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.     

Evaluation of the soil water balance in an alluvial flood plain with a shallow groundwater table

Abstract

Many of the hydrological and ecological functions of alluvial flood plains within watersheds depend on the water flow exchanges between the vadoze soil zone and the shallow groundwater. The water balance of the soil in the flood plain is investigated, in order to evaluate the main hydrological processes that underlie the temporal dynamics of soil moisture and groundwater levels. The soil moisture and the groundwater level in the flood plain were monitored continuously for a three-year period. These data were integrated with the results derived from applying a physically-based numerical model which simulated the variably-saturated vertical water flow in the soil. The analysis indicated that the simultaneous processes of lateral groundwater flow and the vertical recharge from the unsaturated zone caused the observed water table fluctuations. The importance of these flows in determining the rises in the water table varied, depending on soil moisture and groundwater depth before precipitation. The monitoring period included two hydrological years (September 2009–September 2011). About 13% of the precipitation vertically recharged the groundwater in the first year and about 50% in the second. The difference in the two recharge coefficients was in part due to the lower groundwater levels in the recharge season of the first hydrological year, compared to those observed in the second. In the latter year, the shallow groundwater increased the soil moisture in the unsaturated zone due to capillary rise, and so the mean hydraulic conductivity of the unsaturated soil was high. This moisture state of soil favoured a more efficient conversion of infiltrated precipitation into vertical groundwater recharge. The results show that groundwater dynamics in the flood plain are an important source of temporal variability in soil moisture and vertical recharge processes, and this variability must be properly taken into account when the water balance is investigated in shallow groundwater environments.

Citation Pirastru, M. and Niedda, M., 2013. Evaluation of the soil water balance in an alluvial flood plain with a shallow groundwater table. Hydrological Sciences Journal, 58 (4), 898–911.     

Determining hydrological regimes in an agriculturally used tropical inland valley wetland in Central Uganda using soil moisture,groundwater, and digital elevation data

Inadequate knowledge exists on the distribution of soil moisture and shallow groundwater in intensively cultivated inland valley wetlands in tropical environments, which are required for determining the hydrological regime. This study investigated the spatial and temporal variability of soil moisture along 4 hydrological positions segmented as riparian zone, valley bottom, fringe, and valley slope in an agriculturally used inland valley wetland in Central Uganda. The determined hydrological regimes of the defined hydrological positions are based on soil moisture deficit calculated from the depth to the groundwater table. For that, the accuracy and reliability of satellite‐derived surface models, SRTM‐30m and TanDEM‐X‐12m, for mapping microscale topography and hydrological regimes are evaluated against a 5‐m digital elevation model (DEM) derived from field measurements. Soil moisture and depth to groundwater table were measured using frequency domain reflectometry sensors and piezometers installed along the hydrological positions, respectively. Results showed that spatial and temporal variability in soil moisture increased significantly (p < .05) towards the riparian zone; however, no significant difference was observed between the valley bottom and riparian zone. The distribution of soil hydrological regimes, saturated, near‐saturated, and nonsaturated regimes does not correlate with the hydrological positions. This is due to high spatial and temporal variability in depth to groundwater and soil moisture content across the valley. Precipitation strongly controlled the temporal variability, whereas microscale topography, soil properties, distance from the stream, anthropogenic factors, and land use controlled the spatial variability in the inland valley. TanDEM‐X DEM reasonably mapped the microscale topography and thus soil hydrological regimes relative to the Shuttle Radar Topography Mission DEM. The findings of the study contribute to improved understanding of the distribution of hydrological regimes in an inland valley wetland, which is required for a better agricultural water management planning.     

