Coupled modelling and sampling approaches to assess the impacts of human water management on land-sea carbon transfer

Ni, Shaoqiang; Huang, Xiao; Gan, Weixiu; Zorn, Conrad; Xiao, Yuchen; Huang, Guorui; Yu, Chunyan; Cao, Jifu; Zhang, Jie; Feng, Zhao; Yu, Le; Lin, Guanghui; Silvennoinen, Hanna

doi:10.1016/j.scitotenv.2019.134735

Cited by 4 publications

(2 citation statements)

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“…The regions of Central Asia, including Kazakhstan, Turkmenistan, Uzbekistan, Tajikistan, Kyrgyzstan, and Xinjiang province in China, extend from 34.3 • to 55. 4 • N latitude and from 46.5 • to 96.4 • E longitude, encompassing a land area of approximately 5.7 million km 2 . The overall population of Central Asia was approximately 101 million by 2020, which equaled to about 18 people per km 2 , according to the statistics provide by the World Bank (https://data.worldbank.org/indicator/SP.POP.TOTL; accessed 12 February 2022) and China Statistical Yearbook 2021 (http://www.stats.gov.cn/tjsj/ndsj/2021/indexch.htm; accessed 12 February 2022).…”

Section: Study Areamentioning

confidence: 99%

“…Biogeochemical models constrained by high-quality, gridded atmospheric variables are essential for simulating the response of carbon and water dynamics to environmental changes at a regional scale [4,5]. Reducing simulation uncertainties is becoming increasingly significant to further explore the impacts of climate change on terrestrial carbon cycles [6].…”

Section: Introductionmentioning

confidence: 99%

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Contribution of Climate Change and Grazing on Carbon Dynamics in Central Asian Pasturelands

Han

2022

Remote Sensing

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Reducing the uncertainties in carbon balance assessment is essential for better pastureland management in arid areas. Climate forcing data are some of the major uncertainty sources. In this study, a modified Biome-BGC grazing model was driven by an ensemble of reanalysis data of the Climate Forecast System Reanalysis data (CFSR), the European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim), and the Modern-Era Retrospective Analysis for Research and Applications (MERRA), to study the effect of climate change and grazing on the net ecosystem exchange (NEE) of the pasturelands in Central Asia. Afterwards, we evaluated the performance of corresponding climate datasets over four major pastureland types, and quantified the modeling uncertainty induced by climate forcing data. Our results suggest that (1) a significant positive trend in temperature and a negative trend in precipitation were obtained from the three climate datasets. The average precipitation is apparently higher in the CFSR and MERRA data, showing the highest temperature value among the data sets; (2) pasturelands in Central Asia released 2.10 ± 1.60 Pg C in the past 36 years. The highest values were obtained with the CFSR (−1.53 Pg C) and the lowest with the MERRA (−2.35 Pg C) data set; (3) without grazing effects, pasturelands in Central Asia assimilated 0.13 ± 0.06 Pg C from 1981–2014. Grazing activities dominated carbon release (100%), whereas climate changes dominated carbon assimilation (offset 6.22% of all the carbon release). This study offered possible implications to the policy makers and local herdsmen of sustainable management of pastureland and the adaptation of climate change in Central Asia.

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Section: Study Areamentioning

confidence: 99%