Papers by Janga Reddy Manne
Remote Sensing Applications: Society and Environment
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Journal of Hydrology
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Springer International Publishing eBooks, 2022
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Studies in Computational Intelligence, 2022
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Modelling suspended sediment load (SSL) from rivers is a complex problem in river basin managemen... more Modelling suspended sediment load (SSL) from rivers is a complex problem in river basin management. This chapter presents hybrid framework multivariate empirical mode decomposition (MEMD) and stepwise linear regression (SLR) for estimation of SSL from riverflows demonstrated to a case study in Mahanadi River Basin, India. The method involves two major steps: first, the multivariate dataset comprising SSL of current time along with lagged inputs of streamflow and SSL are decomposed into different modes using MEMD; then, the obtained modes are estimated independently by SLR fitting engaging the statistically significant inputs at respective time scales. The sum of the predicted modes gives the desired SSL. The effectiveness of the presented method is evaluated for five models by considering different combinations of inputs, and their performance is compared with traditional multiple linear regression (MLR) and model tree (MT) models. The performance statistics of models showed that fo...
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Physically based distributed hydrological models are an invaluable tool for planning and manageme... more Physically based distributed hydrological models are an invaluable tool for planning and management of water resource projects. However, a reliable prediction from hydrological models can only be expected if their unknown model parameters are estimated accurately. In place of laborious manual calibration of the parameters of the hydrological model, this study presents an automatic calibration scheme for the VIC-RAPID hydrological model using the self-adaptive differential evolution (SaDE) algorithm. The SaDE eliminates the laborious manual tuning of the two control parameters (mutation factor and crossover rate) of the conventional DE algorithm. The proposed approach is demonstrated with a case study in the upper Krishna river sub-basin for estimation of the 15 VIC-RAPID model parameters. The efficacy of the proposed calibration technique for hourly streamflow simulation is evaluated by using standard performance measures such as Nash-Sutcliffe Coefficient (NSE), Coefficient of Corr...
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This book presents the principles and practices of optimal design of irrigation canals considerin... more This book presents the principles and practices of optimal design of irrigation canals considering varying roughness along channel perimeter incorporating slope stability constraint, hydraulic & geometric restrictions, uncertainty associated with the roughness parameter etc. Swarm intelligence based method is followed in optimizing different open channel cross sections and the novel methodologies presented in this book have practical appeal in the design of irrigation canals ensuring cost effectiveness and system reliability.
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Journal of Water Resources Planning and Management, 2020
AbstractThis paper investigates the use of surrogate measures as potential substitutes for reliab... more AbstractThis paper investigates the use of surrogate measures as potential substitutes for reliability in multiobjective design of water distribution networks (WDNs). Assessing WDN reliability with...
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Water Resources Management, 2020
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Science of The Total Environment, 2019
This study investigates the change in dependence structure of bivariate flood flow characteristic... more This study investigates the change in dependence structure of bivariate flood flow characteristics namely magnitude, frequency and timing in the Godavari river basin using a copula based likelihood ratio (CLR) test. Parametric bootstrap was used to obtain critical values of CLR test for the best-fitted copula. The performance of the CLR method was also evaluated for simulated synthetic bivariate series with a known change-point location in the dependence (copula parameter). Then the methodology was applied to two streamflow monitoring sites Bhimkund and Wagholi-Butti, located in the Godavari river basin in India. Streamflow data for 33Â years from 1977 to 2009 was analyzed, by extracting the series of flow characteristics of magnitude, frequency and timing. Initially univariate change-point detection (CPD) test namely standard normal homogeneity test was applied to detect abrupt change-point in mean of the flow series. At Bhimkund site, there was abrupt increase in mean of magnitude, frequency and timing series after the identified change-point year. However, at Wagoli-Butti site, there was abrupt decrease in mean of magnitude and frequency series although timing series got delayed (i.e., abrupt increase). After univariate CPD in mean, the bivariate series i.e., magnitude-frequency and magnitude-timing pairs for these sites were analyzed to detect the change-points in dependence in terms of copula parameters using the CLR method. The results showed that change-points in the copula parameters were detected at year 2003 and 2004 for Wagoli- Butti and Bhimkund sites respectively, and appear to be jointly non-stationary due to human induced change at these two sites. The results of study for detection of the change-point location in the dependency structure of flow characteristics would be useful for flood risk assessment in the basin.
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International Journal of River Basin Management, 2019
ABSTRACT This study presented multiscale characterization of monthly streamflow time series using... more ABSTRACT This study presented multiscale characterization of monthly streamflow time series using Multivariate Empirical Mode Decomposition (MEMD) and developed an innovative approach for streamflow prediction by coupling MEMD with Genetic Programming (GP). Firstly, the possible hydro-climatic teleconnection of monthly streamflows of Mahanadi river basin in India with two large-scale climate oscillations of ElNiño Southern Oscillation (ENSO) and Equatorial Indian Ocean Oscillation (EQUINOO) is investigated by applying MEMD based Time-Dependent Intrinsic Correlation (TDIC) analysis. The TDIC analysis showed that the association between large-scale climate oscillations and streamflows is not unique always, but both the nature and strength of the association varies with time scales and over the time domain. Based on this finding, the study proposed MEMD-GP coupled approach for streamflow prediction, in which different modes corresponding to different process scales obtained by the MEMD are predicted separately using GP; and summation of these predicted modes provides the monthly streamflow at the station. A statistical performance evaluation based on multiple criteria showed that the proposed approach performs better than the multiple linear regression, M5 model tree and GP models for monthly streamflow prediction including extreme low and high flows, due to its unique capability to include the significant predictors at different time scales.