Regional scale spatial and temporal variability of soil moisture in a prairie region

Understanding the dynamics of spatial and temporal variability of soil moisture at the regional scale and daily interval, respectively, has important implications for remote sensing calibration and validation missions as well as environmental modelling applications. The spatial and temporal variability of soil moisture was investigated in an agriculturally dominated region using an in‐situ soil moisture network located in central Saskatchewan, Canada. The study site evaluated three depths (5, 20, 50 cm) through 139 days producing a high spatial and temporal resolution data set, which were analysed using statistical and geostatistical means. Processes affecting standard deviation at the 5‐cm depth were different from the 20‐cm and 50‐cm depths. Deeper soil measurements were well correlated through the field season. Further analysis demonstrated that lag time to maximum correlation between soil depths increased through the field season. Temporal autocorrelation was approximately twice as long at depth compared to surface soil moisture as measured by the e‐folding frequency. Spatial correlation was highest under wet conditions caused by uniform rainfall events with low coefficient of variation. Overall soil moisture spatial and temporal variability was explained well by rainfall events and antecedent soil moisture conditions throughout the Kenaston soil moisture network. It is expected that the results of this study will support future remote sensing calibration and validation missions, data assimilation, as well as hydrologic model parameterization for use in agricultural regions. Copyright © 2016 John Wiley & Sons, Ltd.     

Spatial and temporal variation of precipitation in Sudan and their possible causes during 1948–2005

Temporal and spatial patterns of precipitation are essential to the understanding of soil moisture status which is vital for vegetation regeneration in the arid ecosystems. The purposes of this study are (1) to understand the temporal and spatial variations of precipitation in Sudan during 1948–2005 by using high quality global precipitation data known as Precipitation REConstruction (PREC), which has been constructed at the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center, and (2) to discuss the relationship between precipitation variability and moisture flux based on the NCEP/NCAR reanalysis data in order to ascertain the potential causes of the spatial and temporal variations of precipitation in the region. Results showed that (1) annual and monthly precipitation in Sudan had great spatial variability, and mean annual precipitation varied from almost nil in the North to about 1500 mm in the extreme Southwest; (2) precipitation of the main rain season, i.e., July, August and September, and annual total precipitation in the central part of Sudan decreased significantly during 1948–2005; (3) abrupt change points were found in the annual, July, August and September in the late 1960s, when precipitation decreased more rapidly than in other periods; and (4) the decreasing precipitation was associated with the weakening African summer monsoon. The summer moisture flux over Sudan tended to be decreasing after the late 1960s which decreased the northward propagation of moisture flux in North Africa. This study provides a complementary view to the previous studies that attempted to explain the Sahel persistent drought and possible causes.     

Scaling characteristics of spatial patterns of soil moisture from distributed modelling

Characterizing the spatial dynamics of soil moisture fields is a key issue in hydrology, offering an avenue to improve our understanding of complex land surface–atmosphere interactions. In this paper, the statistical structure of soil moisture patterns is examined using modelled soil moisture obtained from the North American Land Data Assimilation System (NLDAS) at 0.125° resolution. The study focuses on the vertically averaged soil moisture in the top 10 cm and 100 cm layers. The two variables display a weak dependence for lower values of surface soil moisture, with the strength of the relationship increasing with the water content of the top layer. In both cases, the variance of the soil moisture follows a power law decay as a function of the averaging area. The superficial layer shows a lower degree of spatial organization and higher temporal variability, which is reflected in rapid changes in time of the slope of the scaling functions of the soil moisture variance. Conversely, the soil moisture in the top 100 cm has lower variability in time and larger spatial correlation. The scaling of these patterns was found to be controlled by the changes in the soil water content. Results have implications for the downscaling of soil moisture to prevent model bias.     

Soil moisture variability of root zone profiles within SMEX02 remote sensing footprints

Remote sensing of soil moisture effectively provides soil moisture at a large scale, but does not explain highly heterogeneous soil moisture characteristics within remote sensing footprints. In this study, field scale spatio-temporal variability of root zone soil moisture was analyzed. During the Soil Moisture Experiment 2002 (SMEX02), daily soil moisture profiles (i.e., 0–6, 5–11, 15–21, and 25–31 cm) were measured in two fields in Walnut Creek watershed, Ames, Iowa, USA. Theta probe measurements of the volumetric soil moisture profile data were used to analyze statistical moments and time stability and to validate soil moisture predicted by a simple physical model simulation. For all depths, the coefficient of variation of soil moisture is well explained by the mean soil moisture using an exponential relationship. The simple model simulated very similar variability patterns as those observed.As soil depth increases, soil moisture distributions shift from skewed to normal patterns. At the surface depth, the soil moisture during dry down is log-normally distributed, while the soil moisture is normally distributed after rainfall. At all depths below the surface, the normal distribution captures the soil moisture variability for all conditions. Time stability analyses show that spatial patterns of sampling points are preserved for all depths and that time stability of surface measurements is a good indicator of subsurface time stability. The most time stable sampling sites estimate the field average root zone soil moisture value within ±2.1% volumetric soil moisture.     

