# Multifractal analysis of vegetation regulation on ecohydrological processes in a small watershed

## TL;DR

This study explores how vegetation influences water flow in a small watershed using advanced data analysis techniques, revealing seasonal effects and offering insights for ecological management.

## Contribution

The paper introduces a novel integration of remote sensing and multifractal analysis to quantify vegetation's regulation of watershed hydrology.

## Key findings

- Vegetation significantly moderates water retention in the Quxi River watershed, especially during summer.
- Multifractal analysis revealed distinct seasonal correlations between vegetation cover and hydrological responses.
- High-frequency precipitation and runoff cycles showed significant variance, with vegetation dynamics differing between spring and summer despite similar rainfall levels.

## Abstract

Runoff from small catchments facilitate water movement and a hydrologic balance across an area. In the watershed hydrological cycle, precipitation serves as the primary source of runoff, while runoff represents a delayed response to precipitation. Vegetation plays a crucial regulatory role in the relationship between precipitation and runoff through multiple ecohydrological mechanisms, including interception, infiltration regulation, and evapotranspiration. In different small watersheds, the dominant coupling mechanisms between precipitation and runoff exhibit clear temporal-scale dependence due to the variability of meteorological conditions and vegetation dynamics. Moreover, these interactions are strongly influenced by topographic features, vegetation cover, and soil composition, resulting in considerable uncertainty in the interrelationships among precipitation, runoff, and vegetation.

We investigated the nonlinear relationship between precipitation and runoff at various time scales, drawing on long-term observational data (2017–2022) from the Quxi River catchment in China. We used the ensemble empirical mode decomposition (EEMD) and multifractal detrended cross-correlation analysis (MF-DCCA) to explore scale-dependent dynamics. The multifractal parameter was applied to reveal how water retention in the Quxi River small watershed varies across scales. To explore seasonal vegetation effects, we further conducted sliding window and Pearson correlation analyses.

EEMD, detrended fluctuation analysis (DFA), and MF-DCCA analyses were applied to runoff, precipitation, and vegetation cover data in the Quxi River watershed, China. EEMD revealed that high-frequency modes of precipitation and runoff, with a ∼2-week cycle, explained significant data variance. DFA showed precipitation as a random process, while runoff exhibited long-term persistence. MF-DCCA confirmed multifractal characteristics in precipitation-runoff coupling, with the multifractal parameter quantifying hydrological responses. Correlation coefficients between the multifractal parameter and fractional vegetation cover (FVC) were −0.07 (spring), 0.54 (summer), 0.34 (autumn), and 0.42 (winter), indicating vegetation’s moderating effect, especially in summer. Although both spring and summer have substantial precipitation exceeding 1,100 mm, the effects of vegetation dynamics on the watershed’s water retention capacity differ significantly between the two seasons. This is attributed to the vegetation type characteristics of the small watershed. This novel approach, integrating remote sensing and multifractal analysis, quantified vegetation’s regulation of watershed hydrology, offering a robust method to assess water retention capacity. It supports ecological restoration, forest management, and sustainable development in small watersheds, adaptable to regions with large hydraulic projects, enhancing ecosystem stability and biodiversity.