Active microwave remote sensing for soil moisture measurement: a field evaluation using ERS‐2

Active microwave remote sensing observations of backscattering, such as C‐band vertically polarized synthetic aperture radar (SAR) observations from the second European remote sensing (ERS‐2) satellite, have the potential to measure moisture content in a near‐surface layer of soil. However, SAR backscattering observations are highly dependent on topography, soil texture, surface roughness and soil moisture, meaning that soil moisture inversion from single frequency and polarization SAR observations is difficult. In this paper, the potential for measuring near‐surface soil moisture with the ERS‐2 satellite is explored by comparing model estimates of backscattering with ERS‐2 SAR observations. This comparison was made for two ERS‐2 overpasses coincident with near‐surface soil moisture measurements in a 6 ha catchment using 15‐cm time domain reflectometry probes on a 20 m grid. In addition, 1‐cm soil moisture data were obtained from a calibrated soil moisture model. Using state‐of‐the‐art theoretical, semi‐empirical and empirical backscattering models, it was found that using measured soil moisture and roughness data there were root mean square (RMS) errors from 3·5 to 8·5 dB and r² values from 0·00 to 0·25, depending on the backscattering model and degree of filtering. Using model soil moisture in place of measured soil moisture reduced RMS errors slightly (0·5 to 2 dB) but did not improve r² values. Likewise, using the first day of ERS‐2 backscattering and soil moisture data to solve for RMS surface roughness reduced RMS errors in backscattering for the second day to between 0·9 and 2·8 dB, but did not improve r² values. Moreover, RMS differences were as large as 3·7 dB and r² values as low as 0·53 between the various backscattering models, even when using the same data as input. These results suggest that more research is required to improve the agreement between backscattering models, and that ERS‐2 SAR data may be useful for estimating fields‐scale average soil moisture but not variations at the hillslope scale. Copyright © 2004 John Wiley & Sons, Ltd.     

Spatio‐temporal distribution of near‐surface and root zone soil moisture at the catchment scale

Soil moisture is highly variable both spatially and temporally. It is widely recognized that improving the knowledge and understanding of soil moisture and the processes underpinning its spatial and temporal distribution is critical. This paper addresses the relationship between near‐surface and root zone soil moisture, the way in which they vary spatially and temporally, and the effect of sampling design for determining catchment scale soil moisture dynamics. In this study, catchment scale near‐surface (0–50 mm) and root zone (0–300 mm) soil moisture were monitored over a four‐week period. Measurements of near‐surface soil moisture were recorded at various resolutions, and near‐surface and root zone soil moisture data were also monitored continuously within a network of recording sensors. Catchment average near‐surface soil moisture derived from detailed spatial measurements and continuous observations at fixed points were found to be significantly correlated (r² = 0·96; P = 0·0063; n = 4). Root zone soil moisture was also found to be highly correlated with catchment average near‐surface, continuously monitored (r² = 0·81; P < 0·0001; n = 26) and with detailed spatial measurements of near‐surface soil moisture (r² = 0·84). The weaker relationship observed between near‐surface and root zone soil moisture is considered to be caused by the different responses to rainfall and the different factors controlling soil moisture for the soil depths of 0–50 mm and 0–300 mm. Aspect is considered to be the main factor influencing the spatial and temporal distribution of near‐surface soil moisture, while topography and soil type are considered important for root zone soil moisture. The ability of a limited number of monitoring stations to provide accurate estimates of catchment scale average soil moisture for both near‐surface and root zone is thus demonstrated, as opposed to high resolution spatial measurements. Similarly, the use of near‐surface soil moisture measurements to obtain a reliable estimate of deeper soil moisture levels at the small catchment scale was demonstrated. Copyright © 2007 John Wiley & Sons, Ltd.     

