In rapidly growing urban areas in India and the developing world, water demands typically exceed supply. While local governments may implement management programs to reduce demand for freshwater, water savings are dependent on the conservation behaviors of individuals. A household survey is presented here to examine residential water end uses and conservation behaviors in Jaipur, India. The survey explores end uses, engagement in conservation behaviors, and the influence of demographic factors, water sources, beliefs about water, and social pressures on these behaviors are tested. The survey was conducted at 248 households, including 29 households in the slums. Our study finds that while the majority of participants recognize the importance of water conservation, they do not necessarily conserve water themselves. Households report engaging most frequently in water-conservation behaviors that require little effort or financial investment. Multivariate analysis of variance (MANOVA) results and subsequent pairwise comparisons indicate higher incomes, longer water-supply durations, and the belief that droughts are preventable are positively correlated with overall amenability to adoption of water-conservation behaviors and technology. Binomial logistic regression analysis indicates that being in the age group 26–35, having higher income, and giving a neutral response about the responsibility of the government to provide relief during a drought were all predictors of the installation of dual-flush (DF) toilets. Education levels and water awareness were found to have no correlation with conservation behaviors or amenability to conservation technology adoption. Results are applied to examine their possible implications from a demand-management perspective and provide suggestions for further research and policy decisions.

Water availability is increasingly stressed in cities across the world due to population growth, which increases demands, and climate change, which can decrease supply. Novel water markets and water supply paradigms are emerging to address water shortages in the urban environment. This research develops a new peer-to-peer non-potable water market that allows households to capture, use, sell, and buy rainwater within a network of water users. A peer-to-peer non-potable water market, as envisioned in this research, would be enabled by existing and emerging technologies. A dual reticulation system, which circulates non-potable water, serves as the backbone for the water trading network by receiving water from residential rainwater tanks and distributing water to households for irrigation purposes. Prosumer households produce rainwater by using cisterns to collect and store rainwater and household pumps to inject rainwater into the network at sufficiently high pressures. The smart water grid would be enabled through an array of information and communication technologies that provide capabilities for automated and real-time metering of water flow, control of infrastructure, and trading between households. The goal of this manuscript is to explore and test the hydraulic feasibility of a micro-trading system through an agent-based modeling approach. Prosumer households are represented as agents that store rainwater and pump rainwater into the network; consumer households are represented as agents that withdraw water from the network for irrigation demands. An all-pipe hydraulic model is constructed and loosely coupled with the agent-based model to simulate network hydraulics. A set of scenarios are analyzed to explore how micro-trading performs based on the level of irrigation demands that could realistically be met through decentralized trading; pressure and energy requirements at prosumer households; pressure and water quality in the pipe network.

The spread of individual water conservation behaviors within a population can have large impacts on overall water demand. Agent-based models (ABMs) represent individual actors that update their behaviors over time in response to their environment and other agents, and ABMs have been applied to model the adoption of water conservation behaviors and technology. Existing ABM approaches are calibrated based on cumulative water demand data and use assumptions about household-level adoption behaviors. This research develops an ABM of water appliance (dual-flush toilets) adoption and introduces a new approach to calibrate the ABM while allowing for stochasticity and heterogeneity in agent parameters and adoption decisions. The calibration approach uses a noisy genetic algorithm (NGA), and the ABM is calibrated to match household survey data that was collected in Jaipur, India, in 2015. The NGA is applied multiple times to explore variability in the search, and five solutions were found with similar error values. The best-performing solution is applied to project adoption over a 100-year period for varying climate scenarios, and results show quicker adoption rates for dry climates. Sensitivity analysis was conducted for a parameter that represents a delay in adopting dual-flush toilets and a parameter that represents the importance of drought in making adoption decisions. The model presented in this research can be used to aid water resource planning and to anticipate potential impacts of water conservation policies, such as rebate programs or media campaigns.

The growth of urban water demands in many developing countries outpaces the expansion of water infrastructure, and growing populations may meet immediate water needs through private wells and illegal connections. Demand management strategies can avert the depletion of water resources by encouraging conservation and installation of water-efficient technologies. In many developing urban areas, however, significant heterogeneity may exist among water consumers in their sources of water, end use applications, and individual responses to messages about water conservation. Consequently, predicting the performance of demand management strategies using simple demand projections may neglect significant interactions and decision-making among users. An agent-based modeling approach is developed here to simulate the spread of water conservation technologies within a community in response to conservation policies, which target portions of the population using different messaging techniques. Agents represent households, and water use behaviors are coded based on data derived from a household survey of 248 households on water use behaviors and willingness to conserve water. Management strategies are simulated to represent direct messaging from government officials to reduce overall water consumption and indirect messaging from government officials and religious officials. The framework is applied for Jaipur, India, a city with a population of approximately 3.2 million people. The agent-based model is applied to project reduction of overall consumption rates due to the spread of water conservation technology, and results are compared to projected water demands at the current residential water consumption rate.