Rangelands are extremely important for livestock grazing purposes in South Africa. Grazing should thus be regulated in order to conserve grass, shrubs and trees thereby ensuring sustainability of rangelands. In South Africa, the existing national grazing capacity estimate was developed in 1993 and updated in 2005 using National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite data. Largely due to changing land use practices (as well as changing data availability), there exists a clear need to create a new estimate, making use of current available data. For Limpopo, a province shown to be prone to recent land degradation, droughts and climate change, developing such an updated carrying capacity (CC) product (adjusted monthly according to monitoring data and seasonal forecasts) may help support more sustainable agricultural practices. The main objectives of the study are to update current CC products and to create deviation maps from CC for several years with relevant data. For estimation of the CC product, input data have included Satellite Pour l'Observation de la Terre (SPOT) VEGETATION Dry Matter Productivity (DMP), vegetation map of 2009 and downscaled coupled model data (ECHAM4.5–MOM3-DC2). A tree density product of 2003, observed rainfall and secondary ground truth data are also used. Study results show that Remote Sensing (RS) and Geographic Information System (GIS) technology, Earth Observation System (EOS) data and products, climate data and ground truth data are successfully used in a series of steps, processes with modelling to ultimately estimate grazing capacity. It is clear that rainfall is a primary determinant of DMP. The Coupled General Circulation Model (CGCM) shows that the December-January-February (DJF) rainfall season is important as a predictor season for the November through to April (NDJFMA) DMP growing season for the Limpopo Province. This model can discriminate high and low DMP (and GC) seasons. This study shows that the DMP product can, with certain assumptions, be used as a proxy for grass biomass. There is a strong drive towards the application of seasonal forecasts in agriculture. This project demonstrates the development of a tailored forecast, an avenue that should be explored in enhancing relevance of forecasts to agricultural production. / Dissertation (MSc)--University of Pretoria, 2016. / Geography, Geoinformatics and Meteorology / MSc / Unrestricted

In order to make informed decisions, we need to resort to various types of information and we need to know how uncertain this information is. A commonly used source for information and subsequent action is weather forecasts. The communication of uncertainty in weather forecasts has been widely studied for English speaking audiences, resulting in a number of guidelines that practitioners can follow. For forecasts aimed at Russian speaking audiences there are very few, if no, such studies. The aim of this study is to extend previous research on the communication of uncertainties in weather forecasts to the Russian-speaking domain. The underlying hypothesis for this study is that it should be possible to distinguish texts from different types of forecasts, with different inherent uncertainty, by analysing the linguistic uncertainty markers in the text-based section of these forecasts. If this is not the case, this could in a first step be solved by applying the recommendations in the available guidelines, in a second step the guidelines themselves might need to be extended to meet the needs of the practitioners. To test the hypothesis, I analyse the expressed linguistic uncertainty in two different sources of meteorological information: weather forecasts and seasonal outlooks. The analysis shows that the original hypothesis can be confirmed: the differences between these two sources of information can be detected by analysing linguistic uncertainty markers. Further, the recommendations from the guidelines were met to a large extent, but both type of forecasts, in particular the seasonal outlooks, would benefit from a more consolidated approach. The analysis also shows that these guidelines could be improved by placing an increased emphasis on text-based forecasts, highlighting which linguistic means should be used for what purpose. The guidelines could be extended with language-specific best-practise examples. This way the guidelines would cater for a much larger user-base than they do at present.

