This book provides an innovative, realistic and reliable solution to the common problem of Indian water and energy sector due to the onset of the Impact of Climate Change and Large-Scale Urbanization. Twelve Case Studies and One Review Paper that were included in this book depict the way soft computation techniques, simulation and decision-making framework can optimize the best solution from multiple solutions to the problems of water and energy management which corresponds to a novel symbiotic and synchronous nexus between water and the energy sector. All the studies included in this book are collected from all parts of India. The selected studies utilized the latest technologies like Multi-Criteria Decision Frame Work, Neural Networks and Nature-Based Optimization techniques to achieve diverse objectives from the prediction of climatic parameters to yield from ungauged watershed to performance optimization of Water Treatment Plant, Hydropower as well as futuristic alternative energy systems like Wave to Power Plants.

This book highlights the application of nature-based algorithms in natural resource management. The book includes the methodologies to apply what natural flora or fauna do to optimize their survival. The same technique was used to optimize renewable energy generation from water resources, maximization of profit from crop harvesting, forest resource management and decision-making studies. These studies can be used as an example for finding solutions of the other maximization or minimization problems which are common in natural resource management.

This book highlights the application of Geographical Information System (GIS) and nature based algorithms to solve the problems of water and water based renewable energy resources. The irregularity in availability of resources and inefficiency in utilization of the available resources has reduced the potentiality of water and water based renewable energy resources. In recent years various soft computation methods (SCM) along with GIS were adopted to solve critical problems. The book collects various studies where many SCMs were used along with GIS to provide a solution for optimal utilization of natural resources for satisfying the basic needs of the population as well as fulfilling their burgeoning energy demands. The articles depict innovative application of soft computation techniques to identify the root cause and to mitigate the uncertainty for optimal utilization of the available water resources. The advantage of SCM and GIS were used to maximize the utilization of water resources under cost and time constraints in face of climatic abnormalities and effect of rapid urbanization.

As climate change takes hold, there is an ever-growing need to develop and apply strategies that optimize the use of natural resources, both on land and in water. This book covers a huge range of strategies that can be applied to various sectors, from forests to flood control. Its aim, as with resource management itself, is to combine economics, policy and science to help rehabilitate and preserve our natural resources.

Beginning with papers on carbon sequestration, including the practice of artificial desertification, the topics move on to cover the use of distributed modeling and neural networks in estimating water availability and distribution. Further chapters look at uncertainty analysis applied to the spatial variation of hydrologic resources, and finally the book covers attempts at estimating meteorological parameters in the context of hydrological variables such as evapo-transpiration from stream flow.

Within the next decade, the effects of climate change will be severe, and felt by ordinary human beings. This book proposes a raft of measures that can mitigate, if not reverse, the impact of global warming on the resources we have all come to depend on.

This book provides an innovative, realistic and reliable solution to the common problem of Indian water and energy sector due to the onset of the Impact of Climate Change and Large-Scale Urbanization. Twelve Case Studies and One Review Paper that were included in this book depict the way soft computation techniques, simulation and decision-making framework can optimize the best solution from multiple solutions to the problems of water and energy management which corresponds to a novel symbiotic and synchronous nexus between water and the energy sector. All the studies included in this book are collected from all parts of India. The selected studies utilized the latest technologies like Multi-Criteria Decision Frame Work, Neural Networks and Nature-Based Optimization techniques to achieve diverse objectives from the prediction of climatic parameters to yield from ungauged watershed to performance optimization of Water Treatment Plant, Hydropower as well as futuristic alternative energy systems like Wave to Power Plants.

This book highlights the application of Geographical Information System (GIS) and nature based algorithms to solve the problems of water and water based renewable energy resources. The irregularity in availability of resources and inefficiency in utilization of the available resources has reduced the potentiality of water and water based renewable energy resources. In recent years various soft computation methods (SCM) along with GIS were adopted to solve critical problems. The book collects various studies where many SCMs were used along with GIS to provide a solution for optimal utilization of natural resources for satisfying the basic needs of the population as well as fulfilling their burgeoning energy demands. The articles depict innovative application of soft computation techniques to identify the root cause and to mitigate the uncertainty for optimal utilization of the available water resources. The advantage of SCM and GIS were used to maximize the utilization of water resources under cost and time constraints in face of climatic abnormalities and effect of rapid urbanization.

As climate change takes hold, there is an ever-growing need to develop and apply strategies that optimize the use of natural resources, both on land and in water. This book covers a huge range of strategies that can be applied to various sectors, from forests to flood control. Its aim, as with resource management itself, is to combine economics, policy and science to help rehabilitate and preserve our natural resources. Beginning with papers on carbon sequestration, including the practice of artificial desertification, the topics move on to cover the use of distributed modeling and neural networks in estimating water availability and distribution. Further chapters look at uncertainty analysis applied to the spatial variation of hydrologic resources, and finally the book covers attempts at estimating meteorological parameters in the context of hydrological variables such as evapo-transpiration from stream flow. Within the next decade, the effects of climate change will be severe, and felt by ordinary human beings. This book proposes a raft of measures that can mitigate, if not reverse, the impact of global warming on the resources we have all come to depend on.

