Evaluation of two hydro-meteorological ensemble strategies for flash flood forecasting over a catchment of the eastern Pyrenees

This study aims at evaluating the performances of flash flood forecasts issued from deterministic and ensemble meteorological prognostic systems. The hydro-meteorological modeling chain includes the Weather Research and Forecasting model (WRF) forcing the rainfall-runoff model MARINE dedicated to flash flood. Two distinct ensemble prediction systems accounting for (i) perturbed initial and lateral boundary conditions of the meteorological state and (ii) mesoscale model physical parameterizations, have been implemented on the Agly catchment of the Eastern Pyrenees with three sub-catchments exhibiting different rainfall regimes. Different evaluations of the performance of the hydro-meteorological strategies have been performed: (i) verification of short-range ensemble prediction systems and corresponding stream flow forecasts, for a better understanding of how forecasts behave, (ii) usual measures derived from a contingency table approach, to test an alert threshold exceedance, and (iii) overall evaluation of the hydro-meteorological chain using the Continuous Rank Probability Score, for a general quantification of the ensemble performances. Results show that the overall discharge forecast is improved by both ensemble strategies with respect to the deterministic forecast. Threshold exceedance detections for flood warning also benefit from large hydro-meteorological ensemble spread. There are no substantial differences between both ensemble strategies on these test cases in terms both of the issuance of flood warnings and the overall performances, suggesting that both sources of external-scale uncertainty are important to take into account

Potentiality of hydrometeorological ensemble forecasting of flash floods for risk assessment: Application to the Agly catchment (Eastern Pyrenees)

The Western Mediterranean region is prone to heavy precipitations resulting in devastating flash floods. In order to improve the predictability of this kind of events and to increase the forecasting lead time, accurate predictions of small-scale convective systems are needed. But quantitative precipitation forecasts (QPFs) are arduous due to the uncertainties arising from both the physical parameterizations of numerical weather prediction models and the representation of the atmospheric states. These uncertainties can result in deficient QPFs for hydrological forecasting purposes, especially over small-to-medium sized basins. Nowadays, short-range ensemble prediction systems (EPSs) provide the state-of-art framework to generate quantitative discharge forecasts (QDFs) and to cope with the different sources of external-scale uncertainties. We examine the performance of two distinct hydrological EPSs (HEPSs), specially designed to explicitly cope with uncertainties in the initial and lateral boundary conditions of the meteorological state (IC/LBCs), and model physical parameterizations (MPS). Deterministic and probabilistic 48 h atmospheric forecasts have been generated using the Weather Research and Forecasting (WRF) model. This study focuses on a catchment of the Eastern Pyrenees, the Agly catchment, as a test case for implementing the ensemble hydro-meteorological predictions. With a drainage area of 1050 km2, the Agly is the second coastal river of the Eastern Pyrenees. It originates from an elevation of approximately 700 m and drains the Pyrenees foothills. It flows into the Mediterranean Sea at Barcarès with a length of around 80 km. A dam dedicated to flood and water management controls approximately 400 km2 of the catchment. The MARINE distributed model, flash-flood dedicated and process-oriented, has been chosen for this study. This model has been extensively tested on a large panel of hydrologic behaviors around the French Mediterranean area. WRF-driven QPFs have been used to feed the MARINE hydrological model for the medium-size Agly river basin as a support tool for early warning and mitigation strategies. We also explore the uncertainty transference from the atmospheric context down to the hydrological system. Results highlight the benefits of accounting for uncertainties in QPFs and the value of the proposed set-up for the short-range forecasting of floods. Combination of both ensembles (hydrological and meteorological) helps limiting a possible inadequacy of calibrated set of parameters on one hand and takes into account meteorological and parametric uncertainties on the other hand

NRCS-CN estimation from onsite and remote sensing data for management of a reservoir in the Eastern Pyrenees

Onsite and Earth observation (EO) data are used for the calibration of the Natural Resources Conservation Service curve number (NRCS-CN) value in a hydrological simulation model. The model was developed for La Muga catchment (eastern Pyrenees) highly vulnerable to flood and drought episodes. It is an integral part of a regional reservoir management tool, which aims at minimizing the flood risk while maximizing the preservation of water storage. The CN values were optimized for five recorded events for the model to match the observed hydrographs at the reservoir when supported with the measured rainfall intensities. This study also investigates the possibilities of using antecedent moisture conditions (AMC) retrieved from satellite data to inform the selection of the NRCS-CN losses parameter. A good correlation was found between the calibrated CN values and the AMC obtained from satellite data. This correlation highlights the interest in using EO data to update NRCS-CN estimates. This advances in hydrologic-hydraulic coupled modeling combined with new remote sensing datasets present valuable opportunities and potential benefits for flood risk management and water resources preservation

