Estimating evapotranspiration from small watersheds using a water and energy balance approach

Meteorological and environmental data measured in semiarid watersheds during the summer monsoon and winter periods were used to study the interrelationships among flux, meteorological and soil water variables, and to evaluate the effects of these variables on the daily estimation of actual evapotranspiration (AET). The relationship between AET and potential evapotranspiration (PET) as a function of soil water content, as suggested by Thornthwaite–Mather and by Morton, was studied to determine its applicability to the study area. Furthermore, multiple linear regression (MLR) analysis was employed to evaluate the order of importance of the meteorological and soil water factors involved. The results of MLR analysis showed that the combined effects of available energy, soil water content and wind speed were responsible for more than 70% of the observed variations in AET during the summer monsoon period. The analyses also indicate that the combined effects of available energy, vapour pressure deficit and wind speed were responsible for more than 70% of the observed variations in AET during the winter period. However, the test results of two different approaches, using the relationships between AET and PET as a function of soil water content, indicated some inadequacy. Copyright © 2007 John Wiley & Sons, Ltd.     

Understanding of the Common Land Model performance for water and energy fluxes in a farmland during the growing season in Korea

The Common Land Model (CLM) is one of the most widely used land surface models (LSMs) due to the practicality of its simple parameterization scheme and its versatility in embracing a variety of field datasets. The improved assessment of land surface water and energy fluxes using CLM can be an alternative approach for understanding the complex land–atmosphere interactions in data‐limited regions. The understanding of water and energy cycles in a farmland is crucial because it is a dominant land feature in Korea and Asia. However, the applications of CLM to farmland in Korea are in paucity. The simulations of water and energy fluxes by CLM were conducted against those from the tower‐based measurements during the growing season of 2006 at the Haenam site (a farmland site) in Korea without optimization. According to the International Geosphere–Biosphere Programme (IGBP) land cover classification, a homogeneous cropland was selected initially for this study. Although the simulated soil moisture had a similar pattern to that of the observed, the former was relatively drier (at 0·1 m³ m^?3) than the latter. The simulated net radiation showed good agreement with the observed, with a root mean squared error (RMSE) of 41 W m^?2, whereas relatively large discrepancies between the simulation and observation were found in sensible (RMSE of 66 W m^?2) and latent (RMSE of 60 W m^?2) heat fluxes. On the basis of the sensitivity analysis, soil moisture was more receptive to land cover and soil texture parameterizations when compared to soil temperature and turbulent fluxes. Despite the uncertainty in the predictive capability of CLM employed without optimization, the initial performance of CLM suggests usefulness in a data‐limited heterogeneous farmland in Korea. Further studies are required to identify the controls on water and energy fluxes with an improved parameterization. Copyright © 2010 John Wiley & Sons, Ltd.     

Response of water and energy exchange to the environmental variable in a desert‐oasis wetland of Northwest China

A case study on a desert‐oasis wetland ecosystem in the arid region of Northwest China measured the seasonal and interannual variation in energy partitioning and evapotranspiration to analyse the response of water and energy exchange on soil moisture, groundwater, and environmental variables. Energy partitioning showed a clear seasonal and interannual variability, and the process of water and energy exchange differed significantly in the monthly and interannual scales. The net radiation was 7.31 MJ m^?2· day^?1, and sensible heat flux accounted for 50.42% of net radiation in energy fluxes, 40.56% for latent heat flux, and 9.02% for ground heat flux. The parameters in energy fluxes were best described by a unimodal curve, whereas sensible heat flux followed a bimodal curve. Variations in the daily evapotranspiration and crop evapotranspiration also exhibited a single peak curve with annual values of 569.84 and 644.47 mm, respectively. Canopy conductance averaged 20.77 ± 13.75 mm s^?1 and varied from 0.16 to 83.96 mm s^?1 during the two hydrological years. The variation in water and energy exchange reflected environmental conditions and depended primarily on vapour pressure deficit, net radiation, soil moisture, and water depth. Although the effects of precipitation on evapotranspiration showed that the response of this ecosystem to climate changes was not obvious, the variation of air temperatures had a strong influence on evapotranspiration, resulting in a significant increase in evapotranspiration (R = 0.730; P < 0.01). Copyright © 2013 John Wiley & Sons, Ltd.     

