Center for Environmental Sciences & Engineering

<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

The main thrust of this book is focused on addressing the various interrelated processes, analysis and activities bearing upon sound river management. River basins are complex systems. They are open systems with sometimes ill-defined boundaries. It refers to various aspects essential to achieve a sustainable development of river basins, including water demand and river management. Intensified erosion, land water degradation and stream flow pollution which call for appropriate river restoration and training measures. A viable theory for river management must reconcile the various processes that occur at different scales in order to develop a knowledge base by synthesizing research and field studies results. The book is intended to augment the knowledge base of behaviour of rivers and analyse the issues related to rivers so as to develop river system management techniques emerging from in-depth scientific analysis as a priority. This book pools together the expertise, the in-depth knowledge and the experience of the people representing different disciplines bearing on the related aspects of analysis and management of river systems. Audience The book is expected to be useful to academics, practitioners, scientists, water managers, environmentalists, administrators, researchers and students who are involved and have stakes in water management and river system analysis. © 2017 Springer Science+Business Media Singapore.

River System Analysis and Management

River system analysis and management

Statistical independence test and validity of the CA (Cellular Automata) Markov process for projecting future land use and land cover (LULC) changes were carried out in this study. Predicting quantity and location changes have been analyzed, and statistically evaluated. Validity of the CA Markov process has been examined using various Kappa Index of Agreement (KIA or Kstandard) and related statistical variations on the KIA. Statistical test of independence (K2) was performed and markovian suitability has been checked using hypothesis of goodness of fit (Xc2). Hypothesis of statistical independence was rejected, which proved that land use land cover change trends are similar like previous development of land. With acceptance of the hypothesis of goodness of fit (Xc2) proved that actual transition probability of matrix is fitted with expected transition probability prepared using Markov chain method. Statistics indicates Kno, Klocation, Klocation Strata and Kstandard are 0.8347, 0.859, 0.8591 and 0.7928, respectively. © 2016 National Authority for Remote Sensing and Space Sciences

World University root node

Fulltext

Egyptian Journal of Remote Sensing and Space Science

Statistical independence test and validation of CA Markov land use land cover (LULC) prediction results

Spatio-temporal average rainfall erosivity factor map has been generated for India. This study on rainfall erosivity makes use of 101 years monthly rainfall data and 52 spatial points. The results presented here provide the much needed guidance to remove ambiguities regarding the rainfall erosivity factor in the Indian context. This study has a variety of applications in erosion prediction technology, such as Universal Soil Loss Equation or Revised Universal Soil Loss Equation, or in rainfall-data-deficient regions. In-depth observations can develop a deeper understanding of rainfall variation to estimate the erosivity factor. Rainfall erosivity factor map can facilitate agriculturists and soil conservationists to identify rainfall erosivity potential at diverse locations, and thereby apply obligatory safety measures to minimize soil erosion. The rainfall erosivity factor map has been used to provide a more rational value of the average rainfall erosivity factor covering India, in regions where rainfall distribution patterns is of the same order. © 2015 IAHR and WCCE.

Journal of Applied Water Engineering and Research

Rainfall erosivity factor for India using modified fourier index

Abstract: The present study describes the nonlinear vertical velocity distribution in an open channel (with and without hydraulic structure). Conventionally, velocity distribution is based on shear velocity normalization. In this study, maximum velocity has been applied for normalization. Von-Kármán logarithmic distribution (based on Kármán constant), its proposed analogous models, and entropy-based nonlinear velocity distribution have been compared for both the cases (with and without hydraulic structure). An entropy-based nonlinear velocity profile model has been also suggested to describe the velocity field in open channels. The suggested approach has been validated by means of controlled laboratory tests, executed in flume under steady flow conditions and at hydraulically smooth surface. The higher equivalence between the estimated velocity profiles using entropy and the observed ones. Entropy model has found best replicating model with respect to other four models (based on analogous of Prandtl–von Kármán model with the use of maximum velocity parameterization) but it also acquired difficulties regarding its higher number of numerically calculated coefficients. Power analogous model (based on maximum Reynolds number) and entropy model has been suggested as overall robust velocity distribution model and it is performing equally for both (with and without hydraulic structure) conditions. © 2016 Indian Society for Hydraulics.

ISH Journal of Hydraulic Engineering

Nonlinear and entropic velocity distribution in open channel

In the present study, an attempt has been made to compare the performances of six different soft computing techniques for suspended sediment prediction using hydro-meteorological variables as input at Kopili river basin in India. For this purpose, the models namely, artificial neural network (ANN), radial basis function neural networks (RBFNN), least square support vector regression (LS-SVR), multi-linear regression (MLR) and decision tree models such as Classification and Regression Tree (CART) and M5 model tree were employed. The input variable selection was derived considering the statistical properties such as auto-, partial-, and cross-correlation function of the time series. The performances of all the models were judged using statistical indexes i.e. Coefficient of Correlation (CC), Nash-Sutcliffe coefficient (ENS) and RMSE-observations Standard deviation Ratio (RSR). Overall performance of the models shows that, all the studied models are able to simulate suspended sediment of the Kopili River basin satisfactorily. Comparison of results showed that the LSSVR (ENS=89.00%) and ANN (ENS=88.78%) models were able to produce better results than the other models investigated. This study also suggests that, an M5 model tree, which obtains a continuous representation of the output data by fitting a linear regression function to the data, has certain advantages over CART and MLR model because they offer more insight into the generated model. © 2015 Elsevier B.V.

