Climate, river network, and vegetation cover relationships across a climate gradient and their potential for predicting effects of decadal-scale climate change

• We determined relationships between drainage density (Dd) and runoff (R).
• We determined relationships between vegetation cover (V) and precipitation (P).
• We show that Dd(R) follows a saturation–growth model.
• We shows that V(P) exhibits a linear relationship.
• We apply the determined relationships to data from climate prediction models.

SummaryWe determined present-day (1981–2000) relationships between river network drainage density (Dd) and runoff (R), and between vegetation cover (V) and precipitation (P) across a contiguous 470,800 km2 area (the Texas Gulf Coast basin), where P varies from 438 to 1280 mm/yr. Dd(R) follows a saturation–growth model which is similar to process-based equilibrium landscape models. V(P) follows a linear relationship. The models for Dd(R) and V(P) were used to assess how Dd and V might respond to decadal-scale climate changes in R and P anomalies predicted by a regional climate model between 2041–2060 and 1981–2000. The regional climate model, CRCM, was forced following the SRES A2 emissions scenario. Our calculations indicate a tendency of 57,500 km of active river channels to drying up, representing 9.9% of the present-day total of 581,985 km, due to future decrease in R. This will be accompanied by a loss of 8150 km2 in V due to decrease in P. This study extends empirical studies of relationships between climate and landscape properties and explicitly links observations with process-based models. The results provide a simple framework for modeling potential trajectories of the landscape due to climate change.