Nonlinear analysis of seasonality and stochasticity of the Indus River

Abstract

One of the world's largest irrigation networks, based on the Indus River system in Pakistan, faces serious scarcity of water in one season and disastrous floods in another. The system is dominated both by monsoon and by snow and glacier dynamics, which confer strong seasonal and inter-annual variability. In this paper two different forecasting methods are utilized to analyse the long-term seasonal behaviour of the Indus River. The study also assesses whether the strong seasonal behaviour is dominated by the presence of low-dimensional nonlinear dynamics, or whether the periodic behaviour is simply immersed in random fluctuations. Forecasts obtained by nonlinear prediction (NLP) and the seasonal autoregressive integrated moving average (SARIMA) methods show that the performance of NLP is relatively better than the SARIMA method. This, along with the low values of the correlation dimension, is indicative of low-dimensional nonlinear behaviour of the hydrological dynamics. A relatively better performance of NLP, using an inverse technique, may also be indicative of the low-dimensional behaviour. Moreover, the embedding dimension of the best NLP forecasts is in good agreement with the estimated correlation dimension. This provides evidence that the nonlinearity inherent in the monthly river flow due to the snowmelt and the monsoon variations dominate over the high-dimensional components and might be exploited for prediction and modelling of the complex hydrological system.

Citation Hassan, S. A. & Ansari, M. R. K. (2010) Nonlinear analysis of seasonality and stochasticity of the Indus River. Hydrol. Sci. J. 55(2), 250–265.     

Estimation of the generalized logistic distribution of extreme events using partial L-moments

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.     

Spatial modelling of site suitability assessment for hospitals using geographical information system-based multicriteria approach at Qazvin city,Iran

Due to the population growth and continuous migration of people from rural areas to urban areas, it is important to identify the suitable locations for future development in order to find suitable sites for various kinds of facilities such as schools, hospital and fire stations for new and existing urban areas. Site suitability modelling is a complex process involving various kinds of objectives and issues. Such a complex process includes spatial analysis, use of several decision support tools such as high-spatial resolution remotely sensed data, geographical information system (GIS) and multi criteria analysis (MCA) such as analytical hierarchy process (AHP), and in some cases, prediction techniques like cellular automata (CA) or artificial neural networks (ANN). This paper presents a comparison between the results of AHP and the ordinary least square (OLS) evaluation model, based on various criteria, to select suitable sites for new hospitals in Qazvin city, Iran. Based on the obtained results, proximity to populated areas (0.3) and distance to air polluted areas (0.23–0.26) were the two highest important criteria with high weight value. The results show that these two techniques not only have similarity in size (in m²) for each suitability class but they also have similarity in spatial distribution of each class in the entire study area. Based on calculations of both techniques, 1–2%, 25%, 40–43%, 16–20% and 14% of study areas are assigned as ‘not suitable', ‘less suitable', ‘moderately suitable', ‘suitable' and ‘most suitable' areas for construction of new hospitals. Results revealed that a 75% similarity was found in the distribution of suitability classes in Qazvin city using both techniques. Nineteen per cent (19%) of the study area are assigned as ‘suitable' and ‘most suitable' by both methods, so these areas can be considered as safe or secure areas for clinical purposes. Moreover, almost all (99.8%) suitable areas are located in district 3, because of its higher population, less numbers of existing hospitals and large numbers of barren land plots of acceptable size.     

Seismic fragility assessment of low-rise stone masonry buildings

Many historic buildings in old urban centers in Eastern Canada are made of stone masonry reputed to be highly vulnerable to seismic loads.Seismic risk assessment of stone masonry buildings is therefore the first step in the risk mitigation process to provide adequate planning for retrofit and preservation of historical urban centers.This paper focuses on development of analytical displacement-based fragility curves reflecting the characteristics of existing stone masonry buildings in Eastern Canada.The old historic center of Quebec City has been selected as a typical study area.The standard fragility analysis combines the inelastic spectral displacement,a structure-dependent earthquake intensity measure,and the building damage state correlated to the induced building displacement.The proposed procedure consists of a three-step development process:(1) mechanics-based capacity model,(2) displacement-based damage model and(3) seismic demand model.The damage estimation for a uniform hazard scenario of 2% in 50 years probability of exceedance indicates that slight to moderate damage is the most probable damage experienced by these stone masonry buildings.Comparison is also made with fragility curves implicit in the seismic risk assessment tools Hazus and ELER.Hazus shows the highest probability of the occurrence of no to slight damage,whereas the highest probability of extensive and complete damage is predicted with ELER.This comparison shows the importance of the development of fragility curves specific to the generic construction characteristics in the study area and emphasizes the need for critical use of regional risk assessment tools and generated results.     

