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Permafrost-affected ecosystems of the Arctic–boreal zone in northwestern North America are undergoing profound transformation due to rapid climate change. NASA's Arctic Boreal Vulnerability Experiment (ABoVE) is investigating characteristics that make these ecosystems vulnerable or resilient to this change. ABoVE employs airborne synthetic aperture radar (SAR) as a powerful tool to characterize tundra, taiga, peatlands, and fens. Here, we present an annotated guide to the L-band and P-band airborne SAR data acquired during the 2017, 2018, 2019, and 2022 ABoVE airborne campaigns. We summarize the ∼80 SAR flight lines and how they fit into the ABoVE experimental design (Miller et al., 2023; https://doi.org/10.3334/ORNLDAAC/2150). The Supplement provides hyperlinks to extensive maps, tables, and every flight plan as well as individual flight lines. We illustrate the interdisciplinary nature of airborne SAR data with examples of preliminary results from ABoVE studies including boreal forest canopy structure from TomoSAR data over Delta Junction, AK, and the Boreal Ecosystem Research and Monitoring Sites (BERMS) area in northern Saskatchewan and active layer thickness and soil moisture data product validation. This paper is presented as a guide to enable interested readers to fully explore the ABoVE L- and P-band airborne SAR data (https://uavsar.jpl.nasa.gov/cgi-bin/data.pl). [ABSTRACT FROM AUTHOR]

Permafrost-affected ecosystems of the Arctic-boreal zone in northwestern North America are undergoing profound transformation due to rapid climate change. NASA's Arctic Boreal Vulnerability Experiment (ABoVE) is investigating characteristics that make these ecosystems vulnerable or resilient to this change. ABoVE employs airborne synthetic aperture radar (SAR) as a powerful tool to characterize tundra, taiga, peatlands, and fens. Here, we present an annotated guide to the L-band and P band airborne SAR data acquired during the 2017, 2018, 2019, and 2022 ABoVE airborne campaigns. We summarize the ~80 SAR flight lines and how they fit into the ABoVE experimental design. We provide hyperlinks to extensive maps, tables, and every flight plan as well as individual flight lines. We illustrate the interdisciplinary nature of airborne SAR data with examples of preliminary results from ABoVE studies including: boreal forest canopy structure from tomoSAR data over Delta Junction, AK and the BERMS site in northern Saskatchewan and active layer thickness and soil moisture data product validation. This paper is presented as a guide to enable interested readers to fully explore the ABoVE L55 and P-band SAR data. [ABSTRACT FROM AUTHOR]

Satellites are designed to monitor geospatial data over large areas at a catchment scale. However, most of satellite validation works are conducted at local point scales with a lack of spatial representativeness. Although upscaling them with a spatial average of several point data collected in the field, it is almost impossible to reorganize backscattering responses at pixel scales. Considering the influence of soil storage on watershed streamflow, we thus suggested watershed-scale hydrological validation. In addition, to overcome the limitations of backscattering models that are widely used for C-band Synthetic Aperture Radar (SAR) soil moisture but applied to bare soils only, in this study, RADARSAT-2 soil moisture was stochastically retrieved to correct vegetation effects arising from agricultural lands. Roughness-corrected soil moisture retrievals were assessed at various spatial scales over the Brightwater Creek basin (land cover: crop lands, gross drainage area: 1540 km2) in Saskatchewan, Canada. At the point scale, local station data showed that the Root Mean Square Errors (RMSEs), Unbiased RMSEs (ubRMSEs) and biases of Radarsat-2 were 0.06~0.09 m3/m3, 0.04~0.08 m3/m3 and 0.01~0.05 m3/m3, respectively, while 1 km Soil Moisture Active Passive (SMAP) showed underestimation at RMSEs of 0.1~0.22 m3/m3 and biases of −0.036~−0.2080 m3/m3. Although SMAP soil moisture better distinguished the contributing area at the catchment scale, Radarsat-2 soil moisture showed a better discharge hysteresis. A reliable estimation of the soil storage dynamics is more important for discharge forecasting than a static classification of contributing and noncontributing areas. [ABSTRACT FROM AUTHOR]