Potentiality of hydrometeorological ensemble forecasting of flash floods for risk assessment: Application to the Agly catchment (Eastern Pyrenees)

International audienceThe Western Mediterranean region is prone to heavy precipitations resulting in devastating flash floods. In order to improve the predictability of this kind of events and to increase the forecasting lead time, accurate predictions of small-scale convective systems are needed. But quantitative precipitation forecasts (QPFs) are arduous due to the uncertainties arising from both the physical parameterizations of numerical weather prediction models and the representation of the atmospheric states. These uncertainties can result in deficient QPFs for hydrological forecasting purposes, especially over small-to-medium sized basins. Nowadays, short-range ensemble prediction systems (EPSs) provide the state-of-art framework to generate quantitative discharge forecasts (QDFs) and to cope with the different sources of external-scale uncertainties. We examine the performance of two distinct hydrological EPSs (HEPSs), specially designed to explicitly cope with uncertainties in the initial and lateral boundary conditions of the meteorological state (IC/LBCs), and model physical parameterizations (MPS). Deterministic and probabilistic 48 h atmospheric forecasts have been generated using the Weather Research and Forecasting (WRF) model. This study focuses on a catchment of the Eastern Pyrenees, the Agly catchment, as a test case for implementing the ensemble hydro-meteorological predictions. With a drainage area of 1050 km2, the Agly is the second coastal river of the Eastern Pyrenees. It originates from an elevation of approximately 700 m and drains the Pyrenees foothills. It flows into the Mediterranean Sea at Barcarès with a length of around 80 km. A dam dedicated to flood and water management controls approximately 400 km2 of the catchment. The MARINE distributed model, flash-flood dedicated and process-oriented, has been chosen for this study. This model has been extensively tested on a large panel of hydrologic behaviors around the French Mediterranean area. WRF-driven QPFs have been used to feed the MARINE hydrological model for the medium-size Agly river basin as a support tool for early warning and mitigation strategies. We also explore the uncertainty transference from the atmospheric context down to the hydrological system. Results highlight the benefits of accounting for uncertainties in QPFs and the value of the proposed set-up for the short-range forecasting of floods. Combination of both ensembles (hydrological and meteorological) helps limiting a possible inadequacy of calibrated set of parameters on one hand and takes into account meteorological and parametric uncertainties on the other hand

Flood forecasting using a coupled hydrological and hydraulic model (based on FVM) and highresolution meteorological model

A forecasting systems based on the coupling of meteorological, hydrologic, hydraulic and risk models is used to minimize the risks associated to water scarcity and flooding. The fulfilment of such complex forecasting chains can allow obtaining information of the most plausible scenarios of water and risk management up to 96 hours ahead. In the present work, flood forecasting was carried out for different events in the upper La Muga basin (including the reservoir), within the European project “Flood Risk Assessment and Management in the Pyrenees” (http://pgriepm. eu/). The main purpose of the project was to develop a method to optimize the management of flood scenarios in order to minimize the flood risk while maximizing the water resources. The good fit of all the models, obtaining the forecasting rainfall and converting the overland flow in water levels in the reservoir, can give tools and important information to the authorities or dam managers for suitable management during the extreme rainfall and flood events

Flood forecasting using a coupled hydrological and hydraulic model (based on FVM) and highresolution meteorological model

A forecasting systems based on the coupling of meteorological, hydrologic, hydraulic and risk models is used to minimize the risks associated to water scarcity and flooding. The fulfilment of such complex forecasting chains can allow obtaining information of the most plausible scenarios of water and risk management up to 96 hours ahead. In the present work, flood forecasting was carried out for different events in the upper La Muga basin (including the reservoir), within the European project “Flood Risk Assessment and Management in the Pyrenees” (http://pgriepm. eu/). The main purpose of the project was to develop a method to optimize the management of flood scenarios in order to minimize the flood risk while maximizing the water resources. The good fit of all the models, obtaining the forecasting rainfall and converting the overland flow in water levels in the reservoir, can give tools and important information to the authorities or dam managers for suitable management during the extreme rainfall and flood events

