreases. However, traditional visual assessment, which is the primary method in use, is slow and expensive. The present works involve image processing technique for the automatic detection and analysis of cracks in the digital image of a concrete surface.