eChapters

Detailed information on tectonic evolutionary history of the Bay of Bengal is presented followed by elucidation of these characteristics towards tsunamigenesis in this chapter. The Andaman-Nicobar Island Arc (ANIA) is situated on a 1000 km long plate margin and represents a key region in the developing oceanic crustal area of Bay of Bengal. Frequent earthquakes including the tsunamigenic earthquake of 26th December 2004 off the coast of Sunda take place in this region. The subduction of Indian plate under Myanmar-Thailand plate drives formation of chain of Andaman-Nicobar group of Islands. These oceanic crust formation, subduction and arc formation are all seismigenic and generate shallow focus earthquakes in the Bay of Bengal. It is also observed that the seismicity is decreasing as the bathymetry increases towards SW of the Bay of Bengal. Thus, in long term, the slow accumulation of stress as tectonic plates converge may result in many more earthquakes in this region. After a dormancy of over 100 years, the Barren Island volcano renewed its activity following recent earthquakes. The seismic activity along the Andaman-Nicobar trench is continuing with earthquakes of magnitude varying from 4.8 to 7.2 Richter scale. All these observations suggest resurgent and intense tectonic and volcanic activities due to which allied hazards such as tsunami may take place in future.

INTRODUCTION

The evolving Earth, depending on its heat flow pattern in the mantle throughout geological time, had passed through stages, which are diagnosed through characteristic geodynamic signatures. This chapter focuses on a very active region in the crust, namely, the Andaman-Nicobar Island Arc (ANIA) to recognize such signatures and decipher relative safety of surrounding regions including east coast of India. As similar active arc systems such as Sunda Arc & Japan Arc generate volcanic, seismic and tsunami hazards, understanding the ANIA would be of help assess safety of surrounding regions. Abundant geoscientific literature exists on the northern part of the Indian plate, which is undergoing compressive stress since collision between the Indian and Eurasian plates about 55-45my. However, the behavior of remaining part of the Indian plate underneath the Indian Ocean is still sparcely studied. Owing to these reasons, this chapter attempts to fill the gap in our understanding as well as to assess the implications of renewed phases of geohazard occurrences including that of catastrophic earthquake and tsunami of 26^th December 2004.

Abstract

This study was conducted at Directorate of Cashew Research (DCR) Puttur, D.K., Karnataka during 2007-12. In this study, a methodology was standardized to find the area under cashew, barren areas and other areas for expanding cashew cultivation with remote sensing. It was found that the images pertaining to the month of November was best for classifying cashew since the colour of cashew leaves changes during that period. Also, the LISS III images were found to be good for identifying cashew. It was not possible to differentiate between cashew seedling area and cashew graft area using LISS III or LISS IV images. A spatial database of soil moisture was prepared for the irrigation scheduling in cashew and a spatial database of major nutrients was prepared for the site specific nutrient management in cashew gardens. A spatial database of land slope and stream orders was prepared using GIS and suitable soil and water conservation interventions were suggested for the selected area.

Keywords: Cashew, GIS, remote sensing

Introduction

Natural Disasters are inevitable, and Indian subcontinent is prone to all type of Natural Disaster either it is flood, drought, cyclone, earthquakes, tsunami or forest fires etc. Disasters can be classified in several ways. A possible sub-division of disaster is: (i) Natural Disasters; (ii) Human made disasters; (iii) Human induced disasters. Another sub-division is related to the main controlling factors leading to a disaster. These may be meteorological, geomorphological/geological, ecological, technological, global environmental and extra terrestrial. Another useful distinction that can be made between disasters is regarding their duration of impact and the time of forewarning. Some disaster strikes within a short period with devastating outcomes; others have a slow onset period with equally or more serious repercussions. According to the available statistics 60% of the total area of Indian subcontinent is venerable to seismic activity of varying intensities, 16% of the country’s total area is drought prone. In India 68% of total sown area of the country is drought prone. Coastal areas of India is exposed to tropical cyclones, tsunami in recent years and among all the disaster occur in the country, River floods are the most frequent and often the most devastating.

Abstract

Soil Resource Appraisal helps in characterizing the existing land resources, assessing their suitability for various land uses and then helping the user to prepare a rational land use plan suitable for the integrated development of the area. Application of Remote Sensing (RS) and Geographical Information System (GIS) helps not only in the characterization of the resource base, but also in the generation of various thematic maps and preparation of land use and action plans for effective implementation of various developmental plans at farm level.