The main objective of this research was to understand the effects of climate change on soil water content (SWC) across the Qu'Appelle River basin in southern Saskatchewan, Canada. The Soil and Water Assessment Tool (SWAT) and output from 11 high-resolution (0.22°) regional climate models (RCM) were used over three 30-year periods: the near future (2021–2050) and distant future (2051–2080) and the historical reference (1975–2005). The RCM data are from the CORDEX North American domain, which employs the RCP8.5 high-emission scenario. SWC was modeled at the hydrological response units (HRU) level and at daily and monthly (warm season only) intervals for 2015–2020. The model was calibrated and validated using SUFI-2 in SWAT-CUP based on observations for streamflow and SWC, including measured data and Soil Moisture Active Passive (SMAP) Level 4 for surface (up to 5 cm deep) soil moisture. Values of the Nash–Sutcliffe model efficiency (NS) ranged from 0.616 and 0.784 and the coefficient of determination (R2) was 0.8 for calibration and 0.82 for validation. Likewise, the correlation coefficients between ground measurements and SWAT were 0.698 and 0.633, respectively. Future climate forcing of the calibrated SWAT model revealed that warmer and drier growing seasons will prevail in the region. Similarly, the ensemble of all RCMs indicated that the mean temperature will increase by 2.1 °C and 3.4 °C for the middle and late periods, respectively, along with a precipitation increase of 10% and 11.2%. SWC is expected to decrease with an increase in potential evapotranspiration, despite an increase in precipitation. Likewise, the annual SWC is expected to decrease by 3.6% and 4% in the middle and late periods, respectively. The monthly SWC changes showed the highest decreases (5.4%) in April in the late period. The spatial pattern of SWC for 11 RCMs was similar such that the northwest and west of the river basin are wetter than the south and east. SWC projections suggest that southern Saskatchewan could experience significant SWC deficiencies in the summer by the end of this century. [ABSTRACT FROM AUTHOR]

There is little understanding about how soil water stress history and host genotype influence the response of wheat-associated microbiome under short-term decreases in soil moisture. To address this, we investigated how plant breeding history (four wheat genotypes; two with recognized drought resistance and two without) and soil water stress history (same wheat field soil from Saskatchewan with contrasting long-term irrigation) independently or interactively influenced the response of the rhizosphere, root and leaf bacterial and fungal microbiota to short-term decreases in soil water content (SWC). We used amplicon sequencing (16S rRNA gene for bacteria and ITS region for fungi) to characterize the wheat microbiome. Fungal and bacterial communities responses to short-term decreases in SWC were mainly constrained by soil water stress history, with some smaller, but significant influence of plant genotype. One exception was the leaf-associated fungal communities, for which the largest constraint was genotype, resulting in a clear differentiation of the communities based on the genotype's sensitivity to water stress. Our results clearly indicate that soil legacy does not only affect the response to water stress of the microbes inhabiting the soil, but also of the microorganisms more closely associated with the plant tissues, and even of the plant itself. [ABSTRACT FROM AUTHOR]

The St. Denis National Wildlife Area is located in the seasonally frozen and semi-arid Canadian Prairies, close to Saskatoon, Saskatchewan. The site has a hummocky terrain and is underlain by clay-rich glacial tills. Though the site is only 4 km 2 it contains hundreds of wetlands containing ponds which range in size, in permanence (from ephemeral to permanent), and in their interactions with groundwater (recharge and discharge ponds are present). The site was established as a research area in 1968 and has long-term records of hydrological observations, including meteorological, snow, soil moisture, surface water (ponds) and groundwater data. Some records, notably the pond level and chemistry data, span the period 1968 to present. Other datasets, notably water level observations from networks of piezometers, have been collected sporadically at different locations and times. Some datasets are collected manually on an annual basis, including pond surveys and snow surveys. Meteorological data have been collected by automatic weather stations since 1989 and have been maintained and upgraded over time, with a flux tower added to the site in 2011. Automatically logged soil moisture profiles and collocated piezometers have been running since 2013. A lidar survey from 2005 provides a 1 m resolution digital elevation map (DEM) of the site and surrounding landscape. The compiled data are available at 10.20383/101.0115 (Bam et al., 2018). [ABSTRACT FROM AUTHOR]

