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La thèse explore l’utilisation de modèles hydrologiques globaux pour estimer la disponibilité en eau agricole dans le contexte des Andes chiliennes semi-arides. Dans cette région, l’approvisionnement en eau des cultures irriguées de fonds de vallée durant l’été dépend de précipitations se produisant sous forme de neige à haute altitude lors de quelques évènements hivernaux. L’influence des phénomènes ENSO et PDO induit par ailleurs une forte variabilité climatique à l’échelle inter-annuelle, marquée par l’occurrence d’années extrêmement sèches ou humides. La région connaît aussi depuis les années 1980 une progression importante de la viticulture irriguée. Afin de prendre en compte les variations saisonnières et inter-annuelles de la disponibilité et de la consommation en eau d’irrigation, une chaîne de modélisation intégrée a été développée et différentes méthodes de quantification/réduction des incertitudes de simulation ont été mises en œuvre. Les écoulements naturels ont été simulés avec un modèle hydrologique global de type empirique/conceptuel prenant en compte les processus d’accumulation et d’ablation de la neige. En parallèle, les besoins en eau d’irrigation ont été estimés à l’échelle du bassin à partir de modèles phénologiques orientés processus et d’une approche simple du bilan hydrique du sol. Dans l’ensemble, une approche holistique et parcimonieuse a été privilégiée afin de maintenir un niveau d’abstraction mathématique et de représentation des processus équivalent à celui des modèles de bassin couramment utilisés. Afin d’améliorer l’utilité et la fiabilité des simulations obtenues en contexte de changement ou de forte variabilité climatique, l’effet des températures extrêmes sur le développement des cultures et l’impact des pertes en eau par sublimation à haute altitude ont fait l’objet d’une attention particulière. Ce cadre de modélisation conceptuel a été testé pour un bassin typique des Andes semi-arides (1512 km2, 820–5500 m a.s.l.) sur une période de 20 ans incluant une large gamme de conditions climatiques et des pratiques agricoles non-stationnaires (évolution des variétés de vigne, des surfaces et modes d’irrigation, etc). L’évaluation des modèles a été réalisée dans un cadre bayésien en faisant l’hypothèse d’erreurs auto-corrélées, hétéroscédastiques et non-gaussiennes. Différents critères et sources de données ont par ailleurs été mobilisés afin de vérifier l’efficacité et la cohérence interne de la chaîne de modélisation ainsi que la fiabilité statistique et la finesse des intervalles de confiance obtenus. De manière alternative, une caractérisation des erreurs de structure et de l’ambiguïté propre au choix du modèle hydrologique a été réalisée de manière non-probabiliste à partir d’une plate-forme de modélisation modulaire. Dans l’ensemble, la prise en compte explicite de la consommation en eau des cultures a mis en valeur certaines interactions entre paramètres hydrologiques et permis d’améliorer la fiabilité des simulations hydrologiques en année sèche. Finalement, une étude de sensibilité à différents seuils d’augmentation de la température et de la concentration en CO2 a été effectuée afin d’évaluer l’impact potentiel des changements climatiques sur le comportement de l’hydrosystème et la capacité à satisfaire la demande en eau d’irrigation dans le futur. / This thesis investigates the use of lumped catchment models to assess water availability for irrigation in the upland areas of northern-central Chile (30°S). Here, most of the annual water supply falls as snow in the high Cordillera during a few winter storms. Seasonal snowpacks serve as natural reservoirs, accumulating water during the winter and sustaining streams and aquifers during the summer, when irrigation demand in the cultivated valleys is at its peak. At the inter-annual timescale, the influence of ENSO and PDO phenomena result in the occurrence of extremely wet and dry years. Also, irrigated areas and grape growing have achieved a dramatic increase since the early 1980s. To evaluate the usefulness of explicitly accounting for changes in irrigation water-use in lumped catchment models, an integrated modeling framework was developed and different ways of quantifying/reducing model uncertainty were explored. Natural streamflow was simulated using an empirical hydrological model and a snowmelt routine. In parallel, seasonal and inter-annual variations in irrigation requirements were estimated using several process-based phenological models and a simple soil-water balance approach. Overall, this resulted in a low-dimensional, holistic approach based on the same level of mathematical abstraction and process representation as in most commonly-used catchment models. To improve model reliability and usefulness under varying or changing climate conditions, particular attention was paid to the effects of extreme temperatures on crop phenology and the contribution of sublimation losses to water balance at high elevations. This conceptual framework was tested in a typical semi-arid Andean catchment (1512 km2, 820–5500 m a.s.l.) over a 20–year simulation period encompassing a wide range of climate and water-use conditions (changes in grape varieties, irrigated areas, irrigation techniques). Model evaluation was performed from a Bayesian perspective assuming auto-correlated, heteroscedastic and non-gaussian residuals. Different criteria and data sources were used to verify model assumptions in terms of efficiency, internal consistency, statistical reliability and sharpness of the predictive uncertainty bands. Alternatively, a multiple-hypothesis and multi-criteria modeling framework was also developed to quantify the importance of model non-uniqueness and structural inadequacy from a non-probabilistic perspective. On the whole, incorporating the effects of irrigation water-use led to new interactions between the hydrological parameters of the modeling framework and improved reliability of streamflow predictions during low-flow periods. Finally, a sensitivity analysis to changes in climate conditions was conducted to evaluate the potential impacts of increasing temperatures and atmospheric CO2 on the hydrological behavior of the catchment and the capacity to meet future water demands.