Keywords : Soil Resource Appraisal, Land Use Plan, Farm level Developmental Plans

1.0 Introduction

A thorough knowledge and understanding of soils is basic to the development and management of agricultural resources. About 100 years ago, man began systematic study of soils in the field and tried to separate, classify and map their geographic distri­bution. Today we have sufficient knowledge about soils; however the characterisation, classification and mapping of soils is still tedious, time consuming and costly affair. Therefore the need for adopting new and more rapid and accurate methods of mapping soils has resulted in the use of satellite images with image interpretation techniques for soil survey and map­ping.

In India for the country as a whole, soil and other land resources information is available at 1:1 M scale, which was generated from the state level mapping done at 1:250,000 scale under the Soil Resources Mapping Project of India during the period from 1986 to 1995. This information is of general nature and useful for planning on a wide canvas and not particularly useful for farm or watershed level planning in the country. For site-specific needs and for developmental works at watershed level, we need detailed farm level database at 1:10,000 scale. Once this type of information is generated at village/watershed level, this will be useful for identifying site specific constraints, generation of area and site specific agro technologies, land-use options based on soil site suitability assessment, wasteland identification, identification of prime farm lands and farm clusters for zoning and Strategic planning, preparation of farm level development plans by line departments and proactive advice and technology transfer to farmers.

ABSTRACT

In Tamilnadu majority of the people are engaged in agricultural work and they mainly depend upon the water resources. But at present both surface and subsurface water has become deficient because of over exploitation. Since last few years, conventional methods were employed to improve the surface and subsurface water conditions. But these methods provide less accurate result and consume more time. So to improve the conditions modern tools, such as remote sensing and GIS are being used to identify the ground water potential zones in Tamilnadu. It provides accurate resulst and consumes less time.

A project was carried out in Gadilam lower sub basin which falls in the part of Cuddalore District, Tamilnadu. The IRS 1D imagery was collected and interpreted using image processing software and Geo media GIS Software in conjunction with collateral data to prepare Hydro geomorphology, land use, geology and lineament maps Field checks were made and transferred the field data on the base map. By application of overlay analysis of the above thematic maps, using GIS techniques, the recharge zones were identified.

The satellite image mosaic map of Gadilam lower sub basin was generated to identify ground water potential zones. Average monthly rainfall data for the past 50 years were collected. Using Remote sensing and GIS techniques, the thematic maps such as Geology, Geomorphology, Soil, Drainage, Land use, Lineament zones have been generated for this study. Geophysical survey was also conducted in various locations and the aquifer parameters were measured. Details related to land and water resources, cropping pattern, water levels and water qualities from PWD ground water division, land use and well censes data of villages from village Administrative Officer, tank details from PWD were collected and analyzed

After analyzing the various thematic maps, they were finally overlaid. Thus the groundwater potential zones of Gadilam lower sub basin was identified.

ABSTRACT

The present paper highlights the implication of geochemical strategic tools to choose suitable site selection on the coastal region. Geochemical tools and geomorphological survey have been also deployed to identify the suitable site. The geomorphology of the site A reveals enough fresh water accumulation was found and the two elevated crest and the adjacent trough (low land) with surrounding areas further support the fact. The water quality of this site exposes very good quality (< 200ppm TDS) and the dissolved major anions (HCO3, SO4, Cl) and cations (Ca, Mg, Na, K) concentration are well within drinking water standards. The soil samples are of medium to coarse sand nature showing high porosity (40 to 50%) with mica flakes acting as less permeable in nature. The water quality shows very good in nature and similar to Site A. The soil characters additionally proved good in porosity and permeability (SAR 1.5 to 2.1).

2.1 INTRODUCTION

GIS is a tool that can be used in varied disciplines ranging from civil engineering to business. Remote sensing data is often brought into GIS to have a complete data set in many natural resource application areas. Full capability of GIS is not used widely. Many a times people use GIS only for digitising maps and to do simple query on maps. But it can also be used in modeling, simulation and forecasting, only then one may regard GIS technology is utilised to its full potential. Some GIS softwares handle simple problems for location based services while other complex softwares posses advanced modules to do all types of spatial, network and 3D analysis. Integration of softwares used in natural resources study are being interfaced with GIS to create scenarios.

Remote sensing and GIS technology is useful in the following fields:

Abstract

Remote sensing is the art and science of obtaining information about an object or phenomenon without having any contact with the object concerned. Geographical information system is a tool to create, manage, retrieve and query spatial databases. Remote sensing in conjunction with Geographical Information System (GIS) has wide applications in all spheres of life and especially in agriculture. Specifically, this paper reveals some of the applications of remote sensing and GIS in the field of crop condition assessment viz., crop type classification, crop stress detection, crop yield estimation and pest and disease monitoring.

