Hydrogeological model of Mijas mountain aquifers under different climate conditions (Málaga, Spain)

Carbonate aquifers represent an important source of freshwater, both for urban and agricultural uses. This is particularly true in semiarid regions, where intensive pumping has often led to aquifer overexploitation. One example is the Mijas mountain carbonate diffuse flow system (80 km2), located to the SW of the city of Malaga, Spain. From a geolo-gical standpoint, this area consists of Triassic dolomitic and calcareous rocks, which overlay Palaeozoic metapelites. The geological structure is formed by ESE-WNW folds and the me-tapelites anticlinal cores have divided the study area into four aquifer systems. The recharge of Mijas mountain aquifers comes from direct infiltration of rainfall, while pumping is the main discharge. To improve the knowledge of geological and hydrodynamic parameters, and therefore to improve water resources management, a hydrogeological model has been developed with Processing Modflow 8.0.42. Piezometric level and spring flows have been modelled, under steady and transient-flow conditions for a 35-year period. Five future scenarios were simulated for different rainfall and pumping conditions. Outcomes confirm that the water level evolution is determined by the quantity and distribution of rainfall during the hydrological year, with the same pumping rate. The results also suggest that current trends are likely to raise sustainability issues in the future.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Observation and numerical simulation of a convective initiation during COHMEX

Under a synoptically undisturbed condition, a dual-peak convective lifecycle was observed with the COoperative Huntsville Meteorological EXperiment (COHMEX) observational network over a 24-hour period. The lifecycle included a multicell storm, which lasted about 6 hours, produced a peak rainrate exceeding 100 mm/hr, and initiated a downstream mesoscale convective system. The 24-hour accumulated rainfall of this event was the largest during the entire COHMEX. The downstream mesoscale convective system, unfortunately, was difficult to investigate quantitatively due to the lack of mesoscale observations. The dataset collected near the time of the multicell storm evolution, including its initiation, was one of the best datasets of COHMEX. In this study, the initiation of this multicell storm is chosen as the target of the numerical simulations

A model of nitrous oxide evolution from soil driven by rainfall events: 1. Model structure and sensitivity

This paper describes a rain-event driven, process-oriented simulation model, DNDC, for the evolution of nitrous oxide (N2O), carbon dioxide (CO2), and dinitrogen (N2) from agricultural soils. The model consists of three submodels: thermal-hydraulic, decomposition, and denitrification. Basic climate data drive the model to produce dynamic soil temperature and moisture profiles and shifts of aerobic-anaerobic conditions. Additional input data include soil texture and biochemical properties as well as agricultural practices. Between rainfall events the decomposition of organic matter and other oxidation reactions (including nitrification) dominate, and the levels of total organic carbon, soluble carbon, and nitrate change continuously. During rainfall events, denitrification dominates and produces N2O and N2. Daily emissions of N2O and N2 are computed during each rainfall event and cumulative emissions of the gases are determined by including nitrification N2O emissions as well. Sensitivity analyses reveal that rainfall patterns strongly influence N2O emissions from soils but that soluble carbon and nitrate can be limiting factors for N2O evolution during denitrification. During a year sensitivity simulation, variations in temperature, precipitation, organic C, clay content, and pH had significant effects on denitrification rates and N2O emissions. The responses of DNDC to changes of external parameters are consistent with field and experimental results reported in the literature

Seed production, infestation, and viability in Acacia tortilis (synonym: Vachellia tortilis) and Acacia robusta (synonym: Vachellia robusta) across the Serengeti rainfall gradient

