Drought analysis and water resource availability using standardised precipitation evapotranspiration index

Trend analysis for potential evapotranspiration (PET) and climatic water balance (CWB) is critical in identifying the wetness or dryness episodes with respect to the water surplus or deficit. The PET is computed based on the monthly average temperature for the entire Peninsular Malaysia using Thornthwaite parameterization. The trends and slope's magnitude for the PET and CWB were then investigated using Mann-Kendall, Spearman's rho tests and Thiel-Sen estimator. The 1-, 3-, 6- and 12-month standardised precipitation evapotranspiration index (SPEI) is applied to determine the drought episodes and the average recurrence interval are calculated based on the SPEI. The results indicate that most of the stations show an upward trend in annual and monthly PET while majority of the regions show an upward trend in annual CWB except for the Pahang state. The increasing trends detected in the CWB describe water is in excess especially during the northeast monsoons while the decreasing trends imply water insufficiency. The excess water is observed mostly in January especially in the west coast, east coast and southwest regions that suggest more water is available for crop requirement. The average recurrence interval for drought episodes is almost the same for the smaller severity with various time scale of SPEI and high probability of drought occurrence is observed for some regions. The findings are useful for policymakers and practitioners to improve water resources planning and management, in particular to minimise drought effects in the future. Future research shall address the influence of topography on drought behaviour using more meteorological stations and to include east Malaysia in the analysis

Trend analysis for drought event in Peninsular Malaysia

In this paper, the geostatistics application is employed for analysis of drought events in verifying the upward or increasing and downward or decreasing trend during the drought occurrence. About 33 years of daily precipitation data obtained from 69 stations during the period of November, 1975 to October, 2008 in Peninsular Malaysia are analyzed to characterize the trend of dry events. The amount of precipitation is classified based on the standardized precipitation index (SPI) to determine the drought periods and proceed with the Mann-Kendall test for trend identification. These results are further verified by applying the kriging method. The kriging results describe that the trend values for drought events in Peninsular Malaysia interprets an upward trend especially in eastern and western parts

Trivariate copula in drought analysis: a case study in peninsular Malaysia

Drought severity, duration and intensity are three main variables that are useful in providing a deeper and more conclusive understanding of a drought condition. A joint distribution using trivariate copula model was introduced and employed to Peninsular Malaysia in describing the correlation and dependency between the drought variables instead of an independent modelling. The drought variables were categorised using the standardised precipitation index, and subsequently the Akaike Information Criterion was calculated to verify the best fitted copula distribution. The Plackett distribution is identified as the best fitted trivariate copula distribution to describe the relationship between drought severity, duration and intensity. The conditional probability and joint return periods of drought recurrence were further analysed to describe the drought properties comprehensively. The results of joint return period suggest that the western region of Peninsular Malaysia is expected to have more frequent drought recurrences under different conditions. These results are able to describe the three drought properties concurrently, thus is more useful compared to the current practice that use a single variable

Parameter estimation for bivariate mixed lognormal distribution

Bivariate mixed lognormal distribution is a probability model used for representing rainfalls behavior at two monitoring stations. The paper discuss on the parameter estimation for bivariate mixed lognormal distribution in which all parameters are assumed to be unknown. Six cases were considered in the analysis and the parameters were estimated using the maximum likelihood. The optimal model was selected based on the minimum Akaike’s information criterion (AIC) from selected model. The analysis is run by using the rainfall data observed for the time period of 33 years (1975-2007) from Arau, Perlis with each of the other 7 nearby monitoring stations and 5 far distance stations. Among the 7 stations studied, 6 stations (87.5%) choose the same case model (M2) as the minimum AIC procedures. Meanwhile, 4 of the far distance stations choose the case M2 as the best fit case model

Bivariate copula in fitting rainfall data

The usage of copula to determine the joint distribution between two variables is widely used in various areas. The joint distribution of rainfall characteristic obtained using the copula model is more ideal than the standard bivariate modelling where copula is belief to have overcome some limitation. Six copula models will be applied to obtain the most suitable bivariate distribution between two rain gauge stations. The copula models are Ali-Mikhail-Haq (AMH), Clayton, Frank, Galambos, Gumbel-Hoogaurd (GH) and Plackett. The rainfall data used in the study is selected from rain gauge stations which are located in the southern part of Peninsular Malaysia, during the period from 1980 to 2011. The goodness-of-fit test in this study is based on the Akaike information criterion (AIC)

