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Variation in agricultural water demand and its attributions in the arid Tarim River Basin

Published online by Cambridge University Press:  21 May 2018

G. Fang Open the ORCID record for G. Fang [Opens in a new window] ,
Y. Chen  and
Z. Li
G. Fang
Affiliation:
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 830011 Urumqi, China Department of Geography, Ghent University, 9000 Ghent, Belgium
Y. Chen*
Affiliation:
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 830011 Urumqi, China
Z. Li
Affiliation:
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 830011 Urumqi, China
*
Author for correspondence: Y. Chen, E-mail: chenyn@ms.xjb.ac.cn
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Abstract

Agricultural water use accounts for more than 95% of the total water consumption in the extreme arid region of the Tarim River Basin. Understanding the variation of agricultural water demand (AWD) and its attributions is therefore vital for irrigation management and water resource allocation affecting the economy and natural ecosystems in this high water-deficit region. Here spatial–temporal variations of AWD based on weighted crop water requirement (ETc) were estimated using the Penman–Monteith equation and the crop coefficient approach. Then the contributions of meteorological factors and planting structure (i.e. proportions of crop acreages) to AWD variations were quantified based on traditional methods and numerical experiment (i.e. a series calculation of AWD based on different input data). Results indicated that AWD decreased during 1960–1988 at a rate of 2.76 mm/year and then started to increase at a high rate of 9.47 mm/year during 1989–2015. For the first period (1960–1988), wind speed (uz), maximum humidity (RHmax) and sunshine duration (n) were the most important factors leading to decreased AWD, while for the second period the evolution of planting structure was the most significant factor resulting in the rapid increase of AWD, followed by the minimum temperature (Tmin), uz and RHmax. The evolution of planting structure alone would lead to an increase rate for AWD of 7.1 mm/year while the climatic factor would result in an increase rate of 1.9 mm/year during 1989–2015.

Keywords

Attribution analysisClimate changeCrop water requirementEvapotranspirationPenman–Monteith
Type
Climate Change and Agriculture Research Paper
Information
The Journal of Agricultural Science , Volume 156 , Issue 3 , April 2018 , pp. 301 - 311
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Copyright
Copyright © Cambridge University Press 2018 

