Testing gridded NWS 1-day observed precipitation analysis in a daily irrigation scheduler
Testing gridded NWS 1-day observed precipitation analysis in a daily irrigation scheduler作者机构:Biological Systems Engineering University of Nebraska Lincoln USA Department of Agricultural and Biological Engineering Mississippi State University Mississippi USA Southeast Agricultural Research Center Kansas State University Parsons USA USDA Agricultural Research Service Crop Production Systems Research Unit Stoneville USA USDA Agricultural Research Service Grazinglands Research Laboratory El Reno USA USDA Agricultural Research Service New England Plant Soil and Water Research Laboratory University of Maine Orono USA
出 版 物:《Agricultural Sciences》 (农业科学(英文))
年 卷 期:2013年第4卷第12期
页 面:621-627页
学科分类:1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题:Irrigation Daily Precipitation Scheduler Gridded Radar
摘 要:One of the inputs required by daily decision support tools for scheduling irrigation is the amount of water supplied by rainfall. In-field measurements of daily precipitation are expensive or laborious, while measurements from gauges within a few kilometers are frequently not representative due to the high spatiotemporal variability of precipitation. Online radarbased precipitation analyses from NOAA’s National Weather Service (NWS) have obvious potential to provide the needed data, but are known to have varying degrees of accuracy with location and conditions. The NWS precipitation analysis is computed on a 4 km × 4 km grid, so differences should also be expected between the product and individual gauge measurements under each grid cell. In order to test the utility of the NWS precipitation analysis in a daily irrigation scheduler, daily data were gathered in July 2012 from 18 weather stations under 2 NWS precapitation analysis grid cells across instru-mented research and production fields in the Mississippi Delta. Differences between individual station measurements and the NWS precipitation analysis are examined, and root-zone daily soil water deficits computed using both station data and the NWS precipitation analysis. Sub-grid spatial variability between gauge locations, and differences in precipitation between gauges and the gridded NWS analysis, are found to be similar to those reported elsewhere. Differences between time series of soil water deficit computed using the two different precipitation data sources are noted, but prove to be of limited impact on the decision to irrigate or not to irrigate. It is also noted that profile-filling rainfalls limit the impact of accumulating error, resetting the modeled soil water to “full. Given the Delta-local practice of irrigating to replace full evapotranspirational water used, use of the NWS daily precipitation analysis data as input for a daily irrigation scheduler is judged not only acceptable, but also preferabl