Impact of climate change on 24‐h design rainfall depth estimation in Qiantang River Basin,East China

The frequency and magnitude of extreme meteorological or hydrological events such as floods and droughts in China have been influenced by global climate change. The water problem due to increasing frequency and magnitude of extreme events in the humid areas has gained great attention in recent years. However, the main challenge in the evaluation of climate change impact on extreme events is that large uncertainty could exist. Therefore, this paper first aims to model possible impacts of climate change on regional extreme precipitation (indicated by 24‐h design rainfall depth) at seven rainfall gauge stations in the Qiantang River Basin, East China. The Long Ashton Research Station‐Weather Generator is adopted to downscale the global projections obtained from general circulation models (GCMs) to regional climate data at site scale. The weather generator is also checked for its performance through three approaches, namely Kolmogorov–Smirnov test, comparison of L‐moment statistics and 24‐h design rainfall depths. Future 24‐h design rainfall depths at seven stations are estimated using Pearson Type III distribution and L‐moment approach. Second, uncertainty caused by three GCMs under various greenhouse gas emission scenarios for the future periods 2020s (2011–2030), 2055s (2046–2065) and 2090s (2080–2099) is investigated. The final results show that 24‐h design rainfall depth increases in most stations under the three GCMs and emission scenarios. However, there are large uncertainties involved in the estimations of 24‐h design rainfall depths at seven stations because of GCM, emission scenario and other uncertainty sources. At Hangzhou Station, a relative change of ?16% to 113% can be observed in 100y design rainfall depths. Copyright © 2012 John Wiley & Sons, Ltd.     

Computational microstructure modeling to estimate progressive moisture damage behavior of asphaltic paving mixtures

This paper presents a computational microstructure model to estimate the progressive moisture damage of multiphase asphaltic paving mixtures. Moisture damage because of water transport is incorporated with mechanical loading through a finite element method. To simulate nonlinear damage evolution in the mixtures, the model includes Fickian moisture diffusion, a cohesive zone model to simulate the gradual fracture process, and a degradation characteristic function to represent the reduction of material properties because of moisture infiltration. With the model developed, various parametric analyses are conducted to investigate how each model parameter affects the material‐specific moisture damage mechanism and damage resistance potential of the mixtures. Analysis results clearly demonstrate the significance of physical and mechanical properties of mixture components and geometric characteristics of microstructure for the better design of asphaltic paving mixtures and roadway structures. Copyright © 2012 John Wiley & Sons, Ltd.     

The role of anthropogenic activities in karst spring discharge volatility

The traditional hydrological time series methods tend to focus on the mean of whichever variable is analysed but neglect its time‐varying variance (i.e. assuming the variance remains constant). The variances of hydrological time series vary with time under anthropogenic influence. There is evidence that extensive well drilling and groundwater pumping can intercept groundwater run‐off and consequently induce spring discharge volatility or variance varying with time (i.e. heteroskedasticity). To investigate the time‐varying variance or heteroskedasticity of spring discharge, this paper presents a seasonal autoregressive integrated moving average with general autoregressive conditional heteroskedasticity (SARIMA‐GARCH) model, whose the SARIMA model is used to estimate the mean of hydrological time series, and the GARCH model estimates its time‐varying variance. The SARIMA‐GARCH model was then applied to the Xin'an Springs Basin, China, where extensive groundwater development has occurred since 1978 (e.g. the average annual groundwater pumping rates were less than 0.20 m³/s in the 1970s, reached 1.20 m³/s at the end of the 1980s, surpassed 2.0 m³/s in the 1990s and exceeded 3.0 m³/s by 2007). To identify whether human activities or natural stressors caused the heteroskedasticity of Xin'an Springs discharge, we segmented the spring discharge sequence into two periods: a predevelopment stage (i.e. 1956–1977) and a developed stage (i.e. 1978–2012), and set up the SARIMA‐GARCH model for the two stages, respectively. By comparing the models, we detected the role of human activities in spring discharge volatility. The results showed that human activities caused the heteroskedasticity of the Xin'an Spring discharge. The predicted Xin'an Springs discharge by the SARIMA‐GARCH model showed that the mean monthly spring discharge is predicted to continue to decline to 0.93 m³/s in 2013, 0.67 m³/s in 2014 and 0.73 m³/s in 2015. Copyright © 2014 John Wiley & Sons, Ltd.     

Delineation of spatial redox zones using discriminant analysis and geochemical modelling in arsenic‐affected alluvial aquifers

This study characterized the redox conditions in arsenic‐affected groundwater aquifers of the Lanyang plain, Taiwan. Discriminant analysis was adopted to delineate three redox zones (oxidative, transitional and reductive zones) in different aquifers and yielded 92·3% correctness on groundwater quality data. Arsenic is mainly distributed in the reductive zone, and arsenic distribution in the shallow aquifer is mainly affected by surface activities. According to PHREEQC modelling results, possible mechanisms for arsenic release to groundwater in Lanyang plain are explored. Arsenic released to groundwater in the oxidative zone (zone 1) is primarily caused by the oxidations of arsenic‐bearing pyrite minerals, and arsenate is the predominant species. While the reductive dissolution of Fe‐oxides are responsible for the high arsenic concentration found in the transitional and reductive zones (zones 2 and 3), arsenite is the predominant species. The reduction potential of groundwater rises as the depths and zones increase. Some sulphates may be reduced to form sulphide ions, which then react with arsenic to form arseno‐sulphide deposits (such as realgar, orpiment) and then slightly lower groundwater arsenic concentrations. A conceptual diagram which summarized the possible release processes of arsenic in different redox zones along groundwater flow in Lanyang plain is postulated. Arsenic‐bearing pyrite and arsenopyrite (FeAsS) are oxidized as they are exposed to the infiltrated oxygenated rainwater, releasing soluble arsenate Fe(II) and SO₄^2? into zone 1. The dissolution of arsenic‐rich Fe‐oxides due to the onset of reducing conditions in zones 2 and 3 is responsible for the mobility of arsenic and likely to be the primary mechanism of arsenic release to groundwater in the Lanyang plain Copyright © 2007 John Wiley & Sons, Ltd.     

Combined use of spot samples and continuous integrated sampling in a study of storm runoff from a lowland catchment in the south of England

We have used two different sampling techniques to study the geochemical response of a small lowland rural catchment to episodic storm runoff. The first method involves traditional daily spot sampling and has been used to develop a standard end‐member mixing analysis (EMMA) of the relative contributions of ground water flow and surface runoff to the total stream flow. The second method utilizes a continuous sampling device, powered by an osmotic pump, to produce an integrated 24‐h sample of the stream flow. When combined with the EMMA results from the spot samples, analyses of the integrated samples reveal the presence of a third component that makes a significant contribution to the dissolved NO₃, Ca and K export from the catchment during the rising limb of the hydrographic profile of a storm event following a prolonged dry period. The storm occurred in the middle of the night, so that the response of the stream chemistry was not captured by the daily samples. We hypothesize that this third component is derived from the flushing of stored soil water that contains the geochemical signature of decaying vegetation. Copyright © 2011 John Wiley & Sons, Ltd.