Soil moisture variation in relation to topography and land use in a hillslope catchment of the Loess Plateau, China

The profile characteristics and the temporal dynamics of soil moisture variation were studied at 26 locations in Da Nangou catchment (3.5 km²) in the loess area of China. Soil moisture measurements were performed biweekly at five depths in the soil profile (0–5, 10–15, 20–25, 40–45 and 70–75 cm) from May to October 1998 using Delta-T theta probe. Soil moisture profile type and temporal variation type and their relationship to topography and land use were identified by detrended canonical correspondence analysis (DCCA) and correlation analysis. The profile distribution of time-averaged soil moisture content can be classified into three types i.e. decreasing-type, waving-type and increasing-type. The profile features of soil moisture (e.g. profile gradient and profile variability) are influenced by different environmental factors. The profile type of soil moisture is only attributed to land use while profile gradient and profile variability of soil moisture is mainly related to land use and topography (e.g. landform type and slope). The temporal dynamics of layer-averaged soil moisture content is grouped into three types including three-peak type, synchro-four-peak type and lagged-four-peak type. These types are controlled by topography rather than by land use. The temporal dynamic type of soil moisture shows significant correlation with relative elevation, slope, aspect, while temporal variance displays significant relation with slope shape. The mean soil moisture is related to both the profile and dynamics features of soil moisture and is controlled by both land use and topography (e.g. aspect, position, slope and relative elevation). The spatial variability of soil moisture across landscape varies with both soil depths and temporal evolution.     

Temporal stability of soil moisture in an oasis of northwestern China

Temporal stability of soil moisture has been widely used in hydrological monitoring since it emerged. However, the spatial analysis of temporal stability at the landscape scale is often limited because of insufficient sampling numbers. This work made an effort to investigate the spatial variations of temporal stability of soil moisture in an oasis landscape. The specific objectives of the study were to explore the spatial patterns of temporal stability and to determine the controlling factors of temporal stability in the desert oasis. A time series of soil moisture measurements were gathered on 23 occasions at 118 locations over 3 years in a rectangular transect of approximately 100 km². The nonparametric Spearman's rank correlation coefficient, standard deviation of relative difference (SDRD), and mean absolute bias error (MABE) were used to quantify the temporal stability of soil moisture. Results showed that the temporal stability of soil moisture was depth dependent and season dependent. The spatial pattern of soil moisture in a deep soil layer and between two same seasons generally had a high temporal stability. SDRD and MABE were spatially autocorrelated and exhibited strong spatial structures in the geographic space. The concept of temporal stability can be extended to describe the time‐stable areas of soil moisture with geostatistics. There were great differences between SDRD and MABE in describing the temporal stability of soil moisture and in identifying the controlling factors of temporal stability. In this case, MABE was a better alternative to estimate the areal mean soil moisture using representative locations than SDRD. Land use type, soil moisture condition, and soil particle composition were the dominant controls of temporal stability in the oasis. These insights could help to better understand the essence of temporal stability of soil moisture in arid regions.     

Spatial soil moisture scaling structure during Soil Moisture Experiment 2005

Soil moisture state and variability control many hydrological and ecological processes as well as exchanges of energy and water between the land surface and the atmosphere. However, its state and variability are poorly understood at spatial scales larger than the fields (i.e. 1 km²) as well as the ability to extrapolate field scale to larger spatial scales. This study investigates soil moisture profiles, their spatial organization, and physical drivers of variability within the Walnut Creek watershed, Iowa, during Soil Moisture Experiment 2005 and relates the watershed scale findings to previous field‐scale results. For all depths, the watershed soil moisture variability was negatively correlated with the watershed mean soil moisture and followed an exponential relationship that was nearly identical to that for field scales. This relationship differed during drying and wetting. While the overall time stability characteristics were improved with observation depth, the relatively wet and dry locations were consistent for all depths. The most time stable locations, capturing the mean soil moisture of the watershed within ± 0·9% volumetric soil moisture, were typically found on hill slopes regardless of vegetation type. These mild slope locations consistently preserve the time stability patterns from field to watershed scales. Soil properties also appear to impact stability but the findings are sensitive to local variations that may not be well defined by existing soil maps. Copyright © 2010 John Wiley & Sons, Ltd.     