Characterisation of drought properties with bivariate copula analysis

Drought severity and duration are usually modelled independently. However, these two characteristics are known to be related. To model this relationship, a joint distribution of drought severity and duration using a bivariate copula model is proposed and applied to daily rainfall data (1976-2007) of 30 rain gauge stations in Peninsular Malaysia. The drought characteristics are classified using the standardized precipitation index (SPI) and their univariate marginal distributions are further identified by fitting exponential, gamma, generalized extreme value, generalized gamma, generalized logistics, generalized pareto, gumbel max, gumbel min, log-logistic, log-pearson3, log-normal, normal, pearson 5, pearson 6 and weibull distributions. The three-parameter log-normal distribution is identified as the best fitting distribution for drought severity while the generalized pareto distribution is determined as the most appropriate distribution for drought duration with respect to the application of the Anderson-Darling procedure. The dependency among the drought properties is analysed using Kendall's τ method. The maximum likelihood estimation of the univariate marginal distributions and the maximisation of the bivariate likelihood are employed to compute the Akaike Information Criterion (AIC) values in verifying the best fitting copula distribution. The Galambos distribution is recognised as the most appropriate copula distribution for describing the relationship between drought severity and duration. The conditional drought probability and drought return period are further described to explain the drought properties comprehensively. The probabilities of drought occurrences under certain circumstances with a specific seriousness or duration can be determined in order to verify the possibility of drought episodes. The return period of a recurrent drought has also been investigated to identify the time-interval for repeated drought occurrences under similar situation

Introducing the mixed distribution in fitting rainfall data

Several types of mixed distribution are proposed and tested in order to determine the best model in describing daily rainfall amount in Peninsular Malaysia for the time period of 33 years. A mixed distribution is a mixture of discrete and continuous daily rainfall which included the dry days. The mixed distributions tested in this study were exponential distribution, gamma distribution, weibull distribution and lognormal distribution. The model will be selected based on the Akaike Information Criterion (AIC). In general, the mixed lognormal distribution has been selected as the best model for most of the rain gauge stations in Peninsular Malaysia. However, these results are greatly influenced by the topographical, geographical and climatic changes of the rain gauge stations

Parameter estimation for bivariate mixed lognormal distribution

Bivariate mixed lognormal distribution is a probability model used for representing rainfalls behavior at two monitoring stations. The paper discuss on the parameter estimation for bivariate mixed lognormal distribution in which all parameters are assumed to be unknown. Six cases were considered in the analysis and the parameters were estimated using the maximum likelihood. The optimal model was selected based on the minimum Akaike’s information criterion (AIC) from selected model. The analysis is run by using the rainfall data observed for the time period of 33 years (1975-2007) from Arau, Perlis with each of the other 7 nearby monitoring stations and 5 far distance stations. Among the 7 stations studied, 6 stations (87.5%) choose the same case model (M2) as the minimum AIC procedures. Meanwhile, 4 of the far distance stations choose the case M2 as the best fit case model

Rainfall characterisation by application of standardised precipitation index (SPI) in Peninsular Malaysia

The interpretations of trend behaviour for dry and wet events are analysed in order to verify the dryness and wetness episodes. The fitting distribution of rainfall is computed to classify the dry and wet events by applying the standardised precipitation index (SPI). The rainfall amount for each station is categorised into seven categories, namely extremely wet, severely wet, moderately wet, near normal, moderately dry, severely dry and extremely dry. The computation of the SPI is based on the monsoon periods, which include the northeast monsoon, southwest monsoon and inter-monsoon. The trends of the dry and wet periods were then detected using the Mann-Kendall trend test and the results indicate that the major parts of Peninsular Malaysia are characterised by increasing droughts rather than wet events. The annual trends of drought and wet events of the randomly selected stations from each region also yield similar results. Hence, the northwest and southwest regions are predicted to have a higher probability of drought occurrence during a dry event and not much rain during the wet event. The east and west regions, on the other hand, are going through a significant upward trend that implies lower rainfall during the drought episodes and heavy rainfall during the wet events