陆面生态过程的一维数值模拟

建立了一个研究大气、植被、土壤相互作用的传播模式。模式是由多层大气模式、多层土壤模式和植被模式通过界面上能量、水汽传输平衡方程耦合而成。对植被和土壤的不同性质,进行了一系列的数值试验。结果表明,不同的植被覆盖以及降水等因子会对大气、植被、地表界面上能量、水汽传输以及热状态产生显著的影响。此模式还可以耦合进中尺度模式用以研究非均匀区域陆面过程和大气的相互作用。     

半干旱区陆面模式参数对水分循环的敏感性研究

植被覆盖对陆气之间物质和能量交换过程具有极其重要的影响,但植被覆盖对于交换过程的影响因子很多,关系复杂.作者研究了各种植被因子对陆气之间水分循环的作用和相对重要性.首先通过单点NO-AH模式对吉林通榆农田下垫面2004年土壤和边界层各物理量进行模拟,并与观测结果比较和评价,肯定了单点NOAH模式模拟能力.使用这一模式进行敏感试验,将与植被有关的参数分别在其取值范围取较大与较小值,比较水分循环各物理量如土壤湿度、土壤蒸发、植被蒸腾等的变化情况.试验表明在各参数中植被气孔阻抗、根系深度、土壤湿度初值和反照率对水分循环的影响较大,而叶面积指数、粗糙度和冠层阻抗则影响较小.     

Impact of Land Surface Heterogeneity on Mesoscale Atmospheric Dispersion

Prior numerical modelling studies show that atmospheric dispersion is sensitive to surface heterogeneities, but past studies do not consider the impact of a realistic distribution of surface heterogeneities on mesoscale atmospheric dispersion. While these focussed on dispersion in the convective boundary layer, the present work also considers dispersion in the nocturnal boundary layer and above. Using a Lagrangian particle dispersion model (LPDM) coupled to the Eulerian Regional Atmospheric Modeling System (RAMS), the impact of topographic, vegetation, and soil moisture heterogeneities on daytime and nighttime atmospheric dispersion is examined. In addition, the sensitivity to the use of Moderate Resolution Imaging Spectroradiometer (MODIS)-derived spatial distributions of vegetation characteristics on atmospheric dispersion is also studied. The impact of vegetation and terrain heterogeneities on atmospheric dispersion is strongly modulated by soil moisture, with the nature of dispersion switching from non-Gaussian to near-Gaussian behaviour for wetter soils (fraction of saturation soil moisture content exceeding 40%). For drier soil moisture conditions, vegetation heterogeneity produces differential heating and the formation of mesoscale circulation patterns that are primarily responsible for non-Gaussian dispersion patterns. Nighttime dispersion is very sensitive to topographic, vegetation, soil moisture, and soil type heterogeneity and is distinctly non-Gaussian for heterogeneous land-surface conditions. Sensitivity studies show that soil type and vegetation heterogeneities have the most dramatic impact on atmospheric dispersion. To provide more skilful dispersion calculations, we recommend the utilisation of satellite-derived vegetation characteristics coupled with data assimilation techniques that constrain soil-vegetation-atmosphere transfer (SVAT) models to generate realistic spatial distributions of surface energy fluxes.     

Formulation and verification of a land surface parameterization for atmospheric models

The need for a well-defined lower boundary condition for atmospheric numerical models is well documented. This paper describes the formulation of a land surface parameterization, which will be used in atmospheric boundary-layer and mesoscale numerical models. The land surface model has three soil layers for the prediction of soil moisture and soil temperature. Model soil properties depend on soil texture and moisture content. A homogeneous distribution of vegetation is also included, so that transpiration may be included, as well as the interception of precipitation by vegetation elements. The simulated vegetation also affects the mean surface albedo and roughness characteristics.First ISLSCP Field Experiment (FIFE) data are used to verify the model. Three cases during the growing season were chosen, each case having different amounts of vegetation cover. Stand alone simulations, where observations of atmospheric and radiation variables are input to the land surface model, were performed. These simulations show that the model is able to reproduce observed surface energy budgets and surface temperatures reasonably well. The RMS differences between modeled and obsered turbulent fluxes of heat and moisture are quite comparable to those reported by more detailed land surface models.     

