农业分区框架下Hargreaves-Samani公式的逐月回归修正

为验证中国农业综合分区框架下Hargreaves-Samani(HS)公式线性回归修正方案的适用性,利用中国气象数据网发布的124个站点1957—2016年的逐月有效日平均气压、平均最低气温、平均最高气温、平均风速、平均水汽压、月总太阳辐射数据及站点经纬度数据,首先,分别基于Penman-Monteith(PM)公式和HS公式计算了各站点多年逐月的参考作物需水量ET_(0-PM)和ET_(0-HS)。然后,以ET_(0-PM)为真值,基于1957—2010年的逐月ET_(0-PM)和ET_(0-HS),利用线性回归分析方法获取了中国38个农业管理子区的HS公式校正系数a、b,并以2011—2016年为验证年份,通过比较ET_(0-HS)校正前后的相对误差变化,验证了HS公式线性回归校正方法在中国农业区的适用性,并结合验证年份的具体误差结果,确定了各农业区HS公式校正系数a、b的逐月最优取值。结果表明:大部分农业区的大部分月份ET_(0-PM)与ET_(0-HS)的相关系数超过0. 6,可以进行ET_(0-HS)的回归校正;回归校正得到的系数a存在显著的季节变化规律,系数b则表现较为平稳;系数a、b的大小及变化说明了ET_(0-PM)和ET_(0-HS)彼此之间存在差异,且季节性明显;校正前后的ET_(0-HS)均存在不同程度的相对误差,但校正后的ET_(0-HS)的误差范围已经显著缩小;在具体的验证应用中,校正后的ET_(0-HS)并不完全是最优结果,实践中系数a、b的优选使用才是最佳方案。本研究验证的HS公式线性回归校正方法是实践中简便、可行的方案,对大尺度区域快速获得较高精度的参考作物需水量具有实际意义和推广价值。     

中国大陆地区基于太阳辐射经验值计算ET0的适用性研究

太阳辐射是利用FAO推荐的Penman-Monteith(PM)公式计算参考作物需水量(ET_0)的必要参数。为了探究PM公式在辐射数据缺失的条件下,利用FAO推荐的公式及参数获得太阳辐射值(R_(s_c))替代观测值(R_(s_o))在中国大陆地区的适用性,本研究选用了中国大陆112个站点至少15 a的多年月平均观测数据,通过逐点计算分析了R_(s_c)和R_(s_o)的时空差异及二者分别输入PM公式获得的参考作物需水量ET_(0_c)和ET_(0_o)的时空差异。结果表明,R_(s_c)与R_(s_o)存在显著的时空差异性,二者相对差值范围为-2.86～4.41 MJ·m~(-2)·d~(-1),且在4—8月份差异较大;大致以"胡焕庸线"为界,线西北区域R_(s_c)与R_(s_o)的时空差异相对较小,且稳定,线东南区域的时空差异较大,且不稳定。但是,基于二者计算的ET_(0_c)和ET_(0_o)时空差异却不显著,平均只有0.06～0.26 mm·d~(-1)的误差;"胡焕庸线"西北地区的ET_(0_c)和ET_(0_o)绝对差值常年稳定在0.00～0.25 mm·d~(-1),"胡焕庸线"线东南地区则随季节而变化,夏季差异相对较大。在实际的应用中,西北地区全年和北方地区春、秋、冬三季以及长江、珠江流域所覆盖的南方地区在1、2、10、11、12月使用R_(s_c)替代R_(s_o)获得ET_0具有较好的适用性,北方地区的夏季、南方地区的3—9月份使用R_(s_c)计算ET_0则必须研究相应的方法对结果进行矫正,否则会有误差,且偏大。     

Determination of growth-stage-specific crop coefficients (Kc) of cotton and wheat

