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蒸发量的计算及其动态变化特征分析 总被引：1，自引：0，他引：1
应用彭曼公式对蒸发量进行了气候学计算，并对近40a灯塔站蒸发量的动态变化趋势进行了年和生长季等不同时段的分布规律分析，以便为农业水分分析、农业气候影响评价、作物水分平衡等提供气候依据。 相似文献
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作物叶茎蒸腾与株间土壤蒸发之和叫蒸散。作物各生育期的蒸散量直接反映了作物的需水情况,对于研究农田水分平衡、确定旱涝指标以及农业气候区划等都有重要意义。 五十年代初,彭曼根据能量平衡方程,导出一个蒸散量计算公式,但由于所涉及的物理量多而且难于精确测定,故其应用受到限制。布雷特莱—泰勒尔在彭曼公式的基础上,根据统计分析,略去了土壤热通量等对蒸散影响很小的项,建立了如下的计算模式; 相似文献
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水面蒸发量的一种气候学计算方法 总被引：15，自引：1，他引：15
用北京日射站和官厅蒸发站的辐射和蒸发资料对彭曼公式进行订正,得出修正公式 E_0=(ΔH_0+γE_α)/(Δ+γ) H_0=1/59[0.95Q_A(0.167+0.583n/N)-σT_a~4(0.32-0.26e_a~(1/2))(0.30+0.70n/N)] E_a=0.13(e_a-e_d)(1+0.77u),其中H_0是表示为蒸发量单位的辐射平衡,E_a是由风速和饱和差决定的“干燥力”。 自由水面的蒸发量E可用下式表示 E=E_0-F/L,其中F是水面向下的热通量,在升温季节为正值,在降温季节为负值。由于缺少水温梯度观测资料,F不能直接计算。本文建议,对升温或降温季节分别建立水面蒸发E倚蒸发势E_0的回归方程。得出北京地区各月蒸发量的计算公式如下 0.963 E_0-7.0 4—7月 E=0.902 E_0+26.0 9—10月 E_0 8月 相似文献
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《中国主要农作物气候资源图集》由中国农业科学院编绘,气象出版社出版,现已正式发行。 本图集主要是为合理利用农业气候资源和作物品种资源,为农作物合理布局和发展农业生产提供农业气候依据;同时为农业领导部门提供了全国各地主要农作物各生育期的农业气候状况,可作为指导农业生产的参考;并为农业及有关专业的科研和教学单位提供所需的基础资料。 相似文献
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试论华北半湿润半干旱地区降水资源的农业气候评价——以海河平原为例 总被引：2，自引：0，他引：2
本文从农田水分平衡观点出发,用农业气候-水文-水文地质方法计算了有效降水量,并且分析了它的时问分布结构。在此基础上,我们进行了农作物需水盈亏分析,并指出:在海河平原地区,冬小麦(400斤/亩)亏水290毫米左右,夏玉米(500斤/亩)亏水100毫米左右。 相似文献
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在本文中作者制作了我国东半部水量平衡三要素的分布图,并进行了扼要的分析和讨论。各地的多年平均降水量(r)是根据实际观测的数据。多年平均自然蒸发量(z)的数值是根据下列布德科公式计算得来的(参考文献[6]):z=[R_0r/LthrL/R_0(1-chR_0/rL+shR_0/Lr)]~(1/2),式中 th,ch,sh 各代表双曲线正切、余弦及正弦;而 R_0/L=z_0是代表水源不缺条件下湿润地面的最大可能蒸发量,其数值根据作者前文(文献[1])计算的结果。多年平均迳流量(f)则根据水量平衡方程 f=r-z 间接求得。除了计算年蒸发量的分布以外,本文还计算出各季蒸发量的数值,但其精确度自然不及年量的计算。在本文中,还按17个不同流域进行水量平衡的计算和讨论,并绘成多年平均年迳流系数分布图一幅,其结果可与文献[9]相比较。 相似文献
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Chuan Zhang Haofang Yan Haibin Shi Hideki Sugimoto 《Meteorology and Atmospheric Physics》2013,121(3-4):207-214
A field experiment was conducted in a maize field in 2006 in an arid area of the Yellow River Basin in China. The daytime evapotranspiration (ETc) and soil evaporation beneath the maize canopy (E g) were measured by Bowen ratio energy balance method and micro-lysimeters, respectively. The results showed that the total ETc during maize growth season was 696 mm, and the maximum values occurred at about 90–140 days after sowing. The crop coefficient (K c), which was calculated from the ratio of ETc to reference evapotranspiration (ET0), was quite different from the values reported by other researchers in similar climate areas, with average values of 0.34, 0.47, 1.0 and 0.9 for initial, development, mid-season and late-season stages, respectively. High correlations between leaf area index (LAI) and average K c for every 4 days were obtained. The total E g was 201.4 mm with average values ranged from 0.92 to 2.05 for four growth stages of maize; and accounted for around 28.9 % of ETc. The ratio E g/ETc showed high negative relationship with LAI. These results were very important in precise management of irrigation for maize in Yellow River Basin areas. 相似文献
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Evapotranspiration is a major component of both the energy and water balances of wetland tundra environments during the thaw season. Reliable estimates of evapotranspiration are required in the analysis of climatological and hydrological processes occurring within a wetland and in interfacing the surface climate with atmospheric processes. Where direct measurements are unavailable, models designed to accurately predict evapotranspiration for a particular wetland are used.This paper evaluates the performance, sensitivity and limitations of three physically-based, one-dimensional models in the simulation of evaporation from a wetland sedge tundra in the Hudson Bay Lowland near Churchill, Manitoba. The surface of the study site consists of near-saturated peat soil with a sparse sedge canopy and a constantly varying coverage of standing water. Measured evaporation used the Bowen ratio energy balance approach, to which the model results were compared. The comparisons were conducted with hourly and daily simulations.The three models are the Penman-Monteith model, the Shuttleworth-Wallace sparse canopy model and a modified Penman-Monteith model which is weighted for surface area of the evaporation sources.Results from the study suggest that the weighted Penman-Monteith model has the highest potential for use as a predictive tool. In all three cases, the importance of accurately measuring the surface area of each evaporation source is recognized. The difficulty in determining a representative surface resistance for each source and the associated problems in modelling without it are discussed.