陆面模式中土壤湿度影响蒸散参数化方案的评估

本文将四个常见陆面模式CLM3.5（Community Land Model Version 3.5）、Noah_LSM（The Noah Land Surface Model）、VIC（Variable Infiltration Capacity）以及SSiB（The Simplified Simple Biosphere Model）中土壤湿度影响蒸散的参数化方案进行简化,并利用实验观测资料对不同参数化方案进行评估,探究不同陆面模式对土壤湿度与蒸散关系的模拟差异,从而为提高模式的模拟能力提供依据。结果表明,（1）CLM与SSiB中计算土壤湿度影响裸土蒸发的参数化方案较Noah_LSM和VIC更接近真实的物理过程,同时CLM与SSiB模式中土壤湿度对蒸发的影响程度较Noah_LSM和VIC大;而对于下垫面有植被条件下的蒸散而言,CLM中包含了植被光合作用、呼吸作用等生物物理学过程,与实际情况更为接近,并且CLM与SSiB中土壤湿度对植被蒸散的影响程度大于VIC,Noah_LSM最低;（2）根据干旱区、半干旱区、半湿润区以及湿润区各站点的分析可知,CLM、SSiB与Noah_LSM中土壤湿度影响蒸散的参数化方案的拟合效果较VIC好,同时在部分站点CLM与SSiB的参数化方案稍优于Noah_LSM。区域之间比较说明,四个模式对干旱半干旱区的模拟效果明显较半湿润区和湿润区好。     

Sensitivity of an ecosystem model to hydrology and temperature

We tested the sensitivity of a dynamic ecosystem model (LPJ-GUESS) to the representation of soil moisture and soil temperature and to uncertainties in the prediction of precipitation and air temperature. We linked the ecosystem model with an advanced hydrological model (JULES) and used its soil moisture and soil temperature as input into the ecosystem model. We analysed these sensitivities along a latitudinal gradient in northern Russia. Differences in soil temperature and soil moisture had only little influence on the vegetation carbon fluxes, whereas the soil carbon fluxes were very sensitive to the JULES soil estimations. The sensitivity changed with latitude, showing stronger influence in the more northern grid cell. The sensitivity of modelled responses of both soil carbon fluxes and vegetation carbon fluxes to uncertainties in soil temperature were high, as both soil and vegetation carbon fluxes were strongly impacted. In contrast, uncertainties in the estimation of the amount of precipitation had little influence on the soil or vegetation carbon fluxes. The high sensitivity of soil respiration to soil temperature and moisture suggests that we should strive for a better understanding and representation of soil processes in ecosystem models to improve the reliability of predictions of future ecosystem changes.     

江苏省土壤湿度观测资料与再分析资料对比分析研究

利用江苏省2010—2015年的60个站点土壤湿度观测资料,对欧洲中心ERA-Interim再分析资料(ERA)和美国宇航局再分析资料(MERRA)的两套土壤湿度数据在江苏地区的可靠性进行了评估。结果表明:相比于ERA再分析资料,MERRA较好地再现出江苏省次表层年平均土壤湿度的空间分布特征,但是两种资料的次表层和深层土壤湿度的数值均小于观测。ERA和MERRA基本都能揭示出江苏省次表层土壤湿度的季节变化特征,但是深层土壤湿度与观测仍有较大差距。在时间演变方面,ERA次表层土壤湿度与站点观测在研究时段内较为接近,EOF分析揭示出1979—2016年江苏省次表层土壤湿度存在区域一致型与南北偶极型两个主要的年代际变率模态。但是对于深层土壤湿度时间演变而言,两种再分析资料都与观测有较大的差距。总体而言,再分析资料的次表层土壤湿度与站点观测较为接近,但是由于再分析资料陆面模式中地下水等影响深层土壤湿度的关键过程刻画较为简单,使得深层土壤湿度与观测有较大的差距。     

Soil moisture prediction over the Australian continent

Summary This paper describes an attempt to model soil moisture over the Australian continent with an integrated system of dynamic models and a Geographic Information System (GIS) data base. A land surface scheme with improved treatment of soil hydrological processes is described. The non-linear relationships between soil hydraulic conductivity, matric potential and soil moisture are derived from the Broadbridge and White soil model. For a single location, the prediction of the scheme is in good agreement with the measurements of the Hydrological and Atmospheric Pilot Experiment (HAPEX). High resolution atmospheric and geographic data are used in soil moisture prediction over the Australian continent. The importance of reliable land surface parameters is emphasized and details are given for deriving the parameters from a GIS. Predicted soil moisture patterns over the Australian continent in summer, with a 50 km spatial resolution, are found to be closely related to the distribution of soil types, apart from isolated areas and times under the influence of precipitation. This is consistent with the notion that the Australian continent in summer is generally under water stress. In contrast, predicted soil temperatures are more closely related to radiation patterns and changes in atmospheric circulation. The simulation can provide details of soil moisture evolution both in space and time, that are very useful for studies of land use sustainability, such as plant growth modelling and soil erosion prediction.With 12 Figures     

