Water Resources Research
Supporting Information for
Dry-season length and runoff control annual variability in stream DOC dynamics in a small, shallow-groundwater-dominated agricultural watershed
G. Humbert
*1,2,3
, A. Jaffrezic
1,2,3
, O. Fovet
1,2
, G. Gruau
4
, P. Durand
1,2
1
INRA, UMR1069 Sol Agro et hydrosystème Spatialisation, F-35000 Rennes, France
2 AGROCAMPUS OUEST, UMR1069, F-35000 Rennes, France
3
Université européenne de Bretagne, France
4
OSUR, UMR 6118 Géosciences Rennes, Campus de Beaulieu, F-35042 Rennes Cedex,
France
* g.humbert86@gmail.com
, INRA, UMR1069 SAS, 65 rue de Saint-Brieuc 35042
Rennes Cedex, France
Contents of this file
Figures S1 to S4
Introduction
These figures present the method of variable selection used in the study and the results of partial least square regressions and forward stepwise regression (FSR) for annual dissolved organic carbon (DOC) fluxes (stormflow + base flow, stormflow, and base flow) and from FSR for base flow mean DOC concentrations. Results were obtained according to the methods described in the associated article.
1

Figure S1.
The variable-selection procedure followed, including the backward variable selection in partial least square regression (PLSR ; left). Text below gray boxes describes the selection criterion used. RMSEP: root mean squared error of prediction; VIP: variable importance in projection; SLR: simple linear regression; MLR: multiple linear regression.
2

Figure S2. PLS weight plot for the most important variables (variable importance in projection (VIP) > 1) selected through backward variable selection in partial least square regression (BVSPLS) for two-component models that explain (a) annual dissolved organic carbon (DOC) exports: R²Y = 0.99 and Q²Y = 0.98, 14 of 17 variables remained important; (b) annual DOC exports in storm events: R²Y = 0.99 and Q²Y = 0.98, 20 of 36 variables remained important; (c) annual DOC exports in base flow: R²Y = 0.96 and Q²Y
= 0.92, 3 of 3 variables remained important. Variables to explain and explanatory variables are showed with grey bars and white bars, respectively. D: drought; A: rewetting; B: high flow; C: recession; DOC: dissolved organic carbon; GW: groundwater table.
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Figure S3. (a) Simple linear regression between annual dissolved organic carbon (DOC) exports and annual runoff. (b) Simple linear regression between annual dissolved organic carbon (DOC) exports during a storm event and annual runoff during a storm event. (c)
Simple linear regression between annual dissolved organic carbon (DOC) exports in base flow and annual runoff in base flow. Thin lines represent the 95% confidence interval for the regression.
4

Figure S4.
Annual means of base flow DOC concentrations modelled by multiple linear regression (MLR). Dashed segments represent ± 1 standard deviation for measured concentrations and 95% confidence intervals for predicted concentrations. The unfilled circle represents values obtained in water year 2005-2006, which were not included in simple linear regressions and MLR due to a lack of season A that year.
Details of the forward stepwise regression are shown at the top of the graph. GW: groundwater table.
5