Keywords : Remote Sensing, GIS, Yield Forecasting, Crop Stress, Pest and Disease Monitoring

1.0 Introduction

Remote sensing is the art and science of obtaining information about an object or phenomenon without there being any physical contact. The information is so collected using a device called a sensor. The sensors are mounted on a platform at an advantageous position. Accordingly the remote sensing is called ground based (sensor is hand held or mounted on mast), air borne (sensor is on a balloon or aero plane) or space borne (sensor is mounted on a satellite). The basic principle in remote sensing is that each and every object has unique reflecting property like human thumb impression and when the solar energy is falling on an object a part of it gets reflected, which carries the information about the object. The reflected light is converted in to reflection percentage of incoming solar radiation. This percentage of reflection can be used to work out the vegetation indices which are surrogate measure of crop condition.

Geographical Information System (GIS) is software system which enable Collection of large volume of data with spatial relation Integration of data from different source is possible Analyze such data for our requirement Present the data in different formats (maps, table and reports)

Applications of Remote Sensing

The era of satellite remote sensing was open in the 1960s when cameras and electronic sensors were mounted on spacecraft. Nowadays there is a big assortment of satellite systems actively recording information about the Earth. A wide variety of imagery is available from satellites. Both active and passive sensors, operating from the microwave to the ultraviolet regions of the electromagnetic spectrum collect a large amount of information about the earth’s surface every day. Each of the systems vary in terms of their spatial, spectral, radiometic and temporal resolution. Those characteristics play an important role in defining which applications the sensor is best suited for. The main benefits of satellite remote sensing are the following:

Abstract

Any country’s socio-economic development essentially depends on land and water resources. Resource depletion takes place when there is an overstretching due the exploding population, calling for prudent management of the resources. Application of remote sensing and Geographical Information System (GIS) tools in the management of natural resources at different levels including watersheds is quite well known. In addition, applied geoinformatics are also used in research on management of these delicate resources also besides characterization. There is a continuous advent in technology in both hardware and software necessitating updation of application scientist/manager. Once an exclusive tool of elite institutions and government agencies, GISnow became an indispensible part of our day-to-day life. As the urge for information intensifies, new applications of GIS continue to evolve. A concerted effort is needed to develop an information system when vast expanses of natural resources are to be managed and a combination of information tools like remote sensing, global positioning system and GIS always updates the database effectively. However, the cost factor should not hinder the applications at micro level. This necessity calls for attention to popularize free and open sources of software (FOSS) and data (particularly digital elevation models (DEM) and satellite imagery) to put the techniques into use by enthusiasts at village level such that a database at a regional level can be built through participatory GIS. It is in this direc tion the av ailab le li terat ure on appl ied geoinformatics coupled with use of FOSS is reviewed and presented in this article to give an idea as to how an open ended information system could be developed to help the management.

Keywords: Natural resources, management, Remote sensing, GIS, FOSS, DEM

Artificial Intelligence (AI) technology is increasingly used in our everyday lives. It is used in a variety of industries from gaming, journalism/media, to finance, as well as in the research fields from water resources to robotics. In this chapter concept and applications of AI are discussed in brief.

6.1 Historical Background

After World War II, a number of people worked independently on intelligent machines. The English mathematician Alan Turing was the first who explained the concept of intelligent machines through a lecture in 1947. He stated that intelligent machines could be developed by programming computers rather than by building machines. Since late 1950 many researchers are working on intelligent machines, mostly on programming computers

The artificial neural network (ANN), a data driven model, is inherently suited to the problems that are mathematically difficult to describe. An ANN is a flexible mathematical structure that is capable of identifying complex nonlinear relationships between input and output data sets, where explicit knowledge of the internal processes is not available. In this chapter general structure of ANN is described and also explained briefly with a case study.

7.1 What is Artificial Neural Network?

An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous system, such as brain process the information. An ANN is an adaptive (Adaptive means that the system parameters are changed during operation i.e. training phase), most often nonlinear system that learns to perform a function (an input/output map) from data. In more practical term, neural networks are non-linear statistical data modeling tools. They can be used to model complex relationships between inputs and outputs or to find out patterns in the data.

