Understanding and Managing the Potential By-Products of PFAS Destruction     

John Horst  Jeffrey McDonough  Ian Ross  Erika Houtz 《Ground Water Monitoring & Remediation》2020,40(2):17-27

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The Ensemble Kalman Filter for Groundwater Plume Characterization: A Case Study          下载免费PDF全文

James L. Ross  Peter F. Andersen 《Ground water》2018,56(4):571-579

The Kalman filter is an efficient data assimilation tool to refine an estimate of a state variable using measured data and the variable's correlations in space and/or time. The ensemble Kalman filter (EnKF) (Evensen 2004, 2009) is a Kalman filter variant that employs Monte Carlo analysis to define the correlations that help to refine the updated state. While use of EnKF in hydrology is somewhat limited, it has been successfully applied in other fields of engineering (e.g., oil reservoir modeling, weather forecasting). Here, EnKF is used to refine a simulated groundwater tetrachloroethylene (TCE) plume that underlies the Tooele Army Depot‐North (TEAD‐N) in Utah, based on observations of TCE in the aquifer. The resulting EnKF‐based assimilated plume is simulated forward in time to predict future plume migration. The correlations that underpin EnKF updating implicitly contain information about how the plume developed over time under the influence of complex site hydrology and variable source history, as they are predicated on multiple realizations of a well‐calibrated numerical groundwater flow and transport model. The EnKF methodology is compared to an ordinary kriging‐based assimilation method with respect to the accurate representation of plume concentrations in order to determine the relative efficacy of EnKF for water quality data assimilation.  相似文献   

Runoff generation and sediment production on unpaved roads,footpaths and agricultural land surfaces in northern Thailand     

Alan D. Ziegler  Ross A. Sutherland  Thomas W. Giambelluca 《地球表面变化过程与地形》2000,25(5):519-534

Rainfall simulation was used to examine runoff generation and sediment transport on roads, paths and three types of agricultural fields in Pang Khum Experimental Watershed (PKEW), in mountainous northern Thailand. Because interception of subsurface flow by the road prism is rare in PKEW, work focused on Horton overland flow (HOF). Under dry antecedent soil moisture conditions, roads generated HOF in c. 1 min and have event runoff coefficients (ROCs) of 80 per cent, during 45 min, c. 105 mm h⁻¹ simulations. Runoff generation on agricultural fields required greater rainfall depths to initiate HOF; these surfaces had total ROCs ranging from 0 to 20 per cent. Footpaths are capable of generating erosion‐producing overland flow within agricultural surfaces where HOF generation is otherwise rare. Paths had saturated hydraulic conductivity (K_s) values 80–120 mm h⁻¹ lower than those of adjacent agricultural surfaces. Sediment production on roads exceeded that of footpaths and agricultural lands by more than eight times (1·23 versus < 0·15 g J⁻¹). Typically, high road runoff volumes (owing to low K_s, c. 15 mm h⁻¹) transported relatively high sediment loads. Initial road sediment concentrations exceeded 100 g l⁻¹, but decayed with time as loose surface material was removed. Compared with the loose surface layer, the compacted, underlying road surface was resistant to detachment forces. Sediment concentration values for the road simulations were slightly higher than data obtained from a 165 m road section during a comparable natural event. Initial simulation concentration values were substantially higher, but were nearly equivalent to those of the natural event after 20 min simulation time. Higher sediment concentration in the simulations was related to differences in the availability of loose surface material, which was more abundant during the dry‐season simulations than during the rainy season natural event. Sediment production on PKEW roads is sensitive to surface preparation processes affecting the supply of surface sediment, including vehicle detachment, maintenance activities, and mass wasting. The simulation data represent a foundation from which to begin parameterizing a physically based runoff/erosion model to study erosional impacts of roads in the study area. Copyright © 2000 John Wiley & Sons, Ltd.  相似文献