4.7 Article

Analyses of landuse change impacts on catchment runoff using different time indicators based on SWAT model

期刊

ECOLOGICAL INDICATORS
卷 58, 期 -, 页码 55-63

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.ecolind.2015.05.031

关键词

Landuse change; Change in runoff; Flood indicator; Drought indicator; SWAT model; Jinjiang catchment

资金

  1. Science and Technology Major Program of Fujian Province [2015Y4002]
  2. Key Specialized Program of Public Research Institutes of Fujian [2013R04]
  3. National Natural Science Foundation of China [41301031]

向作者/读者索取更多资源

Previous researches mainly focused on the runoff responses to landuse change based on annual, seasonal or monthly time scales, there are few studies based on daily scale. We conducted a comprehensive investigation into runoff responses on the daily scale as well as annual and monthly time scales using SWAT, and compared the impacts of time scales with different time indicators quantitatively. Jinjiang, a coastal catchment of southeast China with a humid sub-tropical climate, was used for simulations. A calibrated SWAT model produced satisfactory reproduction of annual, monthly and daily runoff processes over a nine-year (2002-2010) period at three gauging stations. Runoff was then simulated and compared using the same meteorological input but two different landuse scenarios (1985 and 2006, with reduced forest and increased cropland and urbanized area). The results showed varying change in runoff among three time scales and three catchments. The annual runoff had the smallest increase between two scenarios, monthly runoffs had medium rates (increasing in all months except October November), and daily runoff had the largest rates with the increase in flood peaks but decrease in drought flows, because of the variable influence on interception/evapotranspiration loss, percolation and antecedent soil water storage. Indicators of different time scales (annual runoff, monthly runoff, maximum 1-day and 5-day flood runoff, minimum 1-day and 7-day runoff) proved appropriate for analysing landuse change impacts. (C) 2015 Elsevier Ltd. All rights reserved.

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