Deep ventilation of the Black Sea is inhibited by a sharp salinity gradient within the upper water column, resulting in a shallow anoxic interface at around 100 &ndash / 200 m depth. Understanding biological and chemical processes within the boundary region between oxic and anoxic waters is fundamental to comprehend the biogeochemical response of the Black Sea to climate forcing. The structure and depth of the chemocline is largely determined by the physical processes which transport surface waters to depth. Here we investigate how the structure and stability of the upper water column responds to changes in climatic forcing over interannual to multidecadal time-scales. We report results from two hydrodynamic model reanalysis. The first, extending from 1971-1993 assimilates CTD data. The second, extending from 1992-2001, assimilates altimetry data. Model results are validated against CTD and satellite data and consistency between modeled surface properties and observations is demonstrated. A problem with the data assimilation scheme of the 1992 -2001 model run is identified, which results in model drift and an unrealistic water column structure at intermediate depths. Model results indicate a warming trend of 0.7 &deg / C in sea surface temperature and a freshening trend of 0.4 in sea surface salinity between 1971 and 2001, with an associated increasing trend in the stability of the seasonal thermocline and a declining trend in surface mixed layer depth of 6.3 m. Trends are superimposed on a distinct multiannual variability characterized by relatively warm and saline conditions between 1971 and 1984, relatively cool and fresh conditions between 1985 and 1993 and warm and fresh conditions post-1993. The period between 1985 and 1993 corresponds to higher NAO and EA/WR index values although these indices do not exhibit a similar ~decadal scale variability. Higher frequency interannual variability in water column characteristics is related to the NAO and EA/WR atmospheric indices. Despite the cool conditions prevalent during the 1990s, the persistent freshening trend caused a reduction in the density of mixed layer waters throughout the study period. A positive feedback is proposed between increasing SSTs, reduced vertical mixing and freshening of the surface layer which further increases the stability of the upper water column. CIL characteristics typically mirrored surface temperature characteristics and varied considerably between the relatively warm period during the early part of the study and the subsequent cool period. The mean thickness and temperature of the CIL between 1971 and 1981 were ~39 m and ~7.5 &deg / C respectively, as compared to ~47 m and ~7.4 &deg / C between 1982 and 1993. Freshening of the upper water column also resulted in an increase in the stability maxima that exists at the base of the CIL, suggesting reduced ventilation of the upper water column during winter.

MENVSC (Geography) / Department of Geography and Geo-Information Sciences / Climate variability and change directly affect agricultural production. This is because the agricultural sector is inherently sensitive to climatic conditions and is one of the most vulnerable sectors to risks and impact of global climate change. The aim of this study was to determine maize producer's vulnerability and assess the impact of climate variability and change on maize production in the Makhuduthamaga Local Municipality, of Limpopo Province, South Africa. Climatic and maize yields data utilized in the study are for the period 1985 - 2015). Interviews were also conducted with the producers and various officials from government and non-governmental sectors. The results illustrate significant rainfall and temperature variations both spatially and temporally. The variations observed in the average rainfall and rain days for the period under consideration were not related to the variation in yield of maize for the same period. The regression results revealed low R² values, indicating a weak relationship between maize yields, rain days and rainfall. Furthermore, the results revealed a significant positive relationship between annual rainfall and temperature (r²<0.05 and P<0.05) but not a significant relationship with maize yields. The results of the qualitative data showed that the producers’ perception of the occurrence of climate variability was high, as 65.7% of the respondents indicated that the state of climate is increasingly variable. About 61.5% of the producers implemented or adopted an adaptation strategy to cope with the perceived climate variability and change. Age, gender and access to extension services were determined as important factors that determine the adoption of adaptation strategies. The vulnerability assessment revealed that producers were highly vulnerable to changing climate; this exposes producers to the risks of crop failure, loss of income and food insecurity. The study recommended (a) intervention and adaptation strategies that target mitigation of decreased rainfall impacts (b) increased access to extension service (c) empirical research around the impacts of climate change to increase producers’ level of awareness. / NRF

