Soumendra Nath Kuiry

An existing water distribution network (WDN) may need to be expanded by adding a sub-network for the newly developed areas. The size of the problem becomes larger when the stochastic nature of domestic demands, optimal design and layouts, control, and operation of various hydraulic components are considered. In this study, the single-port Thevenin theorem used in electrical circuits is applied to reduce a large WDN with its equivalent network consisting of a single source and a single pipe. The equivalent network is then attached to a sub-network for focused analysis. The accuracy and robustness of the proposed network reduction procedure are investigated on realistic WDNs for various sub-network demands using steady and extended period simulations. A simplified approach is also presented to achieve the same objective but constrained by the level of accuracy. Hydraulic engineers can use the proposed methodology as an efficient network reduction tool.

The necessity to protect coastal regions from sea-level rise (SLR) and extreme events demands a rigorous assessment of coastal vulnerability. The intergovernmental panel for climate change (IPCC) predicts that climate change will severely impact the coastal region, river systems, and urban infrastructures. The changing climate is observed to be increasing the frequency and magnitude of extreme hydrometeorological conditions, such as storm surges that adversely affect coastal areas by flood inundation. This study emphasizes the need to use extreme events and socio-economic data to evaluate the Coastal Vulnerability Index (CVI) for planning and adaptation measures. Therefore, the present study utilizes spatially varying surge heights for improved estimation of the CVI, unlike the constant surge heights considered in the previous studies. For coastal adaptation measures, synthetic cyclones of different return periods, such as 20-, 50- and 100-year, are simulated using a hydrodynamic model to represent a range of risk and vulnerability in the estimated CVI. The proposed methodology for calculating the CVI is demonstrated by considering the Chennai coast in the state of Tamil Nadu, India. The use of spatial distribution of storm surges from hydrodynamic simulations makes the CVI more realistic. Such thorough assessments utilizing high-resolution CVI maps can help policymakers suggest appropriate measures for specific coastal zones, which are more devastatingly affected by shoreline erosion, SLR and storm surge. The vulnerability assessment indicates that great care is needed in the planning and adaptation of the coastal ecosystem to extreme events for the safety and well-being of coastal populations and infrastructures.

River morphodynamics deals with the evolution of river geometry, flow path, and associated sediment/alluvial depositions. A concise understanding of the river dynamics and spatio-temporal analysis of river morphology is a primary prerequisite for waterway development, waterbody restoration, and flood hazard mitigation. A high degree of unplanned urbanization, human settlements on the floodplains, climate change, and natural disasters have altered the course and morphodynamics of many rivers in the world. This has destroyed the natural biodiversity and has resulted in frequent floods and degradation of water quality. The present study focuses on analyzing morphodynamic changes of the Adyar River flowing through the Chennai city of Tamil Nadu state in India. Temporal evolution for the past 30 years is assessed using Google Earth Engine (GEE) platform and image processing techniques. Cloud masked Landsat satellite images are analyzed using Modified Normalized Difference Water Index, Normalized Difference Vegetation Index, and Enhanced Vegetation Index to extract the annual river channels and alluvial deposits. Results show a slight shift of the flow path and increased deposition of sediments towards the river mouth, where it joins the Bay of Bengal in the Adyar Estuary. This may be attributed to the high degree of unplanned urbanization and floodplain encroachments in the past decades. The morphological changes over time have worsened the damages during the frequent flood events in recent times. The results of this study can be used to regain the health of the Adyar River and consequently reduce the damages caused by floods in the future.

This paper describes the experiments carried out on flood hydrodynamics in a river-network-floodplain set-up for validating numerical models. Fluvial floods in the set-up are generated due to overbank flow. The flood extent is extracted by processing overlapping images of the flooded set-up. The steady-state flow depths and velocities are measured by a point gauge and acoustic Doppler velocimeter (ADV), respectively. The surface velocities are estimated using large scale particle image velocimetry (LSPIV). The details of these measurements, flood hydrodynamics and datasets collected in the experiments are presented and analysed. Two numerical models of varying complexities are applied to reproduce the experimental events. The comparisons of numerical and experimental results on the different aspects of floods highlight the importance of the observed datasets. The complete flood datasets may be used to calibrate flow models, evaluate drying-wetting and model coupling algorithms. The datasets are freely available for academic purpose.

