Quantifying net irrigation across the North China Plain through dual modelling of evapotranspiration

Author(s):  
Julian Koch ◽  
Simon Stisen ◽  
Xin He ◽  
Grith Martinsen

<p>Knowledge of irrigation water use is crucial for ensuring food and water security in water scarce regions. Even though irrigation is one of the most important direct human interferences with the terrestrial water cycle, there exists limited knowledge on the extent of irrigated areas and in particular the amount of water applied for irrigation. In this study, we develop a novel approach that estimates net water loss due to irrigation and apply it over the North China Plain domain, which is a global hotspot for severe groundwater depletion caused by extensive irrigation practices. Our goal is to retrieve spatio-temporal patterns of net irrigation amounts, constituted as evaporative loss of irrigated water, at monthly timescale at 1km<sup>2</sup> spatial resolution. The analysis is based on a direct comparison of two alternative evapotranspiration (ET) models: (1) A remote sensing based model (PT-JPL-thermal) using various MODIS products as input and (2) a one-dimensional, free drainage hydrological model (mHM). The hydrological model is purely driven by rainfall and will therefore naturally show a strong disagreement with the remote sensing based ET during periods of extensive irrigation. We use this systematic residual term that reflects a non-precipitation-based water source, as quantification of net irrigation. The hydrological model is calibrated against the remote sensing based ET at grids that are not affected by irrigation and discharge records representing natural flow. Total water storage anomalies retrieved by GRACE are utilized to evaluate the derived net irrigation amounts over the North China Plain. We find, that irrigation peaks in May, which corresponds to the peak of the growing season of winter wheat. Moreover total irrigation amounts to 116 mm per year (14km<sup>3</sup>), which is in good agreement with previous studies. The net irrigation estimates are at an unprecedented spatial and temporal resolution and are extremely valuable input for water resources management as well as for subsequent groundwater modelling where net irrigation can be utilized as pumping boundary condition.</p>

2020 ◽  
Vol 32 (1) ◽  
Author(s):  
Peifang Leng ◽  
Fadong Li ◽  
Kun Du ◽  
Zhao Li ◽  
Congke Gu ◽  
...  

Abstract Background Groundwater is typically over-saturated in CO2 with respect to atmospheric equilibrium. Irrigation with groundwater is a common agricultural practice in many countries, but little is known about the fate of dissolved inorganic carbon (DIC) in irrigation groundwater and its contribution to the CO2 emission inventory from land to the atmosphere. We performed a mesocosm experiment to study the fate of DIC entering agricultural drainage channels in the North China Plain. Specifically, we aimed to unravel the effect of flow velocity and nutrient on CO2 emissions. Results All treatments were emitting CO2. Approximately half of the DIC in the water was consumed by TOC production (1–16%), emitted to the atmosphere (14–20%), or precipitated as calcite (CaCO3) (14–20%). We found that DIC depletion was stimulated by nutrient addition, whereas more CO2 evasion occurred in the treatments without nutrients addition. On the other hand, about 50% of CO2 was emitted within the first 50 h under high flow velocity. Thus, in the short term, high nutrient levels may counteract CO2 emissions from drainage channels, whereas the final fate of the produced biomass (burial versus mineralization to CO2 or even CH4) determines the duration of the effect. Conclusion Our study reveals that both hydrology and biological processes affect CO2 emissions from groundwater irrigation channels. The estimated CO2 emission from total groundwater depletion in the North China Plain is up to 0.52 ± 0.07 Mt CO2 year−1. Thus, CO2 emissions from groundwater irrigation should be considered in regional CO2 budgets, especially given that groundwater depletion is expected to acceleration in the future.


2019 ◽  
Vol 29 (6) ◽  
pp. 891-908 ◽  
Author(s):  
Xifang Wu ◽  
Yongqing Qi ◽  
Yanjun Shen ◽  
Wei Yang ◽  
Yucui Zhang ◽  
...  

2015 ◽  
Vol 183 ◽  
pp. 31-42 ◽  
Author(s):  
Yi Zhao ◽  
XinPing Chen ◽  
ZhenLing Cui ◽  
David B. Lobell

2006 ◽  
Vol 82 (1-2) ◽  
pp. 25-44 ◽  
Author(s):  
Yonghui Yang ◽  
Masataka Watanabe ◽  
Xiying Zhang ◽  
Jiqun Zhang ◽  
Qinxue Wang ◽  
...  

2012 ◽  
Vol 2012 (3) ◽  
pp. 281-298 ◽  
Author(s):  
Wolfgang Koppe ◽  
Martin L. Gnyp ◽  
Simon D. Hennig ◽  
Fei Li ◽  
Yuxin Miao ◽  
...  

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