Development of crop coefficient (Kc), the ratio of crop evapotranspiration (ETc) to reference evapotranspiration (ETo), can enhance ETc estimates in relation to specific crop phenological development. This research was conducted to determine growth-stage-specific Kc and crop water use for cotton (Gossypium hirsutum) and wheat (Triticum aestivum) at the Texas AgriLife Research field at Uvalde, TX, USA from 2005 to 2008. Weighing lysimeters were used to measure crop water use and local weather data were used to determine the reference evapotranspiration (ETo). Seven lysimeters, weighing about 14 Mg, consisted of undisturbed 1.5 m × 2.0 m × 2.2 m deep soil monoliths. Six lysimeters were located in the center of a 1-ha field beneath a linear-move sprinkler system equipped with low energy precision application (LEPA) and a seventh lysimeter was established to measure reference grass ETo. Crop water requirements, Kc determination, and comparison to existing FAO Kc values were determined over a 2-year period on cotton and a 3-year period on wheat. Seasonal total amounts of crop water use ranged from 689 to 830 mm for cotton and from 483 to 505 mm for wheat. The Kc values determined over the growing seasons varied from 0.2 to 1.5 for cotton and 0.1 to 1.7 for wheat. Some of the values corresponded and some did not correspond to those from FAO-56 and from the Texas High Plains and elsewhere in other states. We assume that the development of regionally based and growth-stage-specific Kc helps in irrigation management and provides precise water applications for this region.     

Estimating reference evapotranspiration with atmometers in a semiarid environment

Reference evapotranspiration (ET₀) estimations require accurate measurements of meteorological variables (solar radiation, air temperature, wind speed, and relative humidity) which are not available in many countries of the world. Alternative approaches are the use of Class A pan evaporimeters and atmometers, which have several advantages compared to meteorological stations: they are simple, inexpensive and provide a visual interpretation of ET₀. The objectives of the study were to compare the evaporation from atmometers (ET_gage) with the evapotranspiration estimated by the FAO-56 Penman-Monteith equation (ET_0PM) and to evaluate the variability between three modified atmometers of a commercial model. Comparison between daily ET_gage measured by the atmometer and ET_0PM showed a good correlation. However, ET_gage underestimated ET_0PM by approximately 9%. Differences between ET_gage and ET_0PM ranged from −2.4 to 2.2 mm d⁻¹ while the mean bias error was −0.41 mm d⁻¹. Underestimations occurred more frequently on days with low maximum temperatures and high wind speeds. On the contrary, atmometer overestimations occurred on days with high maximum temperatures and low wind speeds. Estimates of ET₀ using the atmometer appeared to be more accurate under non-windy conditions and moderate temperatures as well as under windy conditions and high temperatures. Atmometers 2 and 3 overestimated the evaporated water by atmometer 1 with a maximum variability of cumulative water losses of 4.5%. A temperature-based calibration was performed to improve the atmometer accuracy, using maximum temperature as an independent variable, with good results.     

Nitrate leaching in a silage maize field under different irrigation and nitrogen fertilizer rates

Quantification of the interactive effects of nitrogen (N) and water on nitrate (NO₃) loss provides an important insight for more effective N and water management. The goal of this study was to evaluate the effect of different irrigation and nitrogen fertilizer levels on nitrate-nitrogen (NO₃-N) leaching in a silage maize field. The experiment included four irrigation levels (0.7, 0.85, 1.0, and 1.13 of soil moisture depletion, SMD) and three N fertilization levels (0, 142, and 189 kg N ha⁻¹), with three replications. Ceramic suction cups were used to extract soil solution at 30 and 60 cm soil depths for all 36 experimental plots. Soil NO₃-N content of 0-30 and 30-60-cm layers were evaluated at planting and harvest maturity. Total N uptake (NU) by the crop was also determined. Maximum NO₃-N leaching out of the 60-cm soil layer was 8.43 kg N ha⁻¹, for the 142 kg N ha⁻¹ and over irrigation (1.13 SMD) treatment. The minimum and maximum seasonal average NO₃ concentration at the 60 cm depth was 46 and 138 mg l⁻¹, respectively. Based on our findings, it is possible to control NO₃ leaching out of the root zone during the growing season with a proper combination of irrigation and fertilizer management.     

A discussion on and alternative to the Penman-Monteith equation

The Penman-Monteith (PMe) equation that estimates evaporation from leaf/canopy surfaces is based on a few approximations. Several authors discussed ensuing errors and suggested improvements. This paper reminds those discussions which ended in the early nineties. It compares linearized PMe− with non-linear iterative solutions and illustrates resulting deviations. It differentiates between deviations for daily and hourly evaporation rate estimates. The latter are found to be higher. It also demonstrates deviations obtained at two different altitudes above sea level. Considering present tendencies to refine evaporation estimates for practical purposes and making use of easily available methods for solving non-linear equations this paper offers a new method to estimate evaporation.In a first step, a simple algebraic term, the surface temperature control sum, is introduced to find approximate differences between air and evaporating surface (leaf, canopy) temperatures. It suggests to concentrate research on the r_s/r_a ratio. A new formula is derived for estimating leaf/canopy surface temperatures for non-water stressed plants.In a second step, the estimates of temperature differences are used to calculate evaporation estimates. This two-step approximation leads to appreciably smaller errors as compared to the PMe-solution over the full range of input parameters of agro-meteorological relevance. It is, however, less accurate than some of methods proposed in literature. The method is meant for practical application in agricultural water management.     

