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1.
Abstract Statistical analysis of extremes is often used for predicting the higher return-period events. In this paper, the trimmed L-moments with one smallest value trimmed—TL-moments (1,0)—are introduced as an alternative way to estimate floods for high return periods. The TL-moments (1,0) have an ability to reduce the undesirable influence that a small value in the statistical sample might have on a large return period. The main objective of this study is to derive the TL-moments (1,0) for the generalized Pareto (GPA) distribution. The performance of the TL-moments (1,0) was compared with L-moments through Monte Carlo simulation based on the streamflow data of northern Peninsular Malaysia. The result shows that, for some cases, the use of TL-moments (1,0) is a better option as compared to L-moments in modelling those series. Citation Ahmad, U.N., Shabri, A. & Zakaria, Z.A. (2011) Trimmed L-moments (1,0) for the generalized Pareto distribution. Hydrol.Sci. J. 56(6), 1053–1060. 相似文献
2.
An approach based on regional frequency analysis using L moments and LH moments are revisited in this study. Subsequently, an alternative regional frequency analysis using the partial L moments (PL moments) method is employed, and a new relationship for homogeneity analysis is developed. The results were then compared with those obtained using the method of L moments and LH moments of order two. The Selangor catchment, consisting of 37 sites and located on the west coast of Peninsular Malaysia, is chosen as a case study. PL moments for the generalized extreme value (GEV), generalized logistic (GLO), and generalized Pareto distributions were derived and used to develop the regional frequency analysis procedure. PL moment ratio diagram and Z test were employed in determining the best-fit distribution. Comparison between the three approaches showed that GLO and GEV distributions were identified as the suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation used for performance evaluation shows that the method of PL moments would outperform L and LH moments methods for estimation of large return period events. 相似文献
3.
AbstractTransfer function models of the rainfall–runoff relationship with various complexities are developed to investigate the hydrological behaviour of a tropical peat catchment that has undergone continuous drainage for a long time. The study reveals that a linear transfer function model of order one and noise term of ARIMA (1,0,0) best represents the monthly rainfall–runoff relationship of a drained peat catchment. The best-fitted transfer function model is capable of illustrating the cumulative hydrological effects of the catchment when subjected to drainage. Transfer function models of daily rainfall–runoff relationships for each year of the period 1983–1993 are also developed to decipher the changes in hydrological behaviour of the catchment due to drainage. The results show that the amount of rain water temporarily stored in the peat soil decreased and the catchment has become more responsive to rainfall over the study period.Editor Z.W. Kundzewicz; Associate editor D. HughesCitation Katimon, A., Shahid, S., Abd Wahab, A.K., and Shabri, A., 2013. Hydrological behaviour of a drained agricultural peat catchment in the tropics. 2: Time series transfer function modelling approach. Hydrological Sciences Journal, 58 (6), 1310–1325. 相似文献
4.
Ignatius Ani Madu 《GeoJournal》2010,75(2):175-184
The aim of this paper is to describe the rural structure of Nigeria on the basis of some indicators and internationally accepted
methodology rather than just the population criterion that is presently used in the country. This is necessary because as
is the case in most developing countries, this method of determining the rural structure does not make for comparison between
countries. To achieve the aim, 14 indicators were selected from the 2006 Annual Abstract of Statistics and Factor Analysis
employed to determine the structure, while the pattern was mapped by Arc View GIS 3.2a software. The factor analysis identified
five underlying dimensions which explain 77.6% of the total variance that determine the structure of rurality in Nigeria.
Based on the pattern of the factor loadings, five typologies of rural were identified. The research further shows that Nigeria
is still dominantly rural. The implications of the findings and the need for concerted efforts on rural development in the
country are highlighted. 相似文献
5.
The effective density and the strength of flocs formed in the laboratory from mud from the Tamar Estuary reached a maximum
value at a salinity of 10–15‰ within the concentration range studied (0.1–1.0 g liter−1). For a constant salinity and concentration, the density decreases with increasing floc size. The strength of the flocs increases
with the floc diameter. However, the strength of the individual particle bonds within the floc decreases with size. Large
flocs were relatively more brittle than smaller ones. The results suggest that larger flocs may be disrupted by the formation
of unequal fragments. 相似文献
6.
