The dynamics of trophic status estimation of case-2 water bodies on a synoptic mode for frequent ... more The dynamics of trophic status estimation of case-2 water bodies on a synoptic mode for frequent intervals is essential for water quality management. The present study attempts to develop trophic status estimation approaches utilizing Landsat-8 and Sentinel-2 images as inputs. The chlorophyll-a concentration, a proxy parameter for trophic status, was estimated using the empirical method, fluorescence line height (FLH) method, and artificial neural network (ANN) approaches using spectral reflectance values as inputs. The outcomes following the empirical approaches revealed the scope of kernel normalized difference vegetation index (kNDVI) (R 2 ¼ 0.85; RMSE ¼ 2 μg/l) for estimating the chlorophyll-a concentration using Sentinel-2 images of the Godavari River basin. Though the performance of the FLH method (R 2 ¼ 0.91; RMSE ¼ 1.6 μg/l) was superior to kNDVIbased estimation, it lacks the capability to estimate chlorophyll-a concentration above 20 μg/l. Due to the existence of eutrophic regions within the Godavari basin (28%), adopting better approaches like ANN for trophic status estimation is essential. To accomplish the same, the Levenberg-Marquardt algorithm-based ANN was developed using non-redundant bands of Sentinel-2 as inputs, and Sentinel-3 derived chlorophyll-a values as output. The developed architecture was successful in estimating trophic status estimations at all levels.
Hybridisation of the multi-objective optimisation algorithm NSGA-II and local search is proposed ... more Hybridisation of the multi-objective optimisation algorithm NSGA-II and local search is proposed for water distribution system design. Results obtained with the proposed algorithm are presented for four medium-size water networks taken from the literature. Local search is found to be beneficial for one of the networks in terms of finding new solutions not reported earlier. It is also shown that simply using an external archive to save all non-dominated solutions visited by the population, even without local search, leads to substantial improvement in the non-dominated set produced by the algorithm.
Self-adaptive cuckoo search algorithm is used to optimize the design of water distribution system... more Self-adaptive cuckoo search algorithm is used to optimize the design of water distribution system problems. It is proposed to dynamically adjust the two sensitive parameters of the algorithm, (i) step size control parameter 'α' and (ii) discovering probability parameter 'Pa' which largely govern the exploration and exploitation search strategies of the algorithm. These parameters are essential for enhancing the performance of the algorithm and normally the values of these parameters needs careful selection according to the type of problem. Single objective self-adaptive cuckoo search algorithm (SACSA) and multiobjective self-adaptive cuckoo search algorithm (SAMOSCA) are proposed in this study. Robustness and efficiency of these algorithms in single (minimization of cost) and multiobjective scenarios (minimization of cost and maximization of resilience) is validated using standard water distribution benchmark problems i.e. Two loop and Hanoi network. These are later applied to solve a medium size real-life water distribution system located at Pamapur, Telangana, India. A simulation-optimization based program combining the water distribution network simulation software EPANET 2.2 and MATLAB is used for computation. The proposed methodology has provided better results in terms of computational efficiency as well as found better solutions when compared to the previously reported results in both single and multi-objective scenarios. In the case of multi-objective problems, it has been observed that SAMOCSA has been able to find new points in pareto front when compared to the best-known pareto front reported in the literature. Selfadaptive cuckoo search algorithm has been found to be an attractive alternative in both exploration and exploitation of larger search spaces for finding better optimal solutions.
Water Science & Technology: Water Supply, Feb 10, 2023
Optimally designed water distribution networks (WDNs) make engineers' tasks difficult due to vari... more Optimally designed water distribution networks (WDNs) make engineers' tasks difficult due to various challenges like non-linearity between head-loss and flow, commercially available distinct diameters, combinatorial, nondeterministic polynomial-time hard problems and a large number of decision variables. This paper develops a new hybrid NSGA-II algorithm augmented with a random multi-point crossover operator and a local search denoted by RLNSGA-II to design the multiobjective WDN. The efficiency of the proposed algorithm (RLNSGA-II) is tested on three benchmark problems, namely New York, Hanoi and Balerma networks. The results obtained are compared with the best-known algorithms available in the literature. The results have shown that the proposed algorithm RLNSGA-II has found better converged and distributed solutions for all three representative benchmark problems considered in the literature consistently and evidently when compared with the best-known approximation of solutions published. Furthermore, as the complexity of the WDN increases, its advantages over other algorithms become more significant.
