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Irrigation, Damming, and Streamflow Fluctuations Irrigation, damming, and streamflow fluctuations of the Yellow River Zun Yin, Catherine Ottle, Philippe Ciais, Feng Zhou, Xuhui Wang, Polcher Jan, Patrice Dumas, Shushi Peng, Laurent Li, Xudong Zhou, et al. To cite this version: Zun Yin, Catherine Ottle, Philippe Ciais, Feng Zhou, Xuhui Wang, et al.. Irrigation, damming, and streamflow fluctuations of the Yellow River. Hydrology and Earth System Sciences, European Geosciences Union, 2021, 25 (3), pp.1133-1150. 10.5194/hess-25-1133-2021. hal-03171222 HAL Id: hal-03171222 https://hal.archives-ouvertes.fr/hal-03171222 Submitted on 17 Mar 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Distributed under a Creative Commons Attribution - NoDerivatives| 4.0 International License Hydrol. Earth Syst. Sci., 25, 1133–1150, 2021 https://doi.org/10.5194/hess-25-1133-2021 © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. Irrigation, damming, and streamflow fluctuations of the Yellow River Zun Yin1,2,a, Catherine Ottlé1, Philippe Ciais1, Feng Zhou3, Xuhui Wang3, Polcher Jan2, Patrice Dumas4, Shushi Peng3, Laurent Li2, Xudong Zhou2,5,6, Yan Bo3, Yi Xi3, and Shilong Piao4 1Laboratoire des Sciences du Climat et de l’Environnement, IPSL, CNRS-CEA-UVSQ, Gif-sur-Yvette, France 2Laboratoire de Météorologie Dynamique, IPSL UPMC/CNRS, Paris 75005, France 3Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China 4Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Avenue Agropolis, 34398 Montpellier CEDEX 5, France 5Institute of Industrial Science, University of Tokyo, Tokyo, Japan 6State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Center for Global Change and Water Cycle, Hohai University, Nanjing 210098, China apresent address: Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, New Jersey, USA Correspondence: Zun Yin ([email protected]) Received: 8 January 2020 – Discussion started: 16 April 2020 Revised: 5 January 2021 – Accepted: 10 January 2021 – Published: 5 March 2021 Abstract. The streamflow of the Yellow River (YR) is eration does not change the mean streamflows in our model, strongly affected by human activities like irrigation and but it impacts streamflow seasonality, more than the seasonal dam operation. Many attribution studies have focused on change of precipitation. By only considering generic opera- the long-term trends of streamflows, yet the contributions tion schemes, our dam model is able to reproduce the water of these anthropogenic factors to streamflow fluctuations storage changes of the two large reservoirs, LongYangXia have not been well quantified with fully mechanistic mod- and LiuJiaXia (correlation coefficient of ∼ 0.9). Moreover, els. This study aims to (1) demonstrate whether the mech- other commonly neglected factors, such as the large opera- anistic global land surface model ORCHIDEE (ORganiz- tion contribution from multiple medium/small reservoirs, the ing Carbon and Hydrology in Dynamic EcosystEms) is able dominance of large irrigation districts for streamflows (e.g., to simulate the streamflows of this complex rivers with hu- the Hetao Plateau), and special management policies dur- man activities using a generic parameterization for human ing extreme years, are highlighted in this study. Related pro- activities and (2) preliminarily quantify the roles of irriga- cesses should be integrated into models to better project fu- tion and dam operation in monthly streamflow fluctuations ture YR water resources under climate change and optimize of the YR from 1982 to 2014 with a newly developed ir- adaption strategies. rigation module and an offline dam operation model. Val- idations with observed streamflows near the outlet of the YR demonstrated that model performances improved notably with incrementally considering irrigation (mean square er- 1 Introduction ror (MSE) decreased by 56.9 %) and dam operation (MSE decreased by another 30.5 %). Irrigation withdrawals were More than 60 % of all rivers in the world are disturbed by hu- found to substantially reduce the river streamflows by ap- man activities (Grill et al., 2019), contributing altogether to proximately 242:8 ± 27:8 × 108 m3 yr−1 in line with inde- approximately 63 % of surface water withdrawal (Hanasaki pendent census data (231:4 ± 31:6 × 108 m3 yr−1). Dam op- et al., 2018). River water is used for agriculture, industry, drinking water supply, and electricity generation (Hanasaki Published by Copernicus Publications on behalf of the European Geosciences Union. 1134 Z. Yin et al.: Impacts of irrigation and damming on Yellow River streamflows et al., 2018; Wada et al., 2014), these usages being influenced and Tang et al.(2008). Yet, Jia et al.(2006) prescribed cen- by direct anthropogenic drivers and by climate change (Had- sus irrigation and dam operation data as input of their model. deland et al., 2014; Piao et al., 2007, 2010; Yin et al., 2020; Tang et al.