The estimation of maximum storm surges along a coast is indispensable for emergency action planning, design, and adaptation of coastal infrastructure. The existing studies on the Bay of Bengal coast have used synthetic tracks with constant track parameters such as the maximum wind speed, radius of maximum wind, and central pressure to estimate the probable maximum storm surges. However, the analysis of the best tracks from the Joint Typhoon Warning Center during 1978–2019 shows that the track parameters vary from origin to landfall locations. The reported studies along the Bay of Bengal have failed to capture such variations and overestimated probable maximum storm surges due to constant track parameters. Therefore, this study proposes a methodology for estimating wind speed of various return periods and associated track parameters that vary along a synthetic track. The wind speed of different return periods is computed at each eye location using the probabilistic approach. Thus, the calculated wind speeds vary from origin to landfall locations, and such a pattern of wind speed variation is observed to be similar to the historical cyclones. The radius of maximum wind and central pressure is calculated using the regression equations derived from historical tracks. The accuracy of the proposed methodology is investigated by simulating the cyclones Thane and Vardah that occurred along the Tamil Nadu coast. The results suggest that the varying track parameters using the proposed methodology produce realistic surge values similar to parameters from best track data, and it overcomes the overestimation of surge heights. The proposed methodology is further utilized to analyse the maximum surge scenarios along the Tamil Nadu coast resulting from various track shifts and angles of attack. The proposed methodology is expected to improve the estimation of storm surges in other basins.

The boundaries of existing cities are expanding rapidly due to the exponential growth in urban population. Therefore, the existing water distribution networks (WDNs) need to be expanded up to the newly developed areas to meet the additional water demand. The optimal design of a sub-network planned for network expansion requires multiple simulations under various constraints. Simulating the additional sub-network along with the existing network takes a lot of CPU time. In this study, a methodology is proposed to replace an existing large pipe network with its equivalent network consisting of a single source and a single pipe by applying the non-linear Thevenin theorem being used for electrical circuits. The equivalent network model parameters are extracted by fitting the driving-node head-loss characteristics at the connecting node. Unlike all other available methods except the traditionally used reservoir–pump model, the equivalent network presented in this study reduces to only two elements. The theoretical aspect of the reservoir–pump model can be explained by the proposed Thevenin reduction method. The advantage of the proposed method is put forward by deriving an analytical expression for the condition of maximum power transfer from the equivalent main network to the sub-network. The economic diameter value of the connecting pipe is subsequently determined. The proposed network reduction method is demonstrated on different WDNs for various demand patterns. The reduced networks yield accurate results and simulate faster when compared with those of the original networks. The proposed methodology is beneficial for a focused analysis of a sub-network and to transfer maximum power to the sub-network connected to a large existing hydraulic network.

Two-dimensional shallow water models have been widely used in forecasting, risk assessment, and management of floods. Application of these models to large-scale floods with high-resolution terrain data significantly increases the computation cost. In order to reduce computation time, shallow water models are simplified by neglecting the inertial and/or convective acceleration terms in the momentum equations. The local inertial models have proved to significantly improve the computational efficiency even for large-scale flood forecasting. However, instability issues are encountered on smooth surfaces of urban areas having low friction values. This problem was resolved by de Almeida et al. (2012, https://doi.org/10.1029/2011WR011570) by introducing limited artificial diffusion in the form of weighting factors for the neighboring fluxes. The arbitrary value of the weighting factor poses a practical limitation of being case specific and requiring calibration for accurate solutions. This study derives an explicit expression for the weighting factor, an adaptive formulation dependent on local velocity, flow depth, grid, and time step size, which eliminates the need for trials and approximations. Comparisons between analytical, experimental, and real-world applications confirm the accuracy and robustness of the proposed weighting factor. Implementation of adaptive weights results in less computation time compared to LISFLOOD-FP (~1.2 times) and holds a significant advantage over HEC-RAS (~25.9 times) as it allows the use of larger time step at higher Courant-Friedrichs-Lewy (CFL) values. The contribution of the present study therefore resolves an important problem of current large-scale flood simulations, especially those implemented in real time.