Environmental Monitoring and Assessment, Sep 15, 2020
Hydrological models apply different methods to estimate runoff and route flows. Suitability of th... more Hydrological models apply different methods to estimate runoff and route flows. Suitability of these methods is not unique, but varies with catchment conditions. This study aims to find the suitable overland runoff and flow routing methods for a catchment in Hyderabad, India, using customised Storm Water Management Model (SWMM-C). Currently, SWMM adapts only non-linear reservoir (NLR) method to estimate overland runoff. Linear reservoir (LR) and kinematic wave overland flow (KWO) have been incorporated as additional overland runoff methods. For flow routing, SWMM currently has kinematic wave (KW) and dynamic wave (DW) methods. Muskingum, Muskingum Cunge (MC) and lag methods have been included as additional methods in this customised version. SWMM-C was calibrated with four event rainfalls and tested with six event rainfalls using all possible combinations of overland runoff and flow routing methods. Efficiency of SWMM-C in simulating runoff was evaluated using performance indices. Results showed that for low magnitude event rainfalls, NLR, LR and KWO simulated runoff with a maximum deviation of 50%, 60% and 40% from observed runoff, respectively. In high magnitude event rainfalls, NLR, LR and KWO simulated runoff with maximum deviations of 20%, 40% and 20%, respectively, from the observed runoff. It was inferred from model outputs that NLR method could simulate runoff reasonably well for rainfalls that have duration greater than the time of concentration of catchment. LR method could simulate peak runoff better. KWO method was found to be suitable for chosen catchment for all rainfall durations. Flow routing methods KW, DW and MC are found to have minor influences on the runoff.
We recapitulate the approaches of sensible heat flux (H) estimation, which is a critical paramete... more We recapitulate the approaches of sensible heat flux (H) estimation, which is a critical parameter in the remote sensing (RS)-based evapotranspiration (ET) models. We propose a classification scheme for the ET models considering their distinctions in approaches for the estimation of H. Adhering to the proposed classification scheme, the theoretical backgrounds of H estimation in the single-source and two-source RS-based ET models are discussed in brief, along with their unique characteristics. We addressed the role of critical parameters that influenced the H computation under each model and presented the related progress in the research. The importance of data assimilation techniques, as well as the application of unmanned aerial vehicles for the uninterrupted estimation of turbulent heat flux, are discussed in the context of single-source and two-source models. The influence of scale on the validation of the models and the impact of the aggregation methods are discussed. We compared the performance of the popular ET models for the estimation of H, utilizing the information obtained from peer-reviewed articles. The limitations related to the RS datasets in terms of spatial and temporal resolution and the scope of alleviating the shortcomings using the future satellite missions are discussed. We conclude by pointing toward the current challenges and the prospective domain of research, which needs to be addressed critically in the future.
Microplastics are classified as emerging pollutants of the aquatic environment, necessitating a c... more Microplastics are classified as emerging pollutants of the aquatic environment, necessitating a comprehensive understanding of their properties for successful management and treatment. Wastewater treatment plants (WWTPs) serve as point sources of microplastic pollution of the aquatic and terrestrial (eco)systems. The first part of this review explores the basic definitions of microplastics, sources, types, physical and chemical methods of identifying and characterizing microplastics in WWTPs. The next part of the review details the occurrence of microplastics in various unit processes of WWTPs and sewage sludge. Followed by this, various methods for removing microplastics from wastewater are presented. Finally, the research gaps in this area were identified, and suggestions for future perspectives were provided.
The study aims at calibration of the storm water management model (SWMM) with non-dominated sorti... more The study aims at calibration of the storm water management model (SWMM) with non-dominated sorting genetic algorithm-III (NSGA-III) for urban catchment in Hyderabad, India. The SWMM parameters calibrated were Manning's roughness coefficient (N), depression storage for pervious and impervious areas (D P and D i), sub-catchment width (W), curve number (CN), drying time (dry) of soil and percentage of imperviousness (I). The efficacy of calibration was evaluated by comparing the observed and simulated peak flows and runoff using goodness-of-fit indices. The calibration takes into consideration eight event rainfalls resulting in eight calibrated sets. Weights of goodness-of-fit indices were estimated and the best calibrated set was further validated for five continuous rainfalls/ runoffs. Simulated runoff volume and peak runoff over the five continuous rainfalls deviated by 7-22% and 2-20% with respect to observed data. Results indicated that parameters calibrated for an event rainfall could be used for continuous rainfall-runoff modelling. The effect of catchment delineation scale on runoff was also studied. The study indicated that output of the model was sensitive to variation in parameter values of infiltration and imperviousness.
