基于轨道数据的SWAT模型在巴西亚马逊地区监测不足的流域流量和水平衡模拟中的评价

Q3 Social Sciences
Paulo Ricardo Rufino, B. Gücker, M. Faramarzi, I. Boëchat, F. Cardozo, P. R. Santos, Gustavo Domingos Zanin, G. Mataveli, G. Pereira
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引用次数: 3

摘要

亚马逊流域是世界上最大的河流流域,是全球气候的关键调节器。由于缺乏广泛的测量站网络,该流域的监测仍然很差,妨碍了对其水资源的管理。由于亚马逊流域的广大延伸,水文建模是监测其现状的唯一可行方法。在这里,我们使用土壤和水评估工具(SWAT),一个基于过程和时间连续的生态水文模型,模拟了亚马逊流域只有几个监测站(Jari河流域)的河流流量和水文水平衡。SWAT输入包括基于轨道遥感的再分析数据。SWAT模型的校准和验证表明,根据Nash-Sutcliffe (NS, 0.85和0.89),标准偏差比(RSR, 0.39和0.33)和百分比偏差(PBIAS, - 9.5和- 0.6)值,SWAT模型具有良好的一致性。总体而言,该模型令人满意地模拟了水流和平衡特征,如蒸散发、地表径流和地下水。SWAT模型适用于热带流域管理和环境变化情景模拟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of the SWAT Model for the Simulation of Flow and Water Balance Based on Orbital Data in a Poorly Monitored Basin in the Brazilian Amazon
The Amazon basin, the world’s largest river basin, is a key global climate regulator. Due to the lack of an extensive network of gauging stations, this basin remains poorly monitored, hindering the management of its water resources. Due to the vast extension of the Amazon basin, hydrological modeling is the only viable approach to monitor its current status. Here, we used the Soil and Water Assessment Tool (SWAT), a process-based and time-continuous eco-hydrological model, to simulate streamflow and hydrologic water balance in an Amazonian watershed where only a few gauging stations (the Jari River Basin) are available. SWAT inputs consisted of reanalysis data based on orbital remote sensing. The calibration and validation of the SWAT model indicated a good agreement according to Nash-Sutcliffe (NS, 0.85 and 0.89), Standard Deviation Ratio (RSR, 0.39 and 0.33), and Percent Bias (PBIAS, −9.5 and −0.6) values. Overall, the model satisfactorily simulated water flow and balance characteristics, such as evapotranspiration, surface runoff, and groundwater. The SWAT model is suitable for tropical river basin management and scenario simulations of environmental changes.
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来源期刊
Human Geographies
Human Geographies Social Sciences-Geography, Planning and Development
CiteScore
1.10
自引率
0.00%
发文量
7
审稿时长
8 weeks
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