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Variability in the Shape of the Active Length–Streamflow Relationship in Temporary Streams: Insights From an Empirical Analysis
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Variability in the Shape of the Active Length–Streamflow Relationship in Temporary Streams: Insights From an Empirical Analysis
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Journal Article
Variability in the Shape of the Active Length–Streamflow Relationship in Temporary Streams: Insights From an Empirical Analysis
2025
Overview
Non‐perennial stream reaches experience ceaseless shifts between flowing water and dry‐down, depending on the changes of the water availability in the upstream catchment. Consequently, the flowing network length L$L$and the catchment‐scale streamflow Q$Q$jointly evolve mirroring the temporal variations of landscape wetness. The resulting relation between L$L$and Q$Q$represents a powerful tool for monitoring, modeling and classifying non‐perennial rivers. However, a robust formal assessment of the L(Q)$L(Q)$shape across different catchments is still lacking. In this manuscript we analyze 45 case studies with joint empirical observations of L$L$and Q$Q$ , and test three models: the power law, the exponential, and the gamma functions. The empirical data confirms the presence of a high correlation between L$L$and Q$Q$in all case studies. However higher levels of noise emerge in higher frequency data sets. Furthermore, our analysis reveals three classes of L(Q)$L(Q)$shapes: generally increasing relations, relations with a right plateau, and s‐shaped relations. The results indicate that the gamma model produces the lowest errors and is able to describe all three shapes. In contrast, the power law model—while showing good performances—tends to overestimate the right plateaus. The exponential model, instead, proves to be too simple and often reaches the maximum network length for too low discharge values. The study provides a basis for better interpreting and modeling the joint variability of L$L$and Q$Q$ , providing clues about the sensitivity of the flowing length to streamflow changes in different geomorphic and climatic settings. Key Points The empirical relationship between flowing network length L$L$and discharge at the outlet Q$Q$is analyzed for 45 case studies Three qualitative classes of L(Q)$L(Q)$emerge: generally increasing relations, relations with a right plateau, and s‐shaped relations The gamma model shows the best performance in all case studies, while the power law tends to overestimate the right plateaus
