Variation of gross primary production, evapotranspiration and water use efficiency for global croplands

Ai, Zhipin; Wang, Qinxue; Yang, Yonghui; Manevski, Kiril; Yi, Shuang; Zhao, Xin

doi:10.1016/j.agrformet.2020.107935

Cited by 31 publications

(24 citation statements)

References 34 publications

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“…In addition, several factors reduce the prediction quality of surface parameters with ESTARFM, such as temporal variance, cloud coverage, spatial heterogeneity, and view angle effects. Comparing the observed ET or GPP with the estimated WUE based on a dataset from one site could bring uncertainties as a result of differences in the observation orientation and environmental conditions at a given in situ station [95]. In addition to the inherent uncertainties in the validation data of EC and GPP, the mismatched spatial locations between estimated ET, GPP, and EC measurements will also affect the accuracy [88,89].…”

Section: Resultsmentioning

confidence: 99%

“…In many regions around the world, cropland WUE is often applied to farmland to relieve the water resource pressure and improve its irrigation management [95]. Thus, water-saving irrigation aimed at maximizing the WUE of crops is regarded as the primary method to address water resource shortages.…”

Section: Spatial Characteristics Of Et Gpp and Wue For Midstream Oasis Agricultural Areasmentioning

confidence: 99%

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High-Resolution Monitoring and Assessment of Evapotranspiration and Gross Primary Production Using Remote Sensing in a Typical Arid Region

Jin

Zhang

et al. 2021

Land

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Land surface evapotranspiration (ET) and gross primary productivity (GPP) are critical components in terrestrial ecosystems with water and carbon cycles. Large-scale, high-resolution, and accurately quantified ET and GPP values are important fundamental data for freshwater resource management and help in understanding terrestrial carbon and water cycles in an arid region. In this study, the revised surface energy balance system (SEBS) model and MOD17 GPP algorithm were used to estimate daily ET and GPP at 100 m resolution based on multi-source satellite remote sensing data to obtain surface biophysical parameters and meteorological forcing data as input variables for the model in the midstream oasis area of the Heihe River Basin (HRB) from 2010 to 2016. Then, we further calculated the ecosystem water-use efficiency (WUE). We validated the daily ET, GPP, and WUE from ground observations at a crop oasis station and conducted spatial intercomparisons of monthly and annual ET, GPP, and WUE at the irrigation district and cropland oasis scales. The site-level evaluation results show that ET and GPP had better performance than WUE at the daily time scale. Specifically, the deviations in the daily ET, GPP, and WUE data compared with ground observations were small, with a root mean square error (RMSE) and mean absolute percent error (MAPE) of 0.75 mm/day and 26.59%, 1.13 gC/m2 and 36.26%, and 0.50 gC/kgH2O and 39.83%, respectively. The regional annual ET, GPP, and WUE varied from 300 to 700 mm, 200 to 650 gC/m2, and 0.5 to 1.0 gC/kgH2O, respectively, over the entire irrigation oasis area. It was found that annual ET and GPP were greater than 550 mm and 500 gC/m2, and annual oasis cropland WUE had strong invariability and was maintained at approximately 0.85 gC/kgH2O. The spatial intercomparisons from 2010 to 2016 revealed that ET had similar spatial patterns to GPP due to tightly coupled carbon and water fluxes. However, the WUE spatiotemporal patterns were slightly different from both ET and GPP, particularly in the early and late growing seasons for the oasis area. Our results demonstrate that spatial full coverage and reasonably fine spatiotemporal variation and variability could significantly improve our understanding of water-saving irrigation strategies and oasis agricultural water management practices in the face of water shortage issues.

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Section: Resultsmentioning

confidence: 99%

Section: Spatial Characteristics Of Et Gpp and Wue For Midstream Oasis Agricultural Areasmentioning

confidence: 99%

High-Resolution Monitoring and Assessment of Evapotranspiration and Gross Primary Production Using Remote Sensing in a Typical Arid Region

Jin

Zhang

et al. 2021

Land

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“…Second, we modified the algorithm for water stress that was used to regulate the radiation use efficiency. We took the ratio of actual evapotranspiration to potential evapotranspiration as the water stress factor for any point in the simulation, similar to the description of the soil moisture deficit used in other studies (Anderson et al, 2007;Yao et al, 2010). Third, we added a new output variable for the water consumption of Miscanthus and switchgrass to analyze the water consumption and WUE in the crop submodule.…”

Section: H08 and Its Crop Modulementioning

confidence: 99%

“…WUE is an important indicator that shows the efficiency of crops in using water to produce biomass (Ai et al, 2020), which is useful in evaluating bioenergy crop performance (Zeri et al, 2013). Here, WUE is calculated as the ratio of yield to water consumption:…”

Section: Water Use Efficiencymentioning

confidence: 99%

Simulating second-generation herbaceous bioenergy crop yield using the global hydrological model H08 (v.bio1)

Hanasaki

Heck

et al. 2020

Geosci. Model Dev.

