eChapters

1.1 Water and its Importance

Water has played a crucial role in sustainace of lives of all living beings including animals, plants and human beings in this earth since time immemorial. It is there since the creation of the nature and will probably remain till the destruction of the nature. It is used in multifarious uses including domestic, industrial, agricultural, recreational and many other uses. It occurs in the nature in practically three forms i.e. solid, liquid and gaseous forms. All the three forms are important to living beings; but the liquid form of water is more beneficial. The weight of the water helps in running hydroelectric turbines, the density of water helps in floating the ships, the steam energy produced by heating the water helps to run the locomotives and thus is beneficial in many ways. It is considered as the most important resource of the society. It has become part and partial in our life so that we cannot live without water. That is why water is called as life.

In the Asian and Pacific ‘region, it is China alone which produces the largest quantities of agricultural waste and also crop residues. This is followed by India. From the production of rice, corn and wheat alone 587 million tons of residues are generated per year in China. Maheshwari (2014) has surveyed the proportions of waste that Malaysia generates from the production of rice, palm oil, rubber, coconut and forest products. In Myanmar the crop waste and residues constitute about 4 million tons per year out of which more than half constitutes rice husk.

The possibility of making genetic changes in the laboratory in plants, animals and microbes used in food started almost 10,000 years ago. Along with natural changes taken place during the evolution totally different species have come into existence. This has helped in increased food production with better taste and nutrition. The losses caused by biotic and abiotic stresses from fungi and bacterial pathogens have reduced.

All these methods of utilization and the conversion to useful energies depend on the climate, population density of the area and the basic infrastructure. It is important to work out the market for the products which are produced.
 
Bio-waste management: It needs to take from small actions to the ambitious ones. European Commission proposes to use wastes which could make up to 25% of total energy consumption by 2020. They propose to have directives for the promotion of renewable electricity (Directive 2001/77/EC) and biofuels (Directive 2003/30/EC). The waste production in Europe has gone upto 2 kg per capita per day. Recycling rates are also rising (European Commission, 2017). The Member states must develop a national action plan and outline the national policies to develop existing biomass resources and mobilise new biomass resources for different uses. A European project has studied the amount of renewable energy to be used in 2020. According to them it will be around 195 million tons of oil equivalents (Mton) of biomass which is biodegradable part of MSW. This will be 20% of renewable energy target. It has also been estimated that the amount of bio-energy from the MSW will be 20 Mton, which would account for around 7% of all renewable energy in 2020. This may be available after composting and anaerobic digestion (Atanasiu, 2010).

3a. Sources and problems of agricultural wastes
3b. Waste Reduction
3c. Waste Treatment
3d. Waste Disposal
3e. Clean Technology

Different Kinds of Agricultural Wastes
Table 1: Common Hazardous Wastes: Community Source

After the agricultural activities a number of by-products are obtained and these are known as agricultural waste. These include residues of different crops like stalks, straws, leaves, roots, husks and shells. The animal waste is in the form of manure. All these agricultural wastes are free of cost however; they can be utilized as an important resource (Lionel and Arnold, 1931). Agrawal (1998) has mentioned India as the final dumpyard. The wastes obtained from various resources can be converted into heat, steam, charcoal, methanol, ethanol, biofuel, compost, energy, biogas, construction and high valued chemical compounds. Many times these agri-industrial wastes are not completely utilized and either they rot in open areas or are burned in the fields.

In today’s times, a lot of innovation has come into agriculture. This very hard occupation requires an amalgation of farmers with the scientists. From the rural areas after education the technocrats are moving to the cities and this is creating a great loss to the agriculturists. As the population is growing so is the demand for food. Due to shortage in the storage systems the amount of wastage has increased a lot. It is an important aspect to be looked into. A lot of waste material is seen in the vegetable markets, city markets and near the slums. This causes a lot of pollution and spoils the environment. It is important to know why is it increasing and why the facilities for wastes do not exist.

Vegetation is a key component in hydrologic modeling. Transpiration, a component in hydrologic cycle, is contributed by vegetation. Most of the hydrologic model thus includes vegetation as a parameter. For accurate and appropriate model output, first requirement is good quality data. Most of the time, the data on vegetation is confusing, as in literature various researcher have used different values for common vegetation parameters. Here some common parameters of some important crops, which yield good quality results, are given.

Kharif crops are generally sown during last week of May and first week of June, while rabi crop are sown during last week of November and first week of December. But this period will vary from region to region as well as depends on variety of crop.

More information, more accurate and timely decision. In present high tech world, the more information you have it is easier to make an accurate decision. The information comes in many different ways, from reports to digital photos. A new way to analyze data is a geographic information system (GIS). GIS allows to bring all types of data together based on the geographic and locational component of the data. GIS is a useful tool for seeking innovative ways to solve the problems.

9.1 What is GIS?

A geographic information system (GIS) is a system designed to capture, store manipulate, analyze, manage and present all types of geographically referenced data. GIS can be defined as a computer-based system for digital entry, storage, transformation, analysis and display of spatial data. A geographic information system integrates hardware, software and geographically referenced data for further analysis. GIS allows users to interpret the georeferenced data in many ways that reveal relationships, patterns and trends.

Remote sensing is emerged as an important application of science in all fields for collection of information from a far. This chapter describes the fundamental concepts of remote sensing, electromagnetic radiation (EMR), the interactions between EMR and earth surface features, satellites etc.

