Table 2 Data sets evaluated for use as predictor variables in the logistic regression analysis.

Correlations were found using the percentage of measurements exceeding 10 μg/liter in 11 bins of equal member-size across the range of each variable (see Materials and Methods). P values of logistic regression are based on univariate analyses. An asterisk indicates data sets that were not significant and therefore removed from the full logistic regression analysis. n/a, not applicable.

Data setResolutionCorrelation
(P)
Logistic
regression (P)
Potential evapotranspiration
(PET) (72, 73)
30″0.730 (<0.05)<0.05
Precipitation (74)30″−0.776 (<0.05)<0.05
Aridity [precipitation (74)/
PET (72, 73)]
30″−0.779 (<0.05)<0.05
Irrigated area % (75)5’0.967 (<0.05)<0.05
Slope (binary, 0.1°) (76)30″n/a<0.05
Fluvisol probability (%)
(70, 77, 78)
30″0.704 (<0.05)<0.05
Soil organic carbon
(70, 77, 78)
30″−0.778 (<0.05)<0.05
Soil pH (70, 77, 78)30″0.977 (<0.05)<0.05
Soil clay % (70)*30″−0.338 (>0.05)>0.05
Soil silt % (70)*30″−7.22 × 10−2 (>0.05)>0.05
Holocene fluvial sediments
(binary) (69)
Polygonn/a<0.05

*Data sets that were not significant and therefore removed from the full logistic regression analysis.