干旱区生态环境知识资源中心(Arid): A daily spatially explicit stochastic rainfall generator for a semi-arid climate

Arid

DOI	10.1016/j.jhydrol.2019.04.006
	A daily spatially explicit stochastic rainfall generator for a semi-arid climate
	Zhao, Ying 1; Nearing, Mark A.2; Guertin, D. Phillip 1
通讯作者	Zhao, Ying
来源期刊	JOURNAL OF HYDROLOGY
ISSN	0022-1694
EISSN	1879-2707
出版年	2019
卷号	574 页码:181-192
英文摘要	Many semi-arid regions of the world experience rainfall patterns characterized by high spatial variability. Accurate spatial representation of different types of rainfall will facilitate the application of distributed hydrological models in these areas. This study presents a daily, spatially distributed, stochastic rainfall generator based on a first-order Markov chain model, calibrated using 50 years of rainfall observations at 88 gages from 1967 through 2016 in the 148-km(2) Walnut Gulch Experimental Watershed. Three types of rainfall, including convective, frontal, and tropical depression storms, were simulated separately in the generator using biweekly parameterization. Convective storms were simulated based on an elliptical shape rain cell conceptual model, whereas frontal and tropical depression storms were simulated as uniform rainfall fields over the whole watershed with introduced random variability. The rainfall generator was evaluated by comparing the mean statistics of 30 sets of 50-year simulated data versus the 50-year rain gage observed data. Most individual storm statistics and aggregated seasonal rainfall statistics were similar to the measured rainfall observations. The long-term mean values of both summer and winter rainfall amount were statistically satisfactory. This model can serve as a guide for application in areas with convective, frontal, and tropical depression storms.
英文关键词	Rainfall generator Spatial Semi-arid Convective storm Markov chain
类型	Article
语种	英语
国家	USA
收录类别	SCI-E
WOS记录号	WOS:000476962800017
WOS关键词	MULTISITE DAILY PRECIPITATION ; WEATHER GENERATOR ; SIMULATION ; MODEL ; TEMPERATURE ; PATTERNS ; VARIABILITY ; SENSITIVITY ; CELLS ; SCALE
WOS类目	Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向	Engineering ; Geology ; Water Resources
来源机构	University of Arizona
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/217163
作者单位	1.Univ Arizona, Sch Nat Resources & Environm, Tucson, AZ 85719 USA; 2.USDA ARS, Southwest Watershed Res Ctr, Tucson, AZ 85719 USA
推荐引用方式 GB/T 7714	Zhao, Ying,Nearing, Mark A.,Guertin, D. Phillip. A daily spatially explicit stochastic rainfall generator for a semi-arid climate[J]. University of Arizona,2019,574:181-192.
APA	Zhao, Ying,Nearing, Mark A.,&Guertin, D. Phillip.(2019).A daily spatially explicit stochastic rainfall generator for a semi-arid climate.JOURNAL OF HYDROLOGY,574,181-192.
MLA	Zhao, Ying,et al."A daily spatially explicit stochastic rainfall generator for a semi-arid climate".JOURNAL OF HYDROLOGY 574(2019):181-192.