A GCM-based assessment of the global moisture budget and the role of land-surface moisture reservoirs in processing precipitation

The performance of the Canadian Land Surface Scheme (CLASS) when coupled to the CCCma third generation general circulation model is evaluated in an AMIP II simulation. Our primary aim is to understand how CLASS processes moisture and to compare model estimates of moisture budget components with observations. The modelled mean annual precipitation and runoff, and their latitudinal structures, compare well with observations although some discrepancies remain in the simulation of regional values of these quantities. The amplitude and phase of the first harmonic of the precipitation annual cycle also compares well with observations although less well over regions of sparse precipitation and/or high topography. In the model, the canopy plays a major role in processing moisture at the land surface indicating the importance of vegetation in climate. The canopy intercepts a large fraction of the precipitation and provides the medium for returning much moisture back to the atmosphere as evapotranspiration. Though important locally, the snow moisture reservoir plays a relatively minor role in the global moisture budget. It acts primarily as a storage and delay mechanism with winter precipitation released to the ground reservoir on melting. The ground moisture reservoir also plays a major role and processes a similar amount of moisture as the canopy, although in a different manner. The globally averaged model runoff compares well with observation-based estimates, although the model partitioning into surface runoff and drainage does not agree particularly well with the single available observation-based estimate. How moisture is processed at the land surface serves as a basis for model intercomparison and for understanding the modelled moisture budget and its variation and changes with climate change. Only the most basic quantities (precipitation, runoff, and partitioning of runoff into surface runoff and drainage) may be compared with observation-based estimates, however, and the establishment of more complete moisture budget remains an important need.     

Uncertainty in the Specification of Surface Characteristics, Part ii: Hierarchy of Interaction-Explicit Statistical Analysis

The uncertainty in the specification of surface characteristics in soil-vegetation- atmosphere-transfer (SVAT) schemes within planetary boundary-layer (PBL) or mesoscale models is addressed. The hypothesis to be tested is whether the errors in the specification of the individual parameters are accumulative or whether they tend to balance each other in the overall sense for the system. A hierarchy of statistical applications is developed: classical one-at-a-time (OAT) approach, level 1; linear analysis of variance (ANOVA), level 1.5; fractional factorial (FF), or level 2; two-factor interaction (TFI) technique, or level 2.5; and a non-linear response surface methodology (RSM), or level 3. Using the First ISLSCP Field Experiment (FIFE) observations for June 6, 1987 as the initial condition for a SVAT scheme dynamically coupled to a PBL model, the interactions between uncertainty errors are analyzed. A secondary objective addresses the temporal changes in the uncertainty pattern using data for morning, afternoon, and evening conditions. It is found that the outcome from the level 1 OAT-like studies can be considered as the limiting uncertainty values for the majority of mesoscale cases. From the higher-level analyses, it is concluded that for most of the moderate surface scenarios, the effective uncertainty from the individual parameters is balanced and thus lowered. However, for the extreme cases, such as near wilting or saturation soil moisture, the uncertainties add up synergistically and these effects can be even greater than those from the outcomes of the OAT-like studies. Thus, parameter uncertainty cannot be simply related to its deviation alone, but is also dependent on other parameter settings. Also, from the temporal changes in the interaction pattern studies, it is found that, for the morning case soil texture is the important parameter, for afternoon vegetation parameters are crucial, while for the evening case soil moisture is capable of propagating maximum uncertainty in the SVAT processes. Finally, a generic hypothesis is presented that an appropriate question for analysis has to be rephrased from the previous 'which parameters are significant?’ to 'what scenarios make a particular parameter significant?’     