Need for systematic mapping and hazard zonation is emphasized in this chapter. Though prevention of natural disaster is not possible, its destruction could be minimized through implementation of effective hazard management system. With this motive, the coastal region between Tangapatnam and Ovari, Tamilnadu State has been classified into various categories of vulnerability based on its response to the 26th December 2004 tsunami. Based on the extent of seawater inundation and coastal geomorphic features, we have assessed the tsunami impact and estimated the behavior of the beaches in case of similar havoc in future. This study had shown that the maximum seawater inundation recorded in the study area is 750m in Colachel and the minimum is 100m in Kadiapatanam, Mandakadu and Vaniakudy areas. Chinnamuttom, Kanyakumari, Manakudy, Pallam and Colachel areas are under high risk.

INTRODUCTION

On 26^th December 2004, tectonic disturbances happened near Sumatra Island with an intensity of 9.3 in the Richter scale wrecked havoc on southwest part of India. In addition to inflicting life and infrastructure loss, the resultant tsunami event had also eroded severely the coastal region and modified topography of beach and shallow coastal regions. It did raise the concern of scientists and emergency planners about the impact of larger earthquake and consequent tsunami should there be any recurrence of such event. Despite becoming aware of tsunami hazard, there has been confusion about areas at risk and areas of safety. This chapter is an attempt to assess the vulnerability of part of Tamilnadu coast based on its geomorphological conditions and the impact of recent tsunami. The hazard maps have been generated and are intended for educational purposes, to improve awareness of tsunami hazards and to encourage responsible emergency planning efforts by illustrating the range of possible tsunami events.

Abstract

Higher temperature and altered rainfall patterns accompanied by extreme weather events are being considered indications of climate change. These factors impact vegetation growth in natural forest, open scrub and in agriculture land. Vegetation index based on satellite data was used to analyse agricultural vulnerability in India to understand impact of rainfall variability. Time-series Normalized Difference Vegetation Index (NDVI) data products obtained from AVHRR (1982 to 2006) and MODIS (2000-2011) were analyzed to assess spatial and temporal variability. Coefficient of variation of maximum NDVI was assessed for the study period and results were corroborated with Standard Precipitation Index (SPI) instead of actual rainfall. Resolution of AVHRR time-series data facilitated study at regional-scale while MODIS datasets with 250m pixel resolution helped in identifying vulnerability at district-level. Study indicated that over 241 Mha areas in the country may not be vulnerable to rainfall variability induced climate change while over 81.3 Mha in arid, semi-arid and dry sub- humid regions may be vulnerable. Study indicated that over 12.1 and 1.81 Mha of Kharif cropland would be mildly and severally vulnerable while 6.86 and 0.5 Mha of Rabi cropland may be adversely affected in a similar manner. Study indicated that length of cropping season was decreasing due to delay in start of season. The paper also presents analysis of variations in SPI and resultant NDVI in typical drought and flood years in the country.

Keywords: MODIS, AVHRR, NDVI, Rainf ed Agricul ture, Vulnerability, Climate Change

Introduction

Climate change and human activities have emerged as significant factors affecting water resources in diverse regions (Kumar et al. 2022; Haddeland et al. 2014). The escalation in human water consumption for domestic and industrial purposes enhanced by the impacts of climate change has resulted in an overall decline in water availability (Liu et al. 2017; Paul et al. 2021). Rising temperatures and altered precipitation patterns directly influence water availability for ecosystems and agriculture potentially leading to greater evapotranspiration rates, intensified rainfall events, and prolonged droughts (Sharannya et al. 2021; Myers et al. 2023). Furthermore, urbanization, deforestation, and agricultural practices alter landscapes, affecting water resources in these areas.

Water shortages pose threats to ecosystem health, and socio-economic development and disrupt agricultural production (Piao et al. 2010). Thus, ensuring sustainable and efficient water usage necessitates accounting for water usage and quantifying it in a changing environment. To comprehensively assess the significance of water resources in the environment, Falkenmark (1995) introduced the concept of blue water (BW) and green water (GW) water, particularly for managing water resources in water-stressed regions. Green water refers to the portion of precipitation that infiltrates into the unsaturated soil layer and is subsequently utilized by plants through transpiration and soil evaporation. In fact, “blue water” represents surface and groundwater flow in rivers, lakes, and aquifers (Abate et al 2024; Sharannya et al. 2021). While numerous studies have investigated the spatial and temporal variation of BW and GW using the Soil and Water Assessment Tool (SWAT) (Feng et al. 2021; Li et al. 2009; Lyu et al. 2019), fewer publications have focused on assessing these variations and uncertainties at the basin scale under varying climate scenarios (Sharma et al. 2023). Hydrological models such as SWAT, serve as valuable tools for simulating past and future hydrological changes in the watersheds using projected climate data. SWAT specifically can simulate both blue and green flows at the watershed scale.

