A high-resolution carbon balance in a temperate catchment: insights from the Schwabach River, Germany

TL;DR

This study provides a detailed high-resolution analysis of carbon dynamics in the Schwabach River, revealing the dominant sources and fluxes of DIC, DOC, and POC, and emphasizing the importance of sampling frequency for accurate carbon budget estimates.

Contribution

It offers a novel high-resolution dataset on riverine carbon fluxes and highlights the significance of sampling frequency in accurately estimating carbon budgets in small streams.

Findings

DIC is the dominant carbon source, mainly from mineral weathering.

High discharge periods increase DOC inputs from overland runoff.

Bi-monthly sampling captures most fluxes but may miss rapid variations.

Abstract

This study examines stable carbon isotope (d13C) and concentration dynamics of DIC, DOC, and POC over an entire year, using a high resolution dataset. This research was performed in the catchment of the Schwabach River, a small, karstic headwater stream in Germany. The DIC data indicated the dominance of mineral weathering as a DIC source, with a dilution effect during high flow periods. A weakly negative relationship between discharge and d13CDIC indicates an increase in plant-derived organic matter during floods, transported to river waters via overland runoff and intermediate flow. DOC inputs were enhanced during periods of high discharge, indicating a greater importance of overland runoff as a DOC source. POC concentrations seem unaffected by discharge, but a slight negative correlation between d13CPOC and discharge may be derived from increased C4 plant material inputs. CO2 concentrations exceeded ambient atmospheric values throughout the year, confirming that the river surface waters are a net CO2 source. The total riverine carbon flux was dominated by DIC (70%), followed by CO2 efflux (21%), DOC (7%), and POC (2%). While a bi-monthly sampling scheme yielded a similar carbon flux estimate to that utilizing the entire dataset, the use of a monthly sampling interval differed by up to 19%. This discrepancy is due to the inability of a monthly sampling scheme to capture sudden and large variations in river discharge and associated dissolved/particulate carbon concentration changes, such as those observed during flooding. Bi-monthly sampling may be the minimum timeframe required for an acceptable degree of accuracy in carbon flux calculations. The application of high sampling frequencies and comprehensive DIC, DOC, and POC studies in future research would reduce uncertainties in riverine carbon budgets, and clarify the role of small streams in the global carbon cycle.