Climate variability attributable to terrestrial and oceanic forcing in the NCAR CAM3-CLM3 Models

Based on numerical experiments using the NCAR CAM3-CLM3 models, this paper examines the impact of soil moisture, vegetation, and sea surface temperature (SST) on the inter-annual variability of climate over land. For each element, two experiments are carried out, with the inter-annual variability preserved in one experiment and eliminated in the other. Differences in the standard deviation of the precipitation and air temperature at the inter-annual time scale are used to quantify the impacts from soil moisture dynamics, vegetation dynamics, and oceanic forcing. The impact of oceanic forcing is mainly limited to the Tropics, with the strongest signal in the equatorial zone, and moisture convergence is the key linkage between SST forcing and tropical precipitation. Soil moisture plays a significant role in climate variability during the rainy seasons of all semi-arid regions (which is consistent with many previous studies), and during the dry seasons of the humid Amazon. Evapotranspiration is identified as the main mechanism linking precipitation variability to soil moisture. Amazon is the only region where vegetation dynamics has a significant influence on precipitation variability. However, the impact of vegetation dynamics on temperature is strong over the US Great Plains in all four seasons and in the Amazon region during the dry and dry-to-wet transition seasons.     

The role of surface energy balance complexity in land surface models' sensitivity to increasing carbon dioxide

Global simulations with the Bureau of Meteorology Research Centre climate model coupled to the CHAmeleon Surface Model (CHASM) are used to explore the sensitivity of simulated changes in evaporation, precipitation, air temperature and soil moisture resulting from a doubling of carbon dioxide in the atmosphere. Five simulations, using prescribed sea surface temperatures, are conducted which are identical except in the level of complexity used to represent the surface energy balance. The simulation of air temperature, precipitation, evaporation and soil moisture at 1 2 CO₂ and at 2 2 CO₂ are generally sensitive at statistically significant levels to the complexity of the surface energy balance representation (i.e. the level of complexity used to represent these processes affects the simulated climate). However, changes in mean quantities, resulting from a doubling of atmospheric CO₂, are generally insensitive to the surface energy balance complexity. Conversely, changes in the spatial and temporal variance of evaporation and soil moisture are sensitive to the surface energy balance complexity. The addition of explicit canopy interception to the simplest model examined here enables that model to capture the change in the variance of evaporation simulated by the more complex models. In order to simulate changes in the variability of soil moisture, an explicit parameterization of bare soil evaporation is required. Overall, our results increase confidence that the simulation by climate models of the mean impact of increasing CO₂ on climate are reliable. Changes in the variability resulting from increased CO₂ on air temperature, precipitation or evaporation are also likely to be reliable since climate models typically use sufficiently complex land surface schemes. However, if the impact of increased CO₂ on soil moisture is required, then a more complex surface energy balance representation may be needed in order to capture changes in variability. Overall, our results imply that the level of complexity used by most climate models to represent the surface energy balance is appropriate and does not contribute significant uncertainty in the simulation of changes resulting from increasing CO₂. Our results only relate to surface energy balance complexity, and major uncertainties remain in how to model the surface hydrology and changes in the physiology, structural characteristics and distribution of vegetation. Future developments of land surface models should therefore focus on improving the representation of these processes.     

青藏高原土壤湿度的变化特征及其对中国东部降水影响的研究进展

青藏高原土壤湿度受积雪与冻土的共同影响,能够记忆长时间的陆面干湿过程,是气候变化的重要因子,对随后的中国东部降水有预测意义。由于高原观测站点稀少,土壤湿度观测资料匮乏,致使现有相关研究大多是基于再分析资料、模式资料和卫星遥感资料(统称替代资料)进行的,且所得结论既有差异,也存在不确定性。因此本文首先综述了各种土壤湿度替代资料的适用性对比研究,进而讨论了青藏高原地区土壤湿度的变化特征及其对我国东部气候的影响。现有研究表明:1)资料对比研究指出,现有的各种替代资料对高原土壤湿度存在明显的高估或低估现象,且评估结论受评估指标和插值方法不同的影响。相对而言,SSM/I和风云3B的土壤湿度产品与实际观测资料相关性较好。2)高原土壤湿度具有多时间尺度变化特征和空间非均匀性,在年变化上具有显著的融冻特征,年代际变化趋势和年际特征呈现显著的区域性差异。SSM/I资料表明春季高原主体土壤湿度的年代际变化趋势呈现为增加的特征,与高原的增暖相一致;年际变率存在东、西两个高值区,与其相关的潜热、感热通量能共同激发遥相关波列影响我国长江流域降水;同时高原土壤湿度在垂直方向上具有一致性,在空间分布上具有南部边缘最大、由东南向西北递减的特征。3)前人对高原土壤湿度影响中国东部降水的结论各有不同,其可能原因之一是采用的替代资料及其适用性不同,其二是模式试验中忽略土壤湿度的空间差异性而带来的误差等。相关问题需要进一步深入研究。     

