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A watershed‐scale assessment of a process soil CO 2 production and efflux model
Author(s) -
RiverosIregui Diego A.,
McGlynn Brian L.,
Marshall Lucy A.,
Welsch Daniel L.,
Emanuel Ryan E.,
Epstein Howard E.
Publication year - 2011
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 - 10.1029/2010wr009941
Subject(s) - environmental science , watershed , riparian zone , biogeochemical cycle , hydrology (agriculture) , soil science , soil water , ecology , geology , habitat , biology , geotechnical engineering , machine learning , computer science
Growing season soil CO 2 efflux is known to vary laterally by as much as seven fold within small subalpine watersheds (<5 km 2 ), and such degree of variability has been strongly related to the landscape‐imposed redistribution of soil water. Current empirical or process models offer low potential to simulate this variability or to simulate watershed‐scale dynamics of soil CO 2 efflux. We modified an existing process soil CO 2 production and efflux model to include spatially variable soil moisture, and applied it to a well‐studied and moderately complex watershed of the northern Rocky Mountains. We started at the point scale and progressively modeled processes up to the watershed scale. We corroborated model performance using an independent data set of soil CO 2 efflux measurements from 53 sites distributed across the 393 ha watershed. Our approach (1) simulated the seasonality of soil CO 2 efflux at riparian sites; (2) reproduced short‐term (diel) dynamics of soil CO 2 concentration ([CO 2 ]) at riparian sites, particularly observed hysteresis patterns in the soil [CO 2 ]–soil temperature relationship; and (3) simulated growing season estimates of soil CO 2 efflux at dry sites across the landscape (98% of area). Model limitations included poor simulation of growing season (cumulative) soil CO 2 efflux at sites with a large drainage area, likely as a result of poorly modeled soil water content and challenges in parametrization of root and microbial activities. Our study provides important insight into coupling hydrological and biogeochemical models at landscape scales, and highlights the role of landscape structure and heterogeneity when modeling spatial variability of biogeochemical processes.