青藏高原中东部地区土壤湿度模拟性能评估以及误差分析

土壤湿度不仅是地表水循环的重要组成部分,而且对天气和气候也有重要影响,它的模拟误差严重阻碍了人们对水循环的认知.本文首先评估了1°×1°水平分辨率的全球陆面数据同化产品(Global Land Data Assimilation System,GLDAS)对青藏高原中部那曲地区和东部玛曲地区土壤湿度的模拟性能;鉴于GLDAS较粗的分辨率无法精细描述分析区域土壤湿度空间分布特征,于是我们基于通用陆面过程模式(Community Land Surface Model,Version 4.5),开展了高分辨率0.1°×0.1°的模拟,并对高分辨率模拟土壤湿度误差的原因进行了深入分析.结果表明:(1)GLDAS陆面数据同化产品和高分辨率陆面模式模拟结果都可以反映出土壤湿度的季节变化特征,但在非冻结期均存在不同程度的干偏差,尤其是在玛曲地区;(2)对比观测和模拟的土壤湿度发现,观测数据表现出强烈的空间异质性,而模拟结果呈现出的是空间均一性.按照模拟误差进行归类分组,对比模拟性能优劣的两组站点发现,模式物理过程不是模拟性能差异的主要因素,而两组站点间地表特征参数中的土壤质地和地形参数,以及驱动数据均没有体现出空间异质性,这可能是土壤湿度模拟结果没有表现出空间异质性的原因.     

Investigating soil moisture sensitivity to precipitation and evapotranspiration errors using SiB2 model and ensemble Kalman filter

Accurate soil moisture information is useful in agricultural practice, weather forecasting, and various hydrological applications. Although land surface modeling provides a viable approach to simulating soil moisture, many factors such as errors in the precipitation can affect the accuracy of soil moisture simulations. This paper examined how precipitation rate and evapotranspiration rate affect the accuracy of soil moisture simulation using simple biosphere model with and without data assimilation through ensemble Kalman filter (EnKF). For each of the two variables, seven levels of relative errors (?20, ?10, ?5, 0, 5, 10 and 20 %) were introduced independently, thus a total of 49 combined cases were investigated. Observations from Wudaogou Hydrology Experimental site in the Huaihe River basin, China, were used to drive and verify the simulations. Results indicate that when the error of precipitation rate is within 10 % of the observations, the resulting error in soil moisture simulations is less significant and manageable, thus the simulated precipitation can be used to drive hydrological models in poorly gauged catchments when observations are not available. When the error of evapotranspiration rate is within 20 % of the observations, which is partly caused by model structural and parameterization errors, its impact on soil moisture simulation is less significant and can be acceptable. This study also demonstrated that the EnKF can perform consistently well to improve soil moisture simulation with less sensitivity to precipitation errors.     

Controls on evapotranspiration from jack pine forests in the Boreal Plains Ecozone

The exchanges of water, energy and carbon between the land surface and the atmosphere are tightly coupled, so that errors in simulating evapotranspiration lead to errors in simulating both the water and carbon balances. Areas with seasonally frozen soils present a particular challenge due to the snowmelt-dominated hydrology and the impact of soil freezing on the soil hydraulic properties and plant root water uptake. Land surface schemes that have been applied in high latitudes often have reported problems with simulating the snowpack and runoff. Models applied at the Boreal Ecosystem Research and Monitoring Sites in central Saskatchewan have consistently over-predicted evapotranspiration as compared with flux tower estimates. We assessed the performance of two Canadian land surface schemes (CLASS and CLASS-CTEM) for simulating point-scale evapotranspiration at an instrumented jack pine sandy upland site in the southern edge of the boreal forest in Saskatchewan, Canada. Consistent with past reported results, these models over-predicted evapotranspiration, as compared with flux tower observations, but only in the spring period. Looking systematically at soil properties and vegetation characteristics, we found that the dominant control on evapotranspiration within these models was the canopy conductance. However, the problem of excessive spring ET could not be solved satisfactorily by changing the soil or vegetation parameters. The model overestimation of spring ET coincided with the overestimation of spring soil liquid water content. Improved algorithms for the infiltration of snowmelt into frozen soils and plant-water uptake during the snowmelt and soil thaw periods may be key to addressing the biases in spring ET.     