Spatial Variability of Surface Soil Moisture in a Depression Area of Karst Region

An understanding of soil moisture variability is necessary to characterize the linkages between a region's hydrology, ecology, and physiography. In subtropical karst region, the spatial variability of surface soil moisture is still unclear for the rocky ecological environment and intensive land uses. The purpose of this study was to characterize the variation and patterns of soil moisture content at depth of 0–16 cm and to investigate their influencing factors in a karst depression area of southwest China. Soil moisture content was measured at 20 m intervals by intensive sampling on March 11 (dry season) and August 30 (rainy season) in 2005, respectively. Surface soil moisture presented a moderate variability in the depression area at the sampling times. The variability was relatively higher in dry season with lower mean soil moisture, but lower in rainy season with higher mean soil moisture after heavy rain event. Similar results were also obtained from the mosaic patterns of soil moisture generated by ordinary Kriging interpolation with low standard deviations. This suggested that more soil samples might be required and the sampling interval should be shortened in dry season compared with rainy season. The dominant influencing factors on the variability of surface soil moisture were rainfall and land use types. However, altitude, bare‐rock ratio, and soil organic carbon were also important factors, and exerted jointly to control and redistribute the surface soil moisture either in dry or rainy season in the depression area. Such information provided some insights for the study on eco‐hydrological processes of vegetation restoration in the karst degraded ecosystem of southwest China.     

Temporal and spatial features of the soil moisture in boreal spring in eastern China

Soil moisture data of 45 years from European Center for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and the in situ observational data are used to study the temporal and spatial characteristics of the soil moisture in boreal spring in the area to the east of 100°E in China. Results show that ERA-40 soil moisture well reproduces the temporal and spatial features of observations. ERA-40 data capture the spatial pattern that the soils in Northeast China and Southwest China are wetter than those...     

A hillslope hydrology approach for catchment‐scale slope stability analysis

Regional analysis of slope stability is often constrained by availability of data. Model requirements for input data cannot be met at the desired spatial resolution because data are either site‐speci?c or non‐existent. Faced with these dif?culties it has often been the practice to assume that certain parameters are uniform throughout the area of interest. An alternative approach proposed here allows a more detailed discrimination of slope stability conditions. Based on the principles of hillslope hydrology, hydrologic information can be generated at suf?cient resolution to allow higher resolution slope stability analysis. Measurements from an instrumented network in a small area have been used to establish index‐based models for topographic and climate‐related controls of piezometric response. The ability to relate groundwater levels to rainfall and topographic parameters provides a means of up‐scaling to larger catchments and ultimately the opportunity to generate a catchment‐wide prediction of the distribution, magnitude and frequency of rainstorm‐generated groundwater levels. The example provided in this study uses the topography index of TOPMODEL in GIS to predict the spatial patterns of groundwater elevation for seasonal soil moisture conditions and given rainfall inputs. This allows modelling of catchment‐wide response of soil water to rainstorms with different return periods (representing different magnitudes), and is an essential prerequisite for a probabilistic regional slope stability analysis. Copyright © 2004 John Wiley & Sons, Ltd.     

The groundwater–land-surface–atmosphere connection: Soil moisture effects on the atmospheric boundary layer in fully-coupled simulations

This study combines a variably-saturated groundwater flow model and a mesoscale atmospheric model to examine the effects of soil moisture heterogeneity on atmospheric boundary layer processes. This parallel, integrated model can simulate spatial variations in land-surface forcing driven by three-dimensional (3D) atmospheric and subsurface components. The development of atmospheric flow is studied in a series of idealized test cases with different initial soil moisture distributions generated by an offline spin-up procedure or interpolated from a coarse-resolution dataset. These test cases are performed with both the fully-coupled model (which includes 3D groundwater flow and surface water routing) and the uncoupled atmospheric model. The effects of the different soil moisture initializations and lateral subsurface and surface water flow are seen in the differences in atmospheric evolution over a 36-h period. The fully-coupled model maintains a realistic topographically-driven soil moisture distribution, while the uncoupled atmospheric model does not. Furthermore, the coupled model shows spatial and temporal correlations between surface and lower atmospheric variables and water table depth. These correlations are particularly strong during times when the land-surface temperatures trigger shifts in wind behavior, such as during early morning surface heating.     