Potentialities of ensemble strategies for flood forecasting over the Milano urban area

Analysis of ensemble forecasting strategies, which can provide a tangible backing for flood early warning procedures and mitigation measures over the Mediterranean region, is one of the fundamental motivations of the international HyMeX programme. Here, we examine two severe hydrometeorological episodes that affected the Milano urban area and for which the complex flood protection system of the city did not completely succeed. Indeed, flood damage have exponentially increased during the last 60 years, due to industrial and urban developments. Thus, the improvement of the Milano flood control system needs a synergism between structural and non-structural approaches. First, we examine how land-use changes due to urban development have altered the hydrological response to intense rainfalls. Second, we test a flood forecasting system which comprises the Flash-flood Event-based Spatially distributed rainfall-runoff Transformation, including Water Balance (FEST-WB) and the Weather Research and Forecasting (WRF) models. Accurate forecasts of deep moist convection and extreme precipitation are difficult to be predicted due to uncertainties arising from the numeric weather prediction (NWP) physical parameterizations and high sensitivity to misrepresentation of the atmospheric state; however, two hydrological ensemble prediction systems (HEPS) have been designed to explicitly cope with uncertainties in the initial and lateral boundary conditions (IC/LBCs) and physical parameterizations of the NWP model. No substantial differences in skill have been found between both ensemble strategies when considering an enhanced diversity of IC/LBCs for the perturbed initial conditions ensemble. Furthermore, no additional benefits have been found by considering more frequent LBCs in a mixed physics ensemble, as ensemble spread seems to be reduced. These findings could help to design the most appropriate ensemble strategies before these hydrometeorological extremes, given the computational cost of running such advanced HEPSs for operational purposes

Evaluation of two hydrometeorological ensemble strategies for flash-flood forecasting over a catchment of the eastern Pyrenees

This study aims at evaluating the performances of flash flood forecasts issued from deterministic and ensemble meteorological prognostic systems. The hydro-meteorological modeling chain includes the Weather Research and Forecasting model (WRF) forcing the rainfall-runoff model MARINE dedicated to flash flood. Two distinct ensemble prediction systems accounting for (i) perturbed initial and lateral boundary conditions of the meteorological state and (ii) mesoscale model physical parameterizations, have been implemented on the Agly catchment of the Eastern Pyrenees with three sub-catchments exhibiting different rainfall regimes. Different evaluations of the performance of the hydrometeorological strategies have been performed: (i) verification of short-range ensemble prediction systems and corresponding stream flow forecasts, for a better understanding of how forecasts behave, (ii) usual measures derived from a contingency table approach, to test an alert threshold exceedance, and (iii) overall evaluation of the hydro-meteorological chain using the Continuous Rank Probability Score, for a general quantification of the ensemble performances. Results show that the overall discharge forecast is improved by both ensemble strategies with respect to the deterministic forecast. Threshold exceedance detections for flood warning also benefit from large hydro-meteorological ensemble spread. There are no substantial differences between both ensemble strategies on these test cases in terms both of the issuance of flood warnings and the overall performances, suggesting that both sources of external-scale uncertainty are important to take into account.Peer Reviewe

NRCS-CN Estimation from Onsite and Remote Sensing Data for Management of a Reservoir in the Eastern Pyrenees

Onsite and Earth observation (EO) data are used for the calibration of the Natural Resources Conservation Service curve number (NRCS-CN) value in a hydrological simulation model. The model was developed for La Muga catchment (eastern Pyrenees) highly vulnerable to flood and drought episodes. It is an integral part of a regional reservoir management tool, which aims at minimizing the flood risk while maximizing the preservation of water storage. The CN values were optimized for five recorded events for the model to match the observed hydrographs at the reservoir when supported with the measured rainfall intensities. This study also investigates the possibilities of using antecedent moisture conditions (AMC) retrieved from satellite data to inform the selection of the NRCS-CN losses parameter. A good correlation was found between the calibrated CN values and the AMC obtained from satellite data. This correlation highlights the interest in using EO data to update NRCS-CN estimates. This advances in hydrologic-hydraulic coupled modeling combined with new remote sensing datasets present valuable opportunities and potential benefits for flood risk management and water resources preservation