An improved algorithm to estimate the surface soil heat flux over a heterogeneous surface: A case study in the Heihe River Basin

Surface soil heat flux(G0) is an indispensable component of the surface energy balance and plays an important role in the estimation of surface evapotranspiration(ET). This study calculated G0 in the Heihe River Basin based on the thermal diffusion equation, using the observed soil temperature and moisture profiles, with the aim to analyze the spatial-temporal variations of G0 over the heterogeneous area(with alpine grassland, farmland, and forest). The soil ice content was estimated by the difference in liquid soil water content before and after the melting of the frozen soil and its impact on the calculation of G0 was further analyzed. The results show that:(1) the diurnal variation of G0 is obvious under different underlying surfaces in the Heihe River Basin, and the time when the daily maximum value of G0 occurs is a few minutes to several hours earlier than that of the net radiation flux, which is related to the soil texture, soil moisture, soil thermal properties, and the vegetation coverage;(2) the net radiation flux varies with season and reaches the maximum in summer and the minimum in winter, whereas G0 reaches the maximum in spring rather than in summer, because more vegetation in summer hinders energy transfer into the soil;(3) the proportions of G0 to the net radiation flux are different with seasons and surface types, and the mean values in January are 25.6% at the Arou site, 22.9% at the Yingke site and 4.3% at the Guantan site, whereas the values in July are 2.3%, 1.6% and 0.3%, respectively; and(4) G0 increases when the soil ice content is included in thermal diffusion equation, which improves the surface energy balance closure by 4.3%.     

Evapotranspiration models of different complexity for multiple land cover types

A comparison between half‐hourly and daily measured and computed evapotranspiration (ET) using three models of different complexity, namely, the Priestley–Taylor (P‐T), the reference Penman–Monteith (P‐M) and the Common Land Model (CLM), was conducted using three AmeriFlux sites under different land cover and climate conditions (i.e. arid grassland, temperate forest and subhumid cropland). Using the reference P‐M model with a semiempirical soil moisture function to adjust for water‐limiting conditions yielded ET estimates in reasonable agreement with the observations [root mean square error (RMSE) of 64–87 W m^?2 for half‐hourly and RMSE of 0.5–1.9 mm day^?1 for daily] and similar to the complex Common Land Model (RMSE of 60–94 W m^?2 for half‐hourly and RMSE of 0.4–2.1 mm day^?1 for daily) at the grassland and cropland sites. However, the semiempirical soil moisture function was not applicable particularly for the P‐T model at the forest site, suggesting that adjustments to key model variables may be required when applied to diverse land covers. On the other hand, under certain land cover/environmental conditions, the use of microwave‐derived soil moisture information was found to be a reliable metric of regional moisture conditions to adjust simple ET models for water‐limited cases. Further studies are needed to evaluate the utility of the simplified methods for different landscapes. Copyright © 2011 John Wiley & Sons, Ltd.     

Constraining water table depth simulations in a land surface model using estimated baseflow

Several recent studies have shown the significance of representing groundwater in land surface hydrologic simulations. However, optimal methods for model parameter calibration in order to realistically simulate baseflow and groundwater depth have received little attention. Most studies still use globally constant groundwater parameters due to the lack of available datasets for calibration. Moreover, when models are calibrated, various parameter combinations are found to exhibit equifinality in simulated total runoff due to model parameter interactions. In this study, a simple lumped groundwater model is incorporated into the Community Land Model (CLM), in which the water table is interactively coupled to soil moisture through the groundwater recharge fluxes. The coupled model (CLMGW) is successfully validated in Illinois using a 22-year (1984–2005) monthly observational dataset. Baseflow estimates from the digital recursive filter technique are used to calibrate the CLMGW parameters. The advantage obtained from incorporating baseflow calibration in addition to traditional calibration based on measured streamflow alone is demonstrated by a Monte Carlo-type simulation analysis. Using the optimal parameter sets identified from baseflow calibration, flow partitioning and water table depth simulations using CLMGW are improved, and the equifinality problem is alleviated. For other regions that lack observations of water table depth, the baseflow calibration approach can be used to enhance parameter estimation and constrain water table depth simulations.     

