考虑地形对气温影响的ET_0计算方法研究

局部地形因子的剧烈变化对气温的影响会进一步影响参考作物需水量(ET0)的精确估算。以贵州省为例开展地形对气温影响下的ET0计算方法,采用符号回归的方法,构建Modis实测气温值与经度、纬度、海拔、坡度、坡向等地形因子以及插值气温之间的函数关系,并将其代入FAO56PM公式,进而得到考虑地形对气温影响的ET0计算方法。研究结果表明,计算所得的气温与Modis气温实测值之间的相关系数均大于0.49,可以有效减小气温的估算误差,具有较好的模拟效果;考虑地形对气温影响的ET0与传统插值方法所得的贵州省内日ET0空间分布特征相一致且较为连续;考虑地形对气温影响下南坡上的ET0大于北坡,且ET0随坡度的增加而减小,当坡度大于60°时,坡度对ET0的影响不容忽视。研究结果可为贵州地区农业精准灌溉和灌区水资源精准配置提供指导依据。     

新疆车尔臣河流域ET_0计算方法的适用性评价

为实现参考作物蒸散量ET_0在资料缺失情况下的准确计算,对ET_0简化算法在车尔臣河流域的适用性进行科学评价,采用2个气象站点1961-2013年逐日气象资料,以Penman-Monteith(PM)法的计算结果为标准,对具有代表性的5种简易算法Hargreaves-Samani(HS)法、Pristley-Taylor(PT)法、Irmark-Allen(IA)法、Makkink(MAK)法和Penman-Van Bavel(PVB)法的计算精度进行对比,结果表明:研究区六七月蒸散发量最大,1、12月份最小,PT法计算结果偏大,HS法、IA法、MAK法与PVB法计算结果均偏小;5种方法在流域上、下游的计算精度差异明显,HS法和PVB法较为精准,PT法、IA法和MAK法误差较大;流域上、下游最优算法均为HS法。     

参考作物需水量计算方法在纵向岭谷区的应用对比

利用纵向岭谷区内58个典型站点1971~2000年逐月气象资料,以及昆明、元江、大理、景洪、保山等5个站点建站至2000年逐日气象资料,从逐日、月及年的不同时间尺度,以Penman Montieth方程计算结果为标准,分析修正Penman法、Priestley Taylor、Hargreaves等不同方法计算参考作物腾发量的适用性。在月和年时段上,修正Penman法较标准值偏小1%~19%,3~10月份平均误差小于6%,各流域之间存在一定差异。不同水文频率年Priestley Taylor和Hargreaves公式计算的逐日ET0,都不同程度地比标准值小,昆明、保山、大理等半干旱或半湿润地区,Priestley Taylor公式计算结果更接近于标准值,平均误差11%~16%左右;景洪等湿润地区Hargreaves公式与标准值误差最小,为15%左右;但接近干旱区的元江则2种方法的结果都存在较大差异,相对误差大于25%;各月ET0的变异系数是Priestley Taylor大于Hargreaves公式,且绝大多数月份小于0.20;不同天气类型时Priestley Taylor计算精度变化大,晴和多云天气情况下的误差小于16.3%,阴雨天则误差比Hargreaves公式大,后者的计算精度在各种天气条件下较稳定;误差在年内的分布是7~8月最小,年初和年末最大,变化趋势与修正Penman法的对比结果相同。各种方法的ET0计算结果与标准值的相关系数均大于0.80。     

豫西北几种ET_0计算方法的比较及Hargeaves公式的修正

根据豫西北地区30年的气象资料,选用辐射法中的Makkink公式和Priestley-Taylor公式以及温度法的Hargreaves公式和McCloud公式计算了ET0,并以Penman-Monteith公式为标准,分别对各公式年值和旬均值的绝对误差、相对误差和累计误差进行分析,结果显示Hargreaves公式的精度最高。为了进一步提高Hargreaves公式的应用精度,建立了线形回归方程,并对其进行了修正。     

日光温室作物蒸发蒸腾量的计算方法研究及其评价

对FAO推荐计算参考作物蒸发蒸腾量的Penman-Monteith(缩写为P-M)公式,在日光温室微气候的条件应用作了详细的分析。将P-M公式分为2个部分,即辐射项(ETrad)和空气动力学项(ETaero),推导出了计算温室内参考作物蒸发蒸腾量的P-M修正公式,解决了P-M公式假定温室内风速为“0”所引起的一系列问题。并根据2004年和2005年温室内实测气象数据和水面蒸发对其进行了验证,通过相关分析得出用修正后的P-M公式计算作物蒸发蒸腾量比FAO推荐的P-M公式计算值误差小、精度高。建议在日光温室里使用修正后的P-M公式计算参考作物的蒸发蒸腾量。     

