Estimating Growing Season Evapotranspiration and Transpiration of Major Crops over a Large Irrigation District from HJ-1A/1B Data Using a Remote Sensing-Based Dual Source Evapotranspiration Model

Remote Sensing - Tập 12 Số 5 - Trang 865
Bing Yu1, Songhao Shang1
1State Key Laboratory of Hydro-science and Engineering, Tsinghua University, Beijing, 100084, China

Tóm tắt

Crop evapotranspiration (ET) is the largest water consumer of agriculture water in an irrigation district. Remote sensing (RS) technique has provided an effective way to map regional ET using various RS-based ET models over the past several decades. To map growing season ET of different crops and partition ET into evaporation (E) and transpiration (T) at regional scale, appropriate ET models should be further integrated with crop distribution maps in different years and crop growing seasons determined for each crop pixel. In this study, a hybrid dual-source scheme and trapezoid framework-based ET Model (HTEM) fed with HJ-1A/1B data was applied in Hetao Irrigation District (HID) of China from 2009 to 2015 to map crop growing season ET and T at 30 m resolution. The HTEM model with HJ-1A/1B data performed well in estimating ET in HID, and the finer spatial resolution of model input data can improve the estimation accuracy of ET. Combined with the annual crop planting map identified in previous study, and crop growing seasons determined from fitted Normalized Difference Vegetation Index (NDVI) curves for crop pixels, the spatial and temporal variations of growing season ET and T of major crops (maize and sunflower) were examined. The results indicate that ET and T of maize and sunflower reach their minimum values in the southwest HID with smaller crop planting density, and reach their maximum values in northwest HID with higher crop planting density. Over the study period with a decreasing trend of available irrigation water, ET and T in maize and sunflower growing seasons show decreasing trends, while ratios of T/ET show increasing trends, which implies that the adverse effect of decreased irrigation water diversion on crop growth is diminished due to the favorable portioning of E and T in cropland of HID. In addition, the calculation results of crop coefficients show that there is water stress to crop growth in the study area. The present results are helpful to better understand the spatial pattern of crop water consumption and water stress of different crops during crop growing season, and provide the basis for optimizing the spatial distribution of crop planting with less water consumption and more crop yield.

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Tài liệu tham khảo

Kang, 2017, Improving agricultural water productivity to ensure food security in China under changing environment: From research to practice, Agric. Water Manag., 179, 5, 10.1016/j.agwat.2016.05.007

Cao, 2012, Analysis on temporal and spatial differences of water productivity in irrigation districts in China, Trans. Chin. Soc. Agric. Eng., 28, 1

Vorosmarty, 2000, Global Water Resources: Vulnerability from Climate Change and Population Growth, Science, 289, 284, 10.1126/science.289.5477.284

Rosegrant, M.W., Ringler, C., and Gerpacio, R.V. (1997). Water and land resources and global food supply. Food Security, Diversification and Resource Management: Refocusing the Role of Agriculture? Proceedings of the Twenty-Third International Conference of Agricultural Economists, Sacramento, CA, USA, 10–16 August 1997, Routledge.

Koksal, 2018, Crop Evapotranspiration estimations of red pepper using field level remote sensing data and energy balance, Pol. J. Environ. Stud., 28, 165, 10.15244/pjoes/85351

Yu, 2019, Mapping daily evapotranspiration over a large irrigation district from MODIS data using a novel hybrid dual-source coupling model, Agric. For. Meteorol., 276, 107612, 10.1016/j.agrformet.2019.06.011

Yi, Z., Zhao, H., Jiang, Y., Yan, H., Cao, Y., Huang, Y., and Hao, Z. (2018). Daily Evapotranspiration estimation at the field scale: Using the modified SEBS model and HJ-1 data in a desert-oasis area, Northwestern China. Water, 10.

Grosso, C., Manoli, G., Martello, M., Chemin, Y., Pons, D., Teatini, P., Piccoli, L., and Morari, F. (2018). Mapping maize evapotranspiration at field scale using SEBAL: A comparison with the FAO method and soil-plant model simulations. Remote Sens., 10.

Holland, 2013, Micro-Bowen ratio system for measuring evapotranspiration in a vineyard interrow, Agric. For. Meteorol., 177, 93, 10.1016/j.agrformet.2013.04.009

Bowen, 1926, The ratio of heat losses by conduction and by evaporation from any water surface, Phys. Rev., 27, 779, 10.1103/PhysRev.27.779

Wang, 2015, Comparing evapotranspiration from eddy covariance measurements, water budgets, remote sensing, and land surface models over Canada, J. Hydrometeorol., 16, 1540, 10.1175/JHM-D-14-0189.1

Wilson, 2002, Energy balance closure at FLUXNET sites, Agric. For. Meteorol., 113, 223, 10.1016/S0168-1923(02)00109-0

Bai, 2015, Characterizing the footprint of eddy covariance system and large aperture scintillometer measurements to validate satellite-based surface fluxes, IEEE Geosci. Remote Sens. Lett., 12, 943, 10.1109/LGRS.2014.2368580

Kang, 2003, Crop coefficient and ratio of transpiration to evapotranspiration of winter wheat and maize in a semi-humid region, Agric. Water Manag., 59, 239, 10.1016/S0378-3774(02)00150-6

Cheng, J., and Kustas, W. (2019). Using very high resolution thermal infrared imagery for more accurate determination of the impact of land cover differences on evapotranspiration in an irrigated agricultural area. Remote Sens., 11.