Tree recruitment in savannas proceeds in multiple stages characterized by successive filters occurring at the seed and seedling stages. The “demographic bottleneck” hypothesis suggests that such filters ultimately restrict tree density and prevent trees from dominating grasses in savannas, but many of the demographic transitions underlying this assumption have not been quantified. We investigated how short- (1–2 years) and long-term (40 + years) rainfall patterns influenced seed production, infestation, and viability for two dominant species, Acacia robusta and Acacia tortilis across the Serengeti ecosystem mean annual precipitation gradient over a two-year period. We found that neither production, nor infestation, nor viability was influenced by rainfall. Pod production differed between species and increased with tree height in A. robusta. Mean infestation proportion in 2013 was higher (mean ± SE; 0.28 ± 0.08) in A. tortilis than in A. robusta (0.11 ± 0.05) but the trend reversed in 2014, when A. tortilis (0.33 ± 0.10) had lower infestation than A. robusta (0.61 ± 0.09). Under laboratory conditions, A. tortilis and A. robusta seeds had maximum germination (= viability) proportions of 70 and 20%, respectively. Mean seed viability was more than five-fold higher (0.46 ± 0.19) in A. tortilis than in A. robusta (0.08 ± 0.10). Our study has produced important estimates for seed stage demographic dynamics that can be used for modeling tree dynamics in Serengeti system, and savannas in general

Comparison of Two Detailed Models of Aedes aegypti Population Dynamics

The success of control programs for mosquito-­borne diseases can be enhanced by crucial information provided by models of the mosquito populations. Models, however, can differ in their structure, complexity, and biological assumptions, and these differences impact their predictions. Unfortunately, it is typically difficult to determine why two complex models make different predictions because we lack structured side-­by-­side comparisons of models using comparable parameterization. Here, we present a detailed comparison of two complex, spatially explicit, stochastic models of the population dynamics of Aedes aegypti, the main vector of dengue, yellow fever, chikungunya, and Zika viruses. Both models describe the mosquito?s biological and ecological characteristics, but differ in complexity and specific assumptions. We compare the predictions of these models in two selected climatic settings: a tropical and weakly seasonal climate in Iquitos, Peru, and a temperate and strongly seasonal climate in Buenos Aires, Argentina. Both models were calibrated to operate at identical average densities in unperturbedconditions in both settings, by adjusting parameters regulating densities in each model (number of larval development sites and amount of nutritional resources). We show that the models differ in their sensitivityto environmental conditions (temperature and rainfall) and trace differences to specific model assumptions.Temporal dynamics of the Ae. aegypti populations predicted by the two models differ more markedly under strongly seasonal Buenos Aires conditions. We use both models to simulate killing of larvae and/or adults with insecticides in selected areas. We show that predictions of population recovery by the models differ substantially, an effect likely related to model assumptions regarding larval development and (director delayed) density dependence. Our methodical comparison provides important guidance for model improvement by identifying key areas of Ae. aegypti ecology that substantially affect model predictions, and revealing the impact of model assumptions on population dynamics predictions in unperturbed and perturbed conditions.Fil: Legros, Mathieu. University of North Carolina; Estados UnidosFil: Otero, Marcelo Javier. Universidad de Buenos Aires; ArgentinaFil: Romeo Aznar, Victoria Teresa. Universidad de Buenos Aires; ArgentinaFil: Solari, Hernan Gustavo. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Gould, Fred. National Institutes of Health; Estados UnidosFil: Lloyd, Alun L.. National Institutes of Health; Estados Unido

Were rivers flowing across the Sahara during the last interglacial? Implications for human migration through Africa.

Human migration north through Africa is contentious. This paper uses a novel palaeohydrological and hydraulic modelling approach to test the hypothesis that under wetter climates c.100,000 years ago major river systems ran north across the Sahara to the Mediterranean, creating viable migration routes. We confirm that three of these now buried palaeo river systems could have been active at the key time of human migration across the Sahara. Unexpectedly, it is the most western of these three rivers, the Irharhar river, that represents the most likely route for human migration. The Irharhar river flows directly south to north, uniquely linking the mountain areas experiencing monsoon climates at these times to temperate Mediterranean environments where food and resources would have been abundant. The findings have major implications for our understanding of how humans migrated north through Africa, for the first time providing a quantitative perspective on the probabilities that these routes were viable for human habitation at these times

Initiation of a Stable Convective Hydroclimatic Regime in Central America Circa 9000 Years BP