Relationship between soil moisture of near surface and multiple depths of the root zone under heterogeneous land uses and varying hydroclimatic conditions

This paper presents an assessment of the relationship between near-surface soil moisture (SM) and SM at other depths in the root zone under three different land uses: irrigated corn, rainfed corn and grass. This research addresses the question whether or not near-surface SM can be used reliably to predict plant available root zone SM and SM at other depths. For this study, a realistic soil-water energy balance process model is applied to three locations in Nebraska representing an east-to-west hydroclimatic gradient in the Great Plains. The applications were completed from 1982 through to 1999 at a daily time scale. The simulated SM climatologies are developed for the root zone as a whole and for the five layers of the soil profile to a depth of 1·2 m. Over all, the relationship between near-surface SM (0–2·5 cm) and plant available root zone SM is not strong. This applies to all land uses and for all locations. For example, r estimates range from 0·02 to 0·33 for this relationship. Results for near-surface SM and SM of several depths suggest improvement in r estimates. For example, these estimates range from − 0·19 to 0·69 for all land uses and locations. It was clear that r estimates are the highest (0·49–0·69) between near-surface and the second layer (2·5–30·5 cm) of the root zone. The strength of this type of relationship rapidly declines for deeper depths. Cross-correlation estimates also suggest that at various time-lags the strength of the relationship between near-surface SM and plant available SM is not strong. The strength of the relationship between SM modulation of the near surface and second layer over various time-lags slightly improves over no lags. The results suggest that use of near-surface SM for estimating SM at 2·5–30 cm is most promising. Copyright © 2007 John Wiley & Sons, Ltd.     

A new soil freeze/thaw discriminant algorithm using AMSR‐E passive microwave imagery

The soil freeze–thaw controls the hydrological and carbon cycling and thus affects water and energy exchanges at land surface. This article reported a newly developed algorithm for distinguishing the freeze/thaw status of surface soil. The algorithm was based on information from Advanced Microwave Scanning Radiometer Enhanced (AMSR‐E) which records brightness temperature (Tb) in the afternoon and after midnight. The criteria and discriminant functions were obtained from both radiometer observations and model simulations. First of all, the microwave radiation from freeze–thaw soil was examined by carrying out experimental measurements at 18·7 and 36·5 GHz using a Truck‐mounted Multi‐frequency Microwave Radiometer (TMMR) in the Heihe River of China. The experimental results showed that the soil moisture is a key component that differentiates the microwave radiation behaviours during the freeze–thaw process, and the differences in soil temperature and emissivity between frozen and thawed soils were found to be the most important criteria. Secondly, a combined model was developed to consider the impacts of complex ground surface conditions on the discrimination. The model simulations quite followed the trend of in situ observations with an overall relation coefficient (R) of approximately 0·88. Finally, the ratio of Tb18·7H (horizontally polarized Tb at 18·7 GHz) to Tb36·5V was considered primarily as the quasi‐emissivity, which is more reasonable and explicit in measuring the microwave radiation changes in soil freezing and thawing than the spectral gradient. By combining Tb36·5V to indicate the soil temperature variety, a Fisher linear discrimination analysis was used to establish the discriminant functions. After being corrected by TMMR measurements, the new discriminant algorithm had an overall accuracy of 86% when validated by 4‐cm soil temperature. The multi‐year discriminant results also provided a good agreement with the classification map of frozen ground in China. Copyright © 2011 John Wiley & Sons, Ltd.     

Towards the estimation root-zone soil moisture via the simultaneous assimilation of thermal and microwave soil moisture retrievals

The upcoming deployment of satellite-based microwave sensors designed specifically to retrieve surface soil moisture represents an important milestone in efforts to develop hydrologic applications for remote sensing observations. However, typical measurement depths of microwave-based soil moisture retrievals are generally considered too shallow (top 2–5 cm of the soil column) for many important water cycle and agricultural applications. Recent work has demonstrated that thermal remote sensing estimates of surface radiometric temperature provide a complementary source of land surface information that can be used to define a robust proxy for root-zone (top 1 m of the soil column) soil moisture availability. In this analysis, we examine the potential benefits of simultaneously assimilating both microwave-based surface soil moisture retrievals and thermal infrared-based root-zone soil moisture estimates into a soil water balance model using a series of synthetic twin data assimilation experiments conducted at the USDA Optimizing Production Inputs for Economic and Environmental Enhancements (OPE³) site. Results from these experiments illustrate that, relative to a baseline case of assimilating only surface soil moisture retrievals, the assimilation of both root- and surface-zone soil moisture estimates reduces the root-mean-square difference between estimated and true root-zone soil moisture by 50% to 35% (assuming instantaneous root-zone soil moisture retrievals are obtained at an accuracy of between 0.020 and 0.030 m³ m⁻³). Most significantly, improvements in root-zone soil moisture accuracy are seen even for cases in which root-zone soil moisture retrievals are assumed to be relatively inaccurate (i.e. retrievals errors of up to 0.070 m³ m⁻³) or limited to only very sparse sampling (i.e. one instantaneous measurement every eight days). Preliminary real data results demonstrate a clear increase in the R² correlation coefficient with ground-based root-zone observations (from 0.51 to 0.73) upon assimilation of actual surface soil moisture and tower-based thermal infrared temperature observations made at the OPE³ study site.     

