کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5770006 1629198 2017 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Satellite-based crop coefficient and evapotranspiration using surface soil moisture and vegetation indices in Northeast Asia
ترجمه فارسی عنوان
ضریب باردهی ماهواره ای و تبخیر تعرق با استفاده از شاخص های رطوبت خاک و شاخص های پوشش گیاهی در شمال شرقی آسیا
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
چکیده انگلیسی


- Satellite-based crop coefficient(Kc) and evapotranspiration (ET) were estimated.
- Two vegetation indices(VI) and soil moisture(SM) were reasonable for predicting Kc.
- SM and two VIs showed the highest impact on Kc in paddy and mixed forest, respectively.
- Satellite-based Kc showed good correspondence with flux tower based Kc.
- Actual ET from satellite-based Kc was similar to that observed from the flux tower.

Accurate estimation of the crop coefficient (Kc) is crucial for estimating actual crop evapotranspiration (ETa) and planning appropriate irrigation management for efficient crop yield. In this study, satellite-based Kc values were estimated at cropland and mixed forest sites based on the dual crop coefficient approach using merged soil moisture from the European Space Agency as an indicator of evaporation from soil, as well as the Normalized Vegetation Index (NDVI) and the Leaf Area Index (LAI) to explain the effect of transpiration from plants. Comparison of the seasonal patterns and Pearson's correlation coefficient (r) of NDVI, LAI, and surface soil moisture with Kc indicated that it was reasonable to use the three variables as independent variables to estimate Kc. Based on these results, the satellite-based Kc estimated using NDVI, LAI, and soil moisture (Case 1) was compared with the Kc calculated from NDVI and LAI (Case 2) and the flux towers at the significance level of 0.05. The statistical results confirmed that the Kc estimated from Case 1 (Bias: − 0.012 to 0.053, RMSE: 0.144 to 0.172, and r: 0.463 to 0.800) showed better agreement with the observed Kc than that estimated from Case 2 (Bias: − 0.058 to 0.088, RMSE: 0.146 to 0.221, and r: 0.434 to 0.788). Among the three variables, soil moisture had the greatest impact on the rice paddy, while the NDVI showed the highest influence on the mixed forest. Based on these results, Kc estimated from Case 1 was multiplied by MODerate resolution Imaging Spectroradiometer (MODIS)-based potential crop evapotranspiration and compared with the latent heat flux from flux towers. ETa showed reasonable bias (cropland: − 0.224 to 1.364, mixed forest: 0.711 to 1.055), RMSE (cropland: 1.952 to 2.126, mixed forest: 1.085 to 1.878) and r (cropland: 0.529 to 0.832, mixed forest: 0.850 to 0.909) at all of the study sites. After validation of the satellite-based Kc approach under various vegetation types and climate conditions, this approach can be employed not only for developing adequate water and agricultural management plans, but also for analyzing and predicting crop yield productivity and agricultural drought.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: CATENA - Volume 156, September 2017, Pages 305-314
نویسندگان
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