Temporal change of spatial heterogeneity and its effect on regional trend of annual precipitation heterogeneity indices. Issue 18 (12th July 2017)

• Record Type: Journal Article
• Authors: Zhang, Runrun; Chen, Xi; Wang, Huimin; Cheng, Qinbo; Zhang, Zhicai; Shi, Peng
• Is Part Of: Hydrological processes. Volume 31:Issue 18(2017)
• Page Start: 3178
• Page End: 3190
• Publication Date: 2017-07-12
• Subjects: GAMLSS -- intra‐annual precipitation heterogeneity -- regional trend analysis -- spatiotemporal variation -- the Huaihe River; Hydrology -- Periodicals; Hydrology -- Research -- Periodicals; Hydrologic models -- Periodicals; Hydrological forecasting -- Periodicals; 631.432
• DOI: 10.1002/hyp.11225
• Languages: English
• ISSNs: 0885-6087

Abstract

Abstract: A statistical test on climate and hydrological series from different spatial resolution could obtain different regional trend due to spatial heterogeneity and its temporal variability. In this study, annual series of the precipitation heterogeneity indices of concentration index (CI) and the number of wet days (NW) along with annual total amount of precipitation were calculated based on at‐site daily precipitation series during 1962–2011 in the headwater basin of the Huaihe River, China. The regional trends of the indices were first detected based on at‐site series by using the aligned and intrablock methods, and field significance tests that consider spatial heterogeneity over sites. The detected trends were then compared with the trends of the regional index series derived from daily areal average precipitation (DAAP), which averages at‐site differences and thus neglects spatial heterogeneity. It was found that the at‐site‐based regional test shows increasing trends of CI and NW in the basin, which follows the test on individual sites that most of sites were characterized by increasing CI and NW. However, the DAAP‐derived regional series of CI and NW were tested to show a decreasing trend. The disparity of the regional trend test on at‐site‐based regional series and the DAAP‐derived regional series arises from a temporal change of the spatial heterogeneity, which was quantified by the generalized additive models for location, scale, and shape. This study highlights that compared with averaging indices, averaging at‐site daily precipitation could lead to an error in the regional trend inference on annual precipitation heterogeneity indices. More attention should be paid to temporal variability in spatial heterogeneity when data at large scales are used for regional trend detection on hydro‐meteorological events associated with intra‐annual heterogeneity.