Due to rapid urbanization, the existing water distribution networks need to be expanded by adding sub-networks for the newly developed areas. The stochastic nature of demands requires several simulations of the full network for optimum design and cost minimization. The size of the simulation problem thus becomes complex and computationally expensive. The reduced models can be handy for designing and optimizing such networks. This paper describes the usage of equivalent electrical circuit theory to reduce a large water distribution network for focussed analysis of a sub-network. Two methodologies are proposed to obtain the equivalent network using linear and nonlinear forms of the Thevenin theorem. Unlike other network reduction methods, the reduced equivalent networks derived from these methodologies have only two elements, such as a reservoir and an equivalent pipe for the existing network. In the first method, the nonlinear pipe network is replaced and implemented with its analogous linear electrical network in a circuit simulator for finding open circuit voltage and short circuit current at the desired node and branch. The equivalent pipe network parameters are estimated using these values. In the second method, the equivalent network parameters are extracted by ffitting the driving point headloss characteristics at the desired node with a suitable headloss formula. Applicability and comparison of the proposed network reduction methodologies are demonstrated on a realistic water distribution network connected with a sub-network. The simulated results of the reduced networks are compared with the solutions of the original nonlinear network. The reduced network obtained from the second method is found to yield more accurate results than the first method when the driving point headloss characteristic curve is fitted accurately. The reduced networks can be solved in much less computation cost than the original network. Therefore, the proposed network reduction methodologies are beneficial for analyzing a focused part, i.e. sub-network, of a large pipe network with stochastic demands in much less computational effort.

Expansion and reorganization of water distribution networks by connecting sub-networks via single or multiple pipes are common practices in developing cities to serve newly developed areas. In that context, the existing large network is often replaced with its equivalent simplified network for the optimal design of the upcoming sub-networks to avoid the computational burden. The reservoir-pump model is frequently used by practicing hydraulic engineers to replace an existing one; however, such a model should be applied only when the networks are connected through a single pipe. In this study, a new network reduction methodology is developed for multi-port connections utilizing the analogy between electrical circuits and hydraulic networks. The equivalent simple network is obtained by suitably applying the generalized Thevenin theorem for electrical circuits. The number of network elements in the equivalent network is significantly reduced compared to the ones obtained by the existing water distribution network (WDN) reduction methods. Therefore, it is possible to reorganize and expand a large existing network system from a prior knowledge of its most sensitive parts. The accuracy and robustness of the proposed methodology are investigated on realistic WDNs by comparing the results with EPANET, for both Demand Driven Analysis and Pressure Driven Analysis. However, as of now, an electrical simulator is required to implement the proposed methodology due to the absence of current dependent voltage source model in hydraulic simulators. The proposed network reduction method can be of enormous utility for hydraulic engineers and opens up an opportunity to implement new elements in hydraulic simulators.

A hybrid finite-volume/finite-difference scheme is proposed to solve the one-dimensional Boussinesq equations for wave attenuation by vegetation. The effect of vegetation is included as a source term in a form of drag force. The convective part of the equations is discretized by the finite-volume method, while the finite-difference method is used to discretize the remaining terms. The variable values for the local Riemann problem at each cell face are calculated by a fourth-order MUSCL reconstruction method. The source terms and the dispersion terms are discretized using the centered finite-difference schemes up to fourth-order accuracy. The unsteady terms are discretized by the second-order MUSCL-Hancock scheme. The discretized continuity equation is solved explicitly, while the discretized momentum equation is solved using the Thomas algorithm. The developed Boussinesq model is tested with analytical solutions and reported experimental data. To further validate the model, the computed results are compared with the experimental data observed in two vegetated wave flumes. It is demonstrated that the developed model is suitable for predicting wave propagation in vegetated water bodies.