Many Holocene hydroclimate records show rainfall changes that vary with local orbital insolation. However, some tropical regions display rainfall evolution that differs from gradual precessional pacing, suggesting that direct rainfall forcing effects were predominantly driven by sea-surface temperature thresholds or inter-ocean temperature gradients. Here we present a 12,000 yr continuous U/Th-dated precipitation record from a Guatemalan speleothem showing that Central American rainfall increased within a 2000 yr period from a persistently dry state to an active convective regime at 9000 yr BP and has remained strong thereafter. Our data suggest that the Holocene evolution of Central American rainfall was driven by exceeding a temperature threshold in the nearby tropical oceans. The sensitivity of this region to slow changes in radiative forcing is thus strongly mediated by internal dynamics acting on much faster time scales

Climate variability as experienced by farmers. [K-2224-04]

The typical approach of estimating crop response to future climate scenarios may be inappropriate in the case of smallholder multi cropping rain-fed agriculture. Indeed, a crop-by-crop simulation, based on current varieties, cannot take into account the dynamics among crops as well as within crops i.e. among varieties, in time and space. We implemented a comparative study to understand interactions between cropping system dynamics and pas climate variations, taking into account the diversity of farmers' experiences and socio-cultural organization. in Kenya, farmers who adopted maize a few years ago are still cultivating traditional sorghum and pearl millet varieties, while others abandoned them earlier in favour of maize. Farming systems were thus dynamic, with different crop assemblages over time. Thus, retrospectively, farmers' capacity to mitigate crop failure risk due to extreme rainfall events has never been constant. Has the farming system lost part of its capacity to cope with climate variability, as maize is known to be less resistant to drought than sorghum and pearl millet? While this is usually demonstrated using yield parameter, we used see losses, which is consistent with a multicrop system. Combining ecological anthropology and climatology, we confronted the results of a retrospective survey of farmers' seed loss reminiscence about the period 1961-2006 and climatic records for three altitudinal levels on the eastern slope of Mount Kenya were analysed. Over the period 3204 seed loss events were reported independently by 208 farmers, for eight main crops of their rain-fed farming systems. the causes given for these losses according to farmers' experience and knowledge were recorded yearly. We first assessed whether these causes were related to recorded rainfall values, and, second, analysed the proportion of lost seed on a yearly basis, crop by crop and on the whole farming system, using logistic regression. Drought was mentioned 73.5% of the time whereas 8.5% of the losses were attributed to heavy rainfall. Farmers recalls coincided on drought years associated with crop diversity losses: conditional Chi-square tests based on Monte Carlo simulation clearly rejected independence (p = 0.001) between climatic reasons given by farmers and recorded rainfall, for both droughts and heavy rainfall. Farmers' retrospective perception of drought corresponds to major droughts reported for Kenya. By favouring maize at the expense of sorghum and pearl millet, cropping system dynamics have promoted an increasing risk of drought-associated seed loss. t he probability to lose sorghum seed (0.056– 0.065) was significantly lower than the probability to lose maize seed (0.071–0.087). all crops were affected more by droughts than by heavy rainfall. s eed loss probability increased for a rainy season shorter than 50 days, with less than 28 rain days, and with a precipitation under 400 mm. l ogistic regression confirmed that a change in cropping systems increased the risk of seed losses due to drought over the 46-yr period. Farmers experienced climate variability differently, with greater negative impact on farmers cultivating maize. e cological and social components thus cannot be analytically isolated but have to be considered as parts of a socio-ecological system. While usual approaches consider present-day characteristics of agricultural systems to assess their adaptability to hypothetical rainfall variability (projection into the future), our study used farmer experiences to look into the past. i n our approach, past rainfall variability is already known, not hypothetical, while farmers' experiences can allow assessment of the evolution of their agricultural systems, which can be monitored over time, and related to climate variability. t he cropping system dynamics, by favouring maize at the expense of sorghum and pearl millet are partly related to agricultural policies that positively valued maize, whereas sorghum and pearl millet were devalued, being perceived as ''poor people crops''. The current dynamics of agricultural systems thus imply many dimensions, not only economical, political, and agronomical, but also cultural. (Texte intégral