Ani Bin Shabri Zalina Mohd Daud Noratiqah Mohd Ariff 《Theoretical and Applied Climatology》2011,104(3-4):561-570
Information related to distributions of rainfall amounts are of great importance for designs of water-related structures. One of the concerns of hydrologists and engineers is the probability distribution for modeling of regional data. In this study, a novel approach to regional frequency analysis using L-moments is revisited. Subsequently, an alternative regional frequency analysis using the TL-moments method is employed. The results from both methods were then compared. The analysis was based on daily annual maximum rainfall data from 40 stations in Selangor Malaysia. TL-moments for the generalized extreme value (GEV) and generalized logistic (GLO) distributions were derived and used to develop the regional frequency analysis procedure. TL-moment ratio diagram and Z-test were employed in determining the best-fit distribution. Comparison between the two approaches showed that the L-moments and TL-moments produced equivalent results. GLO and GEV distributions were identified as the most suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation was used for performance evaluation, and it showed that the method of TL-moments was more efficient for lower quantile estimation compared with the L-moments. 相似文献
7.
ABSTRACT Urban greening is about bringing vegetation into cities in ways that produce flourishing urban ecologies whilst also making cities more liveable for human inhabitants. We focus here on greening that is done through the maintenance or establishment of gardens, parks, urban forests and informal spaces. We argue that in contexts with established property law systems, such as Australia, making urban ecologies through greening is shaped heavily by relations of property tied to land. This includes constraining the extent to which urban greening can contribute to socio-ecologically just cities. We suggest that progressing greening that is more attentive to the geographies and temporalities of more-than-human life requires us to trouble the hold of property over greening. To do this we explore the possibilities opened up by the lens of urban commons/commoning. We engage with the emerging concept of more-than-human commoning as a way of attuning urban greening to nonhuman agency and affordances. We also grapple with the risk of obscuring or concealing difference between humans in the way commoning makes room for more-than-humans, especially in the context of settler-colonialism. We conclude by calling for a more overt politics of urban greening that encompasses diverse human and more-than-human experiences of the city. 相似文献
8.
Abstract Statistical analysis of extreme events is often carried out to predict large return period events. In this paper, the use of partial L-moments (PL-moments) for estimating hydrological extremes from censored data is compared to that of simple L-moments. Expressions of parameter estimation are derived to fit the generalized logistic (GLO) distribution based on the PL-moments approach. Monte Carlo analysis is used to examine the sampling properties of PL-moments in fitting the GLO distribution to both GLO and non-GLO samples. Finally, both PL-moments and L-moments are used to fit the GLO distribution to 37 annual maximum rainfall series of raingauge station Kampung Lui (3118102) in Selangor, Malaysia, and it is found that analysis of censored rainfall samples of PL-moments would improve the estimation of large return period events. Editor D. Koutsoyiannis; Associate editor K. Hamed Citation Zakaria, Z.A., Shabri, A. and Ahmad, U.N., 2012. Estimation of the generalized logistic distribution of extreme events using partial L-moments. Hydrological Sciences Journal, 57 (3), 424–432. 相似文献
9.
Ummi Nadiah Ahmad Ani Shabri Zahrahtul Amani Zakaria 《Theoretical and Applied Climatology》2013,111(3-4):649-663
TL-moments approach has been used in an analysis to determine the best-fitting distributions to represent the annual series of maximum streamflow data over 12 stations in Terengganu, Malaysia. The TL-moments with different trimming values are used to estimate the parameter of the selected distributions namely: generalized pareto (GPA), generalized logistic, and generalized extreme value distribution. The influence of TL-moments on estimated probability distribution functions are examined by evaluating the relative root mean square error and relative bias of quantile estimates through Monte Carlo simulations. The boxplot is used to show the location of the median and the dispersion of the data, which helps in reaching the decisive conclusions. For most of the cases, the results show that TL-moments with one smallest value was trimmed from the conceptual sample (TL-moments (1,0)), of GPA distribution was the most appropriate in majority of the stations for describing the annual maximum streamflow series in Terengganu, Malaysia. 相似文献
10.
Ani Shabri 《水文科学杂志》2013,58(7):1275-1293
Abstract This paper investigates the ability of a least-squares support vector machine (LSSVM) model to improve the accuracy of streamflow forecasting. Cross-validation and grid-search methods are used to automatically determine the LSSVM parameters in the forecasting process. To assess the effectiveness of this model, monthly streamflow records from two stations, Tg Tulang and Tg Rambutan of the Kinta River in Perak, Peninsular Malaysia, were used as case studies. The performance of the LSSVM model is compared with the conventional statistical autoregressive integrated moving average (ARIMA), the artificial neural network (ANN) and support vector machine (SVM) models using various statistical measures. The results of the comparison indicate that the LSSVM model is a useful tool and a promising new method for streamflow forecasting. Editor D. Koutsoyiannis; Associate editor L. See Citation Shabri, A. and Suhartono, 2012. Streamflow forecasting using least-squares support vector machines. Hydrological Sciences Journal, 57 (7), 1275–1293. 相似文献