Abstract

Land development in urbanized watersheds poses a potential of increasing storm runoff rates, and therefore increasing the risk of flooding in the downstream areas of a watershed. To investigate the impact of change in land use practices on the watershed hydrology, an hydrological analysis was conducted on Little Kitten Creek watershed located near Manhattan city of Riley county, Kansas, USA. Prior to development, land use types in the watershed included woodland, pasture, and fallow land. However, rapid development has occurred in the watershed in the last ten years. Post development land use practices include commercial development, residential housing, and conservation (woodland and grasslands). Data collected and analyzed included digital elevation model (DEM) of study site, stream network and soil data using ArcGIS (ESRI, 2006) and Arc-Hydro Software (Maidment, 2000). Watershed characteristics such as slopes, channel length, circularity ratios, and drainage density were also computed. The delineated watershed boundary, stream segments and soil data layers were over laid to produce soil maps. Time of concentration (Tc) was determined for the pre and post development conditions in the watershed using seven different methods. The time of concentration values computed using Kerby, Federal Aviation Agency, Kinematic Wave and NRCS (SCS) methods found more reasonable compared to the remaining three methods used.

These computed time of concentration values were observed to be shorter for the post-development condition when compared to the pre-development condition of the watershed. The reduced time of concentration in the post development condition is attributed to increase in percentage of impervious areas due to increased residential development in the watershed; therefore increased rates of runoff in the watershed are expected.

Keywords: Rezoning, Time of Concentration, DEM, Kinematic Wave, Drainage density, Circularity ratio.

Abstract

Coastal aquifers are the sources of freshwater which are being over extracted due to increase in population, agriculture and industrial activities. This over exploitation has resulted in decline in groundwater level and intrusion of sea water into the coastal aquifers making it unfit for human utilities. An attempt has been made in the coastal tracts of Pondicherry region using Electrical resistivity imaging. The survey has been attempted in six locations spread thought the study area and the interpretation has been attempted by RES2DINV software. The profile length attempted was between 150 to 300 m with electrode spacings between 5 to 10 m. The apparent resistivity ranges between 0.1 to 1183 & ohm. Sea water intrusion was prominent along the northern parts of the study area and lower resistivity isolated in kirumambakkam has been interpreted as salinity due to the presence of clay minerals. In nallavadu saline intrusion has been identified at shallow depth.

ABSTRACT

A watershed is a topographically delineated area that is drained by a stream system, i.e. the total land area above some point on a stream or river that drains past that point. The watershed is a hydrologic unit that often is used as a physical – biological unit and a social – economic political unit for the planning and management of natural resources. Remote Sensing (RS) and Geographic Information System (GIS) techniques can be used effectively to generate the land use/land cover for evaluating the changes in an area. Conventional methods of runoff measurements are not easy for inaccessible terrain of Tamilnadu. Remote sensing technology can augment the conventional method to a great extent in rainfall-runoff studies. In this study, SCS Curve Number technique modified for Indian condition has been used for generation of CN for an ungauged watershed. A sub watershed of Manimuktha watershed is considered as study area. The daily rainfall data of Virudhachalam rain gauge station is collected and used to predict the daily runoff from the watershed using GIS based Soil Conservation Service -Curve Number (SCS – CN) method (USDA, 1972). Monthly and annual runoff values are obtained from the daily runoff values of the watershed. Base map, Soil map and Land use map of the study area are prepared by using Remote Sensing data and Survey of India (SOI) toposheets. PC Arc/Info GIS software is used for analysis.

Industrial revolution took place in England during the period of 1760-1830. Accordingly, the production prior to demand was introduced. Many countries all over the world adopted industrial policies favouring industrial sector to achieve the fast development of the nation. Government of India also contributed its efforts in the same direction and issued the industrial policy of 1948, 1956, 1977 and so on making several financial and non financial facilities available to have substantial growth and development of industries in particular and nation in general.

Under the name of globalization and making the economy internationally competent, India took a revolutionary decision to follow new industrial policy 1991 opening the doors for investment from foreign countries and private sector even. In addition to this economic reforms have been adopted and advocated for the sake of national development. Three ‘D’ programme consisting of devaluation, decontrol and disinvestment, were also put on the national agenda, to achieve the set targets.

Instrumental methods of chemical analysis are the quantitative methods of analysis that use, as principal measuring devices, instruments other than those employed in conventional gravimetric and volumetric determinations.

The main basis for this method of analysis is the physical property of any particular element or compound being analyzed. These properties include: