Regional flood frequency analysis using Bayesian generalized least squares: a comparison between quantile and parameter regression techniques

Regression‐based regional flood frequency analysis (RFFA) methods are widely adopted in hydrology. This paper compares two regression‐based RFFA methods using a Bayesian generalized least squares (GLS) modelling framework; the two are quantile regression technique (QRT) and parameter regression technique (PRT). In this study, the QRT focuses on the development of prediction equations for a flood quantile in the range of 2 to 100 years average recurrence intervals (ARI), while the PRT develops prediction equations for the first three moments of the log Pearson Type 3 (LP3) distribution, which are the mean, standard deviation and skew of the logarithms of the annual maximum flows; these regional parameters are then used to fit the LP3 distribution to estimate the desired flood quantiles at a given site. It has been shown that using a method similar to stepwise regression and by employing a number of statistics such as the model error variance, average variance of prediction, Bayesian information criterion and Akaike information criterion, the best set of explanatory variables in the GLS regression can be identified. In this study, a range of statistics and diagnostic plots have been adopted to evaluate the regression models. The method has been applied to 53 catchments in Tasmania, Australia. It has been found that catchment area and design rainfall intensity are the most important explanatory variables in predicting flood quantiles using the QRT. For the PRT, a total of four explanatory variables were adopted for predicting the mean, standard deviation and skew. The developed regression models satisfy the underlying model assumptions quite well; of importance, no outlier sites are detected in the plots of the regression diagnostics of the adopted regression equations. Based on ‘one‐at‐a‐time cross validation’ and a number of evaluation statistics, it has been found that for Tasmania the QRT provides more accurate flood quantile estimates for the higher ARIs while the PRT provides relatively better estimates for the smaller ARIs. The RFFA techniques presented here can easily be adapted to other Australian states and countries to derive more accurate regional flood predictions. Copyright © 2011 John Wiley & Sons, Ltd.     

Contrasting Influence of Geology on E. coli and Arsenic in Aquifers of Bangladesh

Arsenic in groundwater has been a concern in South and Southeast Asia for more than a decade. We explore here the possibility that hydrogeologic factors recently shown to influence the distribution of arsenic might also affect the level of contamination of shallow (<20 m) wells with microbial pathogens. A total of 96 shallow tube wells in two nearby villages of Bangladesh were surveyed during the wet and dry seasons, along with 55 deeper wells in neighboring villages. One of the two villages is located in a particularly sandy environment where recharge is rapid and shallow wells contain little arsenic. Shallow aquifers in the other village are capped with an impermeable clay layer, recharge is an order of magnitude slower, and arsenic levels are high. The fecal indicator E. coli was detected in 43% of shallow wells, compared with 12% of deeper wells. More shallow wells contained E. coli during the wet season (61%) than during the dry season (9%). In the wet season, a higher proportion of shallow wells in the village with low arsenic levels (72%) contained E. coli compared with the village having high arsenic levels (43%). Differences in arsenic and E. coli distributions between the two sites are likely due to the differences in permeability of near‐surface sediments although differences in average well‐depth between the two villages (9 ± 4 vs. 15 ± 3 m) may play a role as well. Hydrogeologic conditions that favor high levels of fecal contamination but low levels of arsenic in shallow groundwater should be taken into account during arsenic mitigation throughout South and Southeast Asia.     

Design rainfall estimation in Australia: a case study using L moments and Generalized Least Squares Regression

Design rainfall is an important input to rainfall runoff models and is used for many other water resources planning and design applications. The estimation of design rainfall is generally done by applying a regional frequency analysis technique that uses data from a large number of rainfall stations in the region. This paper presents a regional rainfall frequency analysis technique that uses an L moments based index method coupled with Generalized Least Squares Regression (GLSR). The particular advantages of the GLSR method are that it accounts for the differences in record lengths across various sites in the region and inter-station correlation in deriving regional prediction equations. The proposed method has been applied to a data set consisting of 203 rainfall stations across Australia. It has been found that the proposed method can be applied successfully in deriving reasonably accurate design rainfall estimates from 1 to 72 h durations. It has also been found that the proposed method provides quite consistent estimates where a third order polynomial is adequate in smoothing the intensity–frequency–duration (IFD) curves. The method can readily be extended to a larger data set of Australia and other countries to derive generalized IFD data.     

A numerical study on the long term thermo-poroelastic effects of cold water injection into naturally fractured geothermal reservoirs

The residing fracture system and the prevailing in situ stresses have a significant impact on fluid flow and heat transfer in crystalline rocks. The long term response of fracture systems to changes in effective stresses, in particular the long term geo-mechanical effects of thermal stresses on reservoir characteristics is of particular interest to the geothermal industry.     

Sources of deep groundwater salinity in the southwestern zone of Bangladesh

Twenty groundwater samples were collected from two different areas in Satkhira Sadar Upazila to identify the source of salinity in deep groundwater aquifer. Most of the analyzed groundwater is of Na–Cl–HCO₃ type water. The trends of anion and cation are Cl⁻ > HCO₃ ⁻ > NO₃ ⁻ > SO₄ ²⁻ and Na⁺ > Ca²⁺ > Mg²⁺ > K⁺, respectively. Groundwater chemistry in the study area is mainly governed by rock dissolution and ion exchange. The dissolved minerals in groundwater mainly come from silicate weathering. The salinity of groundwater samples varies from ~1 to ~5%, and its source is possibly the paleo-brackish water which may be entrapped during past geologic periods.     

Arsenic removal from aqueous solutions by mixed magnetite–maghemite nanoparticles

In this study, magnetite–maghemite nanoparticles were used to treat arsenic-contaminated water. X-ray photoelectron spectroscopy (XPS) studies showed the presence of arsenic on the surface of magnetite–maghemite nanoparticles. Theoretical multiplet analysis of the magnetite–maghemite mixture (Fe₃O₄-γFe₂O₃) reported 30.8% of maghemite and 69.2% of magnetite. The results show that redox reaction occurred on magnetite–maghemite mixture surface when arsenic was introduced. The study showed that, apart from pH, the removal of arsenic from contaminated water also depends on contact time and initial concentration of arsenic. Equilibrium was achieved in 3 h in the case of 2 mg/L of As(V) and As(III) concentrations at pH 6.5. The results further suggest that arsenic adsorption involved the formation of weak arsenic-iron oxide complexes at the magnetite–maghemite surface. In groundwater, arsenic adsorption capacity of magnetite–maghemite nanoparticles at room temperature, calculated from the Langmuir isotherm, was 80 μmol/g and Gibbs free energy (∆G⁰, kJ/mol) for arsenic removal was −35 kJ/mol, indicating the spontaneous nature of adsorption on magnetite–maghemite nanoparticles.     

Life history pattern of mosquitofish Gambusia holbrooki (Girard, 1859) in the Tajan River (Southern Caspian Sea to Iran)

Investigation of the ecology of introduced species in new habitats can allow determinations of the degree, direction, and rate of evolutionary change. The introduction of Gambusia holbrooki in the southern Caspian Sea presents such a situation. We evaluated the life history traits of mosquitofish in the Tajan River basin. A total of 744 G. holbrooki specimens were collected between January and December 2008. The maximum observed ages are 0+ years for males and 1+ years for females. Both sexes grew allometrically (negative for males: b=2.442 and positive for females: b=3.232). The overall sex ratio is unbalanced and dominated by females. GSI values suggest that this population of G. holbrooki matures between February–July. The highest mean GSI value is 1.80 for males and 15.97 for females in May. Egg diameter ranges from 1.00 to 3.00 mm with a mean value of 2.098 mm. Absolute fecundity varied from 7 to 57 eggs. Both ova diameter and absolute fecundity were positively correlated to fish size (length and weight). Fecundity relative to total weight fluctuated from 34.44 to 582.64 eggs/g, and to total length from 2.33 to 12.95 eggs/cm. Both were negatively correlated with female size. The characteristics of this population are important with respect to life history of the species.     

Potential ecological risk assessment of heavy metal contamination in sediment and water body around Dhaka export processing zone,Bangladesh

Sediments and surface water contamination by the industrial effluents containing heavy metals is the most detrimental environmental impact. Therefore, the present work attempts to determine the status of eight heavy metal distribution in sediments and water samples, and their ecological risks’ assessment in the studied area. The distribution pattern of heavy metals in the water and sediment follows the sequences: Zn > Cu > Pb > Cr > Mn > Ni > As > Cd and Mn > Zn > Cr > Pb > Cu > Ni > As > Cd, respectively. Gross water pollution is observed at different sampling points of Dhalai Beel and Bangshi River. The comparison of sedimentary mean metal concentrations with several environmental contamination monitoring parameters, viz, threshold effect level (TEL), probable effect level (PEL), and severe effect lever (SEL) indicates that the metal levels are less than PEL except Cr. Moreover, the level of contamination degree (C _d) and modified degree of contamination (mC _d) indicates ‘low’ and ‘nil to low’ degree of contamination, respectively. Pollution load indices (PLI) of the studied area are lower than unity, indicates no pollution. Furthermore, a toxic-response factor is applied to assess the potential ecological risk of these heavy metals into the water body. The results of this study exhibit a low potential ecological risk of heavy metals. The Pearson’s correlation and cluster analysis are also performed to assess the heavy metal interactions in water and sediment samples.     

Back reaction and quantum gravity corrections of Hawking radiation from Schwarzschild-de Sitter black hole

Following the Parikh and Wilczek semiclassical tunneling method of massless particle, hawking radiation of Schwarzschild-de Sitter (SdS) black hole have been computed using null geodesic method. Purely thermal and quantum gravity corrections have been made and have shown that both the corrections give the same results and all the tunneling rates are related to change of Bekenstein-Hawking entropy of SdS black hole. The results obtained for SdS black hole are also in accordance with Parikh and Wilczek’s opinion and gives a correction to the Hawking radiation of SdS black hole.     

Validation of TRMM Precipitation Radar satellite data over Indonesian region

Research has been conducted to validate monthly and seasonal rain rates derived from the Tropical Rainfall Measuring Mission Precipitation Radar (PR) using rain gauge data analysis from 2004 to 2008. The study area employed 20 gauges across Indonesia to monitor three Indonesian regional rainfall types. The relationship of PR and rain gauge data statistical analysis included the linear correlation coefficient, the mean bias error (MBE), and the root mean square error (RMSE). Data validation was conducted with point-by-point analysis and spatial average analysis. The general results of point-by-point analysis indicated satellite data values of medium correlation, while values of MBE and RMSE tended to indicate underestimations with high square errors. The spatial average analysis indicated the PR data values are lower than gauge values of monsoonal and semi-monsoonal type rainfall, while anti-monsoonal type rainfall was overestimated. The validation analysis showed very good correlation with the gauge data of monsoonal type rainfall, high correlation for anti-monsoonal type rainfall, but medium correlation for semi-monsoonal type rainfall. In general, the statistical error level of monthly seasonal monsoonal type conditions is more stable compared to other rainfall types. Unstable correlations were observed in months of high rainfall for semi-monsoonal and anti-monsoonal type rainfall.