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In this paper, we discuss a challenging water resources problem in a developing world city, Chennai, India. The goal is to reconstruct past system behavior and diagnose the causes of a major water crisis. In order to do this, we develop a hydrologic-engineering-economic model to address the complexity of urban water supply arising from consumers' dependence on multiple interconnected sources of water. We integrate different components of the urban water system: water flowing into the reservoir system; diversion and distribution by the public water utility; groundwater flow in the aquifer beneath the city; supply, demand, and prices in the informal tanker-truck-based water market; and consumer behavior. Both the economic and physical impacts of consumers' dependence on multiple sources of water are quantified. The model is calibrated over the period 2002-2006 using a range of hydrologic and socio-economic data. The model's results highlight the inadequacy of the reservoir system and the buffering role played by the urban aquifer and consumers' coping investments during multiyear droughts. [ABSTRACT FROM AUTHOR]

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. Key Points: The inertial formulation of the Saint‐Venant equations is unstable when applied to low friction areas typical of urban environmentsNumerical stability is improved using the diffusive term, but calibration is required to obtain an optimal value of the diffusion coefficientThis study proposes an explicit expression for the diffusion coefficient, obviating the need for trial and error calibration [ABSTRACT FROM AUTHOR]