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En este trabajo se presenta una aplicación práctica del uso de las tecnologías de la información y comunicación (TIC) en la gestión de riesgos de desastres debidos a precipitaciones extremas en regiones urbanas. El objetivo es plantear, a partir del caso de estudio del deslizamiento del cerro del Chiquihuite, una de las formas en las que se puede aprovechar la información del Observatorio Hidrológico del Instituto de Ingeniería de la Universidad Nacional Autónoma de México (OH-IIUNAM) para mejorar la gestión de desastres generadas por precipitaciones extremas. En el caso de estudio, se utilizan los datos del OH-IIUNAM para el análisis temporal y espacial de las tormentas que se presentaron en la Zona Metropolitana del Valle de México entre el 1 y 9 de septiembre de 2021; también se considera el sismo que ocurrió el 7 de septiembre del mismo año. La conjunción de ambos fenómenos produjo un deslizamiento del cerro el 10 de septiembre de 2021, que provocó grandes daños en las viviendas y pérdidas humanas. En el análisis temporal realizado se encontró que las tormentas más importantes ocurrieron entre los días 1 y 8 de septiembre, destacando las tormentas de los días 6 y 7 en intensidad y precipitación acumulada. En cuanto al análisis espacial, se utilizó la interpolación IDW (interpolación de distancia inversa ponderada) para estimar la precipitación en toda la Ciudad de México (CDMX) en el periodo del 1 al 9 de septiembre, encontrándose que la zona del cerro del Chiquihuite fue una de las áreas donde cayó mayor cantidad de agua de lluvia.

Este trabajo representa una contribución para evaluación de las condiciones de las redes de observación de la precipitación en un área urbana, a partir de la comparación entre una red de sensores de disdrómetros ópticos láser (DOL) y una red de pluviómetros de balancín (PB) en la Ciudad de México. En la metodología se seleccionaron 9 estaciones DOL y 16 estaciones PB, las cuales se compararon de dos formas: primero, a partir de la acumulación total de precipitación durante tres años y segundo, por eventos de tormenta. Los resultados indican, que el análisis por eventos de tormenta es más representativo que comparando la precipitación acumulada. Las mediciones son aceptables, ya que estas se comprobaron a partir de correlaciones lineales. Asimismo, se determinó que el número de eventos y la distancia entre las estaciones contribuyen en la correlación de las mediciones. Es deseable que la metodología se aplique en el control de calidad periódico de las mediciones (calibración) y sea parte de las buenas prácticas para la medición del ciclo hidrológico urbano a escala local.

As the world continues urbanizing, including efforts to forge a new framework of urban development is necessary. Recent studies related to flood prediction and mitigation have shown that Ensemble Prediction Systems (EPSs) constitute a valuable and essential tool for an Early Warning System. However, the use of EPS for flood forecasting in urban zones has yet to be understood. This work has the objective to investigate the potential use of the Operational EPS, issued by the European Centre for Medium-Range Weather Forecasts (ECMWF), for probabilistic urban flood prediction. In this research, a precipitation forecast verification was carried out in two study zones: (1) Mexico Valley Basin and (2) Mexico City, where for the latter, forecasts were compared against real-time observed data. The results showed good forecast reliability for a rain threshold of up to 20 mm in 24-hourly accumulations, with the first 36 h of the forecast horizon being the most reliable. The EPS has sufficient resolution and precision for flood prediction in Mexico City, which represents a further step toward developing a flood warning system at the local level based on ensemble forecasts. HIGHLIGHTS ECMWF's forecast evaluation from real-time measurements and at a temporal resolution of less than 12 h.; Implementation of a predictive model to predict the occurrence of a flood event.; To extend the use of EPS to include them in the chain for emergency and decision-making.; This work seeks to shorten the gap of previous research and direct its efforts to the evaluation of urban and flash floods.;

El estado de Tabasco, México, es altamente vulnerable a inundaciones. La más grave de los últimos años fue en 2007 y cubrió el 62% de su territorio. A raíz de este suceso surgió el Plan Hídrico Integral de Tabasco, con el objeto de encontrar soluciones para disminuir la vulnerabilidad de la zona ante eventos extremos.Una de ellas consiste en el desvío de grandes caudales hacia el río Samaria, que desemboca al mar por el río González. Este estudio analiza el comportamiento de los flujos del sistema río González-Mecoacán y el rol de la marea en su regulación. En el río González, el flujo hacia el mar es disminuido de forma considerable en pleamar, llegando a detenerse durante mareas vivas. En el río Hondo (que fluye del río González hacia Mecoacán), el flujo llega a revertirse, mientras que en la boca lagunar está modulado por la marea. Esto sugiere que un aumento considerable en el caudal del río González estaría sujeto a un lento drenaje hacia el mar por efecto de la corriente mareal. Lo anterior causaría un aumento del nivel del río y riesgo de inundación en esa zona durante eventos extremos. Las evidencias de penetración de la onda de marea hasta un sitio alejado de la desembocadura del río sugieren que el flujo río arriba podría también estar modulado por la marea. Además, las observaciones termohalinas indican que la salinidad y temperatura cerca de la desembocadura están gobernadas por intrusión salina, mientras que en sitios alejados dependerían de factores atmosféricos.

The growth of urban population, combined with an increase of extreme events due to climate change call for a better understanding and representation of urban floods. The uncertainty in rainfall distribution is one of the most important factors that affects the watershed response to a given precipitation event. However, most of the investigations on this topic have considered theoretical scenarios, with little reference to case studies in the real world. This paper incorporates the use of spatially-variable precipitation data from a long-range radar in the simulation of the severe floods that impacted the city of Hull, U.K., in June 2007. This radar-based rainfall field is merged with rain gauge data using a Kriging with External Drift interpolation technique. The utility of this spatially-variable information is investigated through the comparison of computed flooded areas (uniform and radar) against those registered by public authorities. Both results show similar skills at reproducing the real event, but differences in the total precipitated volumes, water depths and flooded areas are illustrated. It is envisaged that in urban areas and with the advent of higher resolution radars, these differences will be more important and call for further investigation.

The evaluation of the uncertainties in model predictions is key for advancing urban drainage modelling practice. This paper investigates, for the first time in Mexico, the effect of parameter sensitivity and predictive uncertainty in an application of a well-known urban stormwater model. Two of the most common methods used for assessing hydrological model parameter uncertainties are used: the Generalised Likelihood Uncertainty Estimation (GLUE) and a multialgorithm, genetically adaptive multi-objective method (AMALGAM). The uncertainty is estimated from eight selected hydrologic parameters used in the setup of the rainfall-runoff model. To ensure the reliability of the model, four rainfall events varying from 20 mm to 120 mm from minor to major count classes were selected. The results show that, for the selected storms, both techniques generate results with similar effectiveness, as measured using well-known error metrics; GLUE was found to have a slightly better performance compared to AMALGAM. In particular, it was demonstrated that it is possible to obtain reliable models with an index of agreement (IAd) greater than 60 and average Absolute Percentage Error (EAP) less than 30 percent derived from the uncertainty analysis. Thus, the quantification of uncertainty enables the generation of more reliable flow predictions. Moreover, these methods show the impact of aggregation of errors arising from different sources, minimising the amount of subjectivity associated with the model’s predictions.

This paper describes the most important results of a theoretical, experimental and in situ investigation developed in connection with a water supply pumping pipeline failure. This incident occurred after power failure of the pumping system that caused the burst of a prestressed concrete cylinder pipe (PCCP). Subsequently, numerous hydraulic transient simulations for different scenarios and various air pockets combinations were carried out in order to fully validate the diagnostic. As a result, it was determined that small air pocket volumes located along the pipeline profile were recognized as the direct cause of the PCCP rupture. Further, a detail survey of the pipeline was performed using a combination of non-destructive technologies in order to determine if immediate intervention was required to replace PCC pipes. In addition, a hydraulic model was employed to analyze the behavior of air pockets located at high points of the pipeline.

Drought has been a recurrent phenomenon in Mexico. For its assessment and monitoring, several studies have monitored meteorological droughts using standardized indices of precipitation deficits. Such conventional studies have mostly relied on rain gauge-based measurements, with the main limitation being the scarcity of rain gauge spatial coverage. This issue does not allow a robust spatial characterization of drought. A recent alternative for monitoring purposes can be found in satellite-based remote sensing of meteorological variables. The main objective of this study is to evaluate the standardized precipitation index (SPI) in Mexico during the period 1998 to 2013, using the Tropical Rainfall Measuring Mission (TRMM) satellite product 3B42. Results suggest that Mexico experienced the driest conditions during the great drought between 2011 and 2012; however, temporal variability in the SPI was found across different climatic regions. Nevertheless, a comparison of the SPI derived by TRMM against the rain gauge-based SPI computed by the official Mexican Drought Monitor showed low to medium correlation of the time series though both SPIs managed to capture the most relevant droughts at the national scale. We conclude that the TRMM product can properly monitor meteorological droughts despite its relative short dataset length (~15 years). Finally, we recommend an assimilation of rain gauge and satellite-based precipitation data to provide more robust estimates of meteorological drought severity.