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Hydrological Processes, 2018
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Stochastic Environmental Research and Risk Assessment, 2018
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Modeling Earth Systems and Environment, 2017
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IEEE Geoscience and Remote Sensing Letters, 2016
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ISH Journal of Hydraulic Engineering, 2015
In this study, the performance of a recent meta-heuristic technique, namely, gravitational search... more In this study, the performance of a recent meta-heuristic technique, namely, gravitational search algorithm (GSA) is evaluated for a deterministic as well as for a probabilistic design of canals that have cross-sectional shape of horizontal bottom and parabolic sides (HBPS). The uncertainty in various input parameters is modeled using probabilistic approach and a modified chance-constrained model is presented for an optimal design of HBPS canals with the aim of minimizing the total cost, while satisfying the basic flow constraints and reliability constraints on the canal capacity and overtopping. First, the GSA method is applied to solve the HBPS canal design problem under different constraints, and its performance is evaluated by comparing with the solutions of the deterministic models by the particle swarm optimization and genetic algorithm. Then, the GSA is applied to obtain the solution of the probabilistic model and in view of multiple conflicting goals; pseudo-weight vector approach is adopted to assist in decision-making and demonstrate its applicability for arriving at a suitable decision. The results obtained suggest that the proposed GSA approach has good potential for a reliable and cost-effective design of canals.
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International Journal of Climatology, 2014
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ISH Journal of Hydraulic Engineering, 2013
In this paper, a stochastic model is presented to generate monthly inflows into the Hirakud Dam b... more In this paper, a stochastic model is presented to generate monthly inflows into the Hirakud Dam by using the principles of entropy and copulas. The marginal distributions obtained using the principle of maximum entropy (POME) helps the model to retain the higher-order moment statistics of the historical data, whereas the copula-based joint distributions ensure the preservation of the dependence between the adjacent months. On analysing the moments and dependence structures of the generated data samples and comparing with the corresponding observed data properties, it is found that the developed stochastic models gives good performance by preserving flow properties. Hence the entropy-copula-based model can be used as an effective approach for stochastic generation of hydrological variables.
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ISH Journal of Hydraulic Engineering, 2013
Identification of homogenous regions and their ranking is important to formulate appropriate stra... more Identification of homogenous regions and their ranking is important to formulate appropriate strategies for suitable conservation and management practices within the watershed. In this study, Kohonen neural network (KNN) is employed to classify the micro-watersheds of Kaddam watershed in middle Godavari basin (India) into homogeneous groups. KNN algorithm learns to cluster groups of similar input patterns from a high-dimensional input space in a non-linear fashion onto a low-dimensional layer of neurons. Ten geo-morphological parameters are used for classification of micro-watersheds. An optimal number of groups is chosen based on two cluster validation measures, the Davies–Bouldin Index and the Dunn’s Index. By using the KNN method, 18 micro-watersheds are grouped into five homogenous groups based on selected watershed parameters. The clustering results showed concurrence with general ranking of micro-watersheds. Further, the KNN micro-watershed classification results are validated by comparing with the results of K-means clustering algorithm (KCA). From the comparative analysis, it is observed that both the algorithms give approximately similar kinds of classification of micro-watersheds. The obtained results help in identifying the groups of micro-watersheds that should be given top priority (i.e. those that require immediate conservation measures). The study suggests that identifying homogeneous regions can be helpful for effective planning and management of watersheds, and KNN can be applied effectively for micro-watershed zonation.
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Stochastic Environmental Research and Risk Assessment, 2013
ABSTRACT This study investigated the utility of two meta-heuristic algorithms to estimate paramet... more ABSTRACT This study investigated the utility of two meta-heuristic algorithms to estimate parameters of copula models and for derivation of drought severity–duration–frequency (S–D–F) curves. Drought is a natural event, which has huge impact on both the society and the natural environment. Drought events are mainly characterized by their severity, duration and intensity. The study adopts standardized precipitation index for drought characterization, and copula method for multivariate risk analysis of droughts. For accurate estimation of copula model parameters, two meta-heuristic methods namely genetic algorithm and particle swarm optimization are applied. The proposed methodology is applied to a case study in Trans Pecos, an arid region in Texas, USA. First, drought severity and duration are separately modeled by various probability distribution functions and then the best fitted models are selected for copula modeling. For modeling the joint dependence of drought variables, different classes of copulas, namely, extreme value copulas, Plackett and Student’s t copulas are employed and their performance is evaluated using standard performance measures. It is found that for the study region, the Gumbel–Hougaard copula is the best fitted copula model as compared to the others and is used for the development of drought S–D–F curves. Results of the study suggest that the meta-heuristic methods have greater utility in copula-based multivariate risk assessment of droughts.
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Papers by Janga Reddy Manne