Long records of hillslope runoff and nutrients are rare – on seasonally frozen ground they are almost non-existent. The Swift Current hillslopes at the Swift Current Research and Development Centre on the Canadian Prairies provide such a long-term hydrological record. Runoff, runoff nutrient concentration, snowpack, soil moisture, and soil nutrient concentration were monitored on the three 5 ha hillslopes over a 50-year period (1962–2011). Runoff from the hillslopes was generated episodically during snowmelt and occasional rainfall events. Edge-of-field runoff was measured with a 0.61 m H-flume. Daily runoff nutrient concentration data are available for nitrate (March 1971–April 2011), ammonium (February 1996–April 2011), and orthophosphate (March–April 1971; June 1991–April 2011). Snowpack data (snowpack depth, density and water equivalent) were determined via manual snow surveys carried out several times each winter, between January and March, between 1965 and 2011 Gravimetric soil moisture content was measured in October and April each year between 1971 and 2011 at five depth intervals (0–15, 15–30, 30–60, 60–90, and 90–120 cm) at nine points on each hillslope. We summarize these hillslope data in two publically-available repositories: 1) 1962–2011 data on runoff, runoff nutrients, snowpack, soil moisture, soil nutrients, and crop and tillage practices at https://doi.org/10.23684/hhn5-rz52; and 2) digital elevation data at https://doi.org/10.20383/101.011. Complete climate data recorded at a Environment and Climate Change Canada meteorological station located 390 m from the three hillslopes are publically-available at http://climate.weather.gc.ca/. [ABSTRACT FROM AUTHOR]

Soil moisture and precipitation have been monitored in a hydrometeorological network situated within the Brightwater Creek basin, east of Kenaston, Saskatchewan, since 2007. The majority of the prairie landscape is annually cropped with some sections in pasture. This agricultural region is ideal for remote sensing validation and calibration and, in conjunction with the flux tower situated within the network, hydrological model validation. Remote sensing validation collaborations have included ESA's Soil Moisture Ocean Salinity (SMOS) and NASA's Soil Moisture Active Passive (SMAP). The network was developed to capture soil moisture variation at two spatial scales, one high-resolution network installed over a 10 km² region and a second installed over 40 km². The networks are similar in design with three instrument depths for soil moisture and temperature, as well as precipitation measurement. The 2007-2017 dataset published in this paper has gone through a quality control review process, which involved both automated and manual processes. The dataset is limited to the summer months (May 1-Sept 30) due to the uncertainties and complexities of measurement in frozen soils and the freeze/thaw period each year. Data is available at https://dx.doi.org/10.20383/101.0116. [ABSTRACT FROM AUTHOR]

Hydrological water balance closure is a simple concept, yet in practice it is uncommon to measure every significant term independently in the field. Here we demonstrate the degree to which the field-scale water balance can be closed using only routine field observations in a seasonally frozen prairie pasture field site in Saskatchewan, Canada. Arrays of snow and soil moisture measurements were combined with a precipitation gauge and flux tower evapotranspiration estimates. We consider three hydrologically distinct periods: the snow accumulation period over the winter, the snowmelt period in spring, and the summer growing season. In each period, we attempt to quantify the residual between net precipitation (precipitation minus evaporation) and the change in field-scale storage (snow and soil moisture), while accounting for measurement uncertainties. When the residual is negligible, a simple 1-D water balance with no net drainage is adequate. When the residual is non-negligible, we must find additional processes to explain the result. We identify the hydrological fluxes which confound the 1-D water balance assumptions during different periods of the year, notably blowing snow and frozen soil moisture redistribution during the snow accumulation period, and snowmelt runoff and soil drainage during the melt period. Challenges associated with quantifying these processes, as well as uncertainties in the measurable quantities, caution against the common use of water balance residuals to estimate fluxes and constrain models in such a complex environment. [ABSTRACT FROM AUTHOR]

Abstract: Vertisolic expansive soils are characterized by unique morphological features and extensive volume changes of swelling clay minerals. The engineering properties of such a soil deposit in Regina, Canada, were investigated under in situ conditions. Results indicated a bi-modal SWCC composing of a fissure AEV (10kPa) and a matrix AEV (300kPa based on water content and 6000kPa based on degree of saturation). The latter value matched the field water content and the plastic limit, of which both occurred at Save ≈80%. The swell-shrink path was found to be S-shaped and included a low structural shrinkage (Save =100% to Save =80% at wp) followed by a sharp decline during normal shrinkage (Save =80% to Save =60% at ws) and then by a low decrease during residual shrinkage (Save =60% to Save =0%). An equilibrium soil microstructure for the undisturbed samples mean that for the field conditions (up to the matrix AEV), the soil aggregates remain fully saturated whereas drainage and volume changes primarily occur through the fissures. [Copyright &y& Elsevier]

The Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10) was carried out in Saskatchewan, Canada, from 31 May to 16 June, 2010. Its main objective was to contribute to Soil Moisture and Ocean Salinity (SMOS) mission validation and the prelaunch assessment of the proposed Soil Moisture Active and Passive (SMAP) mission. During CanEx-SM10, SMOS data as well as other passive and active microwave measurements were collected by both airborne and satellite platforms. Ground-based measurements of soil (moisture, temperature, roughness, bulk density) and vegetation characteristics (leaf area index, biomass, vegetation height) were conducted close in time to the airborne and satellite acquisitions. Moreover, two ground-based in situ networks provided continuous measurements of meteorological conditions and soil moisture and soil temperature profiles. Two sites, each covering 33 km × 71 km (about two SMOS pixels) were selected in agricultural and boreal forested areas in order to provide contrasting soil and vegetation conditions. This paper describes the measurement strategy, provides an overview of the data sets, and presents preliminary results. Over the agricultural area, the airborne L-band brightness temperatures matched up well with the SMOS data (prototype 346). The radio frequency interference observed in both SMOS and the airborne L-band radiometer data exhibited spatial and temporal variability and polarization dependency. The temporal evolution of the SMOS soil moisture product (prototype 307) matched that observed with the ground data, but the absolute soil moisture estimates did not meet the accuracy requirements (0.04 m3/m3) of the SMOS mission. AMSR-E soil moisture estimates from the National Snow and Ice Data Center more closely reflected soil moisture measurements. [ABSTRACT FROM PUBLISHER]

This study was conducted as part of the Soil Moisture and Ocean Salinity (SMOS) calibration and validation activities over agricultural and boreal forest sites located in Saskatchewan, Canada. For each site covering 33 km × 71 km (i.e., about two SMOS pixels), we examined the SMOS brightness temperature (L1c) and soil moisture (L2) products from May 1 to September 30, 2010. The consistency of these data with respect to theory and to the temporal variation of surface characteristics was first discussed at both sites. Then, the SMOS L1c (prototype 346) and L2 (prototypes 305-309) products were evaluated using the Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10) ground measurements and L-band passive microwave airborne measurements, in addition to AMSR-E soil moisture estimates and simulations from the zeroth order τ- ω radiative transfer model. For both study sites, the model underestimated SMOS brightness temperatures in V polarization, whereas an overestimation was observed in H polarization. The data sets showed that both the SMOS and AMSR-E soil moisture values were underestimated compared with ground measurements collected during CanEx-SM10 but less so for the AMSR-E estimates. The SMOS soil moisture product was underestimated with a RMSE varying from 0.15 to 0.18 m3/ m3. Furthermore, the overall results showed that errors in the soil moisture estimates increased with the absolute value of soil moisture. [ABSTRACT FROM AUTHOR]

This study has applied the Nondominated Sorting Genetic Algorithm II (NSGA-II) in a two-step assimilation procedure to jointly assimilate brightness temperature into a radiative transfer model and soil moisture into a land surface model. The first assimilation procedure generates a time series of soil moisture by assimilating brightness temperature from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) into the Land Parameter Retrieval Model (LPRM). The second procedure generates assimilated soil moisture by assimilating the soil moisture from LPRM into the Canadian Land Surface Scheme (CLASS). Note that the assimilated soil moisture was generated by merging two soil moisture estimates: one from LPRM and the other from the CLASS simulation. The assimilated soil moisture is better than using the soil moisture determined either from the satellite observation or the land surface scheme alone. This method provides improved model state and parameterizations for both LPRM and CLASS with the aim to facilitate real-time forecasts when satellite information becomes available. Application of this framework to the Brightwater Creek watershed in southern Saskatchewan illustrates the utility of the joint assimilation framework to improve a time series of soil moisture estimates. The estimated soil moisture datasets were evaluated over an agricultural site in southern Saskatchewan using in situ monitoring networks. These results demonstrate that soil moisture generated from assimilation of brightness temperature could be improved by incorporating it into a land surface model. A comparison between the assimilated soil moisture and in situ dataset demonstrates an improvement in accuracy and temporal pattern that is accomplished through the assimilation framework. [ABSTRACT FROM AUTHOR]