Effects of Crop Growth and Development on Land Surface Fluxes

In this study, the Crop Estimation through Resource and Environment Synthesis model (CERES3.0) was coupled into the Biosphere-Atmosphere Transfer Scheme (BATS), which is called BATS CERES, to represent interactions between the land surface and crop growth processes. The effects of crop growth and development on land surface processes were then studied based on numerical simulations using the land surface models. Six sensitivity experiments by BATS show that the land surface fluxes underwent substantial changes when the leaf area index was changed from 0 to 6 m2 m-2. Numerical experiments for Yucheng and Taoyuan stations reveal that the coupled model could capture not only the responses of crop growth and development to environmental conditions, but also the feedbacks to land surface processes. For quantitative evaluation of the effects of crop growth and development on surface fluxes in China, two numerical experiments were conducted over continental China: one by BATS CERES and one by the original BATS. Comparison of the two runs shows decreases of leaf area index and fractional vegetation cover when incorporating dynamic crops in land surface simulation, which lead to less canopy interception, vegetation transpiration, total evapotranspiration, top soil moisture, and more soil evaporation, surface runoff, and root zone soil moisture. These changes are accompanied by decreasing latent heat flux and increasing sensible heat flux in the cropland region. In addition, the comparison between the simulations and observations proved that incorporating the crop growth and development process into the land surface model could reduce the systematic biases of the simulated leaf area index and top soil moisture, hence improve the simulation of land surface fluxes.     

基于风云三号气象卫星微波亮温资料反演东北地区土壤湿度及其对比分析

土壤湿度在陆面过程中发挥着重要作用,是联系陆地水循环和能量循环的纽带和关键环节。遥感技术可以实时地对土壤湿度进行长期、大区域动态监测,已成为监测土壤湿度的有效手段。本文基于风云三号气象卫星（FY3B）微波亮温资料,利用基于微波能量辐射传输方程的陆面参数反演模型（LPRM）反演了中国东北地区的土壤湿度（FY3B_LPRM）。把反演获得的FY3BLRPM土壤湿度与中国气象局农业气象站土壤湿度观测资料、NCEP和ERA-Interim土壤湿度再分析资料、欧洲空间局多卫星融合ECV（Essential Climate Variable）土壤湿度产品和国家卫星气象中心FY3B官方土壤湿度产品（FY3B_offical）进行了对比分析。结果表明:（1）本文反演的FY3B土壤湿度与农业气象站观测资料有较高的一致性;卫星土壤湿度整体上呈现自西向东逐渐增加的空间变化,与农业气象站观测资料较为一致;在季节变化上,两者高度相关,在大部分地区的相关系数都达到0.7以上。（2）在大兴安岭和东北三省东部等地表相对湿润的地区,FY3B_LPRM土壤湿度与NCEP、ERA-Interim和FY3B_offical土壤湿度呈现较强的负相关;再分析资料和FY3B_offical土壤湿度均无法反映该地区土壤干湿状况的季节性变化,甚至与观测资料呈反位相变化特征。FY3B_LPRM土壤湿度与欧洲空间局研发的多卫星融合ECV土壤湿度产品在绝大多数地区有较好的一致性。本文基于风云三号极轨气象卫星微波亮温反演的土壤湿度资料,可用于干旱监测、数值同化与天气预报、水文水资源等领域。     

On the Application of a Genetic Algorithm to the Predictability Problems Involving "On-Off" Switches

The lower bound of maximum predictable time can be formulated into a constrained nonlinear opti- mization problem, and the traditional solutions to this problem are the filtering method and the conditional nonlinear optimal perturbation (CNOP) method. Usually, the CNOP method is implemented with the help of a gradient descent algorithm based on the adjoint method, which is named the ADJ-CNOP. However, with the increasing improvement of actual prediction models, more and more physical processes are taken into consideration in models in the form of parameterization, thus giving rise to the on-off switch problem, which tremendously affects the effectiveness of the conventional gradient descent algorithm based on the ad- joint method. In this study, we attempted to apply a genetic algorithm (GA) to the CNOP method, named GA-CNOP, to solve the predictability problems involving on-off switches. As the precision of the filtering method depends uniquely on the division of the constraint region, its results were taken as benchmarks, and a series of comparisons between the ADJ-CNOP and the GA-CNOP were performed for the modified Lorenz equation. Results show that the GA-CNOP can always determine the accurate lower bound of maximum predictable time, even in non-smooth cases, while the ADJ-CNOP, owing to the effect of on-off switches, often yields the incorrect lower bound of maximum predictable time. Therefore, in non-smooth cases, using GAs to solve predictability problems is more effective than using the conventional optimization algorithm based on gradients, as long as genetic operators in GAs are properly configured.     