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Abstract. Large-scale deployment of bioenergy plantations would have adverse effects on water resources. There is an increasing need to ensure the appropriate inclusion of the bioenergy crops in global hydrological models. Here, through parameter calibration and algorithm improvement, we enhanced the global hydrological model H08 to simulate the bioenergy yield from two dedicated herbaceous bioenergy crops: Miscanthus and switchgrass. Site-specific evaluations showed that the enhanced model had the ability to simulate yield for both Miscanthus and switchgrass, with the calibrated yields being well within the ranges of the observed yield. Independent country-specific evaluations further confirmed the performance of the H08 (v.bio1). Using this improved model, we found that unconstrained irrigation more than doubled the yield under rainfed condition, but reduced the water use efficiency (WUE) by 32 % globally. With irrigation, the yield in dry climate zones can exceed the rainfed yields in tropical climate zones. Nevertheless, due to the low water consumption in tropical areas, the highest WUE was found in tropical climate zones, regardless of whether the crop was irrigated. Our enhanced model provides a new tool for the future assessment of bioenergy–water tradeoffs.

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“…Since 1978, China has experienced rapid economic development, urbanization, and industrialization, resulting in extensive cropland losses that pose Responsible Editor: Philippe Garrigues a serious threat to food security (Chen 2007;Khan et al 2009). Compared to increasing cropland area, promoting productivity on existing cropland is considered a reasonable alternative for enhancing future grain-security (Ai et al 2020;Manevski et al 2017;Tilman et al 2011). Grain production is closely related to water resource availability and agricultural water use accounts for more than 60% of the gross of water withdrawals in China (NBS 2020b).…”

Section: Introductionmentioning

confidence: 99%

Spatial heterogeneity of changes in cropland ecosystem water use efficiency and responses to drought in China

Zhao

Cheng

et al. 2021

Environ Sci Pollut Res

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Understanding cropland ecosystem water use efficiency (eWUE) responses to drought is important for sustainable water resource management and food security. Today in China, the spatiotemporal patterns of eWUE and responses to drought across different cropland classes remain poorly quantified. In this study, we characterized the spatial temporal variability in cropland eWUE and response to drought in China from 1982 to 2017 using the satellite-retrieved evapotranspiration (ET), gross primary production (GPP), and self-calibrating Palmer Drought Severity Index (scPDSI), in conjunction with the Global Food Security-support Analysis Data product for Crop Dominance (GFSAD1KCD) data. Results indicated that (1) mean annual cropland eWUE had a spatial range from 0 to 9.94 g C kg -1 H 2 O, with higher values (2.06 g C kg -1 H 2 O) in class 4 (rainfed: wheat, rice, and soybeans dominant), whereas the lowest eWUE (1.58 g C kg -1 H 2 O) occurred in class 2 (irrigated mixed crop 1: wheat, rice, barley, and soybeans). ( 2) Annual eWUE, GPP, and ET values for croplands in China increased significantly between 1982 and 2017. Class 1 (irrigated wheat and rice) had the highest trend of 0.011 g C kg -1 H 2 O yr -1 , and class 6 (rainfed: corn and soybeans) had the lowest of 0.0007 g C kg -1 H 2 O yr -1 . Apart from class 4, annual GPP and ET were enhanced in most cropland classes from 1982 to 2017 (p<0.01). (3) Rainfed croplands generally had higher eWUE, GPP, and ET values than irrigated croplands. Except for rainfed cropland eWUE, all other cropland variables increased significantly (p<0.001) from 1982 to 2017. (4) Correlation analysis found that the 19.66% (15.62%) of cropland had significant negative (positive) correlations between eWUE and current-year scPDSI. The legacy effects of drought on cropland eWUE indicated that previous and current-year drought impacts on cropland eWUE were in the same direction. Our results provide insights into variability in cropland eWUE and its response to drought in China, where there is a growing demand for agricultural water resource management.

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Variation of gross primary production, evapotranspiration and water use efficiency for global croplands

Cited by 31 publications

References 34 publications

High-Resolution Monitoring and Assessment of Evapotranspiration and Gross Primary Production Using Remote Sensing in a Typical Arid Region

High-Resolution Monitoring and Assessment of Evapotranspiration and Gross Primary Production Using Remote Sensing in a Typical Arid Region

Simulating second-generation herbaceous bioenergy crop yield using the global hydrological model H08 (v.bio1)

Spatial heterogeneity of changes in cropland ecosystem water use efficiency and responses to drought in China

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