Allen, 2006, A recommendation on standardized surface resistance for hourly calculation of reference ETo by the FAO56 Penman-Monteith method, Agric. Water Manag., 81, 1, 10.1016/j.agwat.2005.03.007

Allen, R.G., Pereira, L.S., Raes, D., and Smith, M. (1998). FAO Irrigation and Drainage Paper No. 56, Food and Agriculture Organization of the United Nations.

Ren, 2016, Modeling and assessing field irrigation water use in a canal system of Hetao, upper Yellow River basin: Application to maize, sunflower and watermelon, J. Hydrol., 532, 122, 10.1016/j.jhydrol.2015.11.040

Ren, 2019, Hydrological complexities in irrigated agro-ecosystems with fragmented land cover types and shallow groundwater: Insights from a distributed hydrological modeling method, Agric. Water Manag., 213, 868, 10.1016/j.agwat.2018.12.011

Xue, 2016, Evaluation of crop water productivity under sprinkler irrigation regime using a distributed agro-hydrological model in an irrigation district of China, Agric. Water Manag., 178, 350, 10.1016/j.agwat.2016.10.003

Yang, 2012, Development of a soil-plant-atmosphere continuum model (HDS-SPAC) based on hybrid dual-source approach and its verification in wheat field, Sci. China-Technol. Sci., 55, 2671, 10.1007/s11431-012-4974-7

Ren, 2018, Growth responses of crops and natural vegetation to irrigation and water table changes in an agro-ecosystem of Hetao, upper Yellow River basin: Scenario analysis on maize, sunflower, watermelon and tamarisk, Agric. Water Manag., 199, 93, 10.1016/j.agwat.2017.12.021

He, R., Jin, Y., Kandelous, M., Zaccaria, D., Sanden, B., Snyder, R., Jiang, J., and Hopmans, J. (2017). Evapotranspiration estimate over an almond orchard using landsat satellite observations. Remote Sens., 9.

French, A., Hunsaker, D., Bounoua, L., Karnieli, A., Luckett, W., and Strand, R. (2018). Remote sensing of evapotranspiration over the central Arizona irrigation and drainage district, USA. Agronomy, 8.

Gowda, 2007, ET mapping for agricultural water management: Present status and challenges, Irrig. Sci., 26, 223, 10.1007/s00271-007-0088-6

Bastiaanssen, 1998, A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation, J. Hydrol., 212, 198, 10.1016/S0022-1694(98)00253-4

Norman, 1995, Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface-temperature, Agric. For. Meteorol., 77, 263, 10.1016/0168-1923(95)02265-Y

Yang, 2013, A hybrid dual-source scheme and trapezoid framework-based evapotranspiration model (HTEM) using satellite images: Algorithm and model test, J. Geophys. Res. Atmos., 118, 2284, 10.1002/jgrd.50259

Yang, 2015, Comparison of three dual-source remote sensing evapotranspiration models during the MUSOEXE-12 campaign: Revisit of model physics, Water Resour. Res., 51, 3145, 10.1002/2014WR015619

Bai, 2017, Responses of field evapotranspiration to the changes of cropping pattern and groundwater depth in large irrigation district of Yellow River basin, Agric. Water Manag., 188, 1, 10.1016/j.agwat.2017.03.028

Schmitter, 2015, Contributions of lateral flow and groundwater to the spatio-temporal variation of irrigated rice yields and water productivity in a West-African inland valley, Agric. Water Manag., 152, 286, 10.1016/j.agwat.2015.01.014

Singh, 2010, Rising water table: A threat to sustainable agriculture in an irrigated semi-arid region of Haryana, India, Agric. Water Manag., 97, 1443, 10.1016/j.agwat.2010.04.010

Tan, 2006, Land fragmentation and its driving forces in China, Land Use Pol., 23, 272, 10.1016/j.landusepol.2004.12.001

Zhong, 2016, Automated mapping of soybean and corn using phenology, ISPRS-J. Photogramm. Remote Sens., 119, 151, 10.1016/j.isprsjprs.2016.05.014

Chen, 2016, Impacts of spatial heterogeneity on crop area mapping in Canada using MODIS data, ISPRS-J. Photogramm. Remote Sens., 119, 451, 10.1016/j.isprsjprs.2016.07.007

