D Nagesh Kumar

D Nagesh Kumar
Indian Institute of Science | IISC · Department of Civil Engineering

Ph.D.

About

251
Publications
183,421
Reads
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6,638
Citations
Introduction
D. Nagesh Kumar has been a Professor with the Department of Civil Engineering, IISc, since May 2002. His research interests include climate change, water resource systems, deep learning, evolutionary algorithms and remote sensing & GIS applications in water resources. He has supervised 10 Post-Docs and 22 PhDs. He is the co-author of 8 textbooks and published more than 220 papers including 131 in journals. More details at ​http://www.civil.iisc.ac.in/~nagesh
Additional affiliations
March 2014 - January 2020
Indian Institute of Science
Position
  • CEO
May 2002 - present
Indian Institute of Science
Description
  • Teaching & Research
May 2002 - March 2020
Indian Institute of Science
Position
  • Chair
Education
August 1987 - August 1992
Indian Institute of Science
Field of study
  • Water Resources Systems
July 1985 - January 1987
Anna University, Chennai
Field of study
  • Hydrology and Water Resources Engineering
July 1980 - June 1984

Publications

Publications (251)
Article
Hyperspectral imaging spectroscopy has facilitated the mapping of soil properties at large scales, but since the presence of photosynthetic or non-photosynthetic vegetation affects the reflectance spectra, soil properties mapping is limited to bare soil surfaces. This study analyzed the impact of bare soil pixel identification on clay content estim...
Article
This review provides a broad overview of the current state of flood research, current challenges, and future directions. Beginning with a discussion of flood generating mechanisms, the review synthesizes the literature on flood forecasting, multivariate and non-stationary flood frequency analysis, urban flooding, and the remote sensing of floods. C...
Article
This review provides a broad overview of the current state of flood research, current challenges, and future directions. Beginning with a discussion of flood-generating mechanisms, the review synthesizes the literature on flood forecasting, multivariate and nonstationary flood frequency analysis, urban flooding, and the remote sensing of floods. Ch...
Article
Spectral mixture modelling is one of the most important techniques for classifying hyperspectral data at sub-pixel resolution. The identification of spectrally pure endmembers for estimating their corresponding abundances is an important step in spectral unmixing. The application of spectral reduction prior to endmember extraction would optimize th...
Article
Himalayan tributaries of the northern Brahmaputra plain are vulnerable to rapid channel shift and planform adjustment. Yet, the information and knowledge of their morphological changes are sparse. This paper uses multiple geo-informational data such as archival maps, aerial and satellite imaginaries, field mapping and interviews with the locals, an...
Preprint
This paper documents the bankline dynamics of the Brahmaputra River along the India and Bangladesh region during the period 1976 to 2018. Multiple approaches, including satellite image-based interpretations, fieldwork, and meta-analysis, are performed to explore the factors responsible for the morphological dynamics of the river. Results suggest th...
Article
Pre-harvest crop mapping, the fundamental requirement for many of the crop management decisions, continues to be challenging either due to cloud cover in satellite images or due to spectral separability issues. These limitations are overcome in this study by using Synthetic Aperture Radar (SAR) data and deep learning technique. Two-dimensional conv...
Article
The study investigates the seasonal contribution of surface runoff and baseflow to the Cauvery streamflow using isotope mass balance approach. Stable Isotope measurements (δ2H, δ18O) of Cauvery river water along with groundwater are carried out using consistent sampling protocols. Samples are collected during seasonal time interval spanning from 20...
Article
Hyperspectral (HS) data are proven to be more resourceful compared to multispectral (MS) data for object detection, classification and several other applications. However, absence of any space-borne HS sensor since 2017, which can provide open-source data with global coverage, and high cost and limited obtainability of airborne sensors-based images...
Article
Since 1901, global temperatures have risen by 0.89 °C, seriously impacting precipitation patterns and flowpeaks. However, few assessments of changes in global water balance have been conducted. Here we investigate the effect of rising temperatures on water recharge for 31 major river basins across the world using satellite derived terrestrial water...
Article
Full-text available
The groundwater planning problems are often multiobjective. Due to conflicting objectives and non-linearity of the variables involved, several feasible solutions may have to be evolved rather than single optimal solution. In this study, the simulation model built on an Analytic Element Method (AEM) and the optimization model built on a Non-dominate...
Book
This book comprises select proceedings of the International Conference on Trends and Recent Advances in Civil Engineering (TRACE 2020). The volume focuses on latest research works carried out in the area of water resources and transportation engineering. The topics include technological intervention and solution for water security, sustainability i...
