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A Comparison of Six Transport Models of the MADE‐1 Experiment Implemented With Different Types of Hydraulic Data
Author(s) -
Zech Alraune,
Attinger Sabine,
Bellin Alberto,
Cvetkovic Vladimir,
Dagan Gedeon,
Dentz Marco,
Dietrich Peter,
Fiori Aldo,
Teutsch Georg
Publication year - 2021
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2020wr028672
Subject(s) - plume , hydraulic conductivity , advection , tracer , soil science , aquifer , sampling (signal processing) , geology , mechanics , environmental science , geotechnical engineering , meteorology , engineering , physics , groundwater , electrical engineering , filter (signal processing) , nuclear physics , soil water , thermodynamics
Six conceptually different transport models were applied to the macrodispersion experiment (MADE)‐1 field tracer experiment as a first major attempt for model comparison. The objective was to show that complex mass distributions in heterogeneous aquifers can be predicted without calibration of transport parameters, solely making use of structural and flow data. The models differ in their conceptualization of the heterogeneous aquifer structure, computational complexity, and use of conductivity data obtained from various observation methods (direct push injection logging, DPIL, grain size analysis, pumping tests and flowmeter). They share the same underlying physical transport process of advection by the velocity field solely. Predictive capability is assessed by comparing results to observed longitudinal mass distributions of the MADE‐1 experiment. The decreasing mass recovery of the observed plume is attributed to sampling and no physical process like mass transfer is invoked by the models. Measures like peak location and strength are used in comparing the modeled and measured plume mass distribution. Comparison of models reveals that the predictions of the solute plume agree reasonably well with observations, if the models are underlain by a few parameters of close values: mean velocity, a parameter reflecting log‐conductivity variability, and a horizontal length scale related to conductivity spatial correlation. The robustness of the results implies that conservative transport models with appropriate conductivity upscaling strategies of various observation data provide reasonable predictions of plumes longitudinal mass distribution, as long as key features are taken into account.