List of Symbols
Models BREB Bowen ratio energy balance - P-M Penman-Monteith combination - S-W Shuttleworth-Wallace combination - W-P-M Weighted Penman-Monteith combination Other AE Available energy-all surfaces - AE c Available energy-canopy (S-W, W-P-M) - AE s Available energy-bare soil (S-W, W-P-M) - AE w Available energy-open water (W-P-M) - C p Specific heat of air - D Vapor pressure deficit - DAI Dead area index - FAI Foliage area index - LAI Leaf area index - Q * Net radiation - Q e Latent heat flux-total - Q ec Latent heat flux-canopy (S-W, W-P-M) - Q es Latent heat flux-bare soil (S-W, W-P-M) - Q ew Latent heat flux-open water (W-P-M) - Q g ground heat flux - Q h Sensible heat flux - S Proportion of area in bare soil - W Proportion of surface in open water - r a Aerodynamic resistance (P-M, W-P-M) - r c Canopy resistance - r s Generalized optimized surface resistance - r st Stomatal resistance - r c a Bulk boundary layer resistance (S-W) - r s a Aerodynamic resistance below mean canopy level (S-W) - r s s Soil surface resistance (S-W, W-P-M) Greek Bowen ratio - Psychrometer constant - Air density - Slope of saturation vapour pressure vs temperature curve 相似文献13.
Single and dual crop coefficients and crop evapotranspiration for wheat and maize in a semi-arid region 总被引：1，自引：1，他引：0
In this study, weighing lysimeters were used to investigate the daily crop coefficient and evapotranspiration of wheat and maize in the Fars province, Iran. The locally calibrated Food and Agriculture Organization (FAO) Penman–Monteith equation was used to calculate the reference crop evapotranspiration (ETo). Micro-lysimetry was used to measure soil evaporation (E). Transpiration (T) was estimated by the difference between crop evapotranspiration (ETc) and E. The single crop coefficient (K c) was calculated by the ratio of ETc to ETo. Furthermore, the dual crop coefficient is composed of the soil evaporation coefficient (K e) and the basal crop coefficients (K cb) calculated from the ratio of E and T to ETo, respectively. The maximum measured evapotranspiration rate for wheat was 9.9 mm?day?1 and for maize was 10 mm?day?1. The total evaporation from the soil surface was about 30 % of the total wheat ETc and 29.8 % of total maize ETc. The single crop coefficient (K c) values for the initial, mid-, and end-season growth stages of maize were 0.48, 1.40, and 0.31 and those of wheat were 0.77, 1.35, and 0.26, respectively. The measured K c values for the initial and mid-season stages were different from the FAO recommended values. Therefore, the FAO standard equation for K c-mid was calibrated locally for wheat and maize. The K cb values for the initial, mid-, and end-season growth stages were 0.23, 1.14, and 0.13 for wheat and 0.10, 1.07, and 0.06 for maize, respectively. Furthermore, the FAO procedure for single crop coefficient showed better predictions on a daily basis, although the dual crop coefficient method was more accurate on seasonal scale. 相似文献
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Hossein Tabari P. Hosseinzadeh Talaee Hirad Abghari 《Meteorology and Atmospheric Physics》2012,116(3-4):147-154
Estimation of pan evaporation (E pan) using black-box models has received a great deal of attention in developing countries where measurements of E pan are spatially and temporally limited. Multilayer perceptron (MLP) and coactive neuro-fuzzy inference system (CANFIS) models were used to predict daily E pan for a semi-arid region of Iran. Six MLP and CANFIS models comprising various combinations of daily meteorological parameters were developed. The performances of the models were tested using correlation coefficient (r), root mean square error (RMSE), mean absolute error (MAE) and percentage error of estimate (PE). It was found that the MLP6 model with the Momentum learning algorithm and the Tanh activation function, which requires all input parameters, presented the most accurate E pan predictions (r?=?0.97, RMSE?=?0.81?mm?day?1, MAE?=?0.63?mm?day?1 and PE?=?0.58?%). The results also showed that the most accurate E pan predictions with a CANFIS model can be achieved with the Takagi–Sugeno–Kang (TSK) fuzzy model and the Gaussian membership function. Overall performances revealed that the MLP method was better suited than CANFIS method for modeling the E pan process. 相似文献