The successful prediction of the stream or river water quality is gaining the attention of variou... more The successful prediction of the stream or river water quality is gaining the attention of various governmental agencies, and pollution control boards worldwide due to its useful applications in determining watershed health, biodiversity, ecology, and suitability of potable water needs of the river basin. The physically based computational water quality models would require large spatial and temporal information databases of climatic, hydrologic, and environmental variables and solutions of nonlinear, partial differential equations at each grid point in a river basin. These models suffer from estimability, convergence, stability, approximation, dispersion, and consistency issues. In such a problematic modeling scenario, an artificial neural network (ANN) modeling of 22 stream water quality parameters (SWQPs) is performed from easily measurable data of precipitation, temperature, and novel land use parameters obtained from Geographic Information System (GIS) analysis for the Godavari...
The activities undertaken under the Mahatma Gandhi National Rural Employment Guarantee Act in
potential to enhance and provide environmental services. Key programmes implemented in 20 village... more potential to enhance and provide environmental services. Key programmes implemented in 20 villages during 2009 were studied using rapid scientific assessment methods. An indicator approach was adopted to analyse environmental services such as water for irrigation and improvement in soil quality. The status of environmental services before and after implementation of the activities was examined and vulnerability indices were constructed and compared. The activities were found to have reduced the vulnerability of agricultural production, water resources and livelihoods to uncertain rainfall, water scarcity and poor soil fertility. We thank GTZ India for initiating and supporting the project. In particular, we acknowledge the support provided by Vera Scholtz and Kasturi Basu. We benefi ted from discussions with the Ministry of Rural Development, Government of India, especially with Rita Sharma and Amita Sharma. We thank Joyashree Roy, K Narayanan, and Sandhya Rao for assisting with met...
A Novel Approach to Select Anchor Pixels in Sebal Model by Using Inputs from SAR Images
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
The proper selection of anchor pixels (hot and cold pixels) for calculating the sensible heat flu... more The proper selection of anchor pixels (hot and cold pixels) for calculating the sensible heat flux (H) in SEBAL (Surface Energy Balance Algorithm for Land) is a critical aspect to be considered. The current study proposes a novel method to select the cold and hot pixels using the soil moisture measurements derived from the SAR images. The Water cloud Model (WCM) derived soil moisture values combined with NDVI and Land Surface Temperature values were used to locate the anchor pixels in the current study. The results confirmed that the capability of SAR images combined with optical images will help in the appropriate selection of anchor pixels. The ET values obtained in the study showed good agreement with the ground conditions.
Microplastics are classified as emerging pollutants of the aquatic environment, necessitating a c... more Microplastics are classified as emerging pollutants of the aquatic environment, necessitating a comprehensive understanding of their properties for successful management and treatment. Wastewater treatment plants (WWTPs) serve as point sources of microplastic pollution of the aquatic and terrestrial (eco)systems. The first part of this review explores the basic definitions of microplastics, sources, types, physical and chemical methods of identifying and characterizing microplastics in WWTPs. The next part of the review details the occurrence of microplastics in various unit processes of WWTPs and sewage sludge. Followed by this, various methods for removing microplastics from wastewater are presented. Finally, the research gaps in this area were identified, and suggestions for future perspectives were provided.
Self-adaptive cuckoo search algorithm is used to optimize the design of water distribution system... more Self-adaptive cuckoo search algorithm is used to optimize the design of water distribution system problems. It is proposed to dynamically adjust the two sensitive parameters of the algorithm, (i) step size control parameter 'α' and (ii) discovering probability parameter 'Pa' which largely govern the exploration and exploitation search strategies of the algorithm. These parameters are essential for enhancing the performance of the algorithm and normally the values of these parameters needs careful selection according to the type of problem. Single objective self-adaptive cuckoo search algorithm (SACSA) and multiobjective self-adaptive cuckoo search algorithm (SAMOSCA) are proposed in this study. Robustness and efficiency of these algorithms in single (minimization of cost) and multiobjective scenarios (minimization of cost and maximization of resilience) is validated using standard water distribution benchmark problems i.e. Two loop and Hanoi network. These are later applied to solve a medium size real-life water distribution system located at Pamapur, Telangana, India. A simulation-optimization based program combining the water distribution network simulation software EPANET 2.2 and MATLAB is used for computation. The proposed methodology has provided better results in terms of computational efficiency as well as found better solutions when compared to the previously reported results in both single and multi-objective scenarios. In the case of multi-objective problems, it has been observed that SAMOCSA has been able to find new points in pareto front when compared to the best-known pareto front reported in the literature. Selfadaptive cuckoo search algorithm has been found to be an attractive alternative in both exploration and exploitation of larger search spaces for finding better optimal solutions.
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Papers by Murari Varma