Transpiration and evaporation of grassland using land surface modelling

Partitioning transpiration (T) from evapotranspiration (ET) is a key process for understanding the interaction between land surfaces and the atmosphere. This paper reports daily partitioning results for a grassland over a 10-year period, obtained using the Community Land Model 3.5 (CLM3.5) land surface model. Hourly forcing data were collected from a long-term observation system located in the northeast of Japan ( http://doi.org/10.24575/0001.198108 ). To test the model behavior, total ET was validated using eddy correlation measurements combined with the energy balance method. The results were compared with previous research using an isotope approach for partitioning. The results demonstrate that our model can capture the dynamics of ET and its components at this location. Evaporation (E), originating from the ground and canopy, varied inter-annually, and from 2006 to 2015, average annual E was approximately 285 mm/year from the ground and 45 mm/year from the canopy. Average, T, was approximately 302 mm/year, accounting for approximately 48% of the total ET. Inter-annual results demonstrate that the water flux transported by vegetation ranges from 17 to 83% during the April–October period. A sensitivity test conducted with forcing data indicates air temperature, incident solar radiation, and longwave radiation exhibited a notable effect on all ET components. Relative humidity exhibited the only negative feedback to both evaporation and transpiration, contrary to the other forcing parameters. Our study reemphasized the effectiveness of CLM3.5 in partitioning T from ET and in understanding the complex interaction between land surfaces and the atmosphere.     

Soil moisture states,lateral flow,and streamflow generation in a semi‐arid,snowmelt‐driven catchment

Hydraulic connectivity on hillslopes and the existence of preferred soil moisture states in a catchment have important controls on runoff generation. In this study we investigate the relationships between soil moisture patterns, lateral hillslope flow, and streamflow generation in a semi‐arid, snowmelt‐driven catchment. We identify five soil moisture conditions that occur during a year and present a conceptual model based on field studies and computer simulations of how streamflow is generated with respect to the soil moisture conditions. The five soil moisture conditions are (1) a summer dry period, (2) a transitional fall wetting period, (3) a winter wet, low‐flux period, (4) a spring wet, high‐flux period, and (5) a transitional late‐spring drying period. Transitions between the periods are driven by changes in the water balance between rain, snow, snowmelt and evapotranspiration. Low rates of water input to the soil during the winter allow dry soil regions to persist at the soil–bedrock interface, which act as barriers to lateral flow. Once the dry‐soil flow barriers are wetted, whole‐slope hydraulic connectivity is established, lateral flow can occur, and upland soils are in direct connection with the near‐stream soil moisture. This whole‐slope connectivity can alter near‐stream hydraulics and modify the delivery of water, pressure, and solutes to the stream. Copyright © 2005 John Wiley & Sons, Ltd.     

A land surface soil moisture data assimilation framework in consideration of the model subgrid-scale heterogeneity and soil water thawing and freezing

The Ensemble Kalman Filter (EnKF) is well known and widely used in land data assimilation for its high precision and simple operation. The land surface models used as the forecast operator in a land data assimilation system are usually designed to consider the model subgrid-heterogeneity and soil water thawing and freezing. To neglect their effects could lead to some errors in soil moisture assimilation. The dual EnKF method is employed in soil moisture data assimilation to build a soil moisture data as- similation framework based on the NCAR Community Land Model version 2.0 (CLM 2.0) in considera- tion of the effects of the model subgrid-heterogeneity and soil water thawing and freezing: Liquid volumetric soil moisture content in a given fraction is assimilated through the state filter process, while solid volumetric soil moisture content in the same fraction and solid/liquid volumetric soil moisture in the other fractions are optimized by the parameter filter. Preliminary experiments show that this dual EnKF-based assimilation framework can assimilate soil moisture more effectively and precisely than the usual EnKF-based assimilation framework without considering the model subgrid-scale heteroge- neity and soil water thawing and freezing. With the improvement of soil moisture simulation, the soil temperature-simulated precision can be also improved to some extent.     