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Summary Dryland agricultural cropping systems emphasize sustaining crop yields with limited use of fertilizer while conserving both rain water and the soil. Conservation of these resources may be achieved with management systems that retain residues at the soil surface simultaneously modifying both its energy and water balance. A conservation practice used with cotton grown on erodible soils of the Texas High Plains is to plant cotton into chemically terminated wheat residues. In this study, the partitioning of daily and seasonal evapotranspiration (E
t) into soil and plant water evaporation was compared for a conventional and a terminated-wheat cotton crop using the numerical model ENWATBAL. The model was configured to account for the effects of residue on the radiative fluxes and by introducing an additional resistance to latent and sensible heat fluxes derived from measurements of wind speed and vapor conductance from a soil covered with wheat-stubble. Our results showed that seasonalE
t was similar in both systems and that cumulative soil water evaporation was 50% ofE
t in conventional cotton and 31% ofE
t in the wheat-stubble cotton. Calculated values ofE
t were in agreement with measured values. The main benefit of the wheat residues was to suppress soil water evaporation by intercepting irradiance early in the growing season when the crop leaf area index (LAI) was low. In semiarid regions LAI of dryland cotton seldom exceeds 2 and residues can improve water conservation. Measured soil temperatures showed that early in the season residues reduced temperature at 0.1 m depth by as much as 5°C and that differences between systems diminished with depth and over time. Residues increased lint yield per unit ofE
t while not modifying seasonalE
t and reducing cumulative soil water evaporation.With 8 Figures 相似文献
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作物最大可能蒸散考虑了作物及当地地表状况,为当地地表实际覆盖情况下实际蒸散的理论上限值,能客观分析作物对水分的需求程度和农业干旱状况。基于遥感（叶面积指数和地表反照率）数据和逐日气象数据,利用Penman-Monteith公式,计算黄淮海平原小麦种植区27个气象站冬小麦生育期2000-2015年逐日蒸散,提取得到冬小麦生育期逐日最大可能蒸散数据集,并分析其时空变化特征及成因。结果表明:与联合国粮农组织（FAO）单作物系数法计算的最大可能蒸散Ek对比,区域平均最大可能蒸散Ec的时间变化趋势与Ek一致,空间分布上Ec符合客观实际。黄淮海平原冬小麦全生育期、越冬期和返青-拔节期Ec均呈北低南高的分布特征,日平均值分别为1.99 mm,0.44 mm和2.75 mm;其余3个生育期（越冬前、抽穗期、乳熟-成熟期）在空间分布上差异不大,日平均值分别为1.23 mm,4.71 mm和3.74 mm。冬小麦不同生育期（含全生育期）Ec的空间分布主要受叶面积指数分布特征的影响,二者呈显著正相关关系。 相似文献
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P. Steduto M. Todorovic A. Caliandro P. Rubino 《Theoretical and Applied Climatology》2003,74(3-4):217-225
Summary ?The performance of the Penman-Monteith (PM) equation to estimate daily reference evapotranspiration (ETO) was investigated by attributing three distinct features to the canopy resistance (r
c): (i) r
c constant at 70 s m−1 (Allen et al., 1998; FAO Irrigation and Drainage Paper n. 56), (ii) r
c variable as linear function of a critical resistance r
c, depending on weather variables and empirical parameters relating r
c to r
* (Katerji and Perrier, 1983; Agronomie, 3[6]: 513–521) and (iii) r
c variable as a mechanistic function of weather variables only (Todorovic, 1999; J. Irrig. Drainage Eng., ASCE, 125[5]: 235–245). Daily weather and grass lysimeter data, measured for a period of seven years at Policoro (Southern
Italy), were used. The results confirmed the relative robustness of the PM method with constant r
c while better estimates were obtained only when variable r
c was used. The mechanistic approach of Todorovic (1999) provided the best estimates, while the approach of Katerji and Perrier
(1983), with empirically derived parameters, has shown to be not conservative enough to be extended to different locations
without calibration.