This Brief highlights a novel model to find out the feasibility of any location to produce solar energy. The model utilizes the latest multi-criteria decision making techniques and artificial neural networks to predict the suitability of a location to maximize allocation of available energy for producing optimal amount of electricity which will satisfy the demand from the market. According to the results of the case studies further applications are encouraged.

Hydropower is found to be one of the most reliable and inexpensive options for renewable energy which was now widely been adopted by many countries to substitute fossil fuel sources. This Brief highlights the impact of climate change on hydropower plants, especially on the turbine design, as turbines are responsible for optimal conversion and regular energy production. The vulnerability of turbines is analyzed with the help of Artificial Neural Networks, followed by Multi Criteria Decision Making methods for development of intelligent indices to represent the level of vulnerability of turbines due to the change in climate.

This Brief presents the impact of climatic abnormalities on hydropower potential of different regions of the World. In this regard, multi-criteria decision making and neural network are used to predict the impact of the change cognitively by an index. The results from the study show that the hydro-energy potential of the Asian region is mostly vulnerable with respect to other regions of the World. The model results also encourage further application of the index to analyse the impact of climate change on potential of hydro-energy.

This Brief presents the multi criteria decision making (MCDM) techniques like Fuzzy Analytical Hierarchy Process (AHP) and Fuzzy Analytical Network Process (ANP) to find out the importance of the influencing factors to develop the Climatic Vulnerability Index (CVI) that will represent the vulnerability of the Hydro-Power Plant (HPP) to climatic abnormalities. The cognitive ability of neuro-genetic modeling is applied to minimize CVI so that the conditions required to reduce the effect of climate change on HPP can be identified. The results from the study are found to be encouraging. The scarcity and pollution potential of conventional sources of energy has enforced scientists worldwide to look for efficient, flexible, cost effective but reliable alternative energy resources. Among many available options the energy extracted from water was found to be the least expensive, most flexible and moderately reliable renewable energy source which has the potential to replace the dependency on conventional fuels.

The increase in GHG gases in the atmosphere due to expansions in industrial and vehicular concentration is attributed to warming of the climate world wide. The resultant change in climatic pattern can induce abnormalities in the hydrological cycle. As a result, the regular functionality of river watersheds will also be affected. This Brief highlights a new methodology to rank the watersheds in terms of its vulnerability to change in climate. This Brief introduces a Vulnerability Index which will be directly proportional to the climatic impacts of the watersheds. Analytical Hierarchy Process and Artificial Neural Networks are used in a cascading manner to develop the model for prediction of the vulnerability index.

The uncontrolled utilization of natural resources to supply to the water demands of the ever-growing population has brought about worldwide scarcity. The supply shortage has resulted in conflicts between countries, created prolonged drought, closing of industrial units, shifting of local inhabitants etc. The abnormality in climatic patterns due to global warming has only enhanced the uncertainties. Unregulated discharge of waste water into fresh water resources is also polluting the available water resources and making them non-utilizable. That is why the discrepancy between water supply and demand is slowly but steadily becoming a problem, which may lead to conflict and inequality all over the world. The present investigation is an attempt to find the impact of urbanization in the face of climatic uncertainties on water shortage or scarcity. How is climate responsible? What urbanization factors have an influence on the extent of shortages? What is the role of the socio-economic status of the inhabitants? Industrialization? Consumption pattern? Each of the causes and effects were analyzed with the help of data from a climate model, which was then fed into a hydrologic model. The hydrologic output data was then put into various other novel simulation platforms to predict the uncertainties that can be caused by urbanization in various sectors of the regions of interest. The impact was calculated based on IPCC recommended climatic and five distinct urbanization scenarios. The study results will help to predict what is in store of those living in the developing countries. Possible mitigation measures are also discussed."

This book highlights the application of nature-based algorithms in natural resource management. The book includes the methodologies to apply what natural flora or fauna do to optimize their survival. The same technique was used to optimize renewable energy generation from water resources, maximization of profit from crop harvesting, forest resource management and decision-making studies. These studies can be used as an example for finding solutions of the other maximization or minimization problems which are common in natural resource management.

The present study has attempted to apply the advantage of neuro-genetic algorithms for optimal decision making in maximum utilization of natural resources. Hydro-power is one of the inexpensive, but a reliable source of alternative energy which is foreseen as the possible answer to the present crisis in the energy sector. However, the major problem related to hydro-energy is its dependency on location. An ideal location can produce maximum energy with minimum loss. Besides, such power-plant also requires substantial amount of land which is a precious resource nowadays due to the rapid and uncontrolled urbanization observed in most of the urban centres in the World. The feasibility of such plants also depends on social acceptance as well as the level of environmental casualty and economic benefit, all of which is also spatially dependent. Decision making algorithms are applied to identify better solution if a problem has more than one alternative explication. Nature based algorithms are found to be efficient enough to catalyze such kind of decision making analysis. That is why the present study tries to utilize nature based algorithms to solve the problems of location selection for hydropower plants. The study employed six different types of nature based algorithms to select one of the locations among many available for installation of hydropower plant in the North Eastern part of the Indian subcontinent. The locations are selected based on their in stream resources and included in the decision making as alternatives. A methodology of criteria selection, determination of weightage and applications of bioinspired algorithms are adopted to produce utmost exertion of the available natural resources with minimum hostility and wastage of the same.