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Event-aware SWAT+ calibration for stormflows with monthly nutrient data in the Qingjiang River Basin.

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Title: Event-aware SWAT+ calibration for stormflows with monthly nutrient data in the Qingjiang River Basin.
Authors: Wang, Ruining1 (AUTHOR) 1027560229@qq.com, Zhang, Xianqi1,2,3 (AUTHOR) zhangxq202509@163.com, Zhang, Hongyang1 (AUTHOR) zhyncwu@163.com, Yang, Yanbin1 (AUTHOR) 1330572468@qq.com, Tao, Zelin1 (AUTHOR) 865672350@qq.com
Source: Environmental Monitoring & Assessment. Apr2026, Vol. 198 Issue 4, p1-21. 21p.
Subject Terms: *Runoff, *Optimization algorithms, *Watersheds
Geographic Terms: China
Abstract: Storm-driven nonpoint-source (NPS) export in steep mountain basins is highly sensitive to runoff peaks, yet nutrient monitoring is typically monthly, limiting event-scale calibration. This study proposes an event-aware SWAT+ calibration framework for the Qingjiang River Basin (China) by coupling Hippopotamus Optimization (HO) with SUFI-2 uncertainty fitting. The objective retains monthly Nash–Sutcliffe efficiency (NSE) for discharge and nutrients and adds an event regularization term computed from daily discharge within objectively delineated runoff events (peak magnitude, time-to-peak, and recession slope). Using 2008–2018 for split-sample calibration/validation and 2020–2024 for an out-of-sample test without parameter retuning, HO-SUFI-2 improves monthly discharge NSE from 0.72 to 0.79 (calibration) and from 0.70 to 0.73 (validation) while tightening uncertainty (P-factor 83%→87%; R-factor 1.21→1.09). Peak constraints reduce median relative peak-magnitude error from 0.104 to 0.069 at Gaobazhou and from 0.114 to 0.069 at Changyang, and tighten peak-timing dispersion (|TPK| IQR 2→1 days at Gaobazhou; median |TPK| 1→0 day at Changyang), without degrading monthly nutrient skill (TP NSE 0.70→0.73). In 2020–2024, monthly discharge NSE remains 0.62–0.67 and TN/TP NSE ≥ 0.42 at both stations; remaining biases may reflect post-2020 management and reservoir operations not explicitly represented. The framework provides a practical way to constrain storm hydrograph dynamics under data limitations and to report uncertainty-aware diagnostics for storm-period risk screening in mountainous basins. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
FullText Text:
  Availability: 0
Header DbId: enr
DbLabel: Energy & Power Source
An: 193283029
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Event-aware SWAT+ calibration for stormflows with monthly nutrient data in the Qingjiang River Basin.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Wang%2C+Ruining%22">Wang, Ruining</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> 1027560229@qq.com</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Xianqi%22">Zhang, Xianqi</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> zhangxq202509@163.com</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Hongyang%22">Zhang, Hongyang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> zhyncwu@163.com</i><br /><searchLink fieldCode="AR" term="%22Yang%2C+Yanbin%22">Yang, Yanbin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> 1330572468@qq.com</i><br /><searchLink fieldCode="AR" term="%22Tao%2C+Zelin%22">Tao, Zelin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> 865672350@qq.com</i>
– Name: TitleSource
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Monitoring+%26+Assessment%22">Environmental Monitoring & Assessment</searchLink>. Apr2026, Vol. 198 Issue 4, p1-21. 21p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Runoff%22">Runoff</searchLink><br />*<searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Watersheds%22">Watersheds</searchLink>
– Name: SubjectGeographic
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Storm-driven nonpoint-source (NPS) export in steep mountain basins is highly sensitive to runoff peaks, yet nutrient monitoring is typically monthly, limiting event-scale calibration. This study proposes an event-aware SWAT+ calibration framework for the Qingjiang River Basin (China) by coupling Hippopotamus Optimization (HO) with SUFI-2 uncertainty fitting. The objective retains monthly Nash–Sutcliffe efficiency (NSE) for discharge and nutrients and adds an event regularization term computed from daily discharge within objectively delineated runoff events (peak magnitude, time-to-peak, and recession slope). Using 2008–2018 for split-sample calibration/validation and 2020–2024 for an out-of-sample test without parameter retuning, HO-SUFI-2 improves monthly discharge NSE from 0.72 to 0.79 (calibration) and from 0.70 to 0.73 (validation) while tightening uncertainty (P-factor 83%→87%; R-factor 1.21→1.09). Peak constraints reduce median relative peak-magnitude error from 0.104 to 0.069 at Gaobazhou and from 0.114 to 0.069 at Changyang, and tighten peak-timing dispersion (|TPK| IQR 2→1 days at Gaobazhou; median |TPK| 1→0 day at Changyang), without degrading monthly nutrient skill (TP NSE 0.70→0.73). In 2020–2024, monthly discharge NSE remains 0.62–0.67 and TN/TP NSE ≥ 0.42 at both stations; remaining biases may reflect post-2020 management and reservoir operations not explicitly represented. The framework provides a practical way to constrain storm hydrograph dynamics under data limitations and to report uncertainty-aware diagnostics for storm-period risk screening in mountainous basins. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=193283029
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1007/s10661-026-15187-3
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 21
        StartPage: 1
    Subjects:
      – SubjectFull: Runoff
        Type: general
      – SubjectFull: Optimization algorithms
        Type: general
      – SubjectFull: Watersheds
        Type: general
      – SubjectFull: China
        Type: general
    Titles:
      – TitleFull: Event-aware SWAT+ calibration for stormflows with monthly nutrient data in the Qingjiang River Basin.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Wang, Ruining
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          Name:
            NameFull: Zhang, Xianqi
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            NameFull: Zhang, Hongyang
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            NameFull: Yang, Yanbin
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            NameFull: Tao, Zelin
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          Dates:
            – D: 01
              M: 04
              Text: Apr2026
              Type: published
              Y: 2026
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              Value: 01676369
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              Value: 198
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            – TitleFull: Environmental Monitoring & Assessment
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