Synergistic effect of vegetation and air temperature changes on soil water content in alpine frost meadow soil in the permafrost region of Qinghai‐Tibet

Seasonal changes over 2 years (2004–2006) in soil moisture content (θ_v) of frozen alpine frost meadow soils of the Qinghai‐Tibet plateau permafrost region under three different levels of vegetation cover were investigated. Vegetation cover and air temperature changes had significant effects (synergistic effect) on θ_v and its distribution in the soil profile. During periods of soil freezing or thawing, the less the vegetation cover, the quicker the temperature drop or rise of soil water, and the shorter the duration of the soil water freeze–thaw response in the active soil layer. Under 30% and 65% vegetation cover the amplitude of variation in θ_v during the freezing period was 20–26% greater than that under 93% cover, while during the thawing period, it was 1·5‐ to 40·5‐fold greater. The freezing temperature of the surface soil layer, ^fT_s, was 1·6 °C lower under 30% vegetation cover than under 93% vegetation cover. Changes in vegetation cover of the alpine frost meadow affected θ_v and its distribution, as well as the relationship between θ_v and soil temperature (T_s). As vegetation cover decreased, soil water circulation in the active layer increased, and the response to temperature of the water distribution across the soil profile was heightened. The quantity of transitional soil phase water at different depths significantly increased as vegetation cover decreased. The influence of vegetation cover and soil temperature distribution led to a relatively dry soil layer in the middle of the profile (0·70–0·80 m) under high vegetation cover. Alpine meadow θ_v and its pattern of distribution in the permafrost region were the result of the synergistic effect of air temperature and vegetation cover. Copyright © 2007 John Wiley & Sons, Ltd.     

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 dynamics in coastal savanna soils in the tropics under different soil management practices

Abstract

Soil moisture is important for crop cultivation and its adequacy to meet crop-water requirements is determined by the degree of soil management practised and the quantity of water applied to the soil. This study investigates soil moisture dynamics on three plots: Bare (clean, weeds removed), Weedy (kept weedy), and Mulched (cleared of weeds and fully covered with grass mulch) during rainy and dry periods at the Teaching and Research Farm at the University of Cape Coast, in the coastal savanna zone of Ghana. Soil moisture dynamics under different levels of soil compaction were also studied. A Massey Ferguson tractor (MF265) was used to compact the soil at various levels by making 0, 1, 5, 9 and 13 passes. During both the rainy and the dry periods, moisture retention in the soil under bare, weedy and mulched plots increased with depth. During the rainy period, the mean soil moisture retention was in the order: Mulched > Weedy > Bare at both 0–20 cm and 20–40 cm depths. Within a 7–day period, soil moisture measurements from a day after heavy rainfall (intensity > 7 mm h^?1) gave mean moisture losses of 2.7, 4.1 and 3.9% for the Bare, Weedy and Mulched plots, respectively. During the dry period, however, the mean soil moisture retention was of the order: Mulched > Bare > Weedy at both 0–20 cm and 20–40 cm depths. Mean moisture loss during a 7–day dry period was 4.5, 2.9 and 3.4% for the Bare, Weedy and Mulched plots, respectively. Under different levels of soil compaction, the mean moisture retention in the soil increased from 8.3% at 0 pass to 17.8% at 13 passes within the 0–20 cm depth, whilst it decreased from 13.3 to 5.9% from 0 to 13 passes, respectively, within the 20–40 cm depth. It was realized that at less than two passes, the mean soil moisture retention within the 0–20 cm depth was less than the mean moisture retention within the 20–40 cm depth, but the converse happened for more than two passes. The study showed that mulching the soil surface helped to retain enough soil moisture during both the rainy and the dry seasons. Also, soil with high sand content required some sort of soil compaction in order to retain enough moisture at the crop rooting zone.     

