Preprints
https://doi.org/10.5194/hess-2024-118
https://doi.org/10.5194/hess-2024-118
21 May 2024
 | 21 May 2024
Status: this preprint is currently under review for the journal HESS.

Exploring the Potential Processes Controls for Changes of Precipitation-Runoff Relationships in Non-stationary Environments

Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu

Abstract. The influence of climate change and anthropogenic activities on precipitation-runoff relationships (PRR) has been widely discussed. Traditional models assuming stationary conditions can lead to inaccurate streamflow predictions. To address this issue, we propose a Driving index for changes in Precipitation-Runoff Relationships (DPRR), identified as key PRR influencers, involving climate forcing, groundwater, vegetation dynamics, and anthropogenic influences. According to the quantitative results of inputting the candidate driving factors to a holistic conceptual model, the possible process explanations for changes in the PRR were deduced. This framework is validated across five sub-basins in the Wei River Basin. Moreover, non-stationary hydrological processes were initially detected, and the nonlinear correlations among the factors were assessed. The results show that baseflow emerges as the primary factor positively influencing PRR (enhancing PRR), but with high uncertainty. Potential evapotranspiration plays a dominant role in driving negative PRR changes in the sub-basin which are characterized by a semi-arid climate and minor human interference. Vegetation dynamics negatively influence PRR, with driving levels correlating with the scale of soil and water conservation engineering, displaying lower uncertainty. Anthropogenic influences, represented by Impervious Surface Ratio (ISR), Night-Time Light (NTL), and population density (POP), exhibit varying driving levels, with ISR having the strongest and direct impact, closely linked to urbanization processes and scale. The temporal dynamics of driving factors computed by dynamic DPRR generally correspond with hydrological regime shifts in non-stationary environments. The study's findings offer a comprehensive understanding of hydrological processes, enabling informed decision-making for the development of sustainable hydrological models.

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Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu

Status: open (until 18 Jul 2024)

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Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu
Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu

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Short summary
This study develops an integrated framework based on the novel Driving index for changes in Precipitation-Runoff Relationships (DPRR) to explore the controls for changes in precipitation-runoff relationships in non-stationary environments. According to the quantitative results of the candidate driving factors, the possible process explanations for changes in the precipitation-runoff relationships are deduced. The main contribution offers a comprehensive understanding of hydrological processes.