REGIONAL CLIMATE MODEL PERFORMANCE AND PREDICTION oF SEASONAL RAINFALL AND SURFACE TEMPERATURE oF UGANDA

Knowledge about future climate provides valuable insights into how the challenges posed by climate change and variability can be addressed. This study assessed the skill of the United Kingdom (UK) Regional Climate Model (RCM) PRECIS (Providing REgional Climates for Impacts Studies) in simulating rainfall and temperature over Uganda and also assess future impacts of climate when forced by an ensemble of two Global Climate Models (GCMs) for the period 2070-2100. Results show that the models captured fairly well the large scale flow signals influencing rainfall and temperature patterns over Uganda. Rainfall and temperature patterns were better resolved by the RCM than the GCMs. The rainfall and temperature patterns differed among the three seasons. Rainy season March to May (MAM) is likely to experience increment in both surface temperature (0.9\ub0 C) and rainfall (0.2 mm day-1). For September to october (SON) rainy season, an opposite trend in the two climate parameters, temperature and rainfall, will be registered with the former increasing by 0.9 \ub0C and the latter dropping by 0.7 mm day-1. For the dry season, June to August (JJA), both temperature and rainfall are projected to decrease by 0.3 \ub0 C and 0.4 mm day-1, respectively.La connaissance du climat de demain fournit un aper\ue7u sur la mani\ue8re dont les d\ue9fis pos\ue9s peuvent \ueatre adress\ue9s. Cette \ue9tude a \ue9valu\ue9 la comp\ue9tence du Mod\ue8le Climatique R\ue9gional (RCM) PRECIS du Royaume Uni (fournissant des climats r\ue9gionaux pour des \ue9tudes d\u2019impacts) dans la simulation de la pluviom\ue9trie et la temp\ue9rature en ouganda et, d\u2019autre part, \ue9tudier les impacts des climats une fois forc\ue9e par un ensemble de deux Mod\ue8les Climatiques \ue0 l\u2019\ue9chelle de l\u2019Univers (GCMs) pour les p\ue9riodes 2070-2100. Les r\ue9sultats montrent que les mod\ue8les ont raisonnablement saisi une large \ue9chelle du flow des signaux qui influencent la tendance de la pluviom\ue9trie et la temp\ue9rature en ouganda. Les tendances de la pluviom\ue9trie et la temp\ue9rature \ue9taient mieux d\ue9termin\ue9es par RCM que GCMs. Les tendances de la pluviom\ue9trie et la temp\ue9rature diff\ue9raient au cours des trois saisons. La saison pluvieuse Mars \ue0 Mai (MAM) connaitra probablement une augmentation de la temp\ue9rature (0.9 \ub0C) et de la pluviom\ue9trie (0.2 mm jr-1). Pour la saison de pluie de Septembre \ue0 octobre, une tendance contraire dans les deux param\ue8tres climatiques sera enregistr\ue9e avec la m\ueame augmentation de 0.9 \ub0C et une diminution de 0.7 mm jr-1de pluie. Pour la saison s\ue8che de Juin \ue0 Ao\ufbt (JJA), les projections montrent une diminution de la temp\ue9rature et de la pluie de 0.3 \ub0C et 0.4 mm jr-1, respectivement

Exploring visual soil evaluation and examination methods on highly-weathered tropical soil