Yu, 2017, Multi-year mapping of maize and sunflower in Hetao Irrigation District of China with high spatial and temporal resolution vegetation index series, Remote Sens., 9, 855, 10.3390/rs9080855

Yang, 2012, Remote sensing temporal and spatial patterns of evapotranspiration and the responses to water management in a large irrigation district of North China, Agric. For. Meteorol., 164, 112, 10.1016/j.agrformet.2012.05.011

Piao, 2006, Variations in satellite-derived phenology in China’s temperate vegetation, Glob. Chang. Biol., 12, 672, 10.1111/j.1365-2486.2006.01123.x

Cong, 2012, Spring vegetation green-up date in China inferred from SPOT NDVI data: A multiple model analysis, Agric. For. Meteorol., 165, 104, 10.1016/j.agrformet.2012.06.009

Yang, 2015, Changes in autumn vegetation dormancy onset date and the climate controls across temperate ecosystems in China from 1982 to 2010, Glob. Chang. Biol., 21, 652, 10.1111/gcb.12778

Chen, 2018, Impact of agricultural water-saving practices on regional evapotranspiration: The role of groundwater in sustainable agriculture in arid and semi-arid areas, Agric. For. Meteorol., 263, 156, 10.1016/j.agrformet.2018.08.013

Jiang, 2016, Mapping interannual variability of maize cover in a large irrigation district using a vegetation index – phenological index classifier, Comput. Electron. Agric., 123, 351, 10.1016/j.compag.2016.03.008

Yu, B., and Shang, S. (2018). Multi-Year Mapping of Major Crop Yields in an Irrigation District from High Spatial and Temporal Resolution Vegetation Index. Sensors, 18.

Wang, 2012, Technical system design and construction of China’s HJ-1 satellites, Int. J. Digit. Earth, 5, 202, 10.1080/17538947.2012.658684

Li, Z. (2014). Based on HJ-1A/1B Data of Real Water-Saving Potential Analysis to Hetao Irrigation in Inner Mongolia, Inner Mongolia Agriculture University.

Pan, 2015, Mapping crop phenology using NDVI time-series derived from HJ-1 A/B data, Int. J. Appl. Earth Obs. Geoinform., 34, 188

Parplies, 2016, Phenomapping of rangelands in South Africa using time series of RapidEye data, Int. J. Appl. Earth Obs. Geoinform., 53, 90

Royo, 2004, Leaf and green area development of durum wheat genotypes grown under Mediterranean conditions, Eur. J. Agron., 20, 419, 10.1016/S1161-0301(03)00058-3

Li, 2005, Utility of remote sensing-based two-source energy balance model under low- and high-vegetation cover conditions, J. Hydrometeorol., 6, 878, 10.1175/JHM464.1

Norman, 2003, Remote sensing of surface energy fluxes at 101-m pixel resolutions, Water Resour. Res., 39, 1221, 10.1029/2002WR001775

Kustas, 2008, Modelling surface energy fluxes over maize using a two-source patch model and radiometric soil and canopy temperature observations, Remote Sens. Environ., 112, 1130, 10.1016/j.rse.2007.07.018

Long, 2012, Deriving theoretical boundaries to address scale dependencies of triangle models for evapotranspiration estimation, J. Geophys. Res. Atmos., 117, D017079

Carlson, 2007, An overview of the “triangle method” for estimating surface evapotranspiration and soil moisture from satellite imagery, Sensors, 7, 1612, 10.3390/s7081612

Allen, 2007, Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)—Model, J. Irrig. Drain. Eng., 133, 380, 10.1061/(ASCE)0733-9437(2007)133:4(380)

Li, 2008, Estimation of water consumption and crop water productivity of winter wheat in North China Plain using remote sensing technology, Agric. Water Manag., 95, 1271, 10.1016/j.agwat.2008.05.003

Yang, 2013, Modeling evapotranspiration and its partitioning over a semiarid shrub ecosystem from satellite imagery: A multiple validation, J. Appl. Remote Sens., 7, 073495, 10.1117/1.JRS.7.073495

Dai, 2011, Determination of crop coefficients of main grain and oil crops in Inner Mongolia Hetao irrigated area, J. Irrig. Drain., 30, 23

Šimůnek, J., Šejna, M., Saito, H., Sakai, M., and van Genuchten, M.T. (2009). The HYDRUS-1D Software Package for Simulating the Movement of Water, Heat, and Multiple Solutes in Variably Saturated Media, Version 4.0: HYDRUS Software Series 3, Department of Environmental Sciences, University of California Riverside.

Moriasi, 2007, Model evaluation guidelines for systematic quantification of accuracy in watershed simulations, Trans. ASABE, 50, 885, 10.13031/2013.23153

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Remote Sensing

Tập 12 Số 5

865

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