Use of soil moisture data and curve number method for estimating runoff in the Loess Plateau of China

The Soil Conservation Service curve number (CN) method commonly uses three discrete levels of soil antecedent moisture condition (AMC), defined by the 5‐day antecedent rainfall depth, to describe soil moisture prior to a runoff event. However, this way may not adequately represent soil water conditions of fields and watersheds in the Loess Plateau of China. The objectives of this study were: (1) to determine the effective soil moisture depth to which the CN is most related; (2) to evaluate a discrete and a linear relationship between AMC and soil moisture; and (3) to develop an equation between CN and soil moisture to predict runoff better for the climatic and soil conditions of the Loess Plateau of China. The dataset consisted of 10 years of rainfall, runoff and soil moisture measurements from four experimental plots cropped with millet, pasture and potatoes. Results indicate that the standard CN method underestimated runoff depths for 85 of the 98 observed plot‐runoff events, with a model efficiency E of only 0·243. For our experimental conditions, the discrete and linear approaches improved runoff estimation, but still underestimated most runoff events, with E values of 0·428 and 0·445 respectively. Based on the measured CN values and soil moisture values in the top 15 cm of the soil, a non‐linear equation was developed that predicted runoff better with an E value of 0·779. This modified CN equation was the most appropriate for runoff prediction in the study area, but may need adjustments for local conditions in the Loess Plateau of China. Copyright © 2006 John Wiley & Sons, Ltd.     

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.     

Application of data assimilation with the Root Zone Water Quality Model for soil moisture profile estimation in the upper Cedar Creek,Indiana

Data assimilation techniques have been proven as an effective tool to improve model forecasts by combining information about observed variables in many areas. This article examines the potential of assimilating surface soil moisture observations into a field‐scale hydrological model, the Root Zone Water Quality Model, to improve soil moisture estimation. The Ensemble Kalman Filter (EnKF), a popular data assimilation technique for nonlinear systems, was applied and compared with a simple direct insertion method. In situ soil moisture data at four different depths (5, 20, 40, and 60 cm) from two agricultural fields (AS1 and AS2) in northeastern Indiana were used for assimilation and validation purposes. Through daily update, the EnKF improved soil moisture estimation compared with the direct insertion method and model results without assimilation, having more distinct improvement at the 5 and 20 cm depths than for deeper layers (40 and 60 cm). Local vertical soil property heterogeneity in AS1 deteriorated soil moisture estimates with the EnKF. Removal of systematic bias in the forecast model was found to be critical for more successful soil moisture data assimilation studies. This study also demonstrates that a more frequent update generally contributes in enhancing the open loop simulation; however, large forecasting error can prevent more frequent update from providing better results. In addition, results indicate that various ensemble sizes make little difference in the assimilation results. An ensemble of 100 members produced results that were comparable with results obtained from larger ensembles. Copyright © 2011 John Wiley & Sons, Ltd.     

Spatial and temporal dynamics of soil moisture after rainfall events along a slope in Regosols of southwest China

High frequency seasonal drought in purple soils (Regosols in FAO taxonomy) of the hilly upland areas of Sichuan basin, China, is one of the key restrictive factors for crop production. In order to manage irrigation and fertilizer application in these soils effectively, the soil water content in a sloped plot with 60 cm soil depth was measured by neutron probe devices to investigate the soil moisture regime during the 1998 rainy season after various amounts of rainfall events. The results showed that variation of soil moisture along the slope positions was highest in the top soil layer during the period of sporadic rainfall that did not induce any runoff. The coefficients of variation of soil moisture at various slope positions (upper, middle, and lower) are 17·36%, 8·95%, 10·25%, 8·58%, 8·05% and 9·21% at the 10 cm, 20 cm, 30 cm, 40 cm, 50 cm and 60 cm soil depths respectively. When surface runoff occurred, the soil moisture dynamics at various positions on the plot were then very different. Soil water content decreased more rapidly on the upper slope than on the middle and lower slope positions. When both surface runoff and throughflow occurred, the soil moisture dynamics in the various layers showed a stable period (soil water content is near constant as time elapses) that lasted about 1 week. Also, the pattern of moisture dynamics is ‘decreasing–stabilization–decreasing’. Thus, irrigation and fertilization management according to the spatial and temporal features of soil moisture dynamics on sloped land can increase the water and fertilizer utilization efficacy by reducing their losses during the stable period. Copyright © 2006 John Wiley & Sons, Ltd.     

