Research Article | OPEN ACCESS
Cropland Precipitation Prediction for Food Produce of the Weihe Basin Using Statistical Downscaling Model
1Shibao Lu, 1Xiao Bai, 2Liang Pei and 1Xiaojing Gan
1School of Urban-Rural Planning and Management, Zhejiang University of Finance and Economics, Hang Zhou 310018, China
2Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Advance Journal of Food Science and Technology 2016 1:40-42
Received: May ‎16, ‎2015 | Accepted: July ‎2, ‎2015 | Published: May 05, 2016
Abstract
This study describes the establishment of deferent statistical downscaling equations, using the existing Shannxi hydrological data of the Weihe basin, to downscaly analyze its monthly rainfall and temperature for food produce. The combination of main element analysis with the multi linear regression of downscaling is to get the statistical relationship between the atmosphere circling factors as outputs of global weather model with the rainfall and temperature data of 8 hydrological stations. Using the gradual regression method to analog the rainfall tells the relative error in a range of ±5% but that of standard deviation within -25~-40%, all smaller than the real time values and R2 about 0.45~0.7. For simulating the temperature, it shows almost no error of the average monthly temperature and the standard deviation obviously less than that of the real time and R2 ranging 0.85~0.95 most of the time, except about 0.7 in May, July and September. So, the statistical downscaling method of main element analysis has had a good result in imitating cropland precipitation and temperature for food produce.
Keywords:
Cropland precipitation, food produce, gradual regression, statistical downscaling, weihe basin,
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