Article
Full-text available
Chlorophyll content is one of the essential parameters to assess the growth process of the fruit trees. This present study developed a model for estimation of canopy averaged chlorophyll content (CACC) of pear trees using the convolutional auto-encoder (CAE) features of hyperspectral data. This study also demonstrated the inspection of anomaly amon...
Book
In recent years, remote sensing images have great potential for continuous spatial and temporal monitoring of Earth surface features. High-dimensional hyperspectral (HS) data are highly resourceful compared with multispectral (MS) data but handling such large volume data is a very challenging task, which should be addressed with the use of feature...
Data
The supplementary file includes the Figs S1-S7 of the Manuscript "Transformation of Multispectral Data to Quasi- Hyperspectral Data Using Convolutional Neural Network Regression". These figures present the comparisons of (a) PCC, (b) RMSE, (c) PSNR, and (d) SSIM calculated from different models considering testing data of different land cover types...
Article
Remote sensing has revolutionized the assessment of evapotranspiration by continuous monitoring of the variable at a global scale. However, it is difficult to accurately estimate actual evapotranspiration (AET) in areas with high spatial heterogeneity along with very little ancillary data available. The presence of spatial heterogeneity is observed...
Article
Full-text available
Global climate models (GCMs) are developed to simulate past climate and produce projections of climate in future. Their roles in ascertaining regional issues and possible solutions in water resources planning/management are appreciated across the world. However, there is substantial uncertainty in the future projections of GCM(s) for practical and...
Article
Full-text available
During the last three decades, the water resources engineering field has received a tremendous increase in the development and use of meta-heuristic algorithms like evolutionary algorithms (EA) and swarm intelligence (SI) algorithms for solving various kinds of optimization problems. The efficient design and operation of water resource systems is a...
Article
Full-text available
Actual Evapotranspiration (AET) is a significant hydrological process. It can be studied and estimated using remote sensing-based methods at multiple spatial and temporal scales. Optical and thermal sensors provide reflectance and land surface temperature (LST) data required in these methods only for clear sky conditions, since these are unable to...
Article
Full-text available
The modified topographic index (TIm) based on digital elevation models (DEMs) was employed to delineate flood-prone areas in Mahanadi basin, India. TIm and flood inundation maps were compared to obtain the threshold (τ) beyond which the area is assumed to be inundated by flood and the exponent of the TIm. Scale dependence was also investigated to e...
Article
Full-text available
The rapid changes in global average surface temperature have unfathomed influences on human society, environment, ecosystem, availability of food and fresh water. Multiple lines of evidence indicate that warming of the climate system is unequivocal, and human-induced effects are playing an enhanced role in climate change. It is of utmost importance...
Article
Full-text available
Passive microwave sensors use a radiative transfer model (RTM) to retrieve soil moisture (SM ) using brightness temperatures (TB) at low microwave frequencies. Vegetation optical depth (VOD) is a key input to the RTM. Retrieval algorithms can analytically invert the RTM using dual-polarized TB measurements to retrieve the VOD and SM concurrently. A...
Article
Full-text available
Recent advancements in the remotely sensed data products and machine learning algorithms are utilized effectively for classification of crops over a considerable large-area. This article proposes the use of feature extraction techniques to be employed on the multi-temporal Landsat-8 OLI sensor’s surface reflectances and derived Normalized Differenc...
Article
Hyperspectral (HS) data are enriched with highly resourceful abundant spectral bands. However, analysing and interpreting these ample amounts of data is a challenging task. Optimal spectral bands should be chosen to address the issue of redundancy and to capitalize on the absolute advantages of HS data. Partial informational correlation (PIC) based...
Article
The radiative transfer scheme implemented for the retrieval of soil moisture from passive microwaves is a function of scattering, polarization mixing and attenuation effects of soil and vegetation. Theses factors are usually represented by Vegetation Optical Depth (VOD), vegetation scattering albedo, and surface roughness parameter, along with soil...
Presentation
Convolutional Neural Network (CNN) has established as an effective deep learning model for hyperspectral image classification by considering both spectral and spatial information. In this study, the performance of two-dimensional (2D) CNN architecture is evaluated at hyperspectral and multispectral resolution. Two types of multispectral data are an...
Conference Paper
Full-text available
Convolutional Neural Network (CNN) has established as an effective deep learning model for hyperspectral image classification by considering both spectral and spatial information. In this study, the performance of two-dimensional (2D) CNN architecture is evaluated at hyperspectral and multispectral resolution. Two types of multispectral data are an...
