Evaluation of different gridded rainfall datasets for rainfed wheat yield prediction in an arid environment

The accuracy of daily output of satellite and reanalysis data is quite crucial for crop yield prediction. This study has evaluated the performance of APHRODITE (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation), PERSIANN (Rainfall Estimation from Remotely Sensed...

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Veröffentlicht in:	International journal of biometeorology 2018-08, Vol.62 (8), p.1543-1556
Hauptverfasser:	Lashkari, A., Salehnia, N., Asadi, S., Paymard, P., Zare, H., Bannayan, M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Agricultural production Animal Physiology Arid environments Aridity Artificial neural networks Biological and Medical Physics Biophysics Cereal crops Computer simulation Crop growth Crop yield Daily precipitation Data integration Datasets Dry matter Earth and Environmental Science Environment Environmental Health Grain Ground stations Hydrologic data Leaf area Leaf area index Meteorology Missing data Neural networks Original Paper Plant Physiology Precipitation Precipitation data Rainfall Rainfall estimation Remote sensing Root-mean-square errors Solar radiation Temperature data Tropical rainfall Tropical Rainfall Measuring Mission (TRMM) Wheat Wheat yield
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