Arctic sea ice has undergone a dramatic transformation in recent decades, including a substantial reduction in sea ice extent in summer months. Such changes, combined with relatively recent advancements in seasonal (1-12 months) to decadal forecasting, have prompted a rapidly-growing body of research on forecasting Arctic sea ice on seasonal timescales. These forecasts are anticipated to benefit a vast array of end-users whose activities are dependent on Arctic sea ice conditions. The research goal of this thesis is to address fundamental challenges pertaining to seasonal forecasts of Arcitc sea ice, with a particular focus placed on improving operational sea ice forecasts in the Canadian Seasonal to Interannual Prediction System (CanSIPS). Seasonal forecasts are strongly dependent on the accuracy of observations used as initial condition inputs. A key challenge initializing Arctic sea ice is the sparse availability of Arctic sea ice thickness (SIT) observations. I present on the development of three statistical models that can be used for estimating Arctic SIT in real time for sea ice forecast initialization. The three statistical models are shown to vary in their ability to capture the recent thinning of sea ice, as well as their ability to capture interannual variations in SIT anomalies; however, each of the models is shown to dramatically improve the representation of SIT compared to the climatological SIT estimates used to initialize CanSIPS. I conduct a thorough assessment of sea ice hindcast skill using the Canadian Climate Model, version 3 (one of two models used in CanSIPS), in which the dependence of hindcast skill on SIT initialization is investigated. From this assessment, it can be concluded that all three statistical models are able to estimate SIT sufficiently to improve hindcast skill relative to the climatological initialization. However, the accuracy with which the initialization fields represent both the thinning of the ice pack over time and interannual variability impacts predictive skill for pan-Arctic sea ice area (SIA) and regional sea ice concentration (SIC), with the most robust improvements obtained with two statistical models that adequately represent both processes. The final goal of this thesis is to improve the quantification of uncertainty in seasonal forecasts of regional Arctic sea ice coverage. Information regarding forecast uncertainty is crucial for end-users who want to quantify the risk associated with trusting a particular forecast. I develop statistical post-processing methodology for improving probabilistic forecasts of Arctic SIC. The first of these improvements is intended to reduce sampling uncertainty by fitting ensemble SIC forecasts to a parametric probability distribution, namely the zero- and one- inflated beta (BEINF) distribution. It is shown that overall, probabilistic forecast skill is improved using the parametric distribution relative to a simpler count-based approach; however, model biases can degrade this skill improvement. The second of these improvements is the introduction of a novel calibration method, called trend-adjusted quantile mapping (TAQM), that explicitly accounts for SIC trends and is specifically designed for the BEINF distribution. It is shown that applying TAQM greatly reduces model errors, and results in probabilistic forecast skill that generally surpasses that of a climatological reference forecast, and to some degree that of a trend-adjusted climatological reference forecast, particularly at shorter lead times. / Graduate

Tesis por compendio / [ES] En las próximas décadas, los fenómenos extremos como las sequías podrían volverse más frecuentes e intensos debido al cambio climático, afectando en gran medida a las cuencas con problemas de escasez hídrica. Por lo tanto, el estudio de estos fenómenos es esencial, así como predecir sus impactos asociados para garantizar una buena gestión de los recursos hídricos disponibles, sobre todo en sistemas de explotación altamente regulados y estresados, que bajo estas circunstancias ven afectadas su fiabilidad y vulnerabilidad. En esta tesis se aborda esta problemática por medio de un compendio de cinco publicaciones, todas ellas artículos. Dos de estos artículos están publicados en revistas indexadas en el Journal Citation Report (JCR), otros dos están publicados en una revista de reconocido prestigio de habla hispana, y el último se encuentra en proceso de revisión en otra revista indexada en el JCR. Todos los artículos publicados están relacionados con el desarrollo de una metodología de integración de proyecciones climáticas en la gestión y planificación hidrológica, para ayudar en el proceso de toma de decisiones e intentar prevenir los impactos cuantitativos y cualitativos de futuros eventos de sequía. Por otro lado, el artículo en proceso de revisión se centra en la integración de pronósticos estacionales en la evaluación del riesgo de sequía en tiempo real con la misma finalidad. En ambos casos se lleva a cabo un proceso de evaluación del riesgo de sequía, a medio o largo plazo, mediante una cadena de modelos y procesos de corrección y ajuste al caso de estudio, la cuenca del Júcar. De este proceso se obtiene un indicador de riesgo de sequía muy intuitivo que informa sobre la evolución probabilística de los recursos disponibles en el sistema, facilitando así la toma de decisiones a medio o largo plazo. Los principales resultados asociados a la gestión en tiempo real de la sequía indican que los métodos propuestos son prometedores, ya que todos ellos muestran mejores capacidades de predicción que el método implementado en la actualidad. Por otro lado, los resultados de cambio climático prevén un futuro complicado para la cuenca de estudio, con reducciones importantes de las aportaciones futuras (sobre todo para finales de siglo) y altas probabilidades de disponer de menores recursos hídricos en el sistema. Lo mismo ocurre al analizar la calidad del agua, ya que se estiman mayores afecciones para horizontes futuros, sobre todo en zonas relacionadas con la actividad agrícola. Sin embargo, existe una gran incertidumbre en estos resultados más allá de mediados de siglo, debido principalmente a la naturaleza variante de las proyecciones climáticas. A pesar de esta incertidumbre, las metodologías