(2008) included irrigation as a mechanism in Zhou et al., 2020). In order to meet the fast-growing wa- their DBH (distributed biosphere hydrological) model and ter demand in populated areas and to control floods (Wada investigated the long-term trends of streamflows, but they et al., 2014), reservoirs have been built for regulating the described the irrigation demand simply from satellite leaf temporal distribution of river water (Biemans et al., 2011; area data, so that crop plant water requirements and phenol- Hanasaki et al., 2006), leading to a massive perturbation of ogy were not represented by physical laws. Several global the seasonality and year-to-year variations of streamflows. In hydrological models (GHMs) simulated both irrigation and the midlatitude–northern latitude regions, where a decrease dam operation processes and were applied for future projec- of rainfall is observed historically and projected by climate tion of water resources regionally (Liu et al., 2019) or glob- models (IPCC, 2014), water scarcity will be further exacer- ally (Hanasaki et al., 2018; Wada et al., 2014, 2016). Those bated by the growth of water demand (Hanasaki et al., 2013) global GHM studies acknowledged the complex situation of and by the occurrence of more frequent extreme droughts the YRB where models’ performances are limited, but none (Seneviratne et al., 2014; Sherwood and Fu, 2014; Zscheis- has focused on the sources of error or potential overlooked chler et al., 2018). Thus, adapting river management is a mechanisms in this catchment. crucial question for sustainable development, which requires To model present water resources in the YRB and make comprehensive understanding of the impacts of human ac- future projections, not only natural mechanisms, but also an- tivities on river flow dynamics„ particularly in regions under thropogenic ones must be represented in a model. If a key high water stress (Liu et al., 2017; Wada et al., 2016). mechanism is missing in a model, a calibration of its pa- The Yellow River (YR) is the second longest river in rameters to match observations can compensate for structural China. It flows across arid, semi-arid, and semi-humid re- biases, and projections may be erroneous. For example, the gions, and the catchment contains intensive agricultural HBV model (Hydrologiska Byråns Vattenbalansavdelning) zones and has a population of 107 million inhabitants (Piao was well calibrated with different approaches in 156 catch- et al., 2010). With 2.6 % of total water resources in China, the ments in Austria but failed in predicting streamflow changes Yellow River basin (YRB) irrigates 9.7 % of the croplands due to climate warming (Duethmann et al., 2020), one of the (http://www.yrcc.gov.cn, last access: 28 February 2021). Un- key reasons being that the response of vegetation to climate derground water resources are used in the YRB, but they change was missing in the model. In this study, we inte- only account for 10.3 % of total water resources, outlining grate two key anthropogenic processes (irrigation and dam the importance of streamflow water for regional water use. operation) in the land surface model ORCHIDEE (ORganiz- A special feature of the YRB is the huge spatiotemporal ing Carbon and Hydrology in Dynamic EcosystEms), which variation of its water balance. Precipitation is concentrated has a mechanistic description of plant–climate and soil wa- in the flooding season (from July to October) which consti- ter availability interactions and of river streamflows. Through tutes ∼ 60 % of the annual discharge, whereas the dry season a set of simulations with generic parameter values, we aim (from March to June) represents only ∼ 10 %–20 %. Numer- to preliminarily diagnose how irrigation and dam operation ous dams have been built to regulate the streamflows intra- improve the simulations of observed YRB streamflows. Af- and inter-annually in order to control floods and alleviate wa- ter making sure we understand the impact of adding these ter scarcity (Liu et al., 2015; Zhuo et al., 2019). The YRB two new and crucial processes, the model will be calibrated streamflows are thus highly controlled by human water with- against a suite of observations so that it can be applied for drawals and dam operations, making it difficult to separate future projections. the impacts of human and natural factors on the variability Using a standard version of ORCHIDEE without irrigation and trends. or dams, Xi et al.(2018) performed simulations with a 0.1 ◦ Numerous studies documented the effects of anthro- hypo-resolution atmospheric forcing over China (Chen et al., pogenic factors on streamflows and water resources in the 2011).
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