农业工程学报
農業工程學報
농업공정학보
2013年
8期
115-124
,共10页
赵春江%杨贵军*%薛绪掌%冯海宽%石月婵
趙春江%楊貴軍*%薛緒掌%馮海寬%石月嬋
조춘강%양귀군*%설서장%풍해관%석월선
遥感%蒸散%模型%互补相关%IKONOS%蒸渗仪
遙感%蒸散%模型%互補相關%IKONOS%蒸滲儀
요감%증산%모형%호보상관%IKONOS%증삼의
remote sensing%evapotranspiration%models%complementary relationship%IKONOS%lysimeter
获取田块内高分辨率农田实际蒸散信息对于精准农业中制定灌溉计划、变量处方实施及评价水分利用效率等具有重要参考价值,将传统方法与遥感结合并生成精细田块尺度的农田蒸散成为当前研究热点方向.本文基于互补相关模型和北京2011年3-6月份间内气象观测数据进行了冬小麦实际蒸散估算,并利用大型蒸渗仪对结果进行了验证和分析.最后将互补相关模型与高空间分辨率遥感数据结合实现了田块尺度农田瞬时蒸散估算,并结合蒸发比率不变法实现了日尺度蒸散扩展.结果表明:在2011年3-6月间试验区内冬小麦总耗水量达到469.12 mm,其中在灌浆期5月份耗水比重最大,占到总量近二分之一;互补相关模型估算精度整体较高,其中在5月份估算精度最高(R2=0.863,RMSE=0.103 mm);扩展后的日尺度蒸散量与实测结果非常一致(R2=0.937, RMSE=0.668 mm).上述结果表明在没有土壤温、湿度数据及高分辨率热红外遥感数据条件下,仅利用互补相关模型,并结合气象观测数据和高分辨率遥感数据即可估算出精细尺度农田蒸散.
穫取田塊內高分辨率農田實際蒸散信息對于精準農業中製定灌溉計劃、變量處方實施及評價水分利用效率等具有重要參攷價值,將傳統方法與遙感結閤併生成精細田塊呎度的農田蒸散成為噹前研究熱點方嚮.本文基于互補相關模型和北京2011年3-6月份間內氣象觀測數據進行瞭鼕小麥實際蒸散估算,併利用大型蒸滲儀對結果進行瞭驗證和分析.最後將互補相關模型與高空間分辨率遙感數據結閤實現瞭田塊呎度農田瞬時蒸散估算,併結閤蒸髮比率不變法實現瞭日呎度蒸散擴展.結果錶明:在2011年3-6月間試驗區內鼕小麥總耗水量達到469.12 mm,其中在灌漿期5月份耗水比重最大,佔到總量近二分之一;互補相關模型估算精度整體較高,其中在5月份估算精度最高(R2=0.863,RMSE=0.103 mm);擴展後的日呎度蒸散量與實測結果非常一緻(R2=0.937, RMSE=0.668 mm).上述結果錶明在沒有土壤溫、濕度數據及高分辨率熱紅外遙感數據條件下,僅利用互補相關模型,併結閤氣象觀測數據和高分辨率遙感數據即可估算齣精細呎度農田蒸散.
획취전괴내고분변솔농전실제증산신식대우정준농업중제정관개계화、변량처방실시급평개수분이용효솔등구유중요삼고개치,장전통방법여요감결합병생성정세전괴척도적농전증산성위당전연구열점방향.본문기우호보상관모형화북경2011년3-6월빈간내기상관측수거진행료동소맥실제증산고산,병이용대형증삼의대결과진행료험증화분석.최후장호보상관모형여고공간분변솔요감수거결합실현료전괴척도농전순시증산고산,병결합증발비솔불변법실현료일척도증산확전.결과표명:재2011년3-6월간시험구내동소맥총모수량체도469.12 mm,기중재관장기5월빈모수비중최대,점도총량근이분지일;호보상관모형고산정도정체교고,기중재5월빈고산정도최고(R2=0.863,RMSE=0.103 mm);확전후적일척도증산량여실측결과비상일치(R2=0.937, RMSE=0.668 mm).상술결과표명재몰유토양온、습도수거급고분변솔열홍외요감수거조건하,부이용호보상관모형,병결합기상관측수거화고분변솔요감수거즉가고산출정세척도농전증산.
@@@@Mapping high spatial-temporal resolution evapotranspiration (ET) over large areas is important for water resources planning, precision irrigation and monitoring water use efficiency. Recently accurate estimation of ET is becoming available via a number of methods using surface meteorological and sounding observations, which are used to represent only local processes, meet insuperably difficulty to mapping ET in large areas due to land surface heterogeneity and the dynamic nature of the heat transfer processes. Satellite remote sensing is a promising tool for this purpose. Nevertheless, most of the existing techniques of ET estimation from satellite remote sensing are not satisfactory, because satellite monitoring of ET has not been feasible at high pixel resolution. Therefore, using traditional measurements and high resolution image data to generate high spatial-temporal resolution ET is becoming an important research direction. In this paper, the complementary relationship model (CR) was employed together with meteorological data to estimate actual ET, and the results were validated by lysimeter observation. Furthermore, CR model was combined with high resolution image, IKONOS data, to estimate instantaneous field scale ET and they also were transferred into daily ET. The cumulative evapotranspiration (ET) of winter wheat during the reproductive phase from March to June of 2011 was 469.12 mm, essentially corresponding to the annual precipitation in the Beijing area. The most high accuracy of estimated ET by CR model is also on May(R2=0.863,RMSE=0.103 mm). The daytime ET accounted for 86%of the total ET for the four-month period, while the nighttime ET constituted the remaining 14% of the total. Therefore, the nighttime ET must also be considered. The transferred daily ET by self-preservation of evaporative fraction(EF) method were consistent with lysimeter measurements for all four months(R2=0.937,RMSE=0.668 mm). The estimated daily ET by the EF method was consistent with lysimeter measurement for each of the four months. The IKONOS image-based instantaneous and daily ET over vegetation-covered area increased with increment of leaf area index (LAI) and decreased with increment of albedo. It was proved in this study that CR model can be used to estimate precision field scale ET with meteorological data and high resolution remote sensing data together in a region with limited ground data availability, e.g. without soil moisture and surface temperature .