干旱区生态环境知识资源中心(Arid): The role of cross-correlation between precipitation and temperature in basin-scale simulations of hydrologic variables

Arid

DOI	10.1016/j.jhydrol.2018.12.076
	The role of cross-correlation between precipitation and temperature in basin-scale simulations of hydrologic variables
	Seo, S. B.1; Das Bhowmik, R.2; Sankarasubramanian, A.3; Mahinthakumar, G.3; Kumar, M.4
通讯作者	Das Bhowmik, R.
来源期刊	JOURNAL OF HYDROLOGY
ISSN	0022-1694
EISSN	1879-2707
出版年	2019
卷号	570 页码:304-314
英文摘要	Uncertainty in climate forcings causes significant uncertainty in estimating streamflow and other land-surface fluxes in hydrologic model simulations. Earlier studies primarily analyzed the importance of reproducing cross-correlation between precipitation and temperature (P-T cross-correlation) using various downscaling and weather generator schemes, leaving out how such biased estimates of P-T cross-correlation impact streamflow simulation and other hydrologic variables. The current study investigates the impacts of biased P-T cross-correlation on hydrologic variables using a fully coupled hydrologic model (Penn-state Integrated Hydrologic Model, PIHM). For this purpose, a synthetic weather generator was developed to generate multiple realizations of daily climate forcings for a specified P-T cross-correlation. Then, we analyzed how reproducing/neglecting P-T cross-correlation in climate forcings affect the accuracy of a hydrologic simulation. A total of 50 synthetic data sets of daily climate forcings with different P-T cross-correlation were forced into to estimate streamflow, soil moisture, and groundwater level under humid (Haw River basin in NC, USA) and arid (Lower Verde River basin in AZ, USA) hydroclimate settings. Results show that climate forcings reproducing the P-T cross-correlation yield lesser root mean square errors in simulated hydrologic variables (primarily on the sub-surface variables) as compared to climate forcings that neglect the P-T cross-correlation. Impacts of P-T cross-correlation on hydrologic simulations were remarkable to low flow and sub-surface variables whereas less significant to flow variables that exhibit higher variability. We found that hydrologic variables with lower internal variability (for example: groundwater and soil-moisture depth) are susceptible to the bias in P-T cross-correlation. These findings have potential implications in using univariate linear downscaling techniques to bias-correct GCM forcings, since univariate linear bias-correction techniques reproduce the GCM estimated P-T cross-correlation without correcting the bias in P-T cross-correlation.
英文关键词	Cross-correlation GCM Univariate Bias-correction PIHM Hydrologic simulation
类型	Article
语种	英语
国家	South Korea ; India ; USA
收录类别	SCI-E
WOS记录号	WOS:000460709400024
WOS关键词	CLIMATE ; STREAMFLOW ; RUNOFF ; SENSITIVITIES ; CMIP5 ; RIVER
WOS类目	Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向	Engineering ; Geology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/217133
作者单位	1.Seoul Natl Univ, Inst Engn Res, Seoul, South Korea; 2.Indian Inst Sci, Dept Civil Engn, Bangalore, Karnataka, India; 3.North Carolina State Univ, Dept Civil Construct & Environm Engn, Raleigh, NC 27695 USA; 4.Univ Alabama, Dept Civil Construct & Environm Engn, Tuscaloosa, AL USA
推荐引用方式 GB/T 7714	Seo, S. B.,Das Bhowmik, R.,Sankarasubramanian, A.,et al. The role of cross-correlation between precipitation and temperature in basin-scale simulations of hydrologic variables[J],2019,570:304-314.
APA	Seo, S. B.,Das Bhowmik, R.,Sankarasubramanian, A.,Mahinthakumar, G.,&Kumar, M..(2019).The role of cross-correlation between precipitation and temperature in basin-scale simulations of hydrologic variables.JOURNAL OF HYDROLOGY,570,304-314.
MLA	Seo, S. B.,et al."The role of cross-correlation between precipitation and temperature in basin-scale simulations of hydrologic variables".JOURNAL OF HYDROLOGY 570(2019):304-314.