Spatial distribution of surface energy fluxes over the Loess Plateau in China and its relationship with climate and the environment

China's Loess Plateau is located at the edge of the Asian summer monsoon in a transition zone of climate and ecology. In the Loess Plateau, climate and environments change along with space, which has an obvious impact on the spatial distribution of surface energy fluxes. Because of scarce land-surface observation sites and short observation time in this area, previous studies have failed to fully understand the land-surface energy balance characteristics over the entire the Loess Plateau and their effect mechanisms. In this paper, we first test the simulation ability of the Community Land Model(CLM) model by comparing its simulated data with observed data. Based on the simulation data for the Loess Plateau over the past thirty years, we then analyze the spatial distribution of surface energy fluxes and compare the pattern differences between the area averages for the driest year and wettest year. Furthermore, we analyze the relationship between the spatial distribution of the components of the surface energy balance with longitude, latitude, altitude, precipitation and temperature. The main results are as follows: the spatial distribution of surface energy fluxes are significantly different, with the surface net radiation and sensible heat flux increasing from south to north and latent heat flux and soil heat flux decreasing from southeast to northwest. The sensible heat flux at the driest point is nearly twice as high as that at the wettest point, whereas the latent heat flux and soil heat flux at the driest point are half as much as that at the wettest point. The impact of variations of annual precipitation on the components of the surface energy balance is also obvious, and the maximum magnitude of the changes to the sensible heat flux and latent heat flux is nearly 30%. To a certain extent, geographical factors(including longitude, latitude, and altitude) and climate factors(including temperature and precipitation) affect the surface energy fluxes. However, the surface net radiation is more closely related to latitude and altitude, sensible heat flux is more closely related to the monsoon rainfall and latitude, and latent heat flux and soil heat flux are more closely related to the monsoon rainfall.     

Response of plant growth to surface water balance during a summer dry period in the Kazakhstan steppe

In drylands, water deficit is the primary factor limiting plant growth. In the present study, surface energy balance and plant growth (above‐ground and below‐ground biomass) were measured continuously during the 2002 growing season in semiarid grassland in the northern part of Kazakhstan, Central Asia. Although there was above normal total rainfall during the 2002 growing season (May–November; 244 mm over 183 days), there was a dry period during July and August. Evaporative water was effectively supplied by precipitation and surface soil moisture during the wet season (May and June), during which time above‐ground biomass increased. During the early stages of the dry period, mature plants were likely to tap deeper sources of soil moisture, representing stored snowmelt water. As the soil moisture content decreased during the summer dry period due to the high levels of evapotranspiration and lack of precipitation, the evaporative fraction and above‐ground biomass rapidly decreased, whereas the below‐ground biomass increased. These results suggest that in summer, soil moisture acts to store water, and that soil moisture is essential for plant growth as a direct source of water during the dry period in natural grasslands in the Kazakhstan steppe. Copyright © 2007 John Wiley & Sons, Ltd.     

The role of rainfall temporal and spatial averaging in seasonal simulations of the terrestrial water balance

