基于SIMDualKc模型估算西北旱区冬小麦蒸散量及土壤蒸发量

为研究西北旱区冬小麦蒸散和土壤蒸发规律,以及土壤蒸发比例与其影响因子的关系,利用2 a冬小麦小区控水试验实测数据,对SIMDual Kc模型进行了参数校正和验证,对比大型称重式蒸渗仪的实测蒸散量值(或水量平衡法计算值)与模型模拟值。用建立的模型模拟精度评价标准对模拟值和实测值的误差进行评价。用经参数校验的模型模拟冬小麦农田土壤蒸发,并与微型蒸渗仪的实测值进行对比。基于通径分析方法研究气象因子(最低气温、最高气温、平均相对湿度、2 m处风速、太阳辐射量)和作物因子(地面覆盖度)与土壤蒸发比例的关系。结果表明,该研究建立的模型模拟精度评价标准能够较为全面地评价模型精度;SIMDual Kc模型可以较好地模拟西北旱区不同灌溉制度下冬小麦蒸散量和土壤蒸发量的变化过程,且在模拟长时段累积值时具有较高精度;拔节-灌浆期是冬小麦的需水关键期,冬小麦全生育期土壤蒸发比例呈现出生长中期生长后期快速生长后期生长初期的规律;灌水仅在短时间内影响土壤蒸发,地面覆盖度是影响土壤蒸发的最主要因子;在实测数据不充足的情况下,可以将地面覆盖度和蒸散量作为输入变量,用该研究确定的土壤蒸发比例与地面覆盖度的回归模型计算土壤蒸发量,该模型在计算不同水分条件下冬小麦农田土壤蒸发量时表现出较高的计算精度,决定系数在0.721~0.902之间,可以作为计算土壤蒸发量的简便方法。研究可为西北旱区冬小麦农田节水和灌溉决策提供理论依据。     

由瞬时遥感蒸散量估算农田蒸散日总量的模式

在农田蒸散量日变化规律的基础上，导出了一个由瞬时遥感蒸散量估算农田蒸散日总量的计算模式。并用吴忠春小麦和民勤棉花的田间试验资料对导出的公式进行了验证。结果表明，利用真太阳时９：００～１５：００之间一日一次的瞬时遥感蒸散量由该模式可以较地的估算农田蒸散日总 量。     

农田水量平衡模型对作物根系吸水函数及蒸散公式的敏感性

以田间试验资料为基础,建立了一个农田水量平衡模型,探讨了它对作物根系吸水函数和蒸散公式的敏感性.结果表明.不同的根系吸水函数和蒸散公式对农田水量平衡模型的响应程度差异较大,根据与田间土壤水分实测结果比较,认为用Selim根系吸水函数和Penman-Monteith蒸散公式的组合模式能较好地模拟土壤水分变化过程.     

塔里木河流域白杨农田防护林蒸散量计算模式研究

在综合分析气候、植物生物学特性和土壤湿度三方面因素的基础上,利用多年的白杨农田防护林试验资料,建立了塔里木河流域白杨农田防护林蒸散量的计算模式,并利用白杨林实际蒸散量的测量值,对模式进行了验证。结果表明,该模式计算精度较高,可以作为计算塔里木河流域白杨农田防护林蒸散量的一种方法而使用。     

控制性交替隔沟灌溉对甜椒农田蒸散特征的影响

在张掖地区进行甜椒田间试验,利用农田水量平衡方法计算农田蒸散量,用微型棵间蒸发器测定不同沟灌方式的农田土壤棵间蒸发,在此基础上分析了不同沟灌方式下甜椒农田蒸散、土壤棵间蒸发、蒸发占蒸散的比例及其随叶面积指数和表层土壤含水量的变化关系、灌溉后土壤蒸发的变化过程.结果表明:交替隔沟灌溉在不影响作物蒸腾的条件下减少了表层土壤的湿润面积、减少了棵间土壤蒸发、提高了作物水分利用效率.     

