Flash floods are of major relevance in natural disaster management in the Mediterranean region. In many cases, the damaging effects of flash floods can be mitigated by adequate management of flood control reservoirs. This requires the development of suitable models for optimal operation of reservoirs. A probabilistic methodology for calibrating the parameters of a reservoir flood control model (RFCM) that takes into account the stochastic variability of flood events is presented. This study addresses the crucial problem of operating reservoirs during flood events, considering downstream river damages and dam failure risk as conflicting operation criteria. These two criteria are aggregated into a single objective of total expected damages from both the maximum released flows and stored volumes (overall risk index). For each selected parameter set the RFCM is run under a wide range of hydrologic loads (determined through Monte Carlo simulation). The optimal parameter set is obtained through the overall risk index (balanced solution) and then compared with other solutions of the Pareto front. The proposed methodology is implemented at three different reservoirs in the southeast of Spain. The results obtained show that the balanced solution offers a good compromise between the two main objectives of reservoir flood control management
Abstract:The study presents a method which can be used to define real-time operation rules for gated spillways (named the K-Method). The K-Method is defined to improve the performance of the Volumetric Evaluation Method (VEM), by adapting it to the particular conditions of the basin, the reservoir, or the spillway. The VEM was proposed by the Spanish engineer Fernando Girón in 1988 and is largely used for the specification of dam management rules during floods in Spain. This method states that outflows are lower than or equal to antecedent inflows, outflows increase when inflows increase, and the higher the reservoir level, the higher the percentage of outflow increase. The K-Method was developed by modifying the VEM and by including a K parameter which affects the released flows. A Monte Carlo environment was developed to evaluate the method under a wide range of inflow conditions (100,000 hydrographs) and with return periods ranging from one to 10,000 years. The methodology was applied to the Talave reservoir, located in the South-East of Spain. The results show that K-values higher than one always reduce the maximum reservoir levels reached in the dam. For K-values ranging from one to ten, and for inflow hydrographs with return periods higher than 100 years, we found a decrease in the maximum levels and outflows, when compared to the VEM. Finally, by carrying out a dam risk analysis, a K-value of 5.25 reduced the expected annual damage by 8.4% compared to the VEM, which represents a lowering of 17.3% of the maximum possible reduction, determined by the application of an optimizer based on mixed integer linear programming (MILP method).
This study addresses the question of how to select the minimum set of storms that should be simulated each year in order to estimate an accurate flood frequency curve for return periods ranging between 1 and 1000 years. The Manzanares basin (Spain) was used as a study case. A continuous 100,000-year hourly rainfall series was generated using the stochastic spatial-temporal model RanSimV3. Individual storms were extracted from the series by applying the exponential method. For each year, the extracted storms were transformed into hydrographs by applying an hourly time-step semi-distributed event-based rainfall-runoff model, and the maximum peak flow per year was determined to generate the reference flood frequency curve. Then, different flood frequency curves were obtained considering the N storms with maximum rainfall depth per year, with 1 ď N ď total number of storms. Main results show that: (a) the degree of alignment between the calculated flood frequency curves and the reference flood frequency curve depends on the return period considered, increasing the accuracy for higher return periods; (b) for the analyzed case studies, the flood frequency curve for medium and high return period (50 ď return period ď 1000 years) can be estimated with a difference lower than 3% (compared to the reference flood frequency curve) by considering the three storms with the maximum total rainfall depth each year; (c) when considering only the greatest storm of the year, for return periods higher than 10 years, the difference for the estimation of the flood frequency curve is lower than 10%; and (d) when considering the three greatest storms each year, for return periods higher than 100 years, the probability of achieving simultaneously a hydrograph with the annual maximum peak flow and the maximum volume is 94%.
Abstract:A useful tool is proposed in this paper to assist dam managers in comparing and selecting suitable operating rules. This procedure is based on well-known multiobjective and probabilistic methodologies, which were jointly applied here to assess and compare flood control strategies in hydropower reservoirs. The procedure consisted of evaluating the operating rules' performance using a simulation fed by a representative and sufficiently large flood event series. These flood events were obtained from a synthetic rainfall series stochastically generated by using the RainSimV3 model coupled with a deterministic hydrological model. The performance of the assessed strategies was characterized using probabilistic variables. Finally, evaluation and comparison were conducted by analyzing objective functions which synthesize different aspects of the rules' performance. These objectives were probabilistically defined in terms of risk and expected values. To assess the applicability and flexibility of the tool, it was implemented in a hydropower dam located in Galicia (Northern Spain). This procedure allowed alternative operating rule to be derived which provided a reasonable trade-off between dam safety, flood control, operability and energy production.
Hydrological design of Sustainable urban Drainage Systems (SuDS) is commonly achieved by estimating rainfall volumetric percentiles from daily rainfall series. Nevertheless, urban watersheds demand rainfall data at sub-hourly time step. Temporal disaggregation of daily rainfall records using stochastic methodologies can be applied to improve SuDS design parameters. This paper is aimed to analyze the ability of the synthetic rainfall generation process to reproduce the main characteristics of the observed rainfall and the estimation of the hydrologic parameters often used for SuDS design and by using the generally available daily rainfall data. Other specifics objectives are to analyze the effect of Minimum Inter-event Time (MIT) and storm volume threshold on rainfall volumetric percentiles commonly used in SuDS design. The reliability of the stochastic spatial-temporal model RainSim V.3 to reproduce observed key characteristics of rainfall pattern and volumetric percentiles, was also investigated. Observed and simulated continuous rainfall series with sub-hourly time-step were used to calculate four key characteristics of rainfall and two types of rainfall volumetric percentiles. To separate independent rainstorm events, MIT values of 3, 6, 12, 24, 48 and 72 h and storm volume thresholds of 0.2, 0.5, 1 and 2 mm were considered. Results show that the proposed methodology improves the estimation of the key characteristics of the rainfall events as well as the hydrologic parameters for SuDS design, compared with values directly deduced from the observed rainfall series with daily time-step. Moreover, MITs rainfall volumetric percentiles of total number of rainfall events are very sensitive to MIT and threshold values, while percentiles of total volume of accumulated rainfall series are sensitive only to MIT values.
The study developed a rule operation model for gated spillways (named K-Method) which improved the performance of the volumetric evaluation method (VEM). VEM was proposed by Girón (1988) and is largely used in common practice in Spain. The K-Method was developed by modifying the VEM and by including a K factor which affects the released flows. A Monte Carlo simulation environment was designed to evaluate the method under a wide range of inflow conditions (100,000 hydrographs) and with return periods ranging from 1 to 10,000 years.The methodology was applied to the Talave reservoir, located in the south-east of Spain. Results showed that K-Values higher than one always reduced the maximum reservoir levels reached in the dam. For K-Values ranging from one to ten and for inflow hydrographs with return periods higher than 50 years, we found a decrease of the maximum levels and outflows compared with the VEM. Finally, by carrying out a dam risk analysis, a K-Value of 5.25 was the best reducing 8.4% VEM expected annual damage.
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