遥感降水产品对黄河源区水文干旱特征的模拟性能分析

doi:10.12118/j.issn.1000-6060.2022.631

Abstract

Abstract:

In regions with scarce data, remote sensing precipitation products provide crucial data for the development of the hydrometeorological disaster mechanism and early warning studies. However, the performance of various remote sensing precipitation products exhibits regional heterogeneity. Comprehensively evaluating the performance of remote sensing precipitation products is critical for their use in hydrometeorological-related research and application. Based on this assumption, the study investigated the source region of the Yellow River of China by using the observed precipitation data (CMA) from 1983 to 2018 to drive and calibrate the ABCD hydrological model. Furthermore, the standardized runoff index (SRI) was used to evaluate the simulation performance of three sets of typical remote sensing precipitation products (PERSIANN-CDR, CHIRPS v2.0, MSWEP v2.0) on hydrological drought. Furthermore, hydrological drought events were identified by using run theory, and the potency of remote sensing precipitation to capture hydrological drought characteristics was investigated. The results revealed that: (1) The three precipitation products can accurately capture the temporal and spatial distribution pattern of CMA’s multiyear mean value. Furthermore, the CHIRPS product (Nash-Sutcliffe efficiency coefficient, NSE=0.72) outperformed other two products in term of hydrological simulation. (2) The SRI values (SRI1, SRI3, SRI6, and SRI12) of the four scales simulated by CMA and three sets of remote sensing precipitation products revealed a significant increase trend (P<0.01), which indicated that the river runoff in the source region increased in the last 36 years, and the hydrological drought slowed down. However, the SRI values of the three sets of remote sensing precipitation products were overestimated. This result revealed that the deviation correction of precipitation products in the source area of the Yellow River is necessary. In terms of basic statistical indicators, the SRI calculated by the MSWEP product was the most consistent with CMA and was the best. However, on an annual scale (SRI12), the PERSIANN product achieved the best performance. (3) Three sets of remote sensing precipitation products overestimated the drought duration and intensity of SRI1 and SRI3; the MSWEP product achieved the best simulation performance for SRI6; and the PERSIANN product has the best simulation performance for SRI12. The results of this study can provide scientific decision support for the selection of precipitation product data for studying hydrological drought in the source region of the Yellow River.

Key words: remote sensing precipitation, hydrological drought, ABCD hydrological model, standardized runoff index (SRI), the source region of the Yellow River

CHENG Shuo, LI Yanzhong, XING Yincong, YU Zhiguo, WANG Yuangang, HUANG Manjie. Simulation performance of remote sensing precipitation products on hydrological drought characteristics in the source region of the Yellow River[J].Arid Land Geography, 2023, 46(7): 1063-1072.

Figures/Tables 8

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数据集	年份	空间跨度	数据下载来源
PERSIANN-CDR	1983—2018	60°S~60°N	http://chrsdata.eng.uci.edu/
CHIRPS v2.0	1983—2018	50°S~50°N	ftp://ftp.chg.ucsb.edu/pub/org/chg/products/CHIRPS-2.0
MSWEP v2.0	1979—2018	全球	http://gloh2o.org/

SRI值	干旱程度
-0.5<SRI	无旱
-1.0<SRI≤-0.5	轻度干旱
-1.5<SRI≤-1.0	中度干旱
-2.0<SRI≤-1.5	严重干旱
SRI≤-2.0	极端干旱

不同时间尺度SRI	CMA	遥感降水产品
不同时间尺度SRI	CMA	PERSIANN	MSWEP	CHIRPS
SRI1	0.0016^***	0.0042^***	0.0034^***	0.0035^***
SRI3	0.0016^***	0.0044^***	0.0035^***	0.0036^***
SRI6	0.0016^***	0.0043^***	0.0035^***	0.0037^***
SRI12	0.0015^***	0.0040^***	0.0035^***	0.0036^***

Simulation performance of remote sensing precipitation products on hydrological drought characteristics in the source region of the Yellow River

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