Yashwant B. Katpatal

Development of GIS-based fuzzy pattern recognition model (modified DRASTIC model) for groundwater vulnerability to pollution assessment

Groundwater is one of the main sources of drinking water in Ranchi district and hence its vulnerability assessment to delineate areas that are more susceptible to contamination is very important. In the present study, GIS-based fuzzy pattern recognition model was demonstrated for groundwater vulnerability to pollution assessment. The model considers the seven hydrogeological factors [depth to water table (D), net recharge (R), aquifer media (A), soil media (S), topography (T), impact of vadose zone (I), and hydraulic conductivity (C)] that affect and control the groundwater contamination. The model was applied for groundwater vulnerability assessment in Ranchi district, Jharkhand, India and validated by the observed nitrate concentrations in groundwater in the study area. The performance of the developed model is compared to the standard DRASTIC model. It was observed that GIS-based fuzzy pattern recognition model have better performance than the standard DRASTIC model. Aquifer vulnerability maps produced in the present study can be used for environmental planning and predictive groundwater management. Further, a sensitivity analysis has been performed to evaluate the influence of single parameters on aquifer vulnerability index.

Impact of over-exploitation on groundwater quality: A case study from WR-2 Watershed, India

The WR-2 watershed is located in the Deccan trap basaltic terrain of Maharashtra State, India. The watershed area incorporates a rich orange orchard belt that requires a huge quantity of water for irrigation. This requirement is mostly met through groundwater, extracted from the shallow aquifers of the WR-2 watershed. However, over the years, excess withdrawal of groundwater from these aquifers has resulted in depletion of groundwater level. The declining trends of groundwater level, both long term and short term, have had a negative impact on the groundwater quality of the study area. This effect can be gauged through the rising electrical conductivity (EC) of groundwater in the shallow aquifers (dug wells) of the WR-2 watershed. It is observed that the long term declining trend of groundwater level, during 1977–2010, varied from 0.03 to 0.04 m per year, whereas the corresponding trend of rising EC varied from 1.90 to 2.94 μS/cm per year. During 2007–2010, about 56% dug wells showed a positive correlation between depleting groundwater level and rising EC values. The groundwater level depletion during this period ranged from 0.03 to 0.67 m per year, whereas the corresponding trend of rising EC ranged from 0.52 to 46.91 μS/cm per year. Moreover, the water quality studies reveal that groundwater from more than 50% of the dug wells of the WR-2 watershed is not suitable for drinking purpose. The groundwater, though mostly suitable for irrigation purpose, is corrosive and saturated with respect to mineral equilibrium and shows a tendency towards chemical scale formation.

Urban Spatial Decision Support System for Municipal Solid Waste Management of Nagpur Urban Area Using High-Resolution Satellite Data and Geographic Information System

Solid waste generation is undoubtedly related to anthropogenic activities and culture. The management of solid waste becomes more challenging in densely populated heterogeneous cultures in developing countries. Proper management of solid waste may be done only after proper characterization of the waste, which varies with anthropogenic activities and population densities, which in turn are related to land use patterns of urban areas. The spatial characterization of waste in urban areas is mandatory for designing management strategies, including waste segregation, collection, transportation, and disposal. In this paper, solid waste is characterized within the Nagpur urban area, and coefficients are generated through regression analysis for spatially estimating quantities of waste components for various land use classes. Satellite data are used to generate population indexes for various land use classes. Simple linear regression analysis is used to generate indexes for computing physical and chemical characteristics of solid waste for residential land use classes. Based on the indexes generated, a spatial representation of solid waste components using a geographical information system (GIS) is obtained. This spatial representation acts as a tool to understand the status of parameters within any urban area. A spatial decision support system has also been developed, which can assist a decision maker involved in management of solid waste in urban areas.

Application of geospatial technologies for environmental impact assessment: an Indian Scenario

Geospatial technology is an essential component of the Environmental Impact Assessment (EIA) process, as environmental resources are directly affected by changes in the shape and extent of the proposed disturbance. With the use of spatial techniques like remote sensing, Geographical Information Systems, and Global Positioning Systems, EIA has enhanced substantial viewing, movement, query, and even map‐making capabilities. However, one of the main challenges is to have access to the most up‐to‐date and accurate geospatial data and interpretations. With an emphasis on using geospatial data in particular, the value of the information resource is far higher than is generally available with text and numeric information. This paper focuses on discussing the application of geospatial tools in environmental monitoring and the effective analysis of the natural resources for developmental planning, policy formulation, and decision‐making. Several specific relevant applications of geospatial tools to integrate EIA are presented in the context of an Indian scenario. Applications have included monitoring of natural resources (air, water, land, etc.), ground‐level ozone, soil erosion, study of sea‐level rise due to global warming, change‐detection studies, delineation of ecologically sensitive areas using digital‐image analysis and Geographic Information Systems. This study focuses on the possibility of using a proposed spatial‐decision‐support system to conduct EIA, which should make it possible to upload, evaluate, maintain, and report field and analytical data that have been stored in a variety of formats.

