Improving probabilistic flood forecasting through a data assimilation scheme based on genetic programming

Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS) model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time.

Cálculo de la recarga natural en grandes áreas, en función de la litología y la precipitación = Calculation of natural recharge in large areas, as a function of lithology and rainfall

En una región amplia como España se demuestra —mediante inferencias estadísticas sobre una muestra completa de 875 manantiales en los que se conoce su caudal medio y la litología de su área de alimentación y que han sido agrupados en regiones de distinta pluviometría— que la recarga media anual es una fracción fija de la precipitación media para cada litología. Se han establecido así unas tasas de recarga respecto de la precipitación para seis grupos litológicos de diferente permeabilidad: arenas, gravas y formaciones aluviales en general, 8.3%; conglomerados, 5.6%; areniscas, 7.3%; calizas y dolomías, 34.3%; margas, margocalizas, limos y arcillas, 3.3%; otras rocas, 1.3%. Teniendo en cuenta la representatividad de España, la cual tiene una gran variabilidad de litología, pluviometría, topografía, etcétera, estas tasas de recarga respecto de la precipita-ción son probablemente valores cuasi universales que pueden ser utilizados para estimar la recarga media o los recursos hídricos subterráneos medios de regiones amplias en cualquier parte del mundo, salvo en regiones especiales, como las que tienen permafrost, por ejemplo. En todo caso, estas tasas de recarga podrían ser retocadas para cada región según sus particulares características. Los datos de precipitación y litología son muy corrientes, por lo que el método puede ser ampliamente utilizado para completar balances hidráulicos.In a region as large as Spain, annual mean recharge is shown to be a fixed proportion of the mean rainfall for each lithology. This determination is based on statistical inferences from a complete sample of 875 springs for which mean flow and catchment areas are known and which have been grouped into distinct rainfall regions. Recharge rates have thus been established with respect to rainfall for six lithological groups with different permeability: sands, gravels and generally alluvial formations, 8.3%; conglomerates, 5.6%; sandstones, 7.3%; limestone and dolomite 34.3%; marls, marly limestones, silts and clays, 3.3%; and hard rocks, 1.3%. Considering the representativeness of Spain, which is large in size and has a highly varied lithology, topography and rainfall, these recharge rates for rainfall are probably quasi-universal values that can be used to estimate average recharge or average groundwater resources of large regions in any part of the world (except in special cases such as areas with permafrost, for example). For any case, these recharge rates can be adapted to each region according to its particular characteristics. Rainfall and lithology data are very common, and so the method can be widely used to calculate hydraulic balances.

Assessment of insurance coverage and claims in rainfall related risks in processing tomato in Western Spain

An extension of guarantees related to rainfall-related risks in the insurance of processing tomato crops has been accompanied with a large increase in claims in Western Spain, suggesting that damages may have been underestimated in previous years. A database was built by linking agricultural insurance records, meteorological data from local weather stations, and topographic data. The risk of rainfall-related damages in processing tomato in the Extremenian Guadiana river basin (W Spain) was studied using a logistic model. Risks during the growth of the crop and at harvesting were modelled separately. First, the risk related to rainfall was modelled as a function of meteorological, terrain and management variables. The resulting models were used to identify the variables responsible for rainfall-related damages, with a view to assess the potential impact of extending insurance coverage, and to develop an index to express the suitability of the cropping system for insurance. The analyses reveal that damages at different stages of crop development correspond to different hazards. The geographic dependence of the risk influences the scale at which the model might have validity, which together with the year dependency, the possibility of implementing index based insurances is questioned.

Two-dimensional direct rainfall hydraulic models applied to direct calculation of hydrologic events in dams to prevent overtopping

One of the main concerns when conducting a dam test is the acute determination of the hydrograph for a specific flood event. The use of 2D direct rainfall hydraulic mathematical models on a finite elements mesh, combined with the efficiency of vector calculus that provides CUDA (Compute Unified Device Architecture) technology, enables nowadays the simulation of complex hydrological models without the need for terrain subbasin and transit splitting (as in HEC-HMS). Both the Spanish PNOA (National Plan of Aereal Orthophotography) Digital Terrain Model GRID with a 5 x 5 m accuracy and the CORINE GIS Land Cover (Coordination of INformation of the Environment) that allows assessment of the ground roughness, provide enough data to easily build these kind of models

Assessment of insurance coverage and claims in rainfall related risksin processing tomato in Western Spain

An extension of guarantees related to rainfall-related risks in the insurance of processing tomato crops hasbeen accompanied with a large increase in claims in Western Spain, suggesting that damages may havebeen underestimated in previous years. A database was built by linking agricultural insurance records,meteorological data from local weather stations, and topographic data. The risk of rainfall-related dam-ages in processing tomato in the Extremenian Guadiana river basin (W Spain) was studied using a logisticmodel. Risks during the growth of the crop and at harvesting were modelled separately. First, the riskrelated to rainfall was modelled as a function of meteorological, terrain and management variables. Theresulting models were used to identify the variables responsible for rainfall-related damages, with a viewto assess the potential impact of extending insurance coverage, and to develop an index to express thesuitability of the cropping system for insurance. The analyses reveal that damages at different stages ofcrop development correspond to different hazards. The geographic dependence of the risk influences the scale at which the model might have validity, which together with the year dependency, hampers the possibilityof implementing index based insurances is questioned.