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• W853850474 abstract "Drought monitoring and early warning are essential elements impacting drought sensitive sectors such as primary production, industrial and consumptive water users. A quantitative estimate of the probability of occurrence and the anticipated severity of drought is crucial for the development of mitigating strategies. The overall aim of this study is to develop a methodology to assess drought frequency and severity and to advance the understanding of monitoring and predicting droughts in the future. Seventy (70) meteorological stations across Victoria, Australia were selected for analysis. To achieve the above objective, the analysis was initially carried out to select the most applicable meteorological drought index for Victoria. This is important because to date, no drought indices are applied across Australia by any Commonwealth agency quantifying drought impacts. An evaluation of existing meteorological drought indices namely, the Standardised Precipitation Index (SPI), the Reconnaissance Drought Index (RDI) and Deciles was first conducted to assess their suitability for the determination of drought conditions. The use of the Standardised Precipitation Index (SPI) was shown to be satisfactory for assessing and monitoring meteorological droughts in Australia. When applied to data, SPI was also successful in detecting the onset and the end of historical droughts. Temporal changes in historic rainfall variability and the trend of SPI were investigated using non-parametric trend techniques to detect wet and dry periods across Victoria, Australia. The first part of the analysis was carried out to determine annual rainfall trends using Mann Kendall (MK) and Sen’s slope tests at five selected meteorological stations with long historical records (more than 100 years), as well as a short sub-set period (1949-2011) of the same data set. It was found that different trend results were obtained for the sub-set. For SPI trend analysis, it was observed that, although different results were obtained showing significant trends, SPI gave a trend direction similar to annual precipitation (downward and upward trends). In addition, temporal trends in the rate of occurrence of drought events (i.e. inter-arrival times) were examined. The fact that most of the stations showed negative slopes indicated that the intervals between events were becoming shorter and the frequency of events was temporally increasing. Based on the results obtained from the preliminary analysis, the trend analyses were then carried out for the remaining 65 stations. The main conclusions from these analyses are summarized as follows; 1) the trend analysis was observed to be highly dependent on the start and end dates of analysis. It is recommended that in the selection of time period for the drought, trend analysis should consider the length of available data sets. Longer data series would give more meaningful results, thus improving the understanding of droughts impacted by climate change. 2) From the SPI and inter-arrival drought trends, it was observed that some of the study areas in Victoria will face more frequent dry period leading to increased drought occurrence. Information similar to this would be very important to develop suitable strategies to mitigate the impacts of future droughts. The main objective of this study was the development of a methodology to assess drought risk for each region based on a frequency analysis of the drought severity series using the SPI index calculated over a 12-month duration. A novel concept centric on drought severity-duration-frequency (SDF) curves was successfully derived for all the 70 stations using an innovative threshold approach. The methodology derived using extreme value analysis will assist in the characterization of droughts and provide useful information to policy makers and agencies developing drought response plans. Using regionalisation techniques such as Cluster analysis and modified Andrews curve, the study area was separated into homogenous groups based on rainfall characteristics. In the current Victorian application the study area was separated into six homogeneous clusters with unique signatures. A set of mean SDF curves was developed for each cluster to identify the frequency and severity of the risk of drought events for various return periods in each cluster. The advantage of developing a mean SDF curve (as a signature) for each cluster is that it assists the understanding of drought conditions for an ungauged or unknown station, the characteristics of which fit existing cluster groups. Non-homogeneous Markov Chain modelling was used to estimate the probability of different drought severity classes and drought severity class predictions 1, 2 and 3 months ahead. The non-homogeneous formulation, which considers the seasonality of precipitation, is useful for understanding the evolution of drought events and for short-term planning. Overall, this model predicted drought situations 1 month ahead well. However, predictions 2 and 3 months ahead should be used with caution. Many parts of Australia including Victoria have experienced their worst droughts on record over the last decade. With the threat of climate change potentially further exacerbating droughts in the years ahead, a clear understanding of the impact of droughts is vital. The information on the probability of occurrence and the anticipated severity of drought will be helpful for water resources managers, infrastructure planners and government policy-makers with future infrastructure planning and with the design and building of more resilient communities." @default.
• W853850474 created "2016-06-24" @default.
• W853850474 creator A5068160797 @default.
• W853850474 date "2014-08-01" @default.
• W853850474 modified "2023-09-27" @default.
• W853850474 title "Methodology for development of drought severity-duration-frequency (SDF) Curves" @default.
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