A GIS Based Design of Groundwater Level Monitoring Network Using Multi-Criteria Analysis and Geostatistical Method

Groundwater systems are dynamic and hence, an effective and optimally designed groundwater level (GWL) monitoring network is very essential to minimize monitoring, time and long term expenses. Groundwater scarcity is a big challenge in regions where excessive extraction takes place and GWL monitoring from observation wells (OWs) is the principal source of information. Hence, proper observation and management is necessary to ensure continual availability of water supplies. This study proposes a new and simplified approach using multi-criteria analysis (weighted overlay, analytical hierarchical process, fuzzy) and geostatistical (ordinary kriging) method to design GWL monitoring network of the Wainganga sub-basin, India. Several parameters considered for the analysis include command area (CA) and non command area (NCA), geology, geomorphologic unit, land use/land cover (LU/LC), lineament density, Groundwater level fluctuation (GWLF), recharge, slope and soil media. The study identifies representative or priority zones using multi-criteria analysis and optimum number of OW was determined within the representative zones using geostatistical method. Combination of two approaches helps overcome shortcomings of previously suggested methods of which analytical hierarchical process (AHP)-geostatistical approach gives more accurate results. Sensitivity analysis was carried out to identify importance of each parameter considered for analysis. The study concludes that minimum 80 wells are required for proper monitoring of GWL in the study area. It also reveals that a combination of these two approaches is effective and easy to implement in the regions where data availability is not constrained.

Response of Rainfall and Vegetation to ENSO Events during 2001–2011 in Upper Wardha Watershed, Maharashtra, India

AbstractUnderstanding the variability of rainfall with El Nino Southern Oscillation (ENSO) events at the watershed level is important for water resource managers to discern the pattern of water available for agricultural planning and water and soil conservation. This study was conducted to determine the responses of rainfall and vegetation to El Nino and La Nina events occurring between 2001 and 2011 in the Upper Wardha watershed in Maharashtra, India. Daily rainfall data pertaining to 14 stations in and around the study area were analyzed in conjunction with 16-day global 250-m Normalized Difference Vegetation Index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor abroad the Terra (EOS AM) and Aqua (EOS PM) satellites. Results indicate correlations between ENSO events, rainfall, and vegetation. Both rainfall and vegetation show a positive anomaly during La Nina events and a negative anomaly during El Nino events, but the effects of all events are not the same. A low volum...

Trends and Anomalies in Extreme Climate Indices and Influence of El Niño and La Niña over Pranhita Catchment in Godavari Basin, India

AbstractHydrologic design and planning requires dealing with extremes in precipitation and temperature events caused due to climate change. Long-term trends and variability in 20 extreme climate indices (ECIs) and the influence of El Nino and La Nina over the Pranhita catchment, India are studied for the period of 1951–2013. An overall increase in daily precipitation, more intense rain, and an increase in continuous dry days are observed; however, total rain shows a negative trend. A warming trend is observed with an increase in dry days, warm days, and hot nights, and a decrease in the frequency of cool days and nights. Observed +ve trends for maximum and minimum temperatures are 0.7 and 0.8°C, respectively. El Nino years resulted in −ve anomaly and +ve anomaly was observed during La Nina years for the majority of ECIs. The association between ENSO and yearly temperature indices is found to be weak in comparison with precipitation indices. The study confirmed the multimodal nature of precipitation during...

Cyclical Hierarchical Modeling for Water Quality Model–Based DSS Module in an Urban River System

Environmental systems modeling has always been at the core of gaining insight into the world. Most environmental systems behave very differently from fairly predictable systems because of nonlinearity in approach and behavior. This paper discusses the problem that exists in effectively modeling a multicriterion and nonlinear parametric system. A cyclical hierarchical model was proposed that allows the user to model the effects of various environmental parameters, which not only propagate as forward processes, but also may have dependencies and carryover effects on other primary set of parameters. This is an adaptation from ecological hierarchies for development of parametric modules in an environmental system. This effect was captured by a set of forward and backward carryover functions that are to be generated as process-specific and time-specific functions. The user expresses control over the effect of each parameter on the other and in terms of iterations that are performed within the cyclical hierarch...

Impact of climate change scenarios on hydrologic response of Upper Wardha catchment, Central India

The present study investigates the impact of climate change on response of hydrologic unit based on global climate models in Upper Wardha catchment, India using statistical downscaling tool (SDSM) and the HadCM3 global circulation model (GCM) A2 and B2 scenario data. Changes in extreme climate which affects the society and the environment is studied by seven indices. Future scenarios (2011-2099) developed for TMIN, TMAX and precipitation (PPT) show an increasing trend for TMIN, TMAX and summer season precipitation after calibration (1969-1985) and validation (1986-2001). With general warming over the area, potential-evapo-transpiration showed increase in loss by 5.9% and 6.24% in 2080s. The overall precipitation shows a decrease with respect to base but 54% and 46% rise in summer rains by 2080s. The downscaled variables were used in HEC-HMS model. After calibrating (1988-2005) the model for daily flows (R2 = 0.72) and monthly flows (R2 = 0.81) and validating (2006-2012) for daily flows (R2 = 0.82) and monthly flows (R2 = 0.96), future flow scenarios were generated.

Spatial Analysis of Impact of Orange Cultivation over Groundwater Regime: A Case Study of Kolar Watershed, Nagpur District, Maharashtra

There is a common belief that the area under orange cultivation is increasing day by day in Vidarbha region of Maharashtra. It is posing threat to the groundwater reserve, to the extent of its overexploitation, which is a matter of concern to the state administrators. In view of this, an attempt is made in the present study to analyze temporal variation in the area of orange cultivation for small part of Nagpur district by using high resolution satellite data. The impact of change in the cultivation area of oranges on groundwater regime within the study area has also been analysed. Initially, the change detection study of the area has been carried out for the period 2003 to 2012 which shows that there is drastic reduction in the area under orange cultivation. This has also well reflected in the groundwater assessment as well as in the groundwater table trends of observation wells. The study indicated that a balance between recharge and withdrawal of groundwater has been achieved in the study area and groundwater regime is stabilized over the period of study.