Volume 8, Issue 3 (2020)
ECOPERSIA 2020, 8(3): 169-180 |
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Norouzi Nazar M, Asgari E, Baaghideh M, Lotfi S. Quantifying the Long-Term Flood Regulation Ecosystem Service under Climate Change Using SWAT Model. ECOPERSIA 2020; 8 (3) :169-180
URL: http://ecopersia.modares.ac.ir/article-24-36672-en.html
URL: http://ecopersia.modares.ac.ir/article-24-36672-en.html
1- Civil Engineering Department, Engineering Faculty, University of Sistan and Baluchestan, Zahedan, Iran
2- Climatology & Geomorphology Department, Geography & Environmental Sciences Faculty, Hakim Sabzevari University, Sabzevar, Iran
3- Climatology & Geomorphology Department, Geography & Environmental Sciences Faculty, Hakim Sabzevari University, Sabzevar, Iran , m.baaghideh @hsu.ac.ir
4- School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran
2- Climatology & Geomorphology Department, Geography & Environmental Sciences Faculty, Hakim Sabzevari University, Sabzevar, Iran
3- Climatology & Geomorphology Department, Geography & Environmental Sciences Faculty, Hakim Sabzevari University, Sabzevar, Iran , m.baaghideh @hsu.ac.ir
4- School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran
Abstract: (2434 Views)
Aims: In recent years, interest in quantifying ecosystem services (ESs) has dramatically grown among the scientific society. By increasing global environmental crises as a result of population growth, it is becoming increasingly essential to quantify the impacts that human activities have on ESs. Soil and water assessment tool (SWAT) is a process-based distributed hydrological model that has been widely recommended to quantify the ESs. The purpose of the present study is to employ the SWAT model for quantifying the flood regulation ecosystem service in one of the highest flood prone watersheds in the west of Iran.
Materials & Methods: In this study, after calibration and validation of daily and monthly discharge using SUFI-2 algorithm, the flood regulation index (FRI) was calculated for each year of simulation period (1989-2017).
Findings: The results show that climate variables such as precipitation could severely affect the quantities of FRI in different years. According to middle of 95PPU, the FRI varies from 0.22 in the wettest year of 1994 to 0.72 in the driest year of 2017 with precipitation values of 1080 and 380mm, respectively. The results also indicate that lower, middle, and upper limits of FRI 95PPU show the correlation coefficient of 28, 66, and 72% with the precipitation values in different years.
Conclusion: The available knowledge on the application of SWAT model in addressing ESs can be similarly used in the regions with corresponding environmental challenges of the low delivery level of regulation ESs.
Materials & Methods: In this study, after calibration and validation of daily and monthly discharge using SUFI-2 algorithm, the flood regulation index (FRI) was calculated for each year of simulation period (1989-2017).
Findings: The results show that climate variables such as precipitation could severely affect the quantities of FRI in different years. According to middle of 95PPU, the FRI varies from 0.22 in the wettest year of 1994 to 0.72 in the driest year of 2017 with precipitation values of 1080 and 380mm, respectively. The results also indicate that lower, middle, and upper limits of FRI 95PPU show the correlation coefficient of 28, 66, and 72% with the precipitation values in different years.
Conclusion: The available knowledge on the application of SWAT model in addressing ESs can be similarly used in the regions with corresponding environmental challenges of the low delivery level of regulation ESs.
Article Type: Original Research |
Subject:
Terrestrial Ecosystems
Received: 2019/09/26 | Accepted: 2020/01/9 | Published: 2020/09/20
Received: 2019/09/26 | Accepted: 2020/01/9 | Published: 2020/09/20
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