This investigation evaluates the effects of hydrological uncertainty in the results of flood extent estimates during the incidence of a tropical storm. For this, the methodology is comprised of field measurements, elevation data, a distributed hydrological model and a standard two‐dimensional numerical model. Uncertainty is considered in the distributed hydrological model through the estimation of possible hydrographs from precipitation data registered during the incidence of an extreme event. The characterisation of the run‐off by multiple possibilities opens the door to a probabilistic estimation of flood maps, enabling the consideration of hydrological uncertainties and their propagation to an estimated flood extension. It is shown that during the incidence of the tropical storm Arlene, the estimated flooded area is similar to what was registered by satellite imagery. Although the methodology does not consider all the uncertainties that may be involved in the determination of a flooded area, it is reflected that it favours the preventive action in the generation of flood management strategies. The selected approach is a first iteration in the production of a fully quantified approach to the analysis of flood risk, especially where there are doubts about how the catchment responds to a given extreme precipitation event.

Abstract. Meeting future water demand without degrading ecosystems is one important indicator of sustainable development. Using simulations, we showed that compared to existing policy, more sustainable water supply options are similar or cheaper in cost. We probabilistically forecasted the Mexico City metropolitan zone population for the year 2015 to be 23.5 million and total required water supply to be 106 m 3 s -1. We optimized existing and potential supply sources from aquifers, surface water, treatment/reuse, and efficiency/demand management by cost to meet future supply needs; the applied source supply limits determined the degree of sustainability. In two scenarios to supply 106 m 3 s -1, the business-as-usual scenario (zero sustainability ) had an average relative unit cost of 1.133; while for the most sustainable scenario (it includes reducing potential supply basins' exploitation limits by 50%), the value was 1.121. One extreme scenario to supply the forecast's 95% confidence value (124 m 3 s -1) showed little unit cost change (1.106). The simulation shows sustainable policies can be cost-effective.

No abstract

2015): Failure of a drainage tunnel caused by an entrapped air pocket, Urban Water Journal,A severe storm event occurred over the western area of Mexico City causing the rupture of a drainage tunnel, resulting in surface flooding, severe infrastructure damage and three deaths. This paper describes the methodology followed in order to validate the diagnostic of the event. The detailed investigation comprised in situ observation of the system, as well as hydraulic and structural analyses. In this case, severe pressure oscillations inside the tunnel caused by rapid filling and sudden air leakage through a large orifice (manhole) were recognized as the direct cause of the conduit burst. Further, the low strength of the concrete pipes of the tunnel, constructed without reinforced steel, and the low confinement by the dead load due to the soil above the tunnel also contributed to the rupture. The numerical results show a very unfavorable stress distribution along the tunnel stretch where the accident occurred, sufficient to cause the rupture.

This paper presents the application of genetic programming to the generation of models to assess the total runoff of a basin starting from the total rainfall in it and using data recorded in a sub-basin at the valley of Mexico (the Mixcoac sub-basin to the west of Mexico City). The modelling process is developed contrasting two types of models with different complexity degree: (1) a nonlinear model whose complexity is resolved using multi-objective optimization and (2) a nonlinear model with a given structure obtained by means of a physical interpretation of the dynamics of the direct and the base flow. Data from two storms (rainfall and runoff), one in 1997 and another in 1998, were used in testing the models. First, the storm in 1997 was used for the calibration step and that in 1998 for the validation step. Afterwards, the order was reversed. An interpretation of the results, focused on the applicability and possible improvement of the models in forecasting runoff, is made through their discussion and is summarized in the conclusions.