三类陆面模式模拟土壤湿度廓线的对比研究

针对不同陆面模式对土壤湿度方程求解方法以及对土壤分层结构的差异, 本文选取了三类陆面模式（CLM, CABLE和ECMWF陆面模式）作比较研究。为了避免不同模式参数化方案引起的上边界误差, 上边界采用固定蒸发率、 入渗率和固定表层土壤湿度三类边界条件。土壤分层采用101层（细网格）和11层（粗网格）两种, 并考虑土壤性质沿深度变化。结果表明： 当土壤性质均匀时, 求解的差别主要在第三类边界条件下CLM 求出的水分入渗速度比其它两种快; 改用粗网格后由于土壤深层厚度加大无法与细网格得出的土壤湿度廓线相重合。当土壤性质非均匀时, 模拟结果间差别加大, 只有ECMWF模式模拟的土壤湿度廓线是严格连续的。对于模式和上边界的不同组合, 粗、 细网格模拟结果间均方根偏差不一致。一般而言, CABLE模拟的偏差除第一类条件较小外, 其它都是最大的。第二三类边界条件引起的偏差较大, 第一类最小。上述结果提示我们, 在比较不同陆面模式以及用观测资料来检验模拟结果时应充分考虑土壤分层及土壤性质非均匀性的可能影响。     

Subdaily to Seasonal Change of Surface Energy and Water Flux of the Haihe River Basin in China: Noah and Noah-MP Assessment

The land surface processes of the Noah-MP and Noah models are evaluated over four typical landscapes in the Haihe River Basin(HRB) using in-situ observations. The simulated soil temperature and moisture in the two land surface models(LSMs) is consistent with the observation, especially in the rainy season. The models reproduce the mean values and seasonality of the energy fluxes of the croplands, despite the obvious underestimated total evaporation. Noah shows the lower deep soil temperature. The net radiation is well simulated for the diurnal time scale. The daytime latent heat fluxes are always underestimated, while the sensible heat fluxes are overestimated to some degree. Compared with Noah, Noah-MP has improved daily average soil heat flux with diurnal variations. Generally, Noah-MP performs fairly well for different landscapes of the HRB. The simulated cold bias in soil temperature is possibly linked with the parameterized partition of the energy into surface fluxes. Thus, further improvement of these LSMs remains a major challenge.     

Simulating evapotranspiration in a semi-arid environment

Summary In this work, simulations with the mesoscale meteorological model FOOT3DK for a semi-arid research site in southern morocco are presented. The main aim of this study is to introduce two different ways to improve the soil moisture distribution towards a more realistic pattern. One of them resembles the availability of groundwater resources below the lower boundary of the soil part of the model, the other one resembles irrigation practices in the region. Additionally, we introduce a newly derived land use/land cover data set obtained from analysis of LANDSAT data and compare the simulation results to those obtained with the USGS GLCC data. To evaluate the results with the refinements in soil moisture and land use/land cover, we focus on evapotranspiration, as the quantity which is most tentative to the changes in soil moisture and is an important part of the local hydrological cycle. To evaluate the importance of sub-grid scale surface heterogeneity in soil moisture and land use/land cover, we present simulations with enhanced surface resolution. Simulation results are compared to point measurements at different sites in the research area for validation.The results show, that a deep groundwater table and irrigation of parts of the research area can be represented by the methods we used. Simulated transpiration is overestimated compared to measured values, but this is due to the maximum approach used in this work. Finer tuning of the artificial enhancement of soil moisture with the two methods presented here are expected to lead to realistic distributions of evapotranspiration and related quantities, therewith drastically enhancing simulation accuracy for this site. As uncertainties of soil moisture distribution and restricted representation of soil moisture dynamics in meteorological models is a common problem especially for arid and semi-arid sites, we expect our results to be useful for meteorological simulations in other arid or semi-arid areas as well.