气候变化领域集成服务门户(CCPortal): Comprehensive evaluation of 0.25° precipitation datasets combined with MOD10A2 snow cover data in the ice-dominated river basins of Pakistan

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DOI	10.1016/j.atmosres.2019.104653
	Comprehensive evaluation of 0.25° precipitation datasets combined with MOD10A2 snow cover data in the ice-dominated river basins of Pakistan
	Faiz M.A.; Liu D.; Tahir A.A.; Li H.; Fu Q.; Adnan M.; Zhang L.; Naz F.
发表日期	2020
ISSN	0169-8095
卷号	231
英文摘要	A major portion of Pakistan's economy is based on cultivated lands which are irrigated from the supply of water from Upper Indus River Basins (UIB). Any change in UIB rivers flows may come with catastrophic events and therefore, will destructively affect Pakistan's economy. By aiming this scenario, an uneven and important climate variable (i.e., precipitation) obtained from different gridded and satellite datasets were used for its statistical and hydrological performance evaluation in UIB catchments for the period of 2000 to 2004. In addition, a bias corrected technique and snow cover product (MOD10A2) was also used to enhance the performance of precipitation data sets to obtain realistic discharge simulations. The results indicated that without correcting the biases from the datasets, only APHRODITE precipitation dataset showed higher correlation with observations compared to other precipitation datasets in Hunza River Basin (HRB) with correlation coefficient of (0.44) & and in Gilgit River Basin (GRB) (0.35), respectively. However, after applying bias correction technique (quantile mapping), the performance of precipitation datasets significantly improved. For GRB, correlation coefficient and root mean square values improved up to 48% & 55%, while for HRB up to 53% & 51%, respectively. Likewise, based on hydrological utility which was implied by the well-known hydrological model (snowmelt runoff model), bias corrected CHIRPS and APHRODITE precipitation datasets displayed best performance in simulating the discharge with Nash–Sutcliffe coefficient (0.82 & 0.90) & correlation coefficient (0.83 & 0.84) in HRB and (0.84 & 0.80) and (0.86 & 0.82) in GRB, respectively. Moreover, recalibration was also carried out to assess how the hydrological model can adjust and tolerate the errors of different precipitation data products. The results revealed that after adjusting the model parameters particularly coefficient of rainfall and coefficient of snow, the performance of data products significantly improved in terms of the difference in volumes against in situ measurements. Overall, this study may assist, provide guidelines and efficiently used for snowmelt runoff model coupled with different precipitation datasets for management of Indus River irrigation system of Pakistan. © 2019 Elsevier B.V.
英文关键词	Gridded datasets; Hydrological model; Precipitation; Satellite
URL	https://www2.scopus.com/inward/record.uri?eid=2-s2.0-85070953424&doi=10.1016%2fj.atmosres.2019.104653&partnerID=40&md5=ec9d0b16873814f796b578a37f13e0fe
语种	英语
scopus关键词	Catchments; Climate models; Precipitation (chemical); Runoff; Satellites; Snow; Snow melting systems; Watersheds; Comprehensive evaluation; Correlation coefficient; Discharge simulations; Gridded datasets; Hydrological modeling; Root mean square values; Snow-cover products; Snowmelt runoff model; Rivers; catchment; climate variation; data set; hydrological modeling; precipitation assessment; river basin; satellite data; snow cover; Pakistan
来源期刊	Atmospheric Research
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/77331
作者单位	School of Water Conservancy & Civil Engineering, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Key Laboratory of Effective Utilization of Agricultural Water Resources of Ministry of Agriculture, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Heilongjiang Provincial Collaborative Innovation Center of Grain Production Capacity Improvement, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Key Laboratory of Water-Saving Agriculture of Ordinary University in Heilongjiang Province, Northeast Agricultural University, Harbin, Heilongjiang 150030, China; Department of Environmental Sciences, COMSATS Institute of Information Technology, Abbottabad, 22060, Pakistan; State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou, 730000, China; Department of Civil Engineering, Khawaja Fareed University, Rahim Yar Khan, Pakistan
推荐引用方式 GB/T 7714	Faiz M.A.,Liu D.,Tahir A.A.,et al. Comprehensive evaluation of 0.25° precipitation datasets combined with MOD10A2 snow cover data in the ice-dominated river basins of Pakistan[J]. 中国科学院西北生态环境资源研究院,2020,231.
APA	Faiz M.A..,Liu D..,Tahir A.A..,Li H..,Fu Q..,...&Naz F..(2020).Comprehensive evaluation of 0.25° precipitation datasets combined with MOD10A2 snow cover data in the ice-dominated river basins of Pakistan.Atmospheric Research,231.
MLA	Faiz M.A.,et al."Comprehensive evaluation of 0.25° precipitation datasets combined with MOD10A2 snow cover data in the ice-dominated river basins of Pakistan".Atmospheric Research 231(2020).