Conference Paper
Full-text available
Water availability and food security in most of Asia’s major river basins are imperiled by climate change. Global warming is unequivocal and is mostly the primary cause for the recent increase in magnitude and frequency of extreme events. Recent consecutive floods in the Mahanadi River Basin (MRB) motivated us to analyze the impact of climate chang...
Conference Paper
Full-text available
Classification of crops is very important to study different growth stages and forecast yield. Remote sensing data plays a significant role in crop identification and condition assessment over a large spatial scale. Importance of Normalized Difference Indices (NDIs) along with surface reflectances of remotely sensed spectral bands have been evaluat...
Article
This study presents Multifractal Detrended Fluctuation Analysis (MF‐DFA) to describe the multifractality of Standardized Precipitation Index (SPI) series from 30 meteorological subdivisions of India estimated at different aggregation time scales (3, 6 and 12 months) based on long term monthly rainfall datasets of 1871‐2016 period. The plots of fluc...
Article
Full-text available
Information about basin scale climate change is very crucial for utilization, development, and planning of water. The Tapi basin is climatically sensitive. For policymakers, it is important that changes in individual seasons are elucidated. Any earlier study on streamflows of the Tapi basin mentioned in the literature review had not performed trend...
Presentation
Classification of crops is very important to study different growth stages and forecast yield. Remote sensing data plays a significant role in crop identification and condition assessment over a large spatial scale. Importance of Normalized Difference Indices (NDIs) along with surface reflectances of remotely sensed spectral bands have been evaluat...
Article
Full-text available
With the introduction of the earth observing satellites, remote sensing has become an important tool in analyzing the Earth's surface characteristics, and hence in supplying valuable information necessary for the hydrologic analysis. Due to their capability to capture the spatial variations in the hydro-meteorological variables and frequent tempora...
Chapter
Terrestrial Water Storage (TWS) data, now available for more than 15 years, as furnished by the Gravity Recovery and Climate Experiment (GRACE) satellite mission provided remarkable insights into the hydrological cycle. An expanding volume of scientific literature bears testimony to this. Besides identifying the alarming rate of both global groundw...
Article
South India has seen significant changes in climate. Previous studies have shown that the southern part of India is more susceptible to effects of climate change than the rest of the country. We performed a rigorous climate model-based detection and attribution analysis to determine the root cause of the recent changes in climate over South India u...
Article
Full-text available
Water demand in India is growing due to its increasing population, economic growth and urbanization. Consequently, knowledge of interdependencies of large-scale hydrometeorological processes is crucial for efficient water resources management. Estimates of Groundwater (GW) derived from Terrestrial Water Storage (TWS) data provided by Gravity Recove...
Book
Full-text available
Under changing climatic conditions, a detailed study focusing on the change in hydroclimatic variables is of fundamental importance for ecologists, climatologists and water resources researchers because of its substantial implications on environment and water resources management. As a result of increase in global average surface temperature, aberr...
Article
This study aims to compare different satellite based radiation (Makkink) and temperature (Hargreaves-Samani, Penman Monteith Temperature (PMT)) based reference evapotranspiration (ETo) models with FAO56-PM method over Cauvery basin. Required maximum air temperature (Tmax) in ETo models was estimated using Temperature Vegetation Index (TVX) and Adva...
Article
Full-text available
Fuzzy VIKOR, a decision making technique, is applied to prioritize 224 sub-catchments of Mahanadi Basin, India. Seven geomorphology based criteria viz., drainage density, bifurcation ratio, stream frequency, texture ratio, form factor, elongation ratio and circulatory ratio are estimated from five digital elevation models (DEMs). Triangular members...
Article
Recent studies based on Gravity Recovery and Climate Experiment (GRACE) satellite mission suggested that groundwater has increased in central and southern parts of India. However, surface water, which is an equally important source of water in these semi-arid areas has not been studied yet. In the present study, we outline the study areas based on...
Article
Full-text available
For agriculture-based country like India, seasonal rainfall is very crucial. Trends and variability in rainfall are one of the crucial aspects in studies of climate change. Earlier studies performed on the trend detection analysis of seasonal rainfall of homogeneous regions and all India (ALLIN) are having three drawbacks: (1) they have not conside...
Article
Spatially distributed vegetation coefficients ( ) data with high temporal resolution are in demand for actual evapotranspiration estimation, crop condition assessment, irrigation scheduling, etc. Traditional remotely sensed based data application gets hindered because of two main reasons i.e 1) spectral reflectance based accounts only for transpira...
