Published Article / The objective of this study was to characterize meteorological droughts in the Central Region of South Africa, Modder River Basin, C52A quaternary catchment using two popular drought indices: Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI) and to compare the two indices. Drought events were characterized based on their frequency, duration, magnitude and intensity. The indices were computed for the time-scales that are important for planning and management of water resources, i.e. 3-, 6- and 12-month time-scales. The basic meteorological input data used in the computation of these indices were 57 years (1950-2007) of monthly precipitation and monthly temperature data which were recorded at The Cliff weather station in the quaternary catchment. It was found that both SPI and SPEI responded to drought events in similar fashion in all time-scales. During the analysis period, a total of 37, 26 and 17 drought events were identified in the area based on 3-, 6-, and 12-month times-scales, respectively. Considering event magnitude as severity parameter, results from both indices identified the periods 1984-1985, 1992-1993 and 2003-2005 as the severest drought periods in the area. However, when the effects of both drought duration and magnitude are considered (drought intensity), the most severest drought events were identified during the years 1982/83, 1966 and 1973 based on 3-, 6- and 12-month timescales, respectively. It was concluded that although the SPEI generally exhibits veracity over SPI by including, apart from precipitation, additional meteorological parameter, mean temperature, SPI should be adopted as an appropriate drought monitoring tool in an area, like Africa, where meteorological data are scarce.

Submitted by Viviane Lima da Cunha (viviane@biblioteca.ufpb.br) on 2017-07-19T12:48:07Z No. of bitstreams: 1 arquivototal.pdf: 11581085 bytes, checksum: 664ef10dee0bc5fb53b861022004ca1b (MD5) / Made available in DSpace on 2017-07-19T12:48:07Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 11581085 bytes, checksum: 664ef10dee0bc5fb53b861022004ca1b (MD5) Previous issue date: 2015-09-25 / The precipitation, due to its importance, is considered one of the main variables of the hydrological cycle. An alternative to collect rainfall data is using rainfall measurements by sensors/satellites. Among these kinds of alternative, the Tropical Rainfall Measuring Mission (TRMM) allows the collection with a spatial resolution 0.25º × 0.25º. Thus, the objective of the study is to understand, in more detail, the behavior and distribution of rainfall throughout the Upper São Francisco basin (Sub-40), in a recent period (1998-2013). The survey was conducted in the following steps: collection of TRMM rainfall data from 1998 to 2013 organizing them monthly and yearly; getting Três Marias reservoir in flow data; getting altimetry SRTM data; analyzing the correlation between the TRMM precipitation and the inflows to Três Marias reservoir; generating surface profiles to compare with the precipitation data, analyzing the number of consecutive dry days and consecutive wet days; computing the Standardized Precipitation Index - SPI for each point (169 points); spatial distribution of annual and monthly accumulated rainfall data, the correlation of rainfall and flow, of consecutive wet and dry days, the SPI index and cluster analysis. According to the results, it can be concluded that the years of highest and lowest value of annual rainfall depth was respectively 2009 and 2012. The driest months are June to August, and July is the driest one. In contrast, the wettest months are from November to January, and most rainy month is December. The annual and monthly precipitation depth showed that the northeast region of the basin rains less and the western and southern basin are wetter. The precipitation response to the inflow to the Três Marias reservoir is four days after the rainfall occurs. The relation between precipitation and altimetry shows that most of the annual rainfall depth is directly proportional to altimetry, but in some cases it shows little variability in the ground. Regarding the SPI, it was possible to calculate the beginning, end, intensity and magnitude of each dry and wet season. From the maps, SPI spatial information was produced in order to identify for each period the regions with highest and lowest values. By means of the map and dendrogram clusters, regions with higher and lower similarity between the monthly accumulated rainfall data were identified. Finally, the TRMM sensor proved useful in the analysis of spatial and temporal variability of precipitation over the studied basin, accounting satisfactorily dry and rainy periods. With easy acquisition and handling, satellite data is a viable alternative to collect precipitation data with spatial and temporal quality, especially in areas of difficult access or in developing countries. / A precipitação, pela sua importância, é considerada uma das principais variáveis do ciclo hidrológico. Uma alternativa para coletar dados de chuva é utilizar precipitações obtidas por sensores/satélites. Dentre estes, a Tropical Rainfall Measuring Mission (TRMM) permite a coleta com resolução espacial de 0,25º × 0,25º. Com isso, o objetivo do estudo é compreender, de forma mais detalhada, o comportamento e a distribuição da precipitação ao longo da bacia do Alto São Francisco (Sub-40), em período recente (1998−2013). A pesquisa foi realizada nas seguintes