The partitioning of rainfall into surface runoff and infiltration influences many other aspects of the hydrologic cycle including evapotranspiration, deep drainage and soil moisture. This partitioning is an instantaneous non-linear process that is strongly dependent on rainfall rate, soil moisture and soil hydraulic properties. Though all rainfall datasets involve some degree of spatial or temporal averaging, it is not understood how this averaging affects simulated partitioning and the land surface water balance across a wide range of soil and climate types. We used a one-dimensional physics-based model of the near-surface unsaturated zone to compare the effects of different rainfall discretization (5-min point-scale; hourly point-scale; hourly 0.125° gridded) on the simulated partitioning of rainfall for many locations across the United States. Coarser temporal resolution rainfall data underpredicted seasonal surface runoff for all soil types except those with very high infiltration capacities (i.e., sand, loamy sand). Soils with intermediate infiltration capacities (i.e., loam, sandy loam) were the most affected, with less than half of the expected surface runoff produced in most soil types when the gridded rainfall dataset was used as input. The impact of averaging on the water balance was less extreme but non-negligible, with the hourly point-scale predictions exhibiting median evapotranspiration, drainage and soil moisture values within 10% of those predicted using the higher resolution 5-min rainfall. Water balance impacts were greater using the gridded hourly dataset, with average underpredictions of ET up to 27% in fine-grained soils. The results suggest that “hyperresolution” modelling at continental to global scales may produce inaccurate predictions if there is not parallel effort to produce higher resolution precipitation inputs or sub-grid precipitation parameterizations.     

Utilization of satellite data in land surface hydrology: sensitivity and assimilation

This paper investigates the sensitivity of potential evapotranspiration to input meteorological variables, i.e. surface air temperature and surface vapor pressure. The sensitivity studies have been carried out for a wide range of land surface variables such as wind speed, leaf area index and surface temperatures. Errors in the surface air temperature and surface vapor pressure result in errors of different signs in the computed potential evapotranspiration. This result has implications for use of estimated values from satellite data or analysis of surface air temperature and surface vapor pressure in large‐scale hydrological modeling. The comparison of cumulative potential evapotranspiration estimates using ground observations and satellite observations over Manhattan, Kansas for a period of several months shows a variable difference between the two estimates. The use of satellite estimates of surface skin temperature in hydrological modeling to update the soil moisture using a physical adjustment concept is studied in detail, including the extent of changes in soil moisture resulting from the assimilation of surface skin temperature. The soil moisture of the 1 cm surface layer was adjusted by 0·9 mm over a 10‐day period as a result of a 3 K difference between the predicted and the observed surface temperature. This is a considerable amount given the fact that the top layer can hold only 5 mm of moisture. Copyright © 2001 John Wiley & Sons, Ltd.     

Examination of Morton's CRAE model for estimating daily evaporation from field-sized areas

Morton's complementary relationship areal evapotranspiration (CRAE) model was originally designed to provide regional estimates of monthly evapotranspiration. Often, however, hydrologists and others require estimates of evapotranspiration for field-sized land units under a specific land use, for shorter intervals of time. This paper examines CRAE with respect to the algorithms used to describe different terms and its applicability to reduced spatial and temporal scales.

Daily estimates by CRAE of atmospheric radiation fluxes during the summer months are compared with monitored values. It is shown that errors in estimation of the extra-terrestrial flux, the transmittancy of clouds to short-wave radiation, the surface albedo and the net long-wave flux result in standard deviations of the difference between ‘modelled’ and ‘measured’ net all-wave radiation for 1-, 5- and 10-day periods of 2.58, 1.8 and 1.50 MJm⁻² day⁻¹ respectively.

The assumption in CRAE that the vapour transfer coefficient is independent of wind speed may lead to appreciable error in computing evapotranspiration. A procedure for incorporating a wind correction factor is described and the improvement in estimating regional evaporation is illustrated.

Comparisons of evapotranspiration estimates by CRAE and measurements obtained from soil moisture and precipitation observations in the semi-arid, cold-climate Prairie region of western Canada demonstrate that the assumptions that the soil heat flux and storage terms are negligible, lead to large overestimation by the model during periods of soil thaw.     