Xylem sap flows of irrigated Tamarix elongata Ledeb and the influence of environmental factors in the desert region of Northwest China

Tamarix elongata Ledeb is a desert shrub found in the desert region of Northwest China and is commonly cultivated as a sand‐holding plant in this region. To understand its water requirement and the effects of climate conditions on its growth, trunk xylem sap flows of irrigated 8‐year‐old Tamarix elongata Ledeb plants were monitored continuously with heat‐pulse sap flow meters for the entire season. Soil moisture contents at 0–300 cm layer depth were also measured with a tube type time domain reflectometry (Tube‐TDR). Meteorological factors, i.e. solar radiation, air temperature, relative humidity and wind speed were simultaneously monitored by an automatic weather station at the site. Daily and seasonal variations of the trunk sap fluxes and their correlations with the meteorological factors, reference evapotranspiration and soil moisture contents in the root‐zone were analysed. The results indicated that frost influenced the trunk sap flux greatly under irrigated conditions, although the flux generally fluctuated with the variation of environmental factors and showed a mean trunk sap flux of 4·18 l d^?1. There was a significantly exponential relationship between sap flux and the reference value of crop evapotranspiration, with a correlation coefficient of R² = 0·7172. The sap flux also had a significant correlation with the soil water contents at a depth of 150–300 cm from soil surface (R² = 0·5014). The order of the main meteorological factors affecting the sap flux of Tamarix elongata Ledeb trees was solar radiation > air temperature > vapour pressure deficit > relative humidity > wind speed. Copyright © 2007 John Wiley & Sons, Ltd.     

Seasonal isotope hydrology of three Appalachian forest catchments

Seasonal oxygen-18 variations in precipitation, throughfall, soil water, spring flow and stream baseflow were analysed to compare the hydrology of two forested basins in West Virginia (WV) (34 and 39 ha) and one in Pennsylvania (PA) (1134 ha). Precipitation and throughfall were measured with funnel/bottle samplers, soil water with ceramic-cup suction lysimeters and spring flow/baseflows by grab and automatic sampling during the period March 1989 to March 1990. Isotopic damping depths, or depths required to reduce the amplitude of subsurface oxygen-18 fluctuations to 37% of the surface amplitude, were generally similar for soil water on the larger PA basin, and baseflows and headwater spring flows on the smaller WV basins. Computed annual isotopic damping depths for these water sources averaged 49 cm using soil depth as the flow path length. The equivalent annual mean hydraulic diffusivity for the soil flow paths was 21 cm² d⁻¹. Mean transit times, based upon an assumed exponential distribution of transit times, ranged from 0·2 y for soil water at a depth of 30 cm on the larger catchment, to 1·1–1·3 y for most spring flows and 1·4–1·6 y for baseflows on the smaller catchments. Baseflow on the larger PA basin and flow of one spring on a small WV basin showed no detectable seasonal fluctuations in oxygen-18, indicating flow emanated from sources with mean transit times greater than about 5 y. Based upon this soil flow path approach, it was concluded that seasonal oxygen-18 variations can be used to infer mean annual isotopic damping depths and diffusivities for soil depths up to approximately 170 cm. © 1997 John Wiley & Sons, Ltd.     

On the potential of MetOp ASCAT‐derived soil wetness indices as a new aperture for hydrological monitoring and prediction: a field evaluation over Luxembourg

In situ soil moisture data from the Bibeschbach experimental catchment in Luxembourg are used to evaluate relative surface soil moisture observed with the MetOp‐A Advanced Scatterometer (ASCAT). Filtered and bias‐corrected surface soil wetness indices (SWIs) derived from coarse‐resolution (25 km) C‐band scatterometer observations are shown to be highly correlated (r = 0.86) with catchment‐averaged soil moisture measured in the field. The combination of ASCAT and ENVISAT Advanced Synthetic Aperture Radar (ASAR) data sets yields high‐resolution (1 km) relative surface soil moisture that is equally well correlated with in situ measurements. It is concluded that for soil moisture monitoring applications at a catchment scale, the two soil moisture products are equivalent. The best correlation between the SWI derived from ASCAT and ASCAT‐ASAR with in situ soil moisture observations at ca. 5 cm depth is obtained with a characteristic time length parameter T equal to 288 h. These results suggest that satellite‐derived surface soil wetness may serve as proxy for soil storage that enables the monitoring of abrupt switches in river system dynamics to appear when an effective field capacity is exceeded and rapid subsurface stormflow is initiated. In catchments where soil moisture is the main controlling factor of rapid subsurface flow, MetOp ASCAT–derived SWI has the potential to monitor how a river system approaches a critical threshold. Copyright © 2011 John Wiley & Sons, Ltd.     