Received January 2, 2002; revised October 31, 2002; accepted December 7, 2002 相似文献
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Eugene Yee R. Chan P. R. Kosteniuk G. M. Chandler C. A. Biltoft J. F. Bowers 《Boundary-Layer Meteorology》1994,67(1-2):11-39
A meandering plume model that explicitly incorporates the effects of small-scale structure in the instantaneous plume has been formulated. The model requires the specification of two physically based input parameters; namely, the meander ratio,M, which is dependent on the ratio of the meandering plume dispersion to the instantaneous relative plume dispersion and, a relative in-plume fluctuation measure,k, that is related inversely to the fluctuation intensity in relative coordinates. Simple analytical expressions for crosswind profiles of the higher moments (including the important shape parameters such as fluctuation intensity, skewness, and kurtosis) and for the concentration pdf have been derived from the model. The model has been tested against some field data sets, indicating that it can reproduce many key aspects of the observed behavior of concentration fluctuations, particularly with respect to modeling the change in shape of the concentration pdf in the crosswind direction.List of Symbols
C
Mean concentration in absolute coordinates
-
C
r
Mean concentration in relative coordinates
- C0
Centerline mean concentration in absolute coordinates
- C
r,0
Centerline mean concentration in relative coordinates
-
f
Probability density function of concentration in absolute coordinates
-
f
c
Probability density function of plume centroid position
-
f
r
Probability density function of concentration in relative coordinates
-
i
Absolute concentration fluctuation intensity (standard deviation to mean ratio)
-
i
r
Relative concentration fluctuation intensity (standard deviation to mean ratio)
-
k
Relative in-plume fluctuation measure:k=1/i
r
2
-
K
Concentration fluctuation kurtosis
-
M
Meander ratio of meandering plume variance to relative plume variance
-
S
Concentration fluctuation skewness
-
x
Downwind distance from source
-
y
Crosswind distance from mean-plume centerline
-
z
Vertical distance above ground
-
Instantaneous (random) concentration
-
Crosswind dispersion ofnth concentration moment about zero
-
ny
Mean-plume crosswind (absolute) dispersion
-
y
Plume centroid (meandering) dispersion in crosswind direction
-
y,c
Instantaneous plume crosswind (relative) dispersion
-
Normalized mean concentration in absolute coordinates:C/C
0
-
Particular value taken on by instantaneous concentration, 相似文献
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A model for predicting actual evapotranspiration under soil water stress in a Mediterranean region 总被引：1，自引：0，他引：1
G. Rana N. Katerji M. Mastrorilli M. El Moujabber 《Theoretical and Applied Climatology》1997,56(1-2):45-55
Summary In this paper a model for estimating actual evapotranspiration is developed and tested for field crops (grain sorghum and sunflower) maintained under water stress conditions. The model is based on the Penman-Monteith formulation of ET in which canopy resistance (r
c) is modeled with respect to the crop water status and local climatological conditions. The model was previously tested on reference grass; in this last case no reference was made to soil water conditions andr
c was modeled only as a function of climatological parameters. Herer
c is expressed as a function of available energy, vapour pressure deficit, aerodynamic resistance and crop water status by means of predawn leaf water potential. Results, obtained with various crop water stress intensities, show that, on a daily scale, calculated ET is 98% and 95% of the measured ET for sorghum and sunflower respectively. The correlation between daily calculated and measured ET is very high (r
2 = 0.95 for sorghum andr
2 = 0.98 for sunflower). On an hourly scale, the model works very well when the crops were not stressed and during the senescence stage. In case of weak and strong stress the model has to be used with some precautions.With 9 Figures 相似文献
20.
E. Linacre 《Theoretical and Applied Climatology》1993,48(1):41-48
Summary The evaporation of deep crops such as forests is usually considered in terms of the two-resistance Penman-Monteith model, though this conflates two of the three resistances actually involved, i.e. the canopy resistancer
c
between the transpiring leaves and the top of the canopy, and the resistancer
s
due to the stomates of the leaves. A review of the literature on these and the aerodynamic resistancer
a
(between the crop and the atmosphere) shows how distinctly different they are, and therefore how inappropriate it is to lump any two together.Once the soil has dried substantially,r
s
depends approximately onM
–2, whereM is the fractional available soil moisture.As regards grassed surfaces,r
a
is 300/u s m–1, whereu is the wind speed at 2 m.With 2 Figures 相似文献