The Cold Regions Hydrological Modelling platform (CRHM) was used to create a prairie hydrological model for Smith Creek Research Basin (∼400 km2), eastcentral Saskatchewan, Canada. Physically based modules were sequentially linked in CRHM to simulate snow processes, frozen soils, variable contributing area and wetland storage and runoff generation. Five "representative basins" (RBs) were defined and each was divided into seven hydrological response units (HRUs): fallow, stubble, grassland, river channel, open water, woodland, and wetland. Model parameters were estimated using field survey data, LiDAR digital elevation model (DEM), SPOT 5 satellite imageries, stream network and wetland inventory GIS data. Model simulations were conducted for 2007/2008 and 2008/2009. No calibration was performed. The model performance in predicting snowpack, soil moisture and streamflow was evaluated against field observations. Root mean square differences (RMSD) between simulation and observations ranged from 1.7 to 25.2mm and from 4.3 to 22.4mm for the simulated snow accumulation in 2007/2008 and 2008/2009, respectively, with higher RMSD in grassland, river channel, and open water HRUs. Spring volumetric soil moisture was reasonably predicted compared to a point observation in a grassland area, with RMSD of 0.011 and 0.009 for 2008 and 2009 simulations, respectively. The model was able to capture the timing and magnitude of peak spring basin discharge, but it underestimated the cumulative volume of basin discharge by 32% and 56% in spring 2008 and 2009, respectively. The results suggest prediction of Canadian Prairie basin snow hydrology is possible with no calibration if physically based models are used with physically meaningful model parameters that are derived from high resolution geospatial data. [ABSTRACT FROM AUTHOR]

This study was undertaken to evaluate the effect of soil type, moisture content, and the presence of frost on road substructure permittivity. Permittivity sensitivity of typical road soils was characterized in the laboratory to provide baseline dielectric constant values which were compared to field ground penetrating radar (GPR) survey results. Both laboratorydevices, the complex dielectric network analyzer and the Adek Percometer, as well as the field GPR system were used in this study to measure the dielectric constant of soils. All three systems differentiated between coarse-grained and fine grained soils. In addition, at temperatures below freezing, all three systems identified an increase in water content in soils; however, when frozen, the sensitivity of dielectric constant across soil type and moisture content was significantly reduced. Based on the findings of this study, GPR technology has the ability to characterize in situ substructure soil type and moisture content of typical Saskatchewan road substructure soils. Given the influence of road soil type and moisture content on in-service road performance, this ability could provide road engineers with accurate estimates of in situ structural condition of road structures for preservation and rehabilitation planning and optimization purposes. [ABSTRACT FROM AUTHOR]

Soil water content (SWC) is one of the most important hydrologic variables; it plays a decisive role in the control of various land surface processes. We simulated SWC using a Soil and Water Assessment Tool (SWAT) model in southern Saskatchewan. SWC was calibrated using measured data and Soil Moisture Active Passive (SMAP) Level-4 for the surface (0–5 cm) SWC for hydrological response units (HRU) at daily and monthly (warm season) intervals for the years 2015 to 2020. We used the SUFI-2 technique in SWAT-CUP, and observed daily instrumented streamflow records, for calibration (1995 to 2004) and validation (2005–2010). The results reveal that the SWAT model performs well with a monthly PBIAS < 10% and Nash–Sutcliffe efficiency (NS) and R2 ≥ 0.8 for calibration and validation. The correlation coefficient between ground measurement with SMAP and SWAT products are 0.698 and 0.633, respectively. Moreover, SMAP data of surface SWC coincides well with measurements in terms of both amount and trend compared with the SWAT product. The highest r value occurred in July when the mean r value in SWAT and SMAP were 0.87 to 0.84, and then in June for r value of 0.75. In contrast, the lowest values were in April and May (0.07 and 0.04, respectively) at the beginning of the growing season in southern Saskatchewan. Furthermore, calibration in the SWAT model is based on a batch form whereby parameters are adjusted to corresponding input by modifying simulations with observations. SWAT underestimates the abrupt increase in streamflow during the snowmelt months (April and May). This study achieved the objective of developing a SWAT model that simulates SWC in a prairie watershed, and, therefore, can be used in a subsequent phase of research to estimate future soil moisture conditions under projected climate changes. [ABSTRACT FROM AUTHOR]