风沙区参考作物需水量的计算

根据国内外相关的研究成果 ,分析选择并确定了适宜于风沙区参考作物需水量 (ET0 )的计算模式。利用典型风沙区的气象资料 ,对多年逐旬参考作物需水量及 2 0 0 1年春小麦与春玉米生育时段内逐日参考作物需水量进行了分析计算。结果表明 ,FAO最新修正的 Penman-Moteith公式可较好地用于风沙区参考作物需水量的估算 ,一般 ET0 值在年内与年际间变化较大 ,最高值发生在 6月上旬左右 ,多年平均为 5 .82 mm/ d,最低值发生在 1月上旬 ,多年平均 0 .43 mm/ d左右 ,年内各日 ET0 值受气象因素的影响变幅很大 ,因此 ,精确灌溉应设法提高短期天气预报和灌溉预报的精度     

Measuring versus estimating net radiation and soil heat flux: Impact on Penman–Monteith reference ET estimates in semiarid regions

The standardized ASCE Penman–Monteith and FAO-56 equations were used to estimate reference evapotranspiration (ET₀) using estimated and measured net radiation (R_n) and soil heat flux (G), based on hourly and daily meteorological data. The estimates were evaluated against lysimeter measurements. The results indicate that using measured or estimated values of R_n and G can have significant effect on the accuracy of the ET₀ estimations, especially when calculations were made on an hourly basis. The FAO-56 version performed very well during the irrigation season on a daily basis. The use of measured R_n and G did not improve ET₀ estimation on a daily basis, therefore, the use of estimated R_n and G appears to be dependable when calculations are based on 24-h weather data. When daily ET₀ was calculated from hourly estimations, the results were different depending on the version used. The ASCE version was more accurate, especially when R_n and G were measured. Therefore, measurement of R_n and G may have potential to improve estimation only when daily ET₀ is calculated from hourly estimations. The PM FAO-56 version was always a little less accurate than the ASCE version. For hourly calculations, using a constant surface resistance (as in FAO-56 version), the PM method underpredicted for high evaporative demand and vice versa. The ASCE version performed better than PM FAO-56 version when R_n and G were measured and estimated. Therefore, ASCE version tended to provide quite accurate values of hourly ET₀, even using estimated values of R_n and G. As conclusion, the methods proposed by FAO-56 for estimating R_n and G tended to produce accurate estimates for daily and hourly ET₀ under semiarid conditions and can be used with some degree of confidence for estimating ET₀. In addition, results suggest that the ASCE standardized equation on an hourly basis improved the accuracy of ET₀ estimation with respect to the FAO-56 version.     

基于Blaney-Criddle方法估算潜在蒸散量的评价与校准

为提高Blaney-Criddle(BC)方法在陕西关中地区的估算精度,以Penman方法(PE)为标准,利用1960—1999年陕西关中地区6个站点逐日资料对BC方法进行适用性评价和参数修正,并使用2000—2015年资料对修正的BC方法进行验证,得到基于温度的潜在蒸散量估算方法(CBC方法)。结果表明:BC方法计算的月均ETp(潜在蒸散量)在温度较低时低估,在温度较高时高估。通过改进后,CBC与PE方法计算的月均ETp回归曲线的斜率更接近于1(改进前0.685,改进后0.999 7)。与PE方法的计算结果相比,改进后BC(CBC)计算月均ETp相对误差由-18.022%~16.269%变为1.290%~3.630%,均方根误差由0.529~0.921 mm/d降为0.214~0.283 mm/d;平均偏差由-0.063~0.601 mm/d变为-0.001 121~0.000 737 mm/d。修正前后BC方法计算月均ETp值与PE方法计算值拟合的决定系数由0.942提高到0.966。通过年累计ETp和年内月累计ETp的验证,CBC与PE计算的ETp变化趋势和数值更为接近。综合分析表明,CBC方法能够显著提高潜在蒸散量的计算精度(ETp),可以应用于陕西关中地区ETp的计算。     

基于HHT变换的PSO-LSSVM耦合模型估算气象资料短缺地区ET_0

为准确估算气象资料短缺地区参考作物腾发量,构建了一种基于HHT变换的PSO-LSSVM耦合模型,并利用新疆和田气象站2000—2009年单日数据做训练、双日数据做验证。结果表明,该模型估算ET0方法明显优于常规的PSO-LSSVM和GRNN,预测精度较二者分别提高了15.7%~85.6%和15.8%~93.7%;该方法预测ET0的气象要素重要性为RsTmaxTminRHWn,利用该方法对气象要素组合为Tmax/Tmin/RH/Wn、Tmax/RH/Wn、Tmin/Wn、Wn条件下的ET0预测,MSE分别为0.407、0.185、0.149、0.135,说明该方法可以很好地估算资料缺失地区ET0。     

