Error Autocorrelation and Linear Regression for Temperature‐Based Evapotranspiration Estimates Improvement1

Medeiros, Patrick Valverde, Francisco Fernando Noronha Marcuzzo, Cristián Youlton, and Edson Wendland, 2012. Error Autocorrelation and Linear Regression for Temperature‐Based Evapotranspiration Estimates Improvement. Journal of the American Water Resources Association (JAWRA) 48(2): 297‐305. DOI: 10.1111/j.1752‐1688.2011.00614.x Abstract: Estimates of evapotranspiration on a local scale is important information for agricultural and hydrological practices. However, equations to estimate potential evapotranspiration based only on temperature data, which are simple to use, are usually less trustworthy than the Food and Agriculture Organization (FAO)‐Penman‐Monteith standard method. The present work describes two correction procedures for potential evapotranspiration estimates by temperature, making the results more reliable. Initially, the standard FAO‐Penman‐Monteith method was evaluated with a complete climatologic data set for the period between 2002 and 2006. Then temperature‐based estimates by Camargo and Jensen‐Haise methods have been adjusted by error autocorrelation evaluated in biweekly and monthly periods. In a second adjustment, simple linear regression was applied. The adjusted equations have been validated with climatic data available for the Year 2001. Both proposed methodologies showed good agreement with the standard method indicating that the methodology can be used for local potential evapotranspiration estimates.     

Climatic Controls on Watershed Reference Evapotranspiration Varied during 1961–2012 in Southern China

Reference evapotranspiration (ET_o) is an important hydrometeorological term widely used in understanding and projecting the hydrological effects of future climate and land use change. We conducted a case study in the Qinhuai River Basin that is dominated by a humid subtropical climate and mixed land uses in southern China. Long‐term (1961–2012) meteorological data were used to estimate ET_o by the FAO‐56 Penman–Monteith model. The individual contribution from each meteorological variable to the trend of ET_o was quantified. We found basin‐wide annual ET_o decreased significantly (p < 0.05) by 3.82 mm/yr during 1961–1987, due to decreased wind speed, solar radiation, vapor pressure deficit (VPD), and increased relative humidity (RH). However, due to the increased VPD and decreased RH, the ET_o increased significantly (p < 0.05) in spring, autumn, and annually at a rate of 2.55, 0.56, and 3.16 mm/yr during 1988–2012, respectively. The aerodynamic term was a dominant factor controlling ET_o variation in both two periods. We concluded the key climatic controls on ET_o have shifted as a result of global climate change during 1961–2012. The atmospheric demand, instead of air temperature alone, was a major control on ET_o. Models for accurately predicting ET_o and hydrological change under a changing climate must include VPD in the study region. The shifts of climatic control on the hydrological cycles should be considered in future water resource management in humid regions.     

A Calibrated,High‐Resolution GOES Satellite Solar Insolation Product for a Climatology of Florida Evapotranspiration1

Paech, Simon J., John R. Mecikalski, David M. Sumner, Chandra S. Pathak, Quinlong Wu, Shafiqul Islam, and Taiye Sangoyomi, 2009. A Calibrated, High‐Resolution GOES Satellite Solar Insolation Product for a Climatology of Florida Evapotranspiration. Journal of the American Water Resources Association (JAWRA) 45(6):1328‐1342. Abstract: Estimates of incoming solar radiation (insolation) from Geostationary Operational Environmental Satellite observations have been produced for the state of Florida over a 10‐year period (1995‐2004). These insolation estimates were developed into well‐calibrated half‐hourly and daily integrated solar insolation fields over the state at 2 km resolution, in addition to a 2‐week running minimum surface albedo product. Model results of the daily integrated insolation were compared with ground‐based pyranometers, and as a result, the entire dataset was calibrated. This calibration was accomplished through a three‐step process: (1) comparison with ground‐based pyranometer measurements on clear (noncloudy) reference days, (2) correcting for a bias related to cloudiness, and (3) deriving a monthly bias correction factor. Precalibration results indicated good model performance, with a station‐averaged model error of 2.2 MJ m^?2/day (13%). Calibration reduced errors to 1.7 MJ m^?2/day (10%), and also removed temporal‐related, seasonal‐related, and satellite sensor‐related biases. The calibrated insolation dataset will subsequently be used by state of Florida Water Management Districts to produce statewide, 2‐km resolution maps of estimated daily reference and potential evapotranspiration for water management‐related activities.     

浙江省主要优势农产品产地土壤-农作物镉含量空间分布及相关性研究

针对目前土壤-农作物镉污染问题,以浙江省40个县（市、区）主要优势农产品产区为研究对象,在粮食、油菜、蔬菜种植地以及茶园和果园土壤中共采集898个单元土壤样品及相对应的五大类农作物,并对其镉含量进行分析评价;同时采用富集系数比较不同农作物对土壤重金属镉的吸收差异。结果表明,研究区产地土壤和农作物的镉含量存在一定程度超标,土壤超标率为10.69%,农作物超标率为4.57%。不同农作物对土壤镉的富集系数差异较大,变化范围在0.002～0.257之间。土壤-农作物镉含量的相关性并不显著。