Dataset Information

A spatial-temporal continuous dataset of the transpiration to evapotranspiration ratio in China from 1981-2015.

ABSTRACT: The ratio of plant transpiration to total terrestrial evapotranspiration (T/ET) captures the role of vegetation in surface-atmosphere interactions. However, several studies have documented a large variability in T/ET. In this paper, we present a new T/ET dataset (also including transpiration, evapotranspiration data) for China from 1981 to 2015 with spatial and temporal resolutions of 0.05° and 8 days, respectively. The T/ET dataset is based on a model-data fusion method that integrates the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model with multivariate observational datasets (transpiration and evapotranspiration). The dataset is driven by satellite-based leaf area index (LAI) data from GLASS and GLOBMAP, and climate data from the Chinese Ecosystem Research Network (CERN). Observational annual T/ET were used to validate the model, with R² and RMSE values were 0.73 and 0.07 (12.41%), respectively. The dataset provides significant insight into T/ET and its changes over the Chinese terrestrial ecosystem and will be beneficial for understanding the hydrological cycle and energy budgets between the land and the atmosphere.

SUBMITTER: Niu Z

PROVIDER: S-EPMC7591528 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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A spatial-temporal continuous dataset of the transpiration to evapotranspiration ratio in China from 1981-2015.

Niu Zhongen Z He Honglin H Zhu Gaofeng G Ren Xiaoli X Zhang Li L Zhang Kun K

Scientific data 20201027 1

The ratio of plant transpiration to total terrestrial evapotranspiration (T/ET) captures the role of vegetation in surface-atmosphere interactions. However, several studies have documented a large variability in T/ET. In this paper, we present a new T/ET dataset (also including transpiration, evapotranspiration data) for China from 1981 to 2015 with spatial and temporal resolutions of 0.05° and 8 days, respectively. The T/ET dataset is based on a model-data fusion method that integrates the Prie ...[more]

PMID: 33110108

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Project description:It is of great significance for the efficient utilization of water resources and the construction of the ecological environment in China to fully understand the evolution process of the spatial-temporal pattern of evapotranspiration (ET). With the use of the v2.0 and v2.1 ET data sets combined with the Global Land Data Assimilation System and Noah model, this paper selects pixels as the basic research object to analyse the spatial-temporal variation in ET in China during the 71 years from 1948 to 2018. We first applied the TFPW-MK test to study the annual ET trend in China throughout the 71-year period, including the ET trend of each month from January to December and the annual total ET trend. Moreover, we examined the spatial variation in these trends. In addition, we calculated the variation coefficient of the time series of each pixel's ET throughout the 71-year period and the variation coefficient of the spatial distribution of ET in each year to analyse the spatial-temporal fluctuations in ET in the study area. Finally, the Hurst index was adopted to evaluate the future ET trend. Based on these analyses, we observed the following novel spatial-temporal characteristics of ET: from 1948 to 2018, (1) the ET in most regions covered by 89.5% of all pixels in China exhibits an increasing trend. (2) The ET trend in China varies greatly with the change in months, and many regions show the most or least obvious increasing trend (or decreasing trend) at different times. (3) The area with an increasing trend is the largest in May and the smallest in December, and more than half of the pixels in all months of a year reveal an increasing trend. (4) In the northeast, west and south regions of China, the monthly fluctuation in the ET trend is relatively large, which indicates that the ET trend in these regions is greatly affected by the month. (5) The fluctuation in ET in China is larger in the north than it is in the south and larger in the west than it is in the east. The most stable fluctuation occurs in East China. (6) The ET trend of almost all the pixels in the study area remains consistent from 1948 to 2018, and there are large areas with a notable continuity. This results in the spatial variation in ET in the study area increasing.

Project description:BackgroundTuberculosis (TB) is still one of the most serious infectious diseases in the mainland of China. So it was urgent for the formulation of more effective measures to prevent and control it.MethodsThe data of reported TB cases in 340 prefectures from the mainland of China were extracted from the China Information System for Disease Control and Prevention (CISDCP) during January 2005 to December 2015. The Kulldorff's retrospective space-time scan statistics was used to identify the temporal, spatial and spatio-temporal clusters of reported TB in the mainland of China by using the discrete Poisson probability model. Spatio-temporal clusters of sputum smear-positive (SS+) reported TB and sputum smear-negative (SS-) reported TB were also detected at the prefecture level.ResultsA total of 10?200?528 reported TB cases were collected from 2005 to 2015 in 340 prefectures, including 5?283?983 SS- TB cases and 4?631?734 SS?+?TB cases with specific sputum smear results, 284?811 cases without sputum smear test. Significantly TB clustering patterns in spatial, temporal and spatio-temporal were observed in this research. Results of the Kulldorff's scan found twelve significant space-time clusters of reported TB. The most likely spatio-temporal cluster (RR?=?3.27, P?<? 0.001) was mainly located in Xinjiang Uygur Autonomous Region of western China, covering five prefectures and clustering in the time frame from September 2012 to November 2015. The spatio-temporal clustering results of SS+ TB and SS- TB also showed the most likely clusters distributed in the western China. However, the clustering time of SS+ TB was concentrated before 2010 while SS- TB was mainly concentrated after 2010.ConclusionsThis study identified the time and region of TB, SS+ TB and SS- TB clustered easily in 340 prefectures in the mainland of China, which is helpful in prioritizing resource assignment in high-risk periods and high-risk areas, and to formulate powerful strategy to prevention and control TB.

Dataset Information

A spatial-temporal continuous dataset of the transpiration to evapotranspiration ratio in China from 1981-2015.

Publications

A spatial-temporal continuous dataset of the transpiration to evapotranspiration ratio in China from 1981-2015.

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