Wave climate simulation for southern region of the South China Sea

This study investigates long-term variability and wave characteristic trends in the southern region of the South China Sea (SCS). We implemented the state-of-the art WAVEWATCH III spectral wave model to simulate a 31-year wave hindcast. The simulation results were used to assess the inter-annual variability and long-term changes in the SCS wave climate for the period 1979 to 2009. The model was forced with Climate Forecast System Reanalysis winds and validated against altimeter data and limited available measurements from an Acoustic Wave and Current recorder located offshore of Terengganu, Malaysia. The mean annual significant wave height and peak wave period indicate the occurrence of higher wave heights and wave periods in the central SCS and lower in the Sunda shelf region. Consistent with wind patterns, the wave direction also shows southeasterly (northwesterly) waves during the summer (winter) monsoon. This detailed hindcast demonstrates strong inter-annual variability of wave heights, especially during the winter months in the SCS. Significant wave height correlated negatively with Niño3.4 index during winter, spring and autumn seasons but became positive in the summer monsoon. Such correlations correspond well with surface wind anomalies over the SCS during El Nino events. During El Niño Modoki, the summer time positive correlation extends northeastwards to cover the entire domain. Although significant positive trends were found at 95 % confidence levels during May, July and September, there is significant negative trend in December covering the Sunda shelf region. However, the trend appears to be largely influenced by large El Niño signals.     

Screening Indian Mustard Genotypes for Phytoremediating Arsenic‐Contaminated Soils

Ten Indian mustard (Brassica juncea L.) genotypes were screened for their phytoremediation potential for arsenic (As) contaminated water under laboratory‐controlled conditions. The genotypes were grown in a hydroponic chamber for 20 days in 250‐mL beakers containing As‐contaminated water. During plant development, changes in plant growth, biomass, and total As were evaluated. Of the 10 genotypes (Pusa Agrani, BTO, Pusa Kranti, Pusa Bahar, Pusa Bold, Pusa Basant, Pusa Jai Kisan, Arka Vardhan, Varuna, and Vaibhav) Pusa Jai Kisan was the most effective in phytoremediating As‐contaminated water under hydroponic conditions. This will provide new information for Indian mustard genotypes for phytoremediating As‐contaminated soils.     

Current Status of Textile Industry Wastewater Management and Research Progress in Malaysia: A Review

Textile industry is one of the fastest growing industries and significantly contributes to the economic growth in Malaysia. However, this industry also has high water consumption and subsequently produces high discharge rate of wastewater with high load of contaminants. The release of dyes into the environment during textile fiber dyeing and finishing processes is a main source of water pollution. Individual wastewater treatment through physical, biological, or chemical method is often very costly and results in large amount of sludge. Thus, there is a need to look for alternative treatment processes that covers from pre to post wastewater treatment stage. This paper reviews the current scenario with respect to textile industry effluent in Malaysia and technologies available for the treatment of the effluent. Prospects, challenges, and recommendations for future direction as well as on‐going research works dedicated to the treatment of textile wastewater are also reviewed in detail.     

Dark energy from “extended modified gravity” and Gauss–Bonnet invariant term

We investigate the cosmological dynamics of a four-dimensional Friedmann–Robertson–Walker homogenous and isotropic universe from Gauss–Bonnet higher-order curvature corrections, together with nonminimal coupling and with an infrared effective action of gravity based on a second-order gauge formulation for the Lorentz group. We study the evolution of the universe in such a model, identifying its key properties. Many new interesting features are revealed and discussed in some detail.     

Accelerated expansion of the Universe in the presence of a static traversable wormhole,extra-dimensions and variable modified Chaplygin gas

A modified higher-dimensional cosmology with a static traversable wormhole and dominated by a variable modified Chaplygin gas is constructed. Many interesting features are explored and discussed in some detail.     

Modified Brans-Dicke scalar tensor theories with generalized stringy Gauss-Bonnet corrections

We explore the late-time dynamics of a four-dimensional homogeneous and isotropic universe based on a modified Brans-Dicke scalar tensor theory in the presence of string corrections and Gauss-Bonnet curvature corrections. Many original and attractive cosmological features are revealed and discussed in some details.