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Le Touquet – Paris-Plage, France

Louvet S.,Ecoclimasol | Paturel J.E.,UMR HydroSciences Montpellier | Mahe G.,UMR HydroSciences Montpellier | Rouche N.,UMR HydroSciences Montpellier | Koite M.,DNM Bamako
Theoretical and Applied Climatology | Year: 2016

The climatic evolution of the Bani river watershed, the main tributary to the upper Niger River, is approached through the spatiotemporal variability of rainfall grids over the 1950–2006 period. The analyses are conducted, and their results compared, using four different methods of spatial interpolation of rainfall fields: the spline, kriging, weighted inverse distance, and nearest neighbor methods. The largest changes are observed for all of these grids, but differences—and in some cases divergent results—appear in the details. The analysis shows a substantial decline in rainfall, particularly marked in the center of the basin, during the 1970–2000 period with respect to the 1950–1969 period, and a slight upturn in the northern part, mainly since the beginning of the 1990s. The rainfall deficit can be attributed to a combination of factors: an earlier and drier end of the rainy season, less precipitation in the middle of the rainy season, more dry days and lower amounts of precipitation on rainy days. Two drought indices—the Effective Drought Index and Standardized Precipitation Index—revealed that the maximum duration of drought events increased most in the central part of the basin. Lastly, to supplement this comparison of methods of spatial interpolation of rainfall fields, the sensitivity of a hydrological model (GR2M) to rainfall data was tested. Given the distribution and density of rain gauge stations available in the Bani watershed, the kriging method is found to yield the best hydrological modeling performance. © 2015, Springer-Verlag Wien. Source


Ramarohetra J.,Ecoclimasol | Pohl B.,University of Burgundy | Sultan B.,University Pierre and Marie Curie
Environmental Research Letters | Year: 2015

The challenge of estimating the potential impacts of climate change has led to an increasing use of dynamical downscaling to produce fine spatial-scale climate projections for impact assessments. In this work, we analyze if and to what extent the bias in the simulated crop yield can be reduced by using the Weather Research and Forecasting (WRF) regional climate model to downscale ERA-Interim (European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis) rainfall and radiation data. Then, we evaluate the uncertainties resulting from both the choice of the physical parameterizations of the WRF model and its internal variability. Impact assessments were performed at two sites in Sub-Saharan Africa and by using two crop models to simulate Niger pearl millet and Benin maize yields. We find that the use of the WRF model to downscale ERA-Interim climate data generally reduces the bias in the simulated crop yield, yet this reduction in bias strongly depends on the choices in the model setup. Among the physical parameterizations considered, we show that the choice of the land surface model (LSM) is of primary importance. When there is no coupling with a LSM, or when the LSM is too simplistic, the simulated precipitation and then the simulated yield are null, or respectively very low; therefore, coupling with a LSM is necessary. The convective scheme is the second most influential scheme for yield simulation, followed by the shortwave radiation scheme. The uncertainties related to the internal variability of the WRF model are also significant and reach up to 30% of the simulated yields. These results suggest that regional models need to be used more carefully in order to improve the reliability of impact assessments. © 2015 IOP Publishing Ltd. Source


Nunez P.A.,Instituto Nacional Of Medicina Tropical Inmet | Fernandez-Slezak D.,University of Buenos Aires | Farall A.,Ecoclimasol | Szretter M.E.,University of Buenos Aires | And 2 more authors.
American Journal of Public Health | Year: 2016

Objectives. To estimate trends of undernutrition (stunting and underweight) among children younger than 5 years covered by the universal health coverage programs Plan Nacer and Programa Sumar. Methods. From 2005 to 2013, Plan Nacer and Programa Sumar collected high-quality information on birth and visit dates, age (in days), gender, weight (in kg), and height (in cm) for 1.4 million children in 6386 health centers (13 million records) with broad coverage of vulnerable populations in Argentina. Results.The prevalence of stunting and underweight decreased 45.0% (from 20.6% to 11.3%) and 38.0% (from 4.0% to 2.5%), respectively, with differences between rural versus urban areas, gender, regions, age, and seasons. Conclusions. Undernutrition prevalence substantially decreased in 2 programs in Argentina as a result of universal health coverage. Source


Girard P.,Federal University of Mato Grosso | Boulanger J.-P.,Ecoclimasol | Hutton C.,University of Southampton
Climatic Change | Year: 2014

Climate change impacts are already happening through the world, and it is now clear that there is the need for an adaptive response from global institutions down to the local level. Reducing vulnerability to cope with climate variability might be more challenging in tropical countries than in North America or Europe. The ten papers of this special issue were presented during the Adaptclim conference that was held by the Sinergia Project, the CLARIS LPB project, and the GeoData Institute in Asunción, Paraguay, in 2010. All papers, except one regarding the Brahmaputra Basin in South Asia, present studies from South America. These studies are first contextualized geographically and then are related one to another by a simplified vulnerability concept linking climate stress to sensitivity and adaptive capacity of natural and human systems. One half of the papers focus on actual or future climate change and the present-day causes of the vulnerability of natural and agrosystems. Droughts are and will be the main source of stress for agriculture in South America. Increasing fragmentation of forest of the center of this continent is aggravating their vulnerability to dry spells. Another half of the studies of this special issue deal with the adaptive capacity human populations to system perturbations produced or enhanced by climate change. The studies point out inclusion of traditional knowledge and involvement of local actors in their own vulnerability assessment to increase adaptive capacity. These elements of climate justice, giving voice to those less responsible for carbon emissions but bearing their most severe consequences, allow the particular needs of a community to be considered and can direct adaptation policy toward preserving or rebuilding their specific capabilities under threat from climate change. The special issue also made clear that a basin analysis of the climate change problem could provide information, results, and methods more readily of use for the local population and decision makers. © 2014, Springer Science+Business Media Dordrecht. Source


Roudier P.,Paris-Sorbonne University | Alhassane A.,Regional Center | Baron C.,CIRAD - Agricultural Research for Development | Louvet S.,Ecoclimasol | Sultan B.,Paris-Sorbonne University
Agricultural and Forest Meteorology | Year: 2016

West African farmers need to take every year crucial decisions based on some characteristics of the rainy season such as the onset, the offset, the cumulated rainfall or the occurrence of dry spells. Knowing these parameters in advance may therefore be of interest for them. This paper aims at assessing the impacts of 10-days and seasonal forecasts on Niger millet growers' cropping practices and their income. To do so, we apply an ex-ante approach based on the crop model SARRA-H coupled with an economic model that simulates the choice of cropping strategies among 24 available. The approach takes explicitly risk aversion into account and focuses on two different kinds of typical farmers with restricted and large adaptation capacities, in reference to the availability of viable decision options sensitive to forecast information. Results show (i) that 10-days forecasts alone or a combination of 10-days and seasonal forecasts could be quite beneficial for all types of farmers (e.g. median income change with 10-days forecast ranges from +1.8% to +13% according to adaptation possibilities), (ii) that in most of the cases farmers with access to fertilizers and larger arable land benefit more from forecasts and (iii) that even if seasonal forecasts are not really beneficial alone, they are when used in combination with 10-days forecasts. Despite these positive results, one has to underline that income losses may occur in about 20% of cases when using these forecasts, which may be a limiting factor to their effective adoption. © 2016. Source

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