Improving the representation of soil moisture by using a semi‐analytical infiltration model

Soil moisture is widely recognized as a fundamental variable governing the mass and energy fluxes between the land surface and the atmosphere. In this study, the soil moisture modelling at sub‐daily timescale is addressed by using an accurate representation of the infiltration component. For that, the semi‐analytical infiltration model proposed by Corradini et al. (1997) has been incorporated into a soil water balance model to simulate the evolution in time of surface and profile soil moisture. The performances of this new soil moisture model [soil water balance module‐semi‐analytical (SWBM‐SA)] are compared with those of a precedent version [SWBM‐Green–Ampt (GA)] where the GA approach was employed. Their capability to reproduce in situ soil moisture observations at three sites in Italy, Spain and France is analysed. Hourly observations of quality‐checked rainfall, temperature and soil moisture data for a 2‐year period are used for testing the modelling approaches. Specifically, different configurations for the calibration and validation of the models are adopted by varying a single parameter, that is, the saturated hydraulic conductivity. Results indicate that both SWBMs are able to reproduce satisfactorily the hourly soil moisture temporal pattern for the three sites with root mean square errors lower than 0.024 m³/m³ both in the calibration and validation periods. For all sites, the SWBM‐SA model outperforms the SWBM‐GA with an average reduction of the root mean square error of ~20%. Specifically, the higher improvement is observed for the French site for which in situ observations are measured at 30 cm depth, and this is attributed to the capability of the SA infiltration model to simulate the time evolution of the whole soil moisture profile. The reasonable models performance coupled with the need to calibrate only a single parameter makes them useful tools for soil moisture simulation in different regions worldwide, also in scarcely gauged areas. Copyright © 2013 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.     

Estimation of soil hydraulic properties and their uncertainty: comparison between laboratory and field experiment

Often the soil hydraulic parameters are obtained by the inversion of measured data (e.g. soil moisture, pressure head, and cumulative infiltration, etc.). However, the inverse problem in unsaturated zone is ill‐posed due to various reasons, and hence the parameters become non‐unique. The presence of multiple soil layers brings the additional complexities in the inverse modelling. The generalized likelihood uncertainty estimate (GLUE) is a useful approach to estimate the parameters and their uncertainty when dealing with soil moisture dynamics which is a highly non‐linear problem. Because the estimated parameters depend on the modelling scale, inverse modelling carried out on laboratory data and field data may provide independent estimates. The objective of this paper is to compare the parameters and their uncertainty estimated through experiments in the laboratory and in the field and to assess which of the soil hydraulic parameters are independent of the experiment. The first two layers in the field site are characterized by Loamy sand and Loamy. The mean soil moisture and pressure head at three depths are measured with an interval of half hour for a period of 1 week using the evaporation method for the laboratory experiment, whereas soil moisture at three different depths (60, 110, and 200 cm) is measured with an interval of 1 h for 2 years for the field experiment. A one‐dimensional soil moisture model on the basis of the finite difference method was used. The calibration and validation are approximately for 1 year each. The model performance was found to be good with root mean square error (RMSE) varying from 2 to 4 cm³ cm^?3. It is found from the two experiments that mean and uncertainty in the saturated soil moisture (θ_s) and shape parameter (n) of van Genuchten equations are similar for both the soil types. Copyright © 2010 John Wiley & Sons, Ltd.     

Development of a continuous soil moisture accounting procedure for curve number methodology and its behaviour with different evapotranspiration methods

The curve number (CN) method is widely used for rainfall–runoff modelling in continuous hydrologic simulation models. A sound continuous soil