北京大学陆面过程模式PKULM(Peking University Land Model)介绍及检验

陆面过程模式是气候模式和天气模式的核心组成部分之一.在土壤—植被—大气耦合模式(Soil-PlantAtmosphere Model,SPAM)的基础上,发展了新一代北京大学陆面过程模式PKULM(Peking University Land Model).本文首先介绍了PKULM的辐射传输、湍流输送、光合作用、土壤水热输送等过程的参数化方案;采用隐式迭代计算框架,发展并应用了一个快速的线性方程组求解算法,提高了模式计算稳定性;提出并使用了二分搜索算法计算气孔阻抗,避免了CLM(Community Land Model)等使用的迭代方法在干旱区不稳定的情况,提高了模式的适用性;采用水势为基础的土壤水分扩散方程,使模式能够模拟土壤饱和区的水分输送过程,为进一步与水文过程模式耦合奠定了基础;还发展了一个地表积水与径流过程的机理模型,提高了模式对地表水分平衡过程的模拟能力;最后,使用"中国西北干旱区陆—气相互作用观测试验"平凉站的资料对模式进行了检验并与NOAH(National Center for Environmental Prediction,Oregon State University,Air Force,and Hydrology Lab model)陆面过程模式的模拟结果进行了比较,结果表明PKULM能够较好地模拟西北半干旱区农田下垫面地气交换过程.     

How much does dry‐season fog matter? Quantifying fog contributions to water balance in a coastal California watershed

The seasonally‐dry climate of Northern California imposes significant water stress on ecosystems and water resources during the dry summer months. Frequently during summer, the only water inputs occur as non‐rainfall water, in the form of fog and dew. However, due to spatially heterogeneous fog interaction within a watershed, estimating fog water fluxes to understand watershed‐scale hydrologic effects remains challenging. In this study, we characterized the role of coastal fog, a dominant feature of Northern Californian coastal ecosystems, in a San Francisco Peninsula watershed. To monitor fog occurrence, intensity, and spatial extent, we focused on the mechanisms through which fog can affect the water balance: throughfall following canopy interception of fog, soil moisture, streamflow, and meteorological variables. A stratified sampling design was used to capture the watershed's spatial heterogeneities in relation to fog events. We developed a novel spatial averaging scheme to upscale local observations of throughfall inputs and evapotranspiration suppression and make watershed‐scale estimates of fog water fluxes. Inputs from fog water throughfall (10–30 mm/year) and fog suppression of evapotranspiration (125 mm/year) reduced dry‐season water deficits by 25% at watershed scales. Evapotranspiration suppression was much more important for this reduction in water deficit than were direct inputs of fog water. The new upscaling scheme was analyzed to explore the sensitivity of its results to the methodology (data type and interpolation method) employed. This evaluation suggests that our combination of sensors and remote sensing allows an improved incorporation of spatially‐averaged fog fluxes into the water balance than traditional interpolation approaches.     

Evaluation of multiple surface soil moisture for Korean regional flux monitoring network sites: Advanced Microwave Scanning Radiometer E,land surface model,and ground measurements

In the past few decades, there have been great developments in remotely sensed soil moisture, with validation efforts using land surface models (LSMs) and ground‐based measurements, because soil moisture information is essential to understanding complex land surface–atmosphere interactions. However, the validation of remotely sensed soil moisture has been very limited because of the scarcity of the ground measurements in Korea. This study validated Advanced Microwave Scanning Radiometer E (AMSR‐E) soil moisture data with the Common Land Model (CLM), one of the most widely used LSMs, and ground‐based measurements at two Korean regional flux monitoring network sites. There was reasonable agreement regarding the different soil moisture products for monitoring temporal trends except National Snow and Ice Data Centre (NSIDC) AMSR‐E soil moisture, albeit there were essential comparison limitations by different spatial scales and soil depths. The AMSR‐E soil moisture data published by the National Aeronautics and Space Administration and Vrije Universiteit Amsterdam (VUA) showed potential to replicate temporal variability patterns (root‐mean‐square errors = 0·10–0·14 m³ m^?3 and wet BIAS = 0·09 ? 0·04 m³ m^?3) with the CLM and ground‐based measurements. However, the NSIDC AMSR‐E soil moisture was problematic because of the extremely low temporal variability and the VUA AMSR‐E soil moisture was relatively inaccurate in Gwangneung site characterized by complex geophysical conditions. Additional evaluations should be required to facilitate the use of recent and forthcoming remotely sensed soil moisture data from Soil Moisture and Ocean Salinity and Soil Moisture Active and Passive missions at representative future validation sites. Copyright © 2011 John Wiley & Sons, Ltd.