Catena

Daily suspended sediment simulation using machine learning approach

Increasing demands on water resources to ful ll the growing population needs have led to a great pressure on the water resources. Water resources conservation and management needs exemplary information regarding the water bodies with respect to quality, quantity and the related driving factors responsible for deterioration and depletion of water. Traditional methods existing in literature are limited to the point locations and manually gathered input dataset for analysis of the water system. However, after the development of advance geospatial technologies, now it is possible to build the digital information that can support analysis and interpretation for a large area in short span of time. e chapter introduces the various geospatial technologies, which are playing a vital and inevitable role in the acquisition of information and development of research capabilities towards water resources. ese technologies are required for determining a strategic plan for execution of desired results as applicable to dierent regions and objectives (for e.g. determination of water-river boundaries, water quality and quantity, soil moisture, ood plains, ocean temperature etc). is chapter provides dierent methods/applications to demonstrate the importance of traditional and advanced concepts of geospatial technology in water resources. us, overall goalof this chapter is to provide a summary of dierent research work carried out in various elds of water resources with demonstrated results and ndings that could be able to use in decisionmaking, developing policy and planning at root level. is chapter also provides future challenges in water resources andgeospatial technology. © 2017 by Taylor & Francis Group.

Geospatial Technology for Water Resource Applications

Introduction to geospatial technology for water resources

Agriculture, being a backbone to of India, provides livelihood to about seventy percent of the population and from an economic point of view, from an economic perspective, contributes forty percent towards Gross National Product. High crop yield is termed as “e Green Revolution” now days. It depends on the various factors like climatic conditions, soil type, management practices and other inputs like fertilizers. Fertilizers play the role of the main contributing factor in obtaining an enviable crop yield, but the usage of high quality and quantity of fertilizers to gain more crop yield causing considerable environmental complications. Digital processing of remotely sensed sensing data opened up new opportunities for understanding synoptic and substantial changesin the cropping pattern. e present paper is the study ofRice Equivalent Yield (REY) and Sodium Absorption Ratio (SAR) with the e†ect of di†erent fertilizer amounts like Nitrogen (N), Phosphorous (P) and Potassium (K) in the rice-based cropping pattern, i.e., Rice-Wheat, Rice-Maize, Rice-Mustard, Rice-Lytherus in Katihar and Bhagalpur districts of Bihar, India. e spatial maps of rice-based cropping with the availability of N, P and K are illustrated to determine the REY in the study area. e di†erent soil micronutrients, i.e., Organic Carbon (OC), Electrical Conductivity (EC) and pH are also used to examine the spatial discrepancies of rice-based cropping systems productivity. Ultimately the relational pattern has been drawn an equivalent rice ”eld and nitrate between rice equivalent yield and nitrate. © 2017 by Taylor & Francis Group.

Spatial integration of rice-based cropping systems for soil and water quality assessment using geospatial tools and techniques

Zonation of ood prone area on the basis of ood magnitude and geomorphic features denotes the assessment of a river valley in terms of susceptibility of oods. e Landsat and Resourcesat-1 satellite images (1977, 1990 and 2008) and Landsat MSS derived inundated area (1982) and Dartmouth ood atlas (1998, 2005 and 2008) have been used for identiƒcation of the geomorphic units and ood prone area of the lower Ghaghara river valley. e magnitude of oods in the above mentionedyears has been deƒned on the basis of their areal extent and duration of ooding. e ood prone area along the Ghaghara River (Ayodhya-Turtipar stretch) has been divided into three ood zones using overlay of ood layers of diŠerent magnitude and geomorphic features in the GIS environment. On the basis of geomorphic features, ood magnitude and frequency, vulnerability of hamlets in each ood zone has been assessed. e channel belt and active oodplain denote ood zone 1 which is regularly ooded in monsoon season (August to September). is zone has the most dynamic geomorphic features such as alluvial islands and mid-channel bars due to sedimentation in the channel belt. erefore, hamlet density is low in this zone while the vulnerability of hamlets therein is high. Flood zone 2 covers embankment protected part of the active oodplain which 1 Centre for the Study of Regional Development, School of Social Sciences, Jawaharlal Nehru University, New Delhi, India. © 2017 by Taylor & Francis Group.

Delineation and zonation of flood prone area using geo-hydrological parameters: A case study of lower ghaghara river valley

Introduction to water resources

River engineering study consists of large variation in time and spatial scales. Timescale of river varies from years to second, and, similarly, the variation of spatial scales is from kilometre to millimetre. Spatial scales can be divided into river basin scale and hydraulic scale, and temporal scale can be divided into hydrological, hydraulic and turbulence. Each spatio-temporal scale has fixed contextual uses. In general, turbulence plays the most key role with respect to the influences that rivers have on their channels and beds. Turbulent flows are characterized by asymmetrical patterns, irregular behaviour and the existence of various spatio-temporal scales. To extract better turbulence events and flow structure using point velocity measurements (Eulerian approach) in river, we are proposing generalized three-dimensional octant events instead of conventional two-dimensional quadrant events. Beyond that, we characterize the transitional probability of octant event occurrence in the case of unsteady flow condition. In the field, there is the assumption of steadiness of the flow under high unsteady conditions. Basically, river discharges and all the associated processes are physically unsteady, and river channel flows are typically non-uniform. In this chapter we are mainly discussing the new emerging methodological aspects to characterize the river turbulence using state-of-the-art technology. In this chapter, some of the major issues and developments linked with river dynamics and turbulence study have also been discussed with two case studies. The case studies have been presented and discussed using experimental data and their interpretation in light of river dynamics. The study has significant importance because the turbulent motion is the natural state of river engineering problems. © 2017 Springer Science+Business Media Singapore.