Evaluation of water productivity under climate change in irrigated areas of the arid Northwest China using an assemble statistical downscaling method and an agro-hydrological model

The Heihe River Basin (HRB) is the second largest inland river basin, located in the arid region of Northwest China with a serious water shortage. Evaluation of water productivity will provide scientific implications for agricultural water-saving in irrigated areas of the arid region under clima...

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Main Authors: L. Liu, Z. Guo, G. Huang
Format: Article
Language:English
Published: Copernicus Publications 2018-06-01
Series:Proceedings of the International Association of Hydrological Sciences
Online Access:https://www.proc-iahs.net/379/393/2018/piahs-379-393-2018.pdf
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spelling doaj-b6ee9fa09901453d958b311426f2d5762020-11-24T23:10:44ZengCopernicus PublicationsProceedings of the International Association of Hydrological Sciences2199-89812199-899X2018-06-0137939340210.5194/piahs-379-393-2018Evaluation of water productivity under climate change in irrigated areas of the arid Northwest China using an assemble statistical downscaling method and an agro-hydrological modelL. Liu0L. Liu1Z. Guo2Z. Guo3G. Huang4G. Huang5College of Water Resources & Civil Engineering, China Agricultural University, Beijing 100083, ChinaCenter for Agricultural Water Research in China, China Agricultural University, Beijing 100083, ChinaCollege of Water Resources & Civil Engineering, China Agricultural University, Beijing 100083, ChinaCenter for Agricultural Water Research in China, China Agricultural University, Beijing 100083, ChinaCollege of Water Resources & Civil Engineering, China Agricultural University, Beijing 100083, ChinaCenter for Agricultural Water Research in China, China Agricultural University, Beijing 100083, ChinaThe Heihe River Basin (HRB) is the second largest inland river basin, located in the arid region of Northwest China with a serious water shortage. Evaluation of water productivity will provide scientific implications for agricultural water-saving in irrigated areas of the arid region under climate change. Based on observed meteorological data, 23 GCMs outputs and the ERA-40 reanalysis data, an assemble statistical downscaling model was developed to generate climate change scenarios under RCP2.6, RCP4.5, RCP8.5 respectively, which were then used to drive the SWAP-EPIC model to simulate crop growth in the irrigated areas of the middle HRB for the future period from 2018 to 2047. Crop yield showed an increasing trend, while crop water consumption decreased gradually in Gaotai and Ganzhou irrigated areas. The water productivity in future 30 years showed an increasing trend in both Gaotai and Ganzhou areas, with the most significant increase under RCP4.5 scenario, which were both larger than 2 kg m<sup>−3</sup>. Compared with that of the period from 2012 to 2015, the water productivity during 2018–2047 under three RCP scenarios increased by 9.2, 14.3 and 11.8 % in the Gaotai area, and 15.4, 21.6, 19.9 % in the Ganzhou area, respectively.https://www.proc-iahs.net/379/393/2018/piahs-379-393-2018.pdf
collection DOAJ
language English
format Article
sources DOAJ
author L. Liu
L. Liu
Z. Guo
Z. Guo
G. Huang
G. Huang
spellingShingle L. Liu
L. Liu
Z. Guo
Z. Guo
G. Huang
G. Huang
Evaluation of water productivity under climate change in irrigated areas of the arid Northwest China using an assemble statistical downscaling method and an agro-hydrological model
Proceedings of the International Association of Hydrological Sciences
author_facet L. Liu
L. Liu
Z. Guo
Z. Guo
G. Huang
G. Huang
author_sort L. Liu
title Evaluation of water productivity under climate change in irrigated areas of the arid Northwest China using an assemble statistical downscaling method and an agro-hydrological model
title_short Evaluation of water productivity under climate change in irrigated areas of the arid Northwest China using an assemble statistical downscaling method and an agro-hydrological model
title_full Evaluation of water productivity under climate change in irrigated areas of the arid Northwest China using an assemble statistical downscaling method and an agro-hydrological model
title_fullStr Evaluation of water productivity under climate change in irrigated areas of the arid Northwest China using an assemble statistical downscaling method and an agro-hydrological model
title_full_unstemmed Evaluation of water productivity under climate change in irrigated areas of the arid Northwest China using an assemble statistical downscaling method and an agro-hydrological model
title_sort evaluation of water productivity under climate change in irrigated areas of the arid northwest china using an assemble statistical downscaling method and an agro-hydrological model
publisher Copernicus Publications
series Proceedings of the International Association of Hydrological Sciences
issn 2199-8981
2199-899X
publishDate 2018-06-01
description The Heihe River Basin (HRB) is the second largest inland river basin, located in the arid region of Northwest China with a serious water shortage. Evaluation of water productivity will provide scientific implications for agricultural water-saving in irrigated areas of the arid region under climate change. Based on observed meteorological data, 23 GCMs outputs and the ERA-40 reanalysis data, an assemble statistical downscaling model was developed to generate climate change scenarios under RCP2.6, RCP4.5, RCP8.5 respectively, which were then used to drive the SWAP-EPIC model to simulate crop growth in the irrigated areas of the middle HRB for the future period from 2018 to 2047. Crop yield showed an increasing trend, while crop water consumption decreased gradually in Gaotai and Ganzhou irrigated areas. The water productivity in future 30 years showed an increasing trend in both Gaotai and Ganzhou areas, with the most significant increase under RCP4.5 scenario, which were both larger than 2 kg m<sup>−3</sup>. Compared with that of the period from 2012 to 2015, the water productivity during 2018–2047 under three RCP scenarios increased by 9.2, 14.3 and 11.8 % in the Gaotai area, and 15.4, 21.6, 19.9 % in the Ganzhou area, respectively.
url https://www.proc-iahs.net/379/393/2018/piahs-379-393-2018.pdf
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