参考作物腾发量计算方法的适用性研究

选用5种方法,利用陕西6站的气象资料,计算了各站逐日ET0。并以FAO56 Penman-Monteith(P-M)法为标准,对其它方法进行评价。结果表明,在陕西6地区,5种方法计算的ET0变化趋势基本相同,但数值上有一定差异,所有的差异随ET0的增大而增大。Hargreaves法计算结果差异性较小,适用性较好;1948Penman和Priestley-Taylor二方法估值较FAO24 Penman法更接近P-M法的计算结果;缺气象资料时,Priestley-Taylor法可获得较好估值,且更适用于湿润地区;FAO24 Penman法也能获得较好结果,但其估值精度低于Priestley-Taylor法,一般不宜采用。同时分析了P-M法计算的ET0值和水面蒸发量之间的关系,为利用水面蒸发资料估算陕西6地区ET0值提供参考。     

若尔盖湿地潜在蒸散时空动态特征及影响因子

潜在蒸散(ET0)对水资源评价和气候变化均具有重要意义。利用若尔盖湿地及其周边19个气象站1960—2015年逐日气象资料,根据辐射修正的Penman-Monteith模型计算了湿地潜在蒸散量,采用累积距平、Mann-Kendall检验、Pettitt检验、Theil-Sen趋势度、Hurst指数等方法分析了蒸散变化规律,并对蒸散影响因子进行了主成分分析。结果表明:(1)若尔盖湿地年ET0均值为625.3mm,并以4.89mm/10a的速率显著上升(p<0.01),四季ET0表现为夏季>春季>秋季>冬季。年、秋、冬ET0分别在1968年(p<0.01),1997年(p<0.01),2003年(p<0.1)突变上升,春、夏两季未出现突变。(2)湿地年均ET0呈南部、东部边缘高、西北—东南一线较低的空间分布特征,且变化速率由东北向西南递减,其中西部班玛以北及南部马尔康、黑水之间地区ET0呈缓慢下降趋势。(3)湿地年ET0的Hurst指数在0.56～0.91间,主要呈四周高、中部低的空间分布规律。未来湿地ET0变化趋势以持续性增加为主,面积比例为96.88%。(4)气温上升是引起湿地ET0增加的最主要原因,其次是日照时数的增加和相对湿度的降低。净辐射、风速和降水量的减少引起的ET0减少被气温等其他因素作用所抵消。     

重庆丘陵山区参考作物蒸散量的确定及气候影响因素分析

基于重庆市北碚区2001—2011年气象资料,采用Penman-Monteith公式计算ET0,分析了3种不同太阳辐射(Rs)计算方法所得ET0的差异性,并利用相关性和敏感性分析方法分析气象因子对ET0的影响。结果表明,研究区2001—2011年年内各月ET0呈抛物线变化,年内ET0最大值出现在7月和8月,最小值出现在1月和12月;不同Rs计算方法是引起ET0和辐射项(ET0(rad))差异的主要原因,但差异不显著;研究区ET0主要由空气动力学项(ET0(aero))贡献;最高温度、最高相对湿度和最低相对湿度是研究区ET0的3个最主要的影响因子;采用Pen-man-Monteith公式计算研究区ET0时,建议采用Hargreaves公式计算Rs。     

蒲草群落蒸散耗水规律及影响因子研究

利用Penman-Monteith模型及单作物系数法计算了2013年石佛寺人工湿地蒲草全生育期的逐日实际蒸散量,对比分析了各时期的自由水面蒸发量,并采用偏相关法分析了影响蒲草群落实际蒸散量及水面蒸发量的气象因子。结果表明,蒲草全生育期单位面积的累积蒸散量为607.96mm,整体呈先升高后下降趋势,其中稳定期蒸散强度最大达到4.52mm/d,是生态需水的关键时期,相应全生育阶段的水面蒸发量为560.11mm,蒸散系数达到1.09,说明蒲草的存在能够增加湿地水分的扩散;蒸腾和蒸发受各生育阶段气象因子的影响程度不同,主要受太阳辐射和风速的影响。