Modéliser l'impact du changement climatique sur les écosystèmes aquatiques par approche de downscaling

L'objectif était d'évaluer l'impact du changement global sur les écosystèmes aquatiques au cours du 21ème siècle, dans le bassin Adour Garonne (S-O France). Une approche de " downscaling " a été développée à l'interface entre les sciences du climat, de l'hydro-chimie et de l'écologie. Les résultats suggèrent une augmentation globale des débits hivernaux ainsi que des débits d'étiages plus faibles. Les concentrations en nitrate pourraient augmenter, de même que la distribution des espèces de poissons les plus thermophiles. Toutefois, une diminution des gaz à effet de serre ainsi qu'une modification des pratiques agricoles (ex. diminution des fertilisants azotés) pourraient limiter l'intensité des perturbations écologiques. Cette thèse offre une contribution originale, notamment pour la gestion future des ressources hydriques et écologiques.This thesis aimed at assessing the impact of global change on freshwater ecosystems during the 21st century in the Adour Garonne area (SW France). A downscaling approach was developed linking techniques from climate, hydro-chemical and ecological sciences. The main results suggest an increase of high flows in winter as well as more severe low flows in summer. Nitrogen concentrations and thermophile fish species distribution may also increase. Reducing green house gas emissions and modifying agricultural practices (e.g reducing nitrate fertilizers) could reduce the intensity of ecological disturbances. This study is an original contribution to the management of future hydrological and ecological resources

Selecting the optimal method to calculate daily global reference potential evaporation from CFSR reanalysis data for application in a hydrological model study

Potential evaporation (PET) is one of the main inputs of hydrological models. Yet, there is limited consensus on which PET equation is most applicable in hydrological climate impact assessments. In this study six different methods to derive global scale reference PET daily time series from Climate Forecast System Reanalysis (CFSR) data are compared: Penman-Monteith, Priestley-Taylor and original and re-calibrated versions of the Hargreaves and Blaney-Criddle method. The calculated PET time series are (1) evaluated against global monthly Penman-Monteith PET time series calculated from CRU data and (2) tested on their usability for modeling of global discharge cycles. <br><br> A major finding is that for part of the investigated basins the selection of a PET method may have only a minor influence on the resulting river flow. Within the hydrological model used in this study the bias related to the PET method tends to decrease while going from PET, AET and runoff to discharge calculations. However, the performance of individual PET methods appears to be spatially variable, which stresses the necessity to select the most accurate and spatially stable PET method. The lowest root mean squared differences and the least significant deviations (95% significance level) between monthly CFSR derived PET time series and CRU derived PET were obtained for a cell-specific re-calibrated Blaney-Criddle equation. However, results show that this re-calibrated form is likely to be unstable under changing climate conditions and less reliable for the calculation of daily time series. Although often recommended, the Penman-Monteith equation applied to the CFSR data did not outperform the other methods in a evaluation against PET derived with the Penman-Monteith equation from CRU data. In arid regions (e.g. Sahara, central Australia, US deserts), the equation resulted in relatively low PET values and, consequently, led to relatively high discharge values for dry basins (e.g. Orange, Murray and Zambezi). Furthermore, the Penman-Monteith equation has a high data demand and the equation is sensitive to input data inaccuracy. Therefore, we recommend the re-calibrated form of the Hargreaves equation which globally gave reference PET values comparable to CRU derived values for multiple climate conditions. <br><br> The resulting gridded daily PET time series provide a new reference dataset that can be used for future hydrological impact assessments in further research, or more specifically, for the statistical downscaling of daily PET derived from raw GCM data. The dataset can be downloaded from <a href ="http://opendap.deltares.nl/thredds/dodsC/opendap/deltares/FEWS-IPCC"target="_blank">http://opendap.deltares.nl/thredds/dodsC/opendap/deltares/FEWS-IPCC</a>

Forecasting the spatial and seasonal dynamic of Aedes albopictus oviposition activity in Albania and Balkan countries

The increasing spread of the Asian tiger mosquito, Aedes albopictus, in Europe and US raises public health concern due to the species competence to transmit several exotic human arboviruses, among which dengue, chikungunya and Zika, and urges the development of suitable modeling approach to forecast the spatial and temporal distribution of the mosquito. Here we developed a dynamical species distribution modeling approach forecasting Ae. albopictus eggs abundance at high spatial (0.01 degree WGS84) and temporal (weekly) resolution over 10 Balkan countries, using temperature times series of Modis data products and altitude as input predictors. The model was satisfactorily calibrated and validated over Albania based observed eggs abundance data weekly monitored during three years. For a given week of the year, eggs abundance was mainly predicted by the number of eggs and the mean temperature recorded in the preceding weeks. That is, results are in agreement with the biological cycle of the mosquito, reflecting the effect temperature on eggs spawning, maturation and hatching. The model, seeded by initial egg values derived from a second model, was then used to forecast the spatial and temporal distribution of eggs abundance over the selected Balkan countries, weekly in 2011, 2012 and 2013. The present study is a baseline to develop an easy-handling forecasting model able to provide information useful for promoting active surveillance and possibly prevention of Ae. albopictus colonization in presently non-infested areas in the Balkans as well as in other temperate regions

Combining literature-based and data-driven fuzzy models to predict brown trout (salmo trutta l.) spawning habitat degradation induced by climate change

[EN] A fuzzy rule-based system combining empirical data on hydraulic preferences and literature information on temperature requirements was used to foresee the brown trout (Salmo trutta L.) spawning habitat degradation induced by climate change. The climatic scenarios for the Cabriel River (Eastern Iberian Peninsula) corresponded to two Representative Concentration Pathways (4.5 and 8.5) for the short (2011¿2040) and mid (2041¿2070) term horizons. The hydraulic and hydrologic modelling were undertaken with process-based numerical models (i.e., River2D© and HBV-light) while the water temperature was modelled by assembling the predictions of three machine learning techniques (M5, Multi-Adaptive Regression Splines and Support Vector Regression). The predicted rise in the water temperature will not be compensated by the more benign lower flows. Consequently, the suitable spawning habitat will be reduced between 15.4¿48.7%. The entire population shall suffer the effects of climate change and will probably be extirpated from the downstream segments of the river.The study has been partially funded by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economía y Competitividad) and FEDER funds and by the Confederación Hidrográfica del Júcar (Spanish Ministry of Agriculture, Food and Environment). The authors thank AEMET and UC for the data provided for this work (dataset Spain02). Finally, we are grateful to the colleagues who worked in the field and in preliminary data analyses; especially Marcello Minervini (funded by the EU programme of Erasmus Traineeships, at the Dept. of Hydraulic Engineering and Environment, Universitat Politècnica de València).Muñoz Mas, R.; Marcos-García, P.; Lopez-Nicolas, A.; Martínez-García, F.; Pulido-Velazquez, M.; Martinez-Capel, F. (2018). Combining literature-based and data-driven fuzzy models to predict brown trout (salmo trutta l.) spawning habitat degradation induced by climate change. Ecological Modelling. 386:98-114. https://doi.org/10.1016/j.ecolmodel.2018.08.012S9811438