the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Identifying controlling climate factors conducive to water and nitrogen export from agricultural watershed during snowmelt runoff period by using the SWAT model
Abstract. Temperature and precipitation variations during the freezing-thawing period affect snowmelt and accompanying nitrogen export in a complex manner. These influences can be long-lasting, superimposed, and strengthened. Daily discharge and nitrate nitrogen NO3--N concentrations were monitored during the snowmelt periods of 2015 and 2016 in an agricultural watershed in northeastern China. The SWAT model was used to simulate the water and NO3--N export during the snowmelt period of 1951–2014 to identify the controlling climate factors and confirm their suitable combination that facilitates snowmelt water and NO3--N export. Our results show that the SWAT model performs well for Re values in simulating the daily snowmelt runoff and NO3--N export, but poorly for NSE and R2 values in simulating NO3--N export. This is attributed to the absence of snowmelt water refrozen and hysteresis modules. The number of days and precipitation of the stable freezing period and the stating day of snowmelt period are controlling factors of daily snowmelt runoff, while daily NO3--N export are mostly affected by precipitation during the snowmelt period. The combinations of climatic factors favored by snowmelt runoff and NO3--N export were different. Years with longer stable freezing periods, later snowmelt period starting days, and higher rainfall during snowmelt, more readily generated high snowmelt runoff. Correspondingly, later appeared, higher and concentrated rainfall events, and higher temperatures between these rainfall and snowmelt events favored the NO3--N export. Finally, this study is of great importance for the prevention of spring floods and water pollution during snowmelt periods.
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Status: open (until 29 Mar 2025)
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RC1: 'Comment on egusphere-2024-3984', Anonymous Referee #1, 20 Feb 2025
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The manuscript ‘Identifying controlling climate factors conducive to water and nitrogen export from agricultural watershed during snowmelt runoff period by using the SWAT model’ proposes to elucidate the drivers behind the hydrology and nutrient export during the winter in cold regions using a modelling approach. Although the topic is meritorious, the methodological approach used in the analysis is not robust. Specifically, the study only used two winter seasons to collect observations, each used to calibrate and validate the model (i.e., one year each). This approach is not robust enough and conflicts with sound modelling practices which use several years of data for calibration and validation, respectively. This standard practice ensures several weather patterns (e.g, wet, dry, and average years) are represented during the model fine tuning and validation. Using a single year of data will likely bias the model parameterization and may influence the results. The poor model performance reported in the abstract could be a result of the short records used to calibrate and validate the model. Moreover, the study area is very small (i.e., < 7km2), which results in Maize being the dominant land use (>80% of the study area). These conditions are very specific and reduce the relevance of the findings to other jurisdictions. That is, the hydrological and nutrient export response is largely influenced by the dominant land cover, physiography (e.g. ,soil type) and weather prevailing during the study. To achieve the claim of the manuscript to assess watershed-scale hydrology and water quality response, a larger area that integrates several land uses and management practices, as well as a longer record that captures a representative variation of weather should be used.
Citation: https://doi.org/10.5194/egusphere-2024-3984-RC1 -
AC1: 'Reply on RC1', Qiang Zhao, 05 Mar 2025
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The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2024-3984/egusphere-2024-3984-AC1-supplement.pdf
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AC1: 'Reply on RC1', Qiang Zhao, 05 Mar 2025
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