National and international initiatives have been undertaken in Uganda to improve soil quality and increase crop production. However, means to evaluate and examine soil quality, particularly soil physical quality, is lacking in the country. In this study, visual soil evaluation and examination (VSEE) spade and core tests, which comprise rapid and simple methods to semi-quantitatively assess soil structure, have been tested. The derived soil quality scores Sq were compared with soil quality indicators SQi derived from traditional lab-based methods of soil structure analysis. Tests were conducted and samples taken in Uganda on highly-weathered soils with sandy clay loam texture. Both the 0-15 cm topsoil and the 15-30 cm moderately compacted subsoil were considered. Test and sampling sites comprised 18 farmers' fields (maize, Zea mays L.) that were under conventional tillage, permanent planting basins and rip lines for three years, as well as four locations in a natural forest. All VSEE approaches tested showed a significantly better Sq score in the natural forest (good quality) as compared to maize fields (fair/moderate quality), with the subsoil always showing lower quality than the topsoil. Methods based on Visual Evaluation of Soil Structure (VESS) were more responsive to differences in soil quality than the Visual Soil Assessment (VSA) approach. Statistical analysis showed that there was a good to moderate correlation between the VSEE-based Sq scores and lab-derived SQi values, with Pearson r correlation coefficients of 0.52-0.69 for bulk density, 0.66-0.78 for air capacity, 0.53-0.73 for air permeability, 0.52-0.72 for hydraulic conductivity, 0.18-0.48 for mean weight diameter under fast wetting. The correlation with an overall integrated index of soil quality SQI ranged between 0.56 and 0.77. Minimizing the potential effect of local variability by averaging Sq scores and SQi or SQI values per treatment and depth, improved the correlation, with e.g., Pearson r ranging from 0.84 to 0.95 when relating Sq to SQI We also found a significant correlation between VESS Sq scores and the shape of the water retention curve, particularly in the wet range (r > 0.50). Our results show that in general, VSEE methods are promising alternatives to evaluate differences in physical soil quality of highly-weathered soils in a rapid, intuitive, practical and cheap way

REGIONAL CLIMATE MODEL PERFORMANCE AND PREDICTION oF SEASONAL RAINFALL AND SURFACE TEMPERATURE oF UGANDA

Knowledge about future climate provides valuable insights into how the challenges posed by climate change and variability can be addressed. This study assessed the skill of the United Kingdom (UK) Regional Climate Model (RCM) PRECIS (Providing REgional Climates for Impacts Studies) in simulating rainfall and temperature over Uganda and also assess future impacts of climate when forced by an ensemble of two Global Climate Models (GCMs) for the period 2070-2100. Results show that the models captured fairly well the large scale flow signals influencing rainfall and temperature patterns over Uganda. Rainfall and temperature patterns were better resolved by the RCM than the GCMs. The rainfall and temperature patterns differed among the three seasons. Rainy season March to May (MAM) is likely to experience increment in both surface temperature (0.9° C) and rainfall (0.2 mm day-1). For September to october (SON) rainy season, an opposite trend in the two climate parameters, temperature and rainfall, will be registered with the former increasing by 0.9 °C and the latter dropping by 0.7 mm day-1. For the dry season, June to August (JJA), both temperature and rainfall are projected to decrease by 0.3 ° C and 0.4 mm day-1, respectively.La connaissance du climat de demain fournit un aperçu sur la manière dont les défis posés peuvent être adressés. Cette étude a évalué la compétence du Modèle Climatique Régional (RCM) PRECIS du Royaume Uni (fournissant des climats régionaux pour des études d’impacts) dans la simulation de la pluviométrie et la température en ouganda et, d’autre part, étudier les impacts des climats une fois forcée par un ensemble de deux Modèles Climatiques à l’échelle de l’Univers (GCMs) pour les périodes 2070-2100. Les résultats montrent que les modèles ont raisonnablement saisi une large échelle du flow des signaux qui influencent la tendance de la pluviométrie et la température en ouganda. Les tendances de la pluviométrie et la température étaient mieux déterminées par RCM que GCMs. Les tendances de la pluviométrie et la température différaient au cours des trois saisons. La saison pluvieuse Mars à Mai (MAM) connaitra probablement une augmentation de la température (0.9 °C) et de la pluviométrie (0.2 mm jr-1). Pour la saison de pluie de Septembre à octobre, une tendance contraire dans les deux paramètres climatiques sera enregistrée avec la même augmentation de 0.9 °C et une diminution de 0.7 mm jr-1de pluie. Pour la saison sèche de Juin à Août (JJA), les projections montrent une diminution de la température et de la pluie de 0.3 °C et 0.4 mm jr-1, respectivement