Issues arising from climate change and long-term natural climate variability have become the focus of much recent research. In this study, we specifically explore the impacts of long-term climate variability and climate changes upon flood frequencies. The analyses of the flood frequencies are carried out in a comparative manner in catchments located in semiarid-temperate and tropical landscapes in Australia, namely Perth, Newcastle and Darwin, using a process-based derived flood frequency approach. The derived flood frequency analyses are carried out using deterministic rainfall-runoff models that capture the intrinsic water balance variability in the study catchments, and driven by temporal rainfall event sequences that are generated by a stochastic rainfall model that incorporates temporal variabilities over a multiplicity of time scales, ranging from within-event, between-event to seasonal, multi-annual and multi-decadal time scales. Six climate scenarios are considered for Newcastle, that combine the ENSO (El Niño Southern Oscillation) and IPO (Inter-decadal Pacific Oscillation) modes of variability, and six different climate scenarios are considered for Perth and Darwin that combine these different ENSO modes and step changes in climate (upwards or downwards) that occurred in 1970 in both regions, which were identified through statistical analysis. The results of the analyses showed that La Niña years cause higher annual maximum floods compared to El Niño and Neutral years in all three catchments. The impact of ENSO on annual maximum floods in the Newcastle catchment is enhanced when the IPO is negative and for Perth, the impact of ENSO weakens in the post-1970 period, while it strengthens in Darwin in the same period. In addition, the results of sensitivity and scenario analyses with the derived flood frequency model explored the change of dominant runoff generation processes contributing to floods in each of the study catchments. These analyses highlighted a switch from subsurface stormflow to saturation excess runoff with a change of return period, which was much more pronounced in Perth and Darwin, and not so in Newcastle. In Perth and Darwin this switch was caused by the interactions between the out-of-phase seasonal variabilities of rainfall and potential evaporation, whereas the seasonality was much weaker in Newcastle. On the other hand, the combination of higher rainfall intensities and shallower soil depths led to saturation excess runoff being the dominant mechanism in Newcastle across the full range of return periods. Consequently, within-storm rainfall intensity patterns were important in Newcastle in all major flood producing events (all return periods), where they were only important in Perth and Darwin for floods of high return periods, which occur during wet months in wet years, when saturation excess runoff was the dominant mechanism. Additionally, due to the possibility of a change of process from subsurface stormflow to saturation excess when conditions suited this switch, the estimates of flood frequency are highly uncertain especially at high return periods (in Darwin and Perth) and much less in Newcastle (when no process change was involved).

MRDV / Institute for Rural Development / This study originated from the realisation that non-conventional crops such as Bambara nuts (Vigna subterranea) were becoming increasingly important in addressing food insecurity and malnutrition in the smallholder farming sector of countries in sub-Saharan Africa. Moreover, some of the smallholder crop farmers were observed to be continuing to rely on indigenous techniques to forecast rainfall and adapt agricultural activities in response to climate variability. However, it was not clear how climate change influenced the productivity of V. subterranea. Nor were the indigenous approaches that farmers used to forecast rainfall on this phenomenon well understood. Thus, a study was carried out to identify and document indigenous approaches that smallholder farmers used to forecast rainfall and adaptation practices relating to V. subterranea. The study was conducted in Xigalo and Lambani villages located in Collins Chabane Local Municipality of Vhembe District in Limpopo Province. The villages served as case study areas that helped to compare the native approaches that the Va-Tsonga and Vha-Venda used to forecast rainfall in the course of producing V. subterranea. A multi-case study research design, which was exploratory in nature was adopted. Convenience and snowball sampling techniques were used to identify and select respondents. The triangulation of participatory methods, techniques and tools guided the collection of qualitative data. Key informant interviews, learning circles, photovoice, one-on-one interviews and narrative inquiry techniques were applied during data collection. Smallholder farmers and the elderly members of communities were the respondents. Nine key informants in Xigalo and Lambani villages were interviewed. One retired and two currently serving government extension officers were also interviewed. Separate learning circles comprising mainly elderly men and women were also organised. Each learning circle was made up of 7-10 respondents. Atlas.ti version 7.5.7 software was used to analyse the qualitative data following the thematic content analysis approach. It was observed that the respondents were aware of climate variability events that affected V. subterranea. Some of the events were shifts in rainfall patterns, heavy rainfall, extreme temperatures, scarcity of summer rainfall, the disappearance of lunar signs and the seasonal cycle variations. Eighteen types of phenological signs used to predict rainfall were identified. The most common signs included the Milky Way Galaxy of stars, musical sounds of birds and frogs, moon shapes, cumulus and cumulonimbus cloud types. A close relationship between conservation of V. subterranea and adaptation strategies was said to exist. It was evident that most commonly used conservation strategies were rainmaking ceremonies, planting after the summer rains, hoeing weeds, soaking seeds before planting, hilling or earthing up around the base of the V. subterranea plant and storing the legumes in traditional vessels and sacks. The need for integrating western scientific knowledge with native forecasts to inform the production of V. subterranea was uncovered. In addition to this, the needs of Tsonga and Venda communities should inform local policy interventions. Lastly, adaptation strategies that address food insecurity with V. subterranea being part of the agro-ecosystem deserve attention in scientific investigation and policymaking. / NRF