ESTABLISHING SPATIAL DISTRIBUTIONS OF DROUGHT PHENOMENA ON CULTIVATION SEASONS USING THE SWAT MODEL

IF 0.7 Q4 GEOGRAPHY, PHYSICAL Geographia Technica Pub Date : 2022-05-31 DOI:10.21163/gt_2022.172.01
H. Prasanchum, Nutthasit Tumma, Worapong Lohpaisankrit
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引用次数: 1

Abstract

: Due to global climate change, drought phenomena are becoming longer. As a result, water availability is insufficient to meet demand for agriculture during the cultivation seasons and many areas have affected by drought. These can cause difficulties in water resources management. The main objectives of this study were to establish the spatial distribution of drought phenomena at sub-basin scales in the Lam Khan Chu and Lam Nam Chi Part II watersheds, which is the major headwater of the Chi River Basin, Thailand. The Soil and Water Assessment Tool (SWAT) model was used to synthesize streamflow data at the sub-basins of the watersheds. To estimate drought severity, the Streamflow Drought Index (SDI) was computed from the time series of the synthesized streamflow data during 2008 to 2019. The simulated streamflow of the SWAT model was acceptable based on the R 2 , Nash-Sutcliffe Efficiency (NSE) and Percent bias (PBIAS) reaching good levels in both calibration and verification. According to the SDI calculation, the most severe drought in the study period was in the year 2016. During January and April of 2016, the affected areas of about 3%, 30%, 14%, 30 and 23% of the study area were identified as none, mild, moderate, severe and extreme droughts, respectively. The integration of the hydrological model and drought index to monitor drought severity in space and time will be a useful tool for assessing drought severity. Moreover, the results can support managers for water resources management.
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利用SWAT模型建立栽培季节干旱现象的空间分布
:由于全球气候变化,干旱现象越来越长。因此,水资源不足以满足耕种季节的农业需求,许多地区受到干旱的影响。这些可能会给水资源管理带来困难。本研究的主要目的是建立Lam Khan Chu和Lam Nam Chi第二部分流域的次流域尺度干旱现象的空间分布,该流域是泰国池河流域的主要源头。土壤和水评估工具(SWAT)模型用于综合流域子流域的流量数据。为了估计干旱严重程度,径流干旱指数(SDI)是根据2008年至2019年期间合成径流数据的时间序列计算得出的。基于R2、Nash-Sutcliffe效率(NSE)和百分比偏差(PBIAS)在校准和验证中均达到良好水平,SWAT模型的模拟流量是可接受的。根据SDI的计算,研究期间最严重的干旱发生在2016年。2016年1月和4月,研究区域约3%、30%、14%、30%和23%的受影响区域分别被确定为无干旱、轻度、中度、重度和极端干旱。将水文模型和干旱指数结合起来,在空间和时间上监测干旱的严重程度,将是评估干旱严重程度的有用工具。此外,研究结果可以支持管理人员进行水资源管理。
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来源期刊
Geographia Technica
Geographia Technica GEOGRAPHY, PHYSICAL-
CiteScore
2.30
自引率
14.30%
发文量
34
期刊介绍: Geographia Technica is a journal devoted to the publication of all papers on all aspects of the use of technical and quantitative methods in geographical research. It aims at presenting its readers with the latest developments in G.I.S technology, mathematical methods applicable to any field of geography, territorial micro-scalar and laboratory experiments, and the latest developments induced by the measurement techniques to the geographical research. Geographia Technica is dedicated to all those who understand that nowadays every field of geography can only be described by specific numerical values, variables both oftime and space which require the sort of numerical analysis only possible with the aid of technical and quantitative methods offered by powerful computers and dedicated software. Our understanding of Geographia Technica expands the concept of technical methods applied to geography to its broadest sense and for that, papers of different interests such as: G.l.S, Spatial Analysis, Remote Sensing, Cartography or Geostatistics as well as papers which, by promoting the above mentioned directions bring a technical approach in the fields of hydrology, climatology, geomorphology, human geography territorial planning are more than welcomed provided they are of sufficient wide interest and relevance.
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