A method for estimating soil moisture storage in regions under water stress and storage depletion: a case study of Hai River Basin,North China

Soil moisture is a consideration for soil conservation, agricultural production and climate modelling. This article presents a simple method for estimating soil moisture storage under water stress and storage depletion conditions. The method is driven by the common agro‐hydrologic variables of precipitation (PPT), irrigation (IRR) and evapotranspiration (ET). The proposed method is successfully tested for the 152 000 km² floodplain region of Hai River Basin using 48 consecutive months (2003–2006) of data. Soil moisture data from global land data assimilation system/Noah land surface model are validated with ground‐truth data from 102 soil moisture monitoring sites. The validated soil moisture is used in combination with in situ groundwater data to quantify total water storage change (TWSC) in the region. The estimated storage change is in turn compared with gravity recovery and climate experiment‐derived TWSC for the study area. The soil moisture and TWSC terms show favourable agreements, with discrepancies of < 10% on the average. While there is no consistent seasonal trend in soil moisture, TWSC shows a strong seasonality. It is low in spring and high in summer. This trend corresponds with the IRR–PPT season in the study area. Change in groundwater and total water storage indicates storage depletion in the basin. Storage depletion in the region is driven mainly by groundwater IRR and ET loss. Despite the low PPT and high ET, there is narrowing seasonal trend in soil moisture. This is achieved at the expense of groundwater storage. IRR pumping has induced extensive groundwater depletion in the basin. It is therefore vital to develop cultivation strategies that aim at limiting IRR pumping and ET loss. Water management practices that not only reduce waste but also ensure high productivity and ecological sustainability could also mitigate storage depletion in the region. These measures could reduce further not only the seasonal trend in soil moisture but also that in groundwater storage. Copyright © 2011 John Wiley & Sons, Ltd.     

Factors controlling the spatial variability of surface soil moisture within revegetated‐stabilized desert ecosystems of the Tengger Desert,Northern China

The spatial structure of surface soil moisture was investigated at a grid scale with 10 × 10 m intervals on a plot of 4500 m² in a re‐vegetated desert area in Shapotou, the Tengger Desert. The site topography varies from dune crest to dune hollow, and again to dune crest. Volumetric soil moisture contents were measured 21 times over 6 months in 2006 by using Delta‐T Theta‐Probes in the 0–6 cm surface soil layer before and after rainfall. At the same time, soil texture, relative elevation, and plant coverage were measured, to examine (i) the spatial variability of surface soil moisture; (ii) the main factors controlling the spatial variability patterns; and (iii) how the importance of these factors varies with the seasonal variations in soil moisture content. The results indicated that the normal distribution of surface soil moisture was more obvious in wet conditions than in dry conditions; the spatial variability of surface soil moisture was inherent and decreased with increased soil moisture content; and precipitation increased the spatial dependence of surface soil moisture. The relative elevation of the landscape, the shrub coverage of the community, and the soil texture were the main factors influencing surface soil moisture variability, while the effect of soil texture strengthened gradually following the heavy precipitation events. The correlation between the spatial variability of surface soil moisture and the environmental factors, such as, the dry and wet conditions, the landscape coverage and the relative elevation suggests that increasing stability of the soil moisture resulted in a significant increase of soil moisture. Copyright © 2009 John Wiley & Sons, Ltd.     