Light-use efficiency (LUE) is the ability of vegetated canopies to use light for photosynthesis. Together with remote sensing estimates of canopy cover and meteorological inputs, LUE provides a physical basis for scaling carbon uptake processes from the stand to the global scale. A better understanding of the factors that control LUE will result in improved global estimates of carbon uptake from the terrestrial biosphere. To examine factors that control variability in LUE in stands of different ages during dry and wet conditions, we measured LUE in a chronosequence of four jack pine stands (recent clearcut (age 1–3), regenerating (age 8–9), immature (age 29–30) and mature (∼90 years old)) during one normal (2002), one very dry (2003) and two very wet (2004, 2005) growing seasons in Saskatchewan, Canada. Cumulative CO2 fluxes decreased significantly at all sites during the drought year of 2003, as did mean LUE. Canopy foliage at the recently regenerating jack pine site increased by 19% between 2002 and 2003. Foliage growth rate was reduced by 6% between 2003 and 2004, and foliage biomass decreased by 6% from 2004 to 2005. Over the four years studied, LUE was greatest at the mature jack pine site and lower, but similar, at the other three sites. Mean growing-season LUE varied with mean soil water content at each site, except at that of the newly regenerating stand where soil water had little influence. Mean daily vapor pressure deficit typically had the greatest influence on variability in LUE at all sites. Diffuse versus direct radiation also had significant but varying effects on LUE in jack pine stands of different ages. [ABSTRACT FROM AUTHOR]

In 2001–03, continuous eddy covariance measurements of carbon dioxide (CO2) flux were made above mature boreal aspen, black spruce, and jack pine forests in Saskatchewan, Canada, prior to and during a 3−year drought. During the 1st drought year, ecosystem respiration ( R) was reduced at the aspen site due to the drying of surface soil layers. Gross ecosystem photosynthesis (GEP) increased as a result of a warm spring and a slow decrease of deep soil moisture. These conditions resulted in the highest annual net ecosystem productivity (NEP) in the 9 years of flux measurements at this site. During 2002 and 2003, a reduction of 6% and 34% in NEP, respectively, compared to 2000 was observed as the result of reductions in both R and GEP, indicating a conservative response to the drought. Although the drought affected most of western Canada, there was considerable spatial variability in summer rainfall over the 100−km extent of the study area; summer rainfalls in 2001 and 2002 at the two conifer sites minimized the impact of the drought. In 2003, however, precipitation was similarly low at all three sites. Due to low topographic position and consequent poor drainage at the black spruce site and the coarse soil with low water-holding capacity at the jack pine site almost no reduction in R, GEP, and NEP was observed at these two sites. This study shows that the impact of drought on carbon sequestration by boreal forest ecosystems strongly depends on rainfall distribution, soil characteristics, topography, and the presence of vegetation that is well adapted to these conditions. [ABSTRACT FROM AUTHOR]

Soil moisture is a key variable used to describe water and energy exchanges at the land surface/atmosphere interface. Therefore, there is widespread interest in the use of soil moisture retrievals from passive microwave satellites. In the assimilation of satellite soil moisture data into land surface models, two approaches are commonly used. In the first approach brightness temperature (TB) data are assimilated, while in the second approach retrieved soil moisture (SM) data from the satellite are assimilated. However, there is not a significant body of literature comparing the differences between these two approaches, and it is not known whether there is any advantage in using a particular approach over the other. In this study, TB and SM L2 retrieval products from the Soil Moisture and Ocean Salinity (SMOS) satellite are assimilated into the Canadian Land Surface Scheme (CLASS), for improved soil moisture estimation over an agricultural region in Saskatchewan. CLASS is the land surface component of the Canadian Earth System Model (CESM), and the Canadian Seasonal and Interannual Prediction System (CanSIPS). Our results indicated that assimilating the SMOS products improved the soil moisture simulation skill of the CLASS. Near surface soil moisture assimilation also resulted in improved forecasts of root zone soil moisture (RZSM) values. Although both techniques resulted in improved forecasts of RZSM, assimilation of TB resulted in the superior estimates. [ABSTRACT FROM AUTHOR]