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.     

A soil moisture assimilation scheme based on the ensemble Kalman filter using microwave brightness temperature

This study presents a soil moisture assimilation scheme, which could assimilate microwave brightness temperature directly, based on the ensemble Kalman filter and the shuffled complex evolution method (SCE-UA). It uses the soil water model of the land surface model CLM3.0 as the forecast operator, and a radiative transfer model (RTM) as the observation operator in the assimilation system. The assimilation scheme is implemented in two phases: the parameter calibration phase and the pure soil moisture assimilation phase. The vegetation optical thickness and surface roughness parameters in the RTM are calibrated by SCE-UA method and the optimal parameters are used as the final model parameters of the observation operator in the assimilation phase. The ideal experiments with synthetic data indicate that this scheme could significantly improve the simulation of soil moisture at the surface layer. Furthermore, the estimation of soil moisture in the deeper layers could also be improved to a certain extent. The real assimilation experiments with AMSR-E brightness temperature at 10.65 GHz (vertical polarization) show that the root mean square error (RMSE) of soil moisture in the top layer (0–10 cm) by assimilation is 0.03355 m³ · m⁻³, which is reduced by 33.6% compared with that by simulation (0.05052 m³ · m⁻³). The mean RMSE by assimilation for the deeper layers (10–50 cm) is also reduced by 20.9%. All these experiments demonstrate the reasonability of the assimilation scheme developed in this study.     

Performance evaluation of soil moisture profile estimation through entropy-based and exponential filter models

ABSTRACT

In this study we analyzed two models commonly used in remote sensing-based root-zone soil moisture (SM) estimations: one utilizing the exponential decaying function and the other derived from the principle of maximum entropy (POME). We used both models to deduce root-zone (0–100 cm) SM conditions at 11 sites located in the southeastern USA for the period 2012–2017 and evaluated the strengths and weaknesses of each approach against ground observations. The results indicate that, temporally, at shallow depths (10 cm), both models performed similarly, with correlation coefficients (r) of 0.89 (POME) and 0.88 (exponential). However, with increasing depths, the models start to deviate: at 50 cm the POME resulted in r of 0.93 while the exponential filter (EF) model had r of 0.58. Similar trends were observed for unbiased root mean square error (ubRMSE) and bias. Vertical profile analysis suggests that, overall, the POME model had nearly 30% less ubRMSE compared to the EF model, indicating that the POME model was relatively better able to distribute the moisture content through the soil column.     

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.     

Investigation of soil water hydrological process in the permafrost active layer using stable isotopes

Here, we studied the isotope characteristics and source contributions of soil water in the permafrost active layer by collecting soil samples in July 2018 in Yangtze River basin. Soil moisture and temperature showed decreasing trends from 0–80 cm, and an increasing trend from 80–100 cm. The value of δ¹⁸O and δD first increased and then decreased in the soil profile of 0–100 cm; however, d-excess increased from 0–100 cm. δ¹⁸O values became gradually positive from the southwest to northeast of the study area, while d-excess gradually increased from southeast to northwest. The evaporation water line (EL) was δD = 7.56 δ¹⁸O + 1.50 (R² = 0.90, p < 0.01, n = 96). Due to intense solar radiation and evaporation on the Tibetan Plateau, the elevation did not impact the surface soil. The altitude effect of the soil depths of 0–20 cm was not obvious, but the other soil layers had a significant altitude effect. Soil moisture and temperature were closely related to the stable isotopic composition of soil water. The contribution of precipitation to soil water on the sunny slope was 86%, while the contribution of the shady slope was 84%. However, the contribution of ground ice to soil water on sunny slope was 14% and the shady slope was 16%. The contribution of ground ice to soil water increased with increasing altitude on the sunny slope, but the contribution of ground ice to soil water had no obvious trend on the shady slope.