应用Penman-Monteith公式和土壤湿度指数估算区域地表蒸散

准确计算地表蒸散对于水资源合理利用具有重要意义。Penman-Monteith公式具有坚实的理论基础,被广泛应用于计算地表蒸散,但表面阻抗计算的复杂性阻碍了其向区域应用的进一步推广。本文首先利用地表温度(Ts)-植被指数(Fv)特征空间计算土壤湿度指数,进而计算土壤阻抗,改进和发展了Penman-Monteith蒸散算法,简称为PM-SMI。将该算法与地表温度-植被覆盖特征空间蒸散算法以及Penman-Monteith系列另一种算法(PM-Yuan)进行比较。利用美国南部大平原12个波文比观测数据进行模型比较和验证。研究区域主要覆盖农田和草地,植被覆盖度较低。结果表明在瞬时和日值两个时间尺度PM-SMI整体上都优于其他两种算法,PM-SMI方法适合用于区域地表蒸散估算。     

基于能量平衡的华北平原农田蒸散量的估算

通过测定冬小麦主要生育期农田冠层能量平衡的各分量、少风晴天时冠层温度和气温日变化及每周叶面积指数,分析了农田冠层能量平衡日变化规律、各分量季节变化特征,并以波文比系统实测蒸散值为相对标准,基于遥感冠层表面温度和能量平衡原理,采用Brown-Rosenberg公式对农田蒸散进行了估算和验证。结果表明：考虑夜间能量平衡各分量变化时,土壤热通量只占净辐射的3%左右,且夜间潜热交换值均很小,都在零左右波动;采用Brown-Rosenberg公式引入遥感冠层温度后估算的蒸散量较波文比系统实测值稍大,但忽略土壤热通量和考虑土壤热通量相比,二者相对平均偏差分别为16%和10%左右,差别不大,说明拔节-灌浆期（LAI≥3）估算蒸散时可近似忽略土壤热通量和夜间农田蒸散量,利用Brown-Rosenberg公式估算区域蒸散可行,该方法适用于华北平原农田蒸散计算。研究结果为将Brown-Rosenberg公式引入作物模型、基于热红外遥感冠层表面温度计算区域蒸散和水分胁迫系数进行区域估产提供了地面试验依据。     

基于NOAA/AVH RR数据估算三江平原蒸散量研究初探

蒸散量是水资源相互转化过程中非常重要但又难以定量确定的要素之一.SEBS(Surface Energy BalanceSystem)模型是通过遥感数据计算区域蒸散量的重要模型,该模型可以在较少地面信息的情况下获得蒸散量的区域分布信息,同时具有较高的精度.采用SEBS模型,利用NOAA/AVHRR数据对我国重要的商品粮基地三江平原区域蒸散发量进行了研究,并通过实测数据对估算结果进行了验证.结果表明:从时间分布来看,三江平原蒸散量总体上表现为从4月开始逐渐上升,7月达到最高值,8月后不断下降.在此基础上,探讨了三江平原蒸散量时间分布的原因.同时,结合研究区的土地利用类型,对三江平原区域蒸散量空间分布进行了分析,各种土地利用类型生长季平均蒸散量从大到小可以排列为:林地>水域>湿地>水田>旱田>草地>居工地.     

估算阿拉尔灌区农田白杨防护林4—10月蒸散量的经验模型

植物蒸散量主要受能量、土壤含水量和植物生物学特性影响。在多年野外试验基础上,运用数理统计方法建立了估算阿拉尔灌区农田白杨防护林2003—2007年4—10月蒸散量的经验模型。分析结果表明,白杨农田防护林蒸散量与水面蒸发量的比与根系层土壤含水率的关系服从Logistic曲线。该模式仅需常规气象与土壤湿度资料,计算简便,具有一定的应用价值。     

相对蒸散用于冬小麦水分亏缺诊断及灌溉决策初步探讨

在建立农田相对蒸散计算的指数模型基础上，以模型物理意义的分析为手段、以冬小麦对水分亏缺的生物反应为依据，得出了相对蒸散用于冬小麦水分亏缺诊断和灌溉决策的初步指标：（１）相对蒸散≤５０％，冬小麦水分亏缺明显；（２）必须灌溉的指标下限值为相对蒸散＝５０％，节水灌溉的灌溉定额上限值为相对蒸散＝８０％，丰水灌溉的灌溉定额上限值为相对蒸散＝９４％。     

双源蒸散发模型估算潜在蒸散发量的对比

潜在蒸散发取决于气候条件与下垫面植被覆盖状况,是农田及流域水循环研究的重要内容。该文针对现有的3种估算潜在蒸散发的双源模型(层状模型、块状模型、混合型模型),设定不同的下垫面植被覆盖状况,较为详细地比较了3种模型在不同植被覆盖条件下的潜在蒸散发估算能力,并对其区分土壤表面潜在蒸发与植被冠层潜在蒸腾的合理性进行了评价。结果表明,混合双源模型较层状模型和块状模型具有更好的模拟效果,能够适用于更广的下垫面植被覆盖状况。     

A model for estimating soil moisture changes as an aid to irrigation scheduling and crop water-use studies: I. Operational details and description