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References

Acharjee, TK et al. (2017) Declining trends of water requirements of dry season Boro rice in the north-west Bangladesh. Agricultural Water Management 180, 148–159.Google Scholar
Allen, RG et al. (1998) Crop Evapotranspiration – Guidelines for Computing Crop Water Requirements. FAO Irrigation and drainage paper No. 56. Rome, Italy: FAO.Google Scholar
Allen, RG et al. (2005) FAO-56 dual crop coefficient method for estimating evaporation from soil and application extensions. Journal of Irrigation and Drainage Engineering 131, 2–13.Google Scholar
Calera, A et al. (2017) Remote sensing for crop water management: from ET modelling to services for the end users. Sensors 17, E1104.Google Scholar
Chen, Y (2015) Ecological Protection and Sustainable Management of the Tarim River Basin. Beijing, China: Science Press.Google Scholar
Chen, Y, Ye, Z and Shen, Y (2011) Desiccation of the Tarim river, Xinjiang, China, and mitigation strategy. Quaternary International 244, 264–271.CrossRefGoogle Scholar
Chen, F et al. (2009) Rapid warming in mid-latitude Central Asia for the past 100 years. Frontiers of Earth Science in China 3, 42. https://doi.org/10.1007/s11707-009-0013-9.Google Scholar
Chen, Y et al. (2016) Water and ecological security: dealing with hydroclimatic challenges at the heart of China's silk road. Environmental Earth Sciences 75, 881. https://doi.org/10.1007/s12665-016-5385-z.CrossRefGoogle Scholar
Chen, X et al. (2017) Ecological effect evaluation of comprehensive control project in Tarim River Basin. Bulletin of Chinese Academy of Sciences 32, 20–28.Google Scholar
Deng, M (2016) Prospecting development of south Xinjiang: water strategy and problem of Tarim River Basin. Arid Land Geography 39, 1–11.Google Scholar
Döll, P (2002) Impact of climate change and variability on irrigation requirements: a global perspective. Climatic Change 54, 269–293.Google Scholar
Fan, J et al. (2016) Climate change effects on reference crop evapotranspiration across different climatic zones of China during 1956–2015. Journal of Hydrology 542, 923–937.Google Scholar
Fang, G et al. (2017) Impact of GCM structure uncertainty on hydrological processes in an arid area of China. Hydrology Research, nh2017227. Doi: 10.2166/nh.2017.227.Google Scholar
Guo, D, Westra, S and Maier, HR (2016) An R package for modelling actual, potential and reference evapotranspiration. Environmental Modelling & Software 78, 216–224.Google Scholar
Gao, G et al. (2006) Spatial and temporal variations and controlling factors of potential evapotranspiration in China 1956–2000. Journal of Geographical Sciences 16, 3–12.Google Scholar
Guo, B et al. (2015) Risk assessment of regional irrigation water demand and supply in an arid inland river basin of northwestern China. Sustainability 7, 12958–12973.Google Scholar
Han, DM et al. (2017) Effects of climate change on spring wheat phenophase and water requirement in Heihe River Basin, China. Journal of Earth System Science 126, 9.Google Scholar
Huo, Z et al. (2013) Effect of climate change on reference evapotranspiration and aridity index in arid region of China. Journal of Hydrology 492, 24–34.Google Scholar
IPCC (2013) Climate Change 2013 – The Physical Science Basis. Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge and New York: Cambridge University Press.Google Scholar
Karandish, F, Kalanaki, M and Saberali, SF (2017) Projected impacts of global warming on cropping calendar and water requirement of maize in a humid climate. Archives of Agronomy and Soil Science 63, 1–13.Google Scholar
Konzmann, M, Gerten, D and Heinke, J (2013) Climate impacts on global irrigation requirements under 19 GCMs, simulated with a vegetation and hydrology model. Hydrological Sciences Journal 58, 88–105.Google Scholar
Li, Z et al. (2014) Potential evapotranspiration and its attribution over the past 50 years in the arid region of northwest China. Hydrological Processes 28, 1025–1031.Google Scholar
Li, C et al. (2017 a) Spatial and temporal evolution of climatic factors and its impacts on potential evapotranspiration in loess plateau of northern Shaanxi, China. Science of the Total Environment 589, 165–172.Google Scholar
Li, Z et al. (2017 b) Multivariate assessment and attribution of droughts in Central Asia. Scientific Reports 7, 1316.Google Scholar
Liang, L, Li, L and Liu, Q (2011) Spatio-temporal variations of reference crop evapotranspiration and pan evaporation in the west Songnen plain of China. Hydrological Sciences Journal 56, 1300–1313.Google Scholar
Liu, B et al. (2004) Taking China's temperature: daily range, warming trends, and regional variations, 1955–2000. Journal of Climate 17, 4453–4462.Google Scholar
McCuen, RH (1974) A sensitivity and error analysis CF procedures used for estimating evapotration. JAWRA Journal of the American Water Resources Association 10, 486–497.Google Scholar
McMahon, TA et al. (2013) Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis. Hydrology and Earth System Sciences 17, 1331–1363.Google Scholar
Mo, X et al. (2009) Regional crop yield, water consumption and water use efficiency and their responses to climate change in the north China plain. Agriculture, Ecosystems & Environment 134, 67–78.Google Scholar
Mo, X et al. (2017) Sensitivity of terrestrial water and carbon fluxes to climate variability in semi-humid basins of Haihe River, China. Ecological Modelling 353, 117–128.Google Scholar
Mosaedi, A et al. (2017) Sensitivity analysis of monthly reference crop evapotranspiration trends in Iran: a qualitative approach. Theoretical and Applied Climatology 128, 857–873.Google Scholar
Rodríguez Díaz, JA et al. (2007) Climate change impacts on irrigation water requirements in the Guadalquivir river basin in Spain. Regional Environmental Change 7, 149–159.Google Scholar
Sen, PK (1968) Estimates of the regression coefficient based on Kendall's tau. Journal of the American Statistical Association 63, 1379–1389.Google Scholar
Shen, Y and Chen, Y (2010) Global perspective on hydrology, water balance, and water resources management in arid basins. Hydrological Processes 24, 129–135.Google Scholar
Shen, Y et al. (2013) Estimation of regional irrigation water requirement and water supply risk in the arid region of northwestern China 1989–2010. Agricultural Water Management 128, 55–64.Google Scholar
Sherwood, S and Fu, Q (2014) A drier future? Science 343, 737–739.CrossRefGoogle ScholarPubMed
Statistical Bureau of Xinjiang Uygur Autonomous Region (1989–2016) Xinjiang Statistical Yearbooks. Beijing, China: China Statistics Press. Available at http://tongji.cnki.net/overseas/engnavi/YearBook.aspx?id=N2011100020&floor=1 (Accessed 4 April 2018).Google Scholar
Tabari, H and Talaee, PH (2014) Sensitivity of evapotranspiration to climatic change in different climates. Global and Planetary Change 115, 16–23.CrossRefGoogle Scholar
Toureiro, C et al. (2017) Irrigation management with remote sensing: evaluating irrigation requirement for maize under Mediterranean climate condition. Agricultural Water Management 184, 211–220.Google Scholar
Wang, Z et al. (2015) Jujube drip irrigation water consumption and its crop coefficient in oasis of arid areas. Xinjiang Agricultural Sciences 52, 675–680, [In Chinese with English Abstract].Google Scholar
Wild, M, Grieser, J and Schär, C (2008) Combined surface solar brightening and increasing greenhouse effect support recent intensification of the global land-based hydrological cycle. Geophysical Research Letters 35, L17706. https://doi.org/10.1029/2008GL034842.Google Scholar
Yin, Y et al. (2008) Radiation calibration of FAO56 Penman-Monteith model to estimate reference crop evapotranspiration in China. Agricultural Water Management 95, 77–84.Google Scholar
Zhai, P et al. (2005) Trends in total precipitation and frequency of daily precipitation extremes over China. Journal of Climate 18, 1096–1108.Google Scholar
Zhang, S, Gao, X and Zhang, X (2015) Glacial runoff likely reached peak in the mountainous areas of the Shiyang River Basin, China. Journal of Mountain Science 12, 382–395.Google Scholar
Zhang, L, Zhang, N and Ma, Y (2010) Study on water use of walnut trees under drip irrigation. Modern Agricultural Sciences and Technology 2010–21, 117–121, [In Chinese with English Abstract].Google Scholar
Zhang, J et al. (2016) Dependence of trends in and sensitivity of drought over China (1961–2013) on potential evaporation model. Geophysical Research Letters 43, 206–213.Google Scholar
Zwart, SJ and Bastiaanssen, WGM (2004) Review of measured crop water productivity values for irrigated wheat, rice, cotton and maize. Agricultural Water Management 69, 115–133.Google Scholar