desarrolladas podrían considerarse como el primer paso para tener en cuenta las afecciones de un futuro cambiante en la gestión y planificación hidrológica de forma fiable y robusta, pudiendo implementarse en otras cuencas con la misma problemática y facilitando así la toma de decisiones frente a eventos extremos de sequía. / [CA] En les pròximes dècades, els fenòmens extrems com les sequeres podrien tornar-se més freqüents i intensos a causa del canvi climàtic, afectant en gran mesura a les conques amb problemes d'escassesa hídrica. Per tant, l'estudi d'estos fenòmens és essencial, així com predir els seus impactes associats per a garantir una bona gestió dels recursos hídrics disponibles, sobretot en sistemes d'explotació altament regulats i estressats, que davall estes circumstàncies veuen afectades la seua fiabilitat i vulnerabilitat. En esta tesi s'aborda esta problemàtica per mitjà d'un compendi de cinc publicacions, totes elles articles. Dos d'estos articles estan publicats en revistes indexades en el Journal Citation Report (JCR), altres dos estan publicats en una revista de reconegut prestigi de parla hispana, i l'últim es troba en procés de revisió en una altra revista indexada en el JCR. Tots els articles publicats estan relacionats amb el desenvolupament d'una metodologia d'integració de projeccions climàtiques en la gestió i planificació hidrològica, per a ajudar en el procés de presa de decisions i intentar previndre els impactes quantitatius i qualitatius de futurs esdeveniments de sequera. D'altra banda, l'article en procés de revisió es centra en la integració de pronòstics estacionals en l'avaluació del risc de sequera en temps real amb la mateixa finalitat. En ambdós casos es du a terme un procés d'avaluació del risc de sequera, a mig o llarg termini, per mitjà d'una cadena de models i processos de correcció i ajust al cas d'estudi, la conca del Xúquer. D'este procés s'obté un indicador de risc de sequera molt intuïtiu que informa sobre l'evolució probabilística dels recursos disponibles en el sistema, facilitant així la presa de decisions a mig o llarg termini. Els principals resultats associats a la gestió en temps real de la sequera indiquen que els mètodes proposats són prometedors, ja que tots ells mostren millors capacitats de predicció que el mètode implementat en l'actualitat. D'altra banda, els resultats de canvi climàtic preveuen un futur complicat per a la conca d'estudi, amb reduccions importants de les aportacions futures (sobretot per a finals de segle) i altes probabilitats de disposar de menors recursos hídrics en el sistema. El mateix ocorre al analitzar la qualitat de l'aigua, ja que s'estimen majors afeccions per a horitzons futurs, sobretot en zones relacionades amb l'activitat agrícola. No obstant això, hi ha una gran incertesa en estos resultats més enllà de mitjans de segle, degut principalment a la naturalesa variant de les projeccions climàtiques. A pesar d'esta incertesa, les metodologies desenvolupades podrien considerar-se com el primer pas per a tindre en compte les afeccions d'un futur canviant en la gestió i planificació hidrològica de forma fiable i robusta, podent implementar-se en altres conques amb la mateixa problemàtica i facilitant així la presa de decisions enfront d'esdeveniments extrems de sequera. / [EN] In the coming decades, extreme events such as droughts could become more frequent and intense due to climate change, greatly affecting basins with water scarcity problems. Therefore, the study of these phenomena is essential, as well as predicting their associated impacts to ensure good management of available water resources, especially in highly regulated and stressed exploitation systems, whose reliability and vulnerability are affected under these circumstances. This thesis addresses this problem by means of a compendium of five publications, all of them articles. Two of these articles are published in journals indexed in the Journal Citation Report (JCR), other two are published in a prestigious Spanish-language journal, and the last one is under review in another journal indexed in the JCR. All the published articles are related to the development of a methodology for the integration of climate projections in water planning and management, to help in the decision-making process and try to prevent the quantitative and qualitative impacts of future drought events. On the other hand, the article under revision focuses on the integration of seasonal forecasts in real-time drought risk assessment for the same purpose. In both cases, a drought risk assessment process is carried out, in the medium or long term, by means of a model chain and correction and adjustment processes to the case study, the Júcar River Basin. From this process, a very intuitive drought risk indicator is obtained, providing information on the probabilistic evolution of the resources available in the system and facilitating medium or long-term decision making. The main results associated with real-time drought management indicate that the proposed methods are promising, as they all show better predictive capabilities than the current method implemented in the basin. On the other hand, the climate change results predict a complicated future for the case study, with significant reductions in future inflows (especially by the end of the century) and high probabilities of having lower water resources in the system. The same occurs when analyzing water quality, since greater impacts are estimated for future horizons, especially in areas related to agricultural activity. However, there is great uncertainty in these results beyond mid-century, mainly due to the natural variability of climate projections. Despite this uncertainty, the methodologies developed could be considered as the first step to take into account the effects of a changing future in hydrological management and planning in a reliable and robust way, and could be implemented in other basins with the same problems, thus facilitating decision making to face extreme drought events. / Suárez Almiñana, S. (2021). Incorporación de las predicciones meteorológicas y climáticas en la planificación y gestión de las sequías. Aplicación a la Cuenca del Júcar [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/174533 / Compendio