Abstract. A model was developed to predict evapotranspiration and soil moisture changes, which could be used either for scheduling irrigation or crop water-use studies. The general form of the model is reported here, and its validation for sugarbeet and potatoes is described in a subsequent paper. The soil characteristics required are depth of topsoil, texture or available water capacity of topsoil and subsoil, and whether a significant slope exists. The plant characteristics required are species and planting date. Meteorological data used to calculate potential evapotranspiration are obtained from the Meteorological Office synoptic network, but local rainfall data are preferred.
The model estimates potential evapotranspiration of a reference crop, and uses this to model canopy and root development for all crops at each location. Available options allow for observed data on canopy or root development to be incorporated into the simulations. Estimates of potential evapotranspiration for each crop are then adjusted to allow for the effects of water stress, taking soil characteristics, root depth and evapotranspiration demand into account.
The model enables growers to reduce the risks of under- or over-watering their crops and has proved successful in irrigation management.     

Evaluation of canopy temperature—evapotranspiration models over various crops

Canopy temperatures, when measured remotely, offer a method of estimating evapotranspiration with surface energy balance models. Equations which have been developed by others have been evaluated only at a limited number of locations and with a few crops. Our study was conducted at several locations with weighing lysimeters with a variety of crops around the United States: Brawley, CA; Temple, TX; Lincoln, NE; St. Paul, MN; Fargo, ND; Kimberly, ID; and Davis, CA, to evaluate evapotranspiration utilizing canopy temperature as an input into the surface energy balance. The results show that evapotranspiration calculated from the aerodynamic resistance form of the surface energy balance was well correlated with lysimeter measurements at all locations. The errors using the surface energy balance were less than 10% in all cases for full ground cover. The Bartholic—Namken—Wiegand method was more closely coupled to net radiation than canopy temperature.Under partial canopy cover, differences between the two models were apparent. The Bartholic—Namken—Wiegand model overpredicted when the actual evapotranspiration was above 200 W m^?2 because of its insensitivity to surface temperature. However, the surface energy balance model exhibited only a slight overprediction above 200 W m^?2 when a weighed composite surface temperature (representative of bare soil and crop temperature) was used. This small overprediction could be overcome by considering the soil heat flux term. There was no location bias in the surface energy balance model, which shows that it should work well at other locations.     

非水分胁迫条件下作物腾发的模拟研究

建立了一个充分供水条件下的作物腾发量计算模型ＮＷＳＥ（Ｎｏｎ－Ｗａｔｅｒ Ｓｔｒｅｓｓ Ｅｖａｐｏ－ｔｒａｎｓｐｉｒａｔｉｏｎ）并用田间实验资料进行了验证。模型将作物冠层蒸腾和土壤蒸发作为一个耦联的整体来考虑,可以同时计算棵间蒸发和作物蒸腾。田间实验资料对ＮＷＳＥ模型验证结果表明地表温度模拟值与观测值吻合良好。利用ＮＷＳＥ模型和Ｐｅｎｍａｎ－Ｍｏｎｔｅｉｔｈ公式以及常规气象资料分别计算了作物的最大腾发量。计算结果比较表明,在叶面积指数较小时,ＮＷＳＥ模型计算结果与Ｐｅｎｍａｎ－Ｍｏｎｔｅｉｔｈ计算结果存在差别。在叶面积指数较大时,二者的一致性较好。     

额济纳绿洲草地蒸散系数研究

联合国粮农组织推荐的蒸散计算方法中,蒸散系数是计算实际蒸散必不可少的参数。本文从蒸散系数的定义出发,在2005年额济纳绿洲生长季连续观测的基础上,运用波文比能量平衡法计算额济纳绿洲草地的实际蒸散量,利用FAO 56Penman-Monteith模型计算草地的参考蒸散,将实际蒸散与参考蒸散相除即得到额济纳绿洲草地的蒸散系数。通过研究发现:生长季草地的蒸散量(ETc)为446.96mm,从生长季初期开始,草地的蒸散量开始增加,在6月后半月达到最大值6.724mm/d,此后蒸散量开始快速下降,在生长季末期达到最低值1.215mm/d;蒸散系数(Kc)呈现出与蒸散量(ETc)相同的变化趋势,自生长季初期开始蒸散系数快速上升,在6月后半月达到生长季最大值0.623,之后随着草地生长减缓,蒸散系数快速下降,直至生长季末期草地停止生长。对额济纳绿洲草地蒸散系数的计算可以为该地区准确估算草地生态需水量提供依据。     

