Comparison of modeling approaches to quantify residue architecture effects on soil temperature and water

RZ-SHAW is a hybrid model, comprised of modules from the Simultaneous Heat and Water (SHAW) model integrated into the Root Zone Water Quality Model (RZWQM) that allows more detailed simulation of different residue types and architectures that affect heat and water transfer at the soil surface. RZ-SHAW allows different methods of surface energy flux evaluation to be used: (1) the SHAW module, where evapotranspiration (ET) and soil heat flux are computed in concert with a detailed surface energy balance; (2) the Shuttleworth–Wallace (S–W) module for ET in which soil surface temperature is assumed equal air temperature; and (3) the PENFLUX module, which uses a Penman transformation for a soil slab under incomplete residue cover. The objective of this study was to compare the predictive accuracy of the three RZ-SHAW modules to simulate effects of residue architecture on net radiation, soil temperature, and water dynamics near the soil surface. The model was tested in Akron, Colorado in a wheat residue-covered (both standing and flat) no-till (NT) plot, and a reduced till (RT) plot where wheat residue was incorporated into the soil. Temperature difference between the soil surface and ambient air frequently exceeded 17 °C under RT and NT conditions, invalidating the isothermal assumption employed in the S–W module. The S–W module overestimated net radiation (R_n) by an average of 69 Wm⁻² and underestimated the 3-cm soil temperature (T_s3) by 2.7 °C for the RT plot, attributed to consequences of the isothermal assumption. Both SHAW and PENFLUX modules overestimated midday T_s3 for RT conditions but underestimated T_s3 for NT conditions. Better performances of the SHAW and PENFLUX surface energy evaluations are to be expected as both approaches are more detailed and consider a more discretized domain than the S–W module. PENFLUX simulated net radiation slightly better than the SHAW module for both plots, while T_s3 was simulated the best by SHAW, with a mean bias error of +0.1 °C for NT and +2.7 °C for RT. Simulation results for soil water content in the surface 30 cm (θ_v30) were mixed. The NT conditions were simulated best by SHAW, with mean bias error for θ_v30 within 0.006 m³ m⁻³; RT conditions were simulated best by the PENFLUX module, which was within 0.010 m³ m⁻³.     

用Penman-Monteith方法与Penman修正算法计算参照作物腾发量的比较

利用阿克苏地区1975-2004年的逐日气象资料,分别采用Penman—Monteith公式与Penman修正公式计算了新疆农一师灌区的参照作物腾发量及其辐射项和空气动力项的逐日均值和旬日均值,比较了2种计算方法的绝对偏差和相对偏差,并对引起偏差的原因进行了分析。     

Comparison of artificial neural networks and prediction models for reference evapotranspiration estimation in a semi-arid region

Estimation of reference evapotranspiration (ET_o) is essential for determination of crop water requirements. In this research, Penman–FAO (P-FAO) and Penman–Monteith (PM) equations were calibrated and validated by lysimeter-measured ET_o with six and four weather parameters. Furthermore, two input structures (six and four weather parameters) to artificial neural networks (ANNs) were investigated. Results showed that the accuracy of the PM equation is greater than that of the P-FAO equation. An empirical equation was developed to estimate daily ET_o using mean daily temperature and relative humidity, and sunshine hours. The accuracy of the equation to estimate daily ET_o using smooth weather data is greater than that of an equation using original data. Furthermore, ANNs were able to estimate ET_o properly. The accuracy of ANNs with six inputs is higher than that obtained using the P-FAO equation and is similar to that determined using the PM equation. A decrease in number of inputs to ANNs generally decreased the accuracy of estimation, however, ANNs were able to estimate ET_o properly when wind speed and solar radiation were unavailable. Furthermore, the accuracy of ANNs, with four input parameters is greater than that obtained using the PM equation and is similar to that obtained with P–FAO and the developed empirical equations.     

Evaluation of pan coefficient equations for estimating reference crop evapotranspiration in the arid region

Reference evapotranspiration (ET₀) can be estimated on basis of pan evaporation data (E_pan), whose measurements have the advantage of low cost, simplicity of the measuring equipment, simple data interpretation and application as well as suitability for locations with limited availability of meteorological data. E_pan values were converted to ET₀ using the pan evaporation coefficient (K_pan). In this study, seven common K_pan equations were evaluated for prediction of ET₀ in the growing season (April to October) in arid region of Iran. The Cuenca approach was best suited compared to the standard FAO Penman–Monteith method (FAO-56 PM).     

A Computer Program for Automatic Watering Based on Potential Evapotranspiration by Penman Method and Predicted Leaf Area in Miniature Pot Rose Production

In this study, we developed a computer program for automatic prediction of watering time point by considering the environmental factors such as solar radiation, air temperature and relative humidity based on the multiple linear regression equation of leaf area and Penman Method. The experiments were carried out for a year in two watering experimental plots, one of which was controlled by pF value, and the other by the computer program. After comparing the results of the two plots, the following findings were obtained. In the computer program plot, the observed and predicted values of both leaf area and evapotranspiration indicated significant correlation at the 1% level, which suggested that the computer program had high prediction accuracy. In addition, no significant difference was observed between the two experimental plots with respects to the plant height, plant diameter, leaf area, leaf number, fresh weight, and dry weight, which demonstrated that the plants in the computer program plot had normal growth. On the other hand, although the number of flower buds and flowering shoots showed higher values at the end of certain cultivations in the computer program plot than those in pF value plot, we proposed that it was due to the effect of cumulative daily solar radiation in the greenhouse, rather than the watering. Thus, we have reached the conclusion that the computer program for automatic prediction of watering time point developed by this study has high applicability in miniature pot rose production.     