作物水分供需分析中使用平均ET_0的误差分析

以 3个气象站的 4 8年气象资料为基础 ,详细分析了作物水分供需分析中使用平均 ET0 的可行性 ,以及由此可能带来的误差程度。分析结果指出 ,在作物水分供需关系中 ,降雨变异所起的作用要远大于 ET0 变异的作用 ,但二者尚处于同一数量级上。因此 ,平均 ET0 法可以在适当的条件下和适宜的范围内使用。但这种方法也存在着引起较大误差的可能性 ,使用时需要慎重的分析和判断。     

基于灰色关联法的小型农田水利工程建设项目绩效评价研究

运用灰色关联法原理,采用均方差法计算指标权重,根据近年来湖北省进行小型农田水利工程建设项目绩效评价的实际情况,建立了小型农田水利工程建设项目评价定性定量混合指标体系和模型,应用该模型和方法对湖北省2012年第二批20个小农水重点县工程建设项目进行了评价(作为研究,各县、市名以汉语拼音字头代替)。结果表明:LHK、SSS、ZJS、DJK、XTS等14个县为优秀,XCX、TMS、JSX等5个县为良好,CYX为一般,无及格等级的重点县。评价结果与实际基本相符。证明本文所提出的模型和方法可应用于实际,是一种快速便捷的评价工具。     

黄土高原丘陵沟壑区多种参考作物需水量模型对比分析

利用米脂地区2000—2005年逐日气象资料,以FAO56-PM方程计算结果为标准,通过线性回归、均方根误差（RMSE）和平均偏差,在日、月及年时间尺度上分析、评价10种ET0计算模型。结果表明,除Hargreaves和Turc模型外,其他8种模型计算的日ET0值与FAO56-PM的R2均大于0.9。不同模型与FAO5...     

基于改进TOPSIS法的通辽市水土资源利用效益评价

为提高半干旱区农灌区水土资源利用效益,以通辽市为例,从经济、社会与生态3方面选取评价指标,应用基于灰色关联分析法与熵值法改进的TOPSIS法,分别对2000年、2005年、2010年和2013年各旗县的水土资源利用效益进行评价。结果表明,通辽市各旗县水土资源利用效益整体较优,其中节灌率、灌溉水利用系数、有效灌溉率、人均农业产值、单位灌溉面积产值以及林草覆盖率等6项指标是影响水土资源利用效益的主要因素,且改进的TOPSIS法对于水土资源利用效益评价方面具有一定的可信度,值得在同类研究中推广应用。     

Simulation of transpiration, drainage, N uptake, nitrate leaching, and N uptake concentration in tomato grown in open substrate

Free-drainage or “open” substrate system used for vegetable production in greenhouses is associated with appreciable NO₃⁻ leaching losses and drainage volumes. Simulation models of crop N uptake, N leaching, water use and drainage of crops in these systems will be useful for crop and water resource management, and environmental assessment. This work (i) modified the TOMGRO model to simulate N uptake for tomato grown in greenhouses in SE Spain, (ii) modified the PrHo model to simulate transpiration of tomato grown in substrate and (iii) developed an aggregated model combining TOMGRO and PrHo to calculate N uptake concentrations and drainage NO₃⁻ concentration. The component models simulate NO₃⁻-N leached by subtracting simulated N uptake from measured applied N, and drainage by subtracting simulated transpiration from measured irrigation. Three tomato crops grown sequentially in free-draining rock wool in a plastic greenhouse were used for calibration and validation. Measured daily transpiration was determined by the water balance method from daily measurements of irrigation and drainage. Measured N uptake was determined by N balance, using data of volumes and of concentrations of NO₃⁻ and NH₄⁺ in applied nutrient solution and drainage. Accuracy of the two modified component models and aggregated model was assessed by comparing simulated to measured values using linear regression analysis, comparison of slope and intercept values of regression equations, and root mean squared error (RMSE) values. For the three crops, the modified TOMGRO provided accurate simulations of cumulative crop N uptake, (RMSE = 6.4, 1.9 and 2.6% of total N uptake) and NO₃⁻-N leached (RMSE = 11.0, 10.3, and 6.1% of total NO₃⁻-N leached). The modified PrHo provided accurate simulation of cumulative transpiration (RMSE = 4.3, 1.7 and 2.4% of total transpiration) and cumulative drainage (RMSE = 13.8, 6.9, 7.4% of total drainage). For the four cumulative parameters, slopes and intercepts of the linear regressions were mostly not statistically significant (P < 0.05) from one and zero, respectively, and coefficient of determination (r²) values were 0.96-0.98. Simulated values of total drainage volumes for the three crops were +21, +1 and −13% of measured total drainage volumes. The aggregated TOMGRO-PrHo model generally provided accurate simulation of crop N uptake concentration after 30-40 days of transplanting, with an average RMSE of approximately 2 mmol L⁻¹. Simulated values of average NO₃⁻ concentration in drainage, obtained with the aggregated model, were −7, +18 and +31% of measured values.