etapas: coleta de dados do TRMM para o período de 1998 a 2013 organizando-os em acumulados mensais e anuais; coleta dos dados de vazão do reservatório Três Marias; coleta de dados de altimetria SRTM; correlação diária entre os elementos de precipitação TRMM; analisar o comportamento da precipitação anual da Sub-40 frente aos dados altimétricos; identificar a quantidade de dias secos e úmidos consecutivos de cada ponto da grade utilizado; extração do Índice Padronizado de Precipitação - SPI para cada ponto (169 pontos); espacialização dos dados de precipitação acumulada anual e mensal, da correlação de chuva e vazão, dos dias secos e úmidos consecutivos, do Índice SPI e da análise de cluster. De acordo com os resultados obtidos, pode-se concluir que os anos de maior e menor valor de precipitações acumuladas anuais foram respectivamente os anos de 2009 e 2012. Os meses mais secos foram os de junho a agosto, sendo julho o mês mais seco. Em contrapartida, os meses mais úmidos foram de novembro a janeiro, com maior precipitação ocorrendo em dezembro. Os dados de precipitação acumuladas anuais e mensais mostraram que a região nordeste da bacia chove menos e que o oeste e sul da bacia são mais úmidos. O tempo de resposta da precipitação frente à vazão afluente ao reservatório Três Marias é de quatro dias após a ocorrência de chuvas. A relação entre a precipitação e altimetria mostra que a maioria dos dados de precipitações acumuladas anuais é diretamente proporcional à altimetria, mas que em alguns casos ela apresenta pouca variabilidade em relação ao terreno. Com relação ao SPI, a partir dos mapas, produziram-se informações de SPI de maneira espacializada identificando a cada período as regiões de maiores e menores valores. Observando os mapas de clusters e dendrograma identificaram-se as regiões com maior e menor similaridade entre os dados de precipitação acumulada mensal. Por fim, o sensor TRMM se mostrou hábil na análise da variabilidade espaço-temporal da precipitação sobre a bacia, representando de forma satisfatória os períodos secos e chuvosos. Com fácil aquisição e manuseio, os dados do satélite são uma alternativa viável para se coletar informações pluviométricas com qualidade espacial e temporal, principalmente em regiões de difícil acesso ou em países em desenvolvimento.

Meteorological drought indices are commonly calculated from climatic stations that have long-term historical data and then converted to a regular grid using spatial interpolation methods. The gridded drought indices are mapped to aid decision making by policy makers and the general public. This study analyzes the spatial performance of interpolation methods for meteorological drought indices in the United States based on data from the Co-operative Observer Network (COOP) and United States Historical Climatology Network (USHCN) for different months, climatic regions and years. An error analysis was performed using cross-validation and the results were compared for the 9 climate regions that comprise the United States. Errors are generally higher in regions and months dominated by convective precipitation. Errors are also higher in regions like the western United States that are dominated by mountainous terrain. Higher errors are consistently observed in the southeastern U.S. especially in Florida. Interpolation errors are generally higher in the summer than winter. The accuracy of different drought indices was also compared. The Standardized Precipitation and Evapotranspiration Index (SPEI) tends to have lower errors than Standardized Precipitation Index (SPI) in seasons with significant convective precipitation. This is likely because SPEI uses both precipitation and temperature data in its calculation, whereas SPI is based solely on precipitation. There are also variations in interpolation accuracy based on the network that is used. In general, COOP is more accurate than USHCN because the COOP network has a higher density of stations. USHCN is a subset of the COOP network that is comprised of high quality stations that have a long and complete record. However the difference in accuracy is not as significant as the difference in spatial density between the two networks. For multiscalar SPI, USHCN performs better than COOP because the stations tend to have a longer record. The ordinary kriging method (with optimal function fitting) performed better than Inverse Distance Weighted (IDW) methods (power parameters 2.0 and 2.5) in all cases and therefore it is recommended for interpolating drought indices. However, ordinary kriging only provided a statistically significant improvement in accuracy for the Palmer Drought Severity Index (PDSI) with the COOP network. Therefore it can be concluded that IDW is a reasonable method for interpolating drought indices, but optimal ordinary kriging provides some improvement in accuracy. The most significant factor affecting the spatial accuracy of drought indices is seasonality (precipitation climatology) and this holds true for almost all the regions of U.S. for 1-month SPI and SPEI. The high-quality USHCN network gives better interpolation accuracy with 6-, 9- and 12-month SPI and variation in errors amongst the different SPI time scales is minimal. The difference between networks is also significant for PDSI. Although the absolute magnitude of the differences between interpolation with COOP and USHCN are small, the accuracy of interpolation with COOP is much more spatially variable than with USHCN.