Spatial prediction of temporal soil moisture dynamics using HYDRUS‐1D

This article investigates the soil moisture dynamics within two catchments (Stanley and Krui) in the Goulburn River in NSW during a 3‐year period (2005–2007) using the HYDRUS‐1D soil water model. Sensitivity analyses indicated that soil type, and leaf area index were the key parameters affecting model performance. The model was satisfactorily calibrated on the Stanley microcatchment sites with a single point rainfall record from this microcatchment for both surface 30 cm and full‐profile soil moisture measurements. Good correlations were obtained between observed and simulated soil water storage when calibrations for one site were applied to the other sites. We extended the predictions of soil moisture to a larger spatial scale using the calibrated soil and vegetation parameters to the sites in the Krui catchment where soil moisture measurement sites were up to 30 km distant from Stanley. Similarly good results show that it is possible to use a calibrated soil moisture model with measurements at a single site to extrapolate the soil moisture to other sites for a catchment with an area of up to 1000 km² given similar soils and vegetation and local rainfall data. Site predictions were effectively improved by our simple data assimilation method using only a few sample data collected from the site. This article demonstrates the potential usefulness of continuous time, point‐scale soil moisture data (typical of that measured by permanently installed TDR probes) and simulations for predicting the soil wetness status over a catchment of significant size (up to 1000 km²). Copyright © 2012 John Wiley & Sons, Ltd.     

Validation of ERS scatterometer‐derived soil moisture data in the central part of the Duero Basin,Spain

The objective of this study was to validate the soil moisture data derived from coarse‐resolution active microwave data (50 km) from the ERS scatterometer. The retrieval technique is based on a change detection method coupled with a data‐based modelling approach to account for seasonal vegetation dynamics. The technique is able to derive information about the soil moisture content corresponding to the degree of saturation of the topmost soil layer (∼5 cm). To estimate profile soil moisture contents down to 100 cm depth from the scatterometer data, a simple two‐layer water balance model is used, which generates a red noise‐like soil moisture spectrum. The retrieval technique had been successfully applied in the Ukraine in a previous study. In this paper, the performance of the model in a semi‐arid Mediterranean environment characterized by low annual precipitation (400 mm), hot dry summers and sandy soils is investigated. To this end, field measurements from the REMEDHUS soil moisture station network in the semi‐arid parts of the Duero Basin (Spain) were used. The results reveal a significant coefficient of determination (R² = 0·75) for the averaged 0–100 cm soil moisture profile and a root mean square error (RMSE) of 2·2 vol%. The spatial arrangement of the REMEDHUS soil moisture stations also allowed us to study the influence of the small‐scale variability of soil moisture within the ERS scatterometer footprint. The results show that the small‐scale variability in the study area is modest and can be explained in terms of texture fraction distribution in the soil profiles. Copyright © 2004 John Wiley & Sons, Ltd.     

A top–down soil moisture and sap flux sampling design of a rain–snow transition mountain watershed

This paper presents a top–down approach for soil moisture and sap flux sampling design with the goal of understanding ecohydrologic response to interannual climate variation in the rain–snow transition watersheds. The design is based on a priori estimates of soil moisture and transpiration patterns using a physical distributed model, Regional Hydro‐Ecologic Simulation System (RHESSys). RHESSys was initially calibrated with existing snow depth and streamflow data. Calibrated model estimates of seasonal trajectories of snowmelt, root‐zone soil moisture storage, and transpiration were used to develop five hydrologic similarity indicators and map these at (30 m) patch scale across the study watershed. The partitioning around medoids‐clustering algorithm was then used to define six distinctive spatially explicit clusters based on the five hydrologic similarity indictors. A representative site within each cluster was identified for sampling. For each site, soil moisture sensors were installed at the 30‐ and 90‐cm depths and at the five soil pits and a sap flux sensor at the averaged‐size white fir tree for each site. The model‐based cluster analysis suggests that the elevation gradient and topographically driven flow drainage patterns are the dominant drivers of spatial patterns of soil moisture and transpiration. The comparison of model‐based calculated hydrological similarity indicators with measured‐data‐based values shows that spatial patterns of field‐sampled soil moisture data typically fell within uncertainty bounds of model‐based estimates for each cluster. There were however several notable exceptions. The model failed to capture the soil moisture and sap flux dynamics in a riparian zone site and in a site where lateral subsurface flow may not follow surface topography. Results highlight the utility of using a hypothesis driven sampling strategy, based on a physically based model, for efficiently providing new information that can drive both future measurements and strategic refinements to model inputs, parameters, or structure that might reduce these errors. Future research will focus on strategies for using of finer scale representations of microclimate, topography, vegetation, and soil properties to improve models.