Article
Full-text available
Evolutionary Algorithms are gaining prominence due to their flexibility in handling non-linearity, high dimensionality, and multiobjectiveness in integrated water resources management. Its applications include reservoir operation and capacity planning, ground water optimization, conjunctive use of water resources, and water quality management. In a...
Presentation
Many observations and studies have shown that the water availability in most the major river basins of Asia are perilled by climate change. Hence, an insight into the hydroclimatological change and variability at a river basin scale is crucial and is important for efficient water resource management and planning strategies. An increase in global av...
Conference Paper
Many observations and studies have shown that the water availability in most the major river basins of Asia are perilled by climate change. Hence, an insight into the hydroclimatological change and variability at a river basin scale is crucial and is important for efficient water resource management and planning strategies. An increase in global av...
Presentation
Full-text available
Presenting Interactive COntent (PICO) Abstract: Hyperspectral (HS) datasets are comprised of large numbers of spectral bands (100-300) with very narrow bandwidth (5-10 nm), which are proven to be very efficient for land-use land-cover classification and numerous other applications. However, the fine spectral and spatial resolution of the HS dataset...
Article
Hyperspectral (HS) data comprises of continuous spectral responses of hundreds of narrow spectral bands with very fine spectral resolution or bandwidth, which offer feature identification and classification with high accuracy. In the present study, Mutual Information (MI) based Segmented Stacked Autoencoder (S-SAE) approach for spectral-spatial cla...
Article
Full-text available
Recession flows of a basin provide valuable information about its storage-discharge relationship as during recession periods discharge occurs due to depletion of storage. Storage-discharge analysis is generally performed by plotting −dQ/dt against Q, where Q is discharge at time t. For most real world catchments, −dQ/dt vs Q show a power-law relati...
Book
This book gives an overview of various aspects of climate change by integrating global climate models, downscaling approaches, and hydrological models. It also covers themes that help in understanding climate change in a holistic manner. The book includes worked-out examples, revision questions, exercise problems, and case studies, making it releva...
Chapter
This chapter presents data compression techniques, namely, cluster and fuzzy cluster analysis, Kohonen neural networks for clustering GCMs and principal component analysis for transforming a set of observations of possible correlation into a set of linearly uncorrelated variables applying an orthogonal transformation. F--statistic test which can be...
Chapter
This chapter describes Global Climate Models (GCMs), limitations and uncertainties associated with the formulation of GCMs due to the effect of aerosols which are differently parameterized in GCMs, initial and boundary conditions for each GCM, parameters and model structure of GCMs, randomness, future greenhouse gas emissions, and scenarios leading...
Chapter
This chapter describes basic definitions, classification of models into various categories, with procedures for solving water resources engineering problems using hydrological models. Storm Water Management Model (SWMM), Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS), Soil and Water Assessment Tool (SWAT), and Variable Infiltrat...
Chapter
This chapter presents various real-world global case studies in AR3 and AR5 perspective that are related to the evaluation of GCMs for maximum and minimum temperatures for India, intercomparison of statistical downscaling methods for projection of extreme precipitation in Europe, downscaling of climate variables using Support Vector Machine, Multip...
Chapter
Describes downscaling techniques where GCM outputs are interpolated to the scale of hydrological modeling or local scale requirement. Statistical downscaling techniques that facilitate statistical relationships that metamorphose large-scale atmospheric variables/predictors simulated by GCMs to local scale variables/predictand are discussed in detai...
Article
Full-text available
The frequent occurrence of flood and drought worldwide has drawn attention to assessing whether the hydroclimatology of major river basins has changed. The Mahanadi river basin (MRB) is the major source of fresh water for both Chattisgarh and Odisha states (71 million people approximately) in India. The MRB (141 600 km² area) is one of the most vul...
Conference Paper
Studies on climate change impact assessment and influence of temperature have become crucial as these may affect the sustainability of water resources and their long term planning. In this regard, Global Climate Models (GCM) are gaining importance. Thirty Six Coupled Model Intercomparison Project-5 (CMIP5) based GCMs are evaluated for the climate v...
Article
Soil moisture is widely recognized as an important land surface variable that provides a deeper knowledge of land atmosphere interactions and climate change. Space-borne passive and active microwave sensors have become valuable and essential sources of soil moisture observations at global scales. Over the past four decades, several active and passi...
Article
Frequent occurrence of flood and drought worldwide has drawn attention to assess whether the hydroclimatology of major river basins has changed. Mahanadi river basin (MRB) is the major source of fresh water for both Chattisgarh and Odisha states (71 million population approximately) of India. The MRB (141,600 km2 area) is one of the most vulnerable...