Predicting suitability of different scale-dependent dispersivities for reactive solute transport through stratified porous media

In this paper,the behavior of breakthrough curves(BTCs) for reactive solute transport through stratified porous media is investigated.A physical laboratory model for layered porous media was constructed,in which thin layer of gravel was sandwiched in between two thick layers of natural soil.Gravel layer and natural soil layers were hydraulically connected as single porous continuum.A constant source of tracer was connected through gravel layer and elucidated at different sampling points in the direction of flow.Flexible multiprocess non-equilibrium(MPNE) transport equation with scale-dependent dispersivity function was used to simulate experimental BTCs of reactive solute transport through layered porous media.The values of equilibrium sorption coefficient and other input parameters were obtained experimentally.The simulation of BTC was performed using MPNE model with scale-dependent dispersivity.The simulation of different scale-dependent dispersivities was then compared and it was found that for field scale of estimation of dispersivity,asymptotic and exponential dispersivity functions performed better.In continuation to the comparison of simulated BTCs obtained using different models,spatial moment analysis of each aforesaid scale-dependent dispersivity model was also done.Spatial moment analysis provides the information related to mean solute mass,rate of mass travel,and mean plume dispersion.Linear and constant dispersivities showed higher variance as compared to asymptotic and exponential dispersion functions.This supports the field applicability of asymptotic and exponential dispersivity functions.The BTCs were also found to elucidate a nonzero concentration with time,which was clearly affected by physical non-equilibrium.In natural condition,such information is required in effective aquifer remediation process.

黑河流域地理观测分析——复杂性科学视角（英文）

Since 2005,dozens of geographical observational stations have been established in the Heihe River Basin(HRB),and by now a large amount of meteorological,hydrological,and ecological observations as well as data pertaining to water resources,soil and vegetation have been collected.To adequately analyze these available data and data to be further collected in future,we present a perspective from complexity theory.The concrete materials covered include a presentation of adaptive multiscale filter,which can readily determine arbitrary trends,maximally reduce noise,and reliably perform fractal and multifractal analysis,and a presentation of scale-dependent Lyapunov exponent(SDLE),which can reliably distinguish deterministic chaos from random processes,determine the error doubling time for prediction,and obtain the defining parameters of the process examined.The adaptive filter is illustrated by applying it to obtain the global warming trend and the Atlantic multidecadal oscillation from sea surface temperature data,and by applying it to some variables collected at the HRB to determine diurnal cycle and fractal properties.The SDLE is illustrated to determine intermittent chaos from river flow data.

Drivers of microbial beta-diversity in wastewater treatment plants in China

As one of the most well-documented biogeographic patterns,the distance-decay relation-ship provides insights into the underlying mechanisms driving biodiversity distribution.Al-though wastewater treatment plants(WWTPs)are well-controlled engineered ecosystems,this pattern has been seen among microbial communities in activated sludge(AS).However,little is known about the relative importance of environmental heterogeneity and dispersal limitation in shaping AS microbial community across China;especially they are related to spatial scale and organism types.Here,we assessed the distance-decay relationship based on different spatial scales and microbial phylogenetic groups by analyzing 132 activated sludge(AS)samples across China comprising 3,379,20016S rRNA sequences.Our results in-dicated that the drivers of distance-decay pattern in China were scale-dependent.Microbial biogeographic patterns in WWTPs were mainly driven by dispersal limitation at both local and national scales.In contrast,conductivity,SRT,and pH played dominant roles in shaping AS microbial community compositions at the regional scale.Turnover rates and the drivers of beta-diversity also varied with microorganism populations.Moreover,a quantitative re-lationship between dispersal limitation ratio and AS microbial turnover rate was generated.Collectively,these results highlighted the importance of considering multiple spatial scales and micro-organism types for understanding microbial biogeography in WWTPs and pro-vided new insights into predicting variations in AS community structure in response to environmental disturbance.