Anthropogenic activities including urbanization, rapid industrialization, deforestation and burning of fossil fuels are broadly agreed on as primary causes for ongoing climate change. Scientists agree that climate change over the next century will continue to impact water resources with serious implications including storm surge flooding and a sea level rise projected for North America. To date, the majority of climate change studies conducted across the globe have been for large-sized watersheds; more attention is required to assess the impact of climate change on smaller watersheds, which can help to better frame sustainable water management strategies. In the first of three studies described in this dissertation, trends in annual precipitation and air-temperature across the Commonwealth of Kentucky were evaluated using the non-parametric Mann-Kendall test considering meteorological time series data from 84 weather stations. Results indicated that while annual precipitation and mean annual temperature have been stable for most of Kentucky over the period 1950-2010, there is evidence of increases (averages of 4.1 mm/year increase in annual precipitation and 0.01 °C/year in mean annual temperature) along the borders of the Kentucky. Considered in its totality, available information indicates that climate change will occur – indeed, it is occurring – and while much of the state might not clearly indicate it at present, Kentucky will almost certainly not be exempt from its effects. Spatial analysis of the trend results indicated that eastern part of the state, which is characterized by relatively high elevations, has been experiencing decreasing trends in precipitation. In the second study, trends and variability of seven extreme precipitation indices (total precipitation on wet days, PRCPTOT; maximum length of dry and wet periods, CDD and CWD, respectively; number of days with precipitation depth ≥20 mm, R20mm; maximum five-day precipitation depth, RX5day; simple daily precipitation intensity, SDII; and standardized precipitation index, SPI were analyzed for the Kentucky River Basin for both baseline period of 1986-2015 and the late-century time frame of 2070-2099. For the baseline period, the majority of the indices demonstrated increasing trends; however, statistically significant trends were found for only ~11% of station-index combinations of the 16 weather stations considered. Projected magnitudes for PRCPTOT, CDD, CWD, RX5day and SPI, indices associated with the macroweather regime, demonstrated general consistency with trends previously identified and indicated modest increases in PRCPTOT and CWD, slight decreases in CDD, mixed results for RX5day, and increased non-drought years in the late century relative to the baseline period. The study’s findings indicate that future conditions might be characterized by more rainy days but fewer large rainfall events; this might lead to a scenario of increased average annual rainfall but, at the same time, increased water scarcity during times of maximum demand. In the third and final study, the potential impact of climate change on hydrologic processes and droughts over the Kentucky River basin was studied using the watershed model Soil and Water Assessment Tool (SWAT). The SWAT model was successfully calibrated and validated and then forced with forecasted precipitation and temperature outputs from a suite of CMIP5 global climate model (GCMs) corresponding to two different representative concentration pathways (RCP 4.5 and 8.5) for two time periods: 2036-2065 and 2070-2099, referred to as mid-century and late-century, respectively. Climate projections indicate that there will be modest increases in average annual precipitation and temperature in the future compared to the baseline (1976-2005) period. Monthly variations of water yield and surface runoff demonstrated an increasing trend in spring and autumn, while winter months are projected as having decreasing trends. In general, maximum drought length is expected to increase, while drought intensity might decrease under future climatic conditions. Hydrological droughts (reflective of water availability), however, are predicted to be less intense but more persistent than meteorological droughts (which are more reflective of only meteorological variables). Results of this study could be helpful for preparing any climate change adaptation plan to ensure sustainable water resources in the Kentucky River Basin.