ECOWAT—A model for ecosystem evapotranspiration estimation

In recent years, the availability of near real-time and forecast standardized reference evapotranspiration (E₀) has increased dramatically. Use of the E₀ information in conjunction with calibration coefficients that adjust for differences between the vegetation and the reference surface provides a method to greatly improve the estimates of actual evapotranspiration (E_a) from landscapes (or ecosystems). Difficulties in estimating evapotranspiration (ET) of well-watered vegetation in an ecosystem depend on local advection and edge effects, wide variations in radiation resulting from undulating terrain, wind blockage or funnelling, and differences in temperature due to spatial variation in radiation, wind, etc. Estimating the ET of an ecosystem that is water stressed is even further complicated because of stomatal closure and reduced transpiration. The Ecosystem Water Program (ECOWAT) was developed to help improve estimates of E_a of ecosystems by accounting for microclimate, vegetation type, plant density, and water stress. The first step in estimating E_a is to calculate E₀ using monthly climate data from one representative weather station in the study area. Then, local microclimate data are used to determine a standardized reference evapotranspiration for the local microclimate (E_m). The ratio K_m = E_m/E₀ is calculated and applied as a microclimate correction factor to estimate E_m. The product of E_m and a vegetation coefficient (K_v = E_v/E_m) is used to estimate the evapotranspiration of the ecosystem vegetation (E_v) under well-watered conditions with a full-canopy cover within the same microclimate. Next, a coefficient for plant density (K_d), which is based on the percentage ground cover, is used to adjust the full-canopy E_v to the evapotranspiration of a sparse canopy from a well-watered ecosystem (E_w). A stress (K_s) coefficient, which varies between 1.0 with no stress to 0.0 with full stress, is determined as a function of available water in the root zone. The predicted actual ecosystem evapotranspiration (E_p) is estimated as E_p = E_w × K_s. In this paper, we present how the ECOWAT model works and how it performs when the predicted actual evapotranspiration (E_p) is compared with measured actual evapotranspiration (E_a) collected in several Mediterranean ecosystems (three in Italy and two in California) over a number of years. The potential use of ECOWAT in integrated fire danger systems is discussed.     

河套灌区玉米和向日葵ET的S-I估算模型关键参数分析

农田作物蒸散的快速评估对于灌区水资源最优调配和灌溉实时管理至关重要。简化S-I模型综合考虑作物冠层温度、田间气象参数和作物特征参数,可以进行实时农田作物ET的精确估算。该文利用河套灌区解放闸灌域2015—2016年2 a田间试验观测资料,对主要农作物玉米和向日葵的S-I模型中2个特征参数分别进行了率定和验证,并分析了模型蒸散估算的相关影响因素。结果表明:1)利用S-I简化模型可以对玉米和向日葵田间进行作物日蒸散量(daily evapotranspiration,ET_d)的估算,在该地区以13:00时率定和验证结果最优。在玉米主要生育期(6—8月),利用S-I模型估算ET_d可以达到较高的精度;而在7—8月,采用模型估算向日葵地ET_d也可以达到很高的精度;2)S-I模型中特征参数值受风速、地表覆盖度、表面粗糙度等因素的影响,不同作物其值不同。13:00时玉米S-I模型中特征参数值皆为负值,而向日葵中特征参数值为1正1负,进而影响模型估算精度。叶面积指数变化对特征参数值大小的影响在玉米和向日葵田块呈相反的趋势,而风速的影响则为一致。推荐13:00时率定的参数值可以在河套灌区玉米和向日葵作物需水量估算时直接应用。     

基于气象-生理的夏玉米作物系数及蒸散估算

准确估算作物系数对预测作物实际蒸散量和制定精准的灌溉计划至关重要。为反映作物逐日作物系数变化,综合考虑气象和生物因子对作物生长的共同影响,采用五道沟水文实验站大型蒸渗仪夏玉米实测蒸散及气象数据,基于地温及叶面积指数建立了气象-生理双函数乘法模型,并结合梯度下降法对模型进行了精度优化。结果表明,在整个玉米生长期中,作物系数实测值和计算值平均绝对误差为0.12,均方根误差为0.15,相关性为0.91,蒸散量实测值与计算值平均绝对误差为1.0 mm/d,均方根误差为4.5 mm/d,相关性为0.75。该模型计算的全生育期蒸散量准确率(误差在2～3 mm/d以内)相比使用联合国粮农组织(FAO)推荐的作物系数计算所得准确率提高了3倍以上,可更精确用于作物系数及蒸散量计算。