Mexico contains a high percentage of marginalized communities, as well as geographic areas with high annual precipitation (approximately 2000 mm). This study uses regional water access and precipitation data to determine municipalities that would most benefit from the installation of Domestic Rain Water Harvesting Systems (DRWHS). The main objective was to find a relationship between local conditions (marginalization, expected level of service, and precipitation) and the physical components of DRWHS. First, monthly precipitation and the number of inhabitants per household were determined for each municipality. Catchment area and tank size were then calculated for a single dwelling by municipality using water demand, run-off coefficient, monthly precipitation, and number of inhabitants per household. In general, municipalities with very low access to municipal water and very high precipitation were found in the southern area of the country. A curve that estimates catchment area based on annual precipitation was developed using the selected municipalities, which produced an average catchment area of 113.3 m² for a water demand of 100 L/capita/day. While any DRWHS must be designed specific to local conditions, this study has determined that a regional approximation can be used to select ideal communities for these systems, which can in turn facilitate national implementation.

Urban groundwater management requires complex environmental models to represent interactions between hydrogeological processes and infrastructure systems. While the impacts of external uncertainties, such as climate and population growth, have been widely studied, there is limited understanding of how decision support is altered by endogenous uncertainties arising from model parameters and observations used for calibration. This study investigates (1) the importance of observation choice and parameter values on aquifer management objectives when controlling for model error and (2) how the relative performance of management alternatives varies when exposed to endogenous uncertainties, both individually and in combination. We use a spatially distributed groundwater model of the Valley of Mexico, where aquifer management alternatives include demand management, targeted infiltration, and wastewater reuse. The effects of uncertainty are evaluated using global sensitivity analysis, performance ranking of alternatives under a range of human–natural parameters, and identification of behavioral parameter sets filtered with an error metric calculated from varying subsets of observations. Results show that the parameters governing hydraulic conductivity and total water use in the basin have the greatest effect on management objectives. Error metrics (i.e., squared residuals of piezometric head) are not necessarily controlled by the same parameters as the head-based objectives needed for decision-making. Additionally, observational and parameter uncertainty each play a larger role in objective variation than the management alternatives themselves. Finally, coupled endogenous uncertainties have amplifying effects on decision-making, leading to larger variations in the ranking of management alternatives than each on their own. This study highlights how the uncertain parameters of a physically based model and their interactions with uncertain observations can affect water supply planning decisions in densely populated urban areas.

Achieving sustainable water resources management objectives can work in tandem with poverty reduction efforts. This study evidenced the strong social hydrological linkages that exist in Cambodia, which allowed for presenting a broader understanding of water resources challenges to better formulate and connect policies at the local and national levels. Models are often not developed with household- or community-level input, but rather with national- or coarse-level datasets. The method used in this study consisted of linking qualitative and quantitative social analysis with a previously developed technical water planning model. The results from the social inequalities analysis were examined for three water use types: domestic, rice production, and fishing in three parts of the watershed, namely, upstream, midstream, and downstream. Knowledge generated from the social analysis was used to refine previous water planning modeling. The model results indicate that without household data to consider social inequalities, the technical analysis for the Stung Chinit watershed was largely underrepresenting the shortages in irrigation supply seen by groups in the most downstream sections of the irrigation system. Without adding social considerations into the model, new policies or water infrastructure development suggested by the model could reinforce existing inequalities.

The interlinkages between water for irrigation and for fish habitat are complex. This is particularly true in the Stung Chinit, a tributary to one of the most robust fisheries in the world, where livelihoods rely heavily on rice production and fishing and there is pressure to increase rice production with increased irrigation. This study assesses the tradeoffs between various management options and irrigation strategies in the Stung Chinit watershed under multiple projections of climate change. Due to the relative demands for instream flows and rice, if dry season rice is widely promoted, flows will be severely impacted. However, implementing a flow requirement protects these flows, while only causing minor shortages to rice when planted once or twice per year. These shortages may be alleviated with improved cooperation, management and shifting rice irrigation practices. While climate change will lead to warming temperatures and potentially higher demands for irrigation, the larger threat to rice and ecosystems appears to be water management (or lack thereof). This study suggests that there is sufficient water in the system to expand the irrigated area by 10%, grow rice twice per year and protect downstream flows under climate change; however, well-coordinated management is required to achieve this.