8.1 What is Remote Sensing?

Remote sensing is nothing but acquiring information about an object without touching the object itself. In other words, remote sensing is the acquisition of information about an object or phenomenon, without making physical contact with that object. In present era, the term generally refers to the use of aerial sensor technologies to detect and classify objects on the Earth by means of propagated signals. As remote sensing is obtaining information about objects without making physical contact with them, remote sensing can be described as ‘reconnaissance from a distance’, ‘teledetection’ or a form of the common phrase ‘look but don’t touch’.

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.

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

Data mining is a powerful technology which helps in extracting future trends and behaviour from large databases. Thereby it helps decision makers to make knowledge-driven decisions. One common form of real-world data is time series. The suitable models are required to analyze time series data. This chapter provides a short introduction to stochastic system, uncertainty, basic statistics time series analysis and some stochastic models.

In this era of computer, mathematical models become integral part of hydrologic studies due to advancement in soft technology. But question always arises as ‘Why should modeling?’ It was well expressed by Rosenblueth and Wiener (1945) as

No substantial part of the universe is so simple that it can be grasped and controlled without abstraction. Abstraction consists in replacing the parts of the universe under consideration by a model of similar but simpler structure. Models, formal or intellectual on the one hand, or material on the other are thus a central necessity of scientific procedure.

Modeling is heart of hydroinformatics. Simulation modeling became integrated part of modern science to justify feasibility of selected option among various competitive alternatives. Simulation modeling is a tool to evaluate the performance of a system, existing or proposed, under different configurations of interest and over long periods of real time. This chapter describes basic concepts, model simulation, model variables, modeling process, model performance etc. in brief.

Data collection is a tedious and time consuming work, particularly from remote places. So many times the collected data is noisy. But data is the base for future planning and management of water resources. Planning based on noisy data could lead to failure. The modern data collection and subsequent control system i.e. telemetry and SCADA, are introduced in this chapter.

Water is a social requirement. Society now become aware about it’s dependence upon water and hence realized the importance of water in sustaining not only the development but also life. Water: too little, too much, too dirty; is general scenario in the world. But with increase in population water become limiting resource and is becoming scarcer and scarcer day by day. As water become scarcer commodity, the users (stakeholders) become more conscious regarding their share in water and ultimately this situation may lead to water conflicts. Earlier water related problems were generally tackled by hydro-engineers, but now in present climate changed scenario these problems go beyond the hydraulics and hydrology. Now a days politicians, ecologists, Non Government Organizations (NGOs), the media and the stakeholders etc are playing a crucial role in decision making in respect to water management issues. Now water projects are designed in reference to social context (Social context means cultural, economic, political, sociological, legal and other such aspects). When social factors are taken into consideration while tackling the water problems, it could not possible to satisfy all involved. Thus it is required to agree upon a compromise solution acceptable to all. Over recent few decades, information and communication technology (ICT) flourishes with great advances. It provides the ways to search for compromise solutions. In this chapter information, hydroinformatics, evolution of hydroinformatics and role of internet in hydroinformatics are discussed.

Introduction

Famous French postmodern philosopher Jean Baudrillard commented on information once. “Information can tell us everything. It has all the answers. But they are answers to questions we have not asked, and which doubtless don’t even arise.” This seemingly paradox observation fits contemporary Internet age perfectly. Internet is a vast repository of information of all kinds and is bursting on its seams. The seeker needs to search with monumental grit and determination to have a full handle on the range of information available for any particular search. A search string for GIS returns more than 1185000 results, in a mere 0.26 seconds. Recommending a comprehensive resource list is not possible as new material gets continually added by way of additions and updates. However for a beginner the list given below will be handy. The flip side is GIS has innumerable resources and a broad range of content. Software vendors, organizations, individuals, universities and companies have provided a wealth of information. The readers are exhorted to make use of the materials to improve their understanding of the subject.

Introduction

The term geographic information systems (GIS) has come to mean, variously, an industry, a product, a technology, and a science. As such, the term invokes different perceptions dependent on whether the viewpoint is that of the software developer, the system marketer, the data provider, the application specialist, or the academic researcher, among others. A newcomer to the field is likely to be bewildered by the multiple uses of the same term, or, seen alternatively, different definitions of the same term. For instance some find it distasteful to use of the conventional acronym GIS and prefer Geospatial Technology. With all the variety of perceptions predicting the future of GIS is a cumbersome business. The most certain inference we can gain from the available trends is, it is growing and is poised for further growth. Geotechnology along with Nanotechnology and Biotechnology is considered as of the three most promising growth industries for the near future.

Topology building

Boolean operations

Query and model building

Customization

Introduction

At human scales, the world consists of objects, events, processes, and a background environment. Cognition is about knowledge: its acquisition, storage and retrieval, manipulation, and use by humans and other intelligent creatures. Cognition includes sensation and perception, thinking, imagery, reasoning and problem-solving, memory, learning, and language. Cognitive structures and process are part of the mind, which emerges from a brain and nervous system inside of a body that exists in a social and physical world. Spatial cognition deals with the cognition of spatial properties of the world, including location, size, distance, direction, shape, pattern, movement, and inter-object relations. GIS design will be largely influenced by spatial cognition.