干旱区受损植被生态恢复需水量——以新疆哈巴河县平原区为例

[目的]分析干旱区受损植被恢复过程中生态需水量,为生态恢复不同阶段所需水资源量及水资源优化配置提供科学依据。[方法]基于1990,2000,2010,2015,2020年Landsat系列影像,采用遥感技术,结合改进的彭曼公式法,对新疆哈巴河县平原区植被耗水量时空演变特征及生态恢复需水量进行了定量研究。[结果](1)1990—2020年天然植被平均耗水量为7.55×10⁸ m³,以3.60×10⁷ m³/5 a的速率减小,与之对应的是天然植被面积以17.36 km²/a的速率减小,植被覆盖度从高植被覆盖度向中植被覆盖度转化,生态受损严重。(2)区域内植被耗水量时空分布均存在较大差异：空间上高值主要分布于哈巴河流域,别列则克河流域植被耗水量整体偏低;时间上年际变化以2000年植被耗水量为最高,年内植被耗水量则主要集中在生长中期。(3)绿洲区生态恢复需水量如下：维持现状(2020年)生态需水量为4.62×10⁸ m³,恢复到1990—20...     

江西省域蒸发皿蒸发量变化特征及其成因

为了探讨气候变化对陆面水文过程的影响,该文利用江西省79个气象站1960－2005年的常规观测资料为基础,结合修正的Penman公式,得出了日照百分率、风速、实际水汽压、最低温度、最高温度变化对蒸发皿年蒸发量变化的贡献。结果表明：在过去46 a中,全流域的平均蒸发皿年蒸发量呈显著下降趋势,其速率为-4.57 mm/a;日照百分率和风速的减小是导致流域平均蒸发皿年蒸发量下降的主要因子,其贡献分别为-2.06、-2.58 mm/a,实际水汽压的减小、最低温度和最高温度的升高导致流域平均蒸发皿年蒸发量上升,但作用相对较小,分别为0.12、0.50、0.30 mm/a,各占观测的蒸发皿年蒸发量变化趋势的45.08%、56.46%、-2.63%、-10.94%、-6.57%。因此,影响江西省蒸发皿年蒸发量变化的气候因子的主次关系为：风速＞日照百分率＞最低温度＞最高温度＞实际水汽压。     

基于SPAC理论的田间腾发量计算模式

基于SPAC理论，从能量平衡方程与空气动力学方程出发，提出了根据气象条件、作物长势与土壤表面温湿度估计田间腾发量的计算模式。该方法假定作物叶片表面饱和并进行线性化处理，同时给出土壤表面水汽压的经验表达，通过冠层模型的求解可以分别计算出作物蒸腾量、棵间蒸发量与腾发量。利用土壤水分运动数值计算的结果，验证了该方法的可靠性。此外，还分析了该方法与Penman模式、Shuttleworth-Wallace模式之间的联系。由于模型所需的输入均可以通过常规的田间观测获得，该方法在生产与科研实践中具有一定的应用价值。     

基于系统动力学的黑河中游地区FAO Penman Monteith模型评价研究

研究利用系统动力学软件STELLA构建FAO Penman Monteith模型,进行系统动力学建模与生态建模相结合的尝试。研究发现,实际太阳辐射模拟值与GIS空间插值结果基本吻合,变化趋势一致;潜在蒸散发量估算值与SEBS模型估算值接近,基于时间序列的变化趋势基本相同,较好地反映了逐日蒸散发量的时间异质性;敏感性分析发现潜在蒸散发量对反照率、回归常数、辐射系数和研究区纬度值（取值范围为37°39°）变化不敏感;系统动力学在分析复杂系统动态、模拟不同条件下系统因子之间相互作用以及响应过程中具有明显优势;STELLA本身强大的建模功能及友好图形界面在生态学及相关研究领域中有广阔前景;多学科方法、多时空尺度、多物理过程相耦合的研究将是以后该领域研究的重点和趋势之一。     

新疆主要农作物生产水足迹计算分析

从农作物生产水足迹角度出发,基于彭曼公式结合CROPWAT软件计算,分析了2011年新疆13个地（州）主要农作物的生产水足迹情况。结果表明：新疆地区棉花的单位面积及单位质量需水量分别为8650 m3· hm－2、4．82 m3·kg－1,均大于小麦和玉米的需水量,是三种农作物中最耗水的作物;新疆主要农作物需水以蓝水为主,其中棉花的蓝水比重最高达93．31％,南疆地区蓝水利用量最大;2011年新疆全区主要农作物生产水足迹为2049．31×107m3,其中蓝水足迹为1651．65×107m3,绿水足迹为186．88×107m3,灰水足迹为210．78×107m3;巴州、阿克苏、喀什地区的作物生产水足迹总量较大,是水资源治理的主要地区。对于水资源缺乏的新疆地区,合理调整农作物的种植结构及减少化肥施用量,是落实最严格水资源管理制度的有效措施。