Weather Radar Data and Distributed Hydrological Modelling: An Application for Mexico Valley

Abstract

<span>The frequent occurrence of exceptionally very heavy rainfall in Mexico during the summer causes flash floods in many areas and major economic losses. As a consequence, a significant part of the annual government budget is diverted to the reconstruction of the disasters caused by floods every year, resulting hold up in the country development. A key element to mitigate the flash flood hazards is the implementation of an early warning system with the ability to process the necessary information in the shortest possible time, in order to increase structural and non-structural resilience in flood prone regions. The real-time estimation of rainfall is essential for the implementation of such systems and the use of remote sensing instruments that feed the operational rainfall-runoff hydrological models is becoming of increasing importance worldwide. However, in some countries such as Mexico, the application of such technology for operational purposes is still in its infancy. Here the implementation of an operational hydrological model is described for the Mixcoac river basin as part of the non-structural measures that can be applied for intense precipitation events. The main goal is to examine the feasibility of the use of remote sensing instruments and establish a methodology to predict the runoff in real time in urban river basins with complex topography, to increase the resilience of the areas affected by annual floods. The study takes data from weather radar operated by the National Meteorological Service of Mexico, as input to a distributed hydrological model. The distributed unit hydrograph model methodology is used in order to assess its feasibility in urban experimental basin. The basic concepts underlying the model, as well as calibration and validation are discussed. The results demonstrate the feasibility of using weather radar data for modeling rainfall-runoff process with distributed parameter models for urban watersheds. A product resulting from this study was the development of software Runoff Forecast Model (ASM), for application in distributed hydrological models with rainfall data in real time in watersheds with complex terrain, which are usually found in Mexico.</span><span></span

Modelo hidrológico distribuido con imágenes GPM-IMERG en la cuenca del río Huaynamota, Nayarit, México

“…Además, si los datos requeridos son horarios y se tienen exigencias en cuanto a su distribución espacial, la complejidad de tenerlos crece, porque requiere una capacidad de datos temporal y espacial. Méndez-Antonio et al (2013) señalan que tecnologías como el radar y satélites meteorológicos tienen la capacidad para estimar la variabilidad espacial de la precipitación en tiempo real, lo cual es muy útil en modelaciones hidrológicas. Con el apoyo de aplicaciones SIG (Sistema de Información Geográfica) es posible generar información con poca variabilidad temporal al momento del evento.…”

Tropical Andes Radar Precipitation Estimates Need High Temporal and Moderate Spatial Resolution

“…In this regard, rainfall data acquired from different remote sensors, such as weather radar systems, have become more accessible over the last few years [5]. This technology has allowed us to study rainfall with high spatial and temporal resolutions [6], and it can be used in several applications, such as input data in rainfall forecasting studies [7][8][9][10][11], different hydrological models [12,13], early warning systems for floods [14], erosion studies [1,15], research related to atmospheric chemistry [16], and many others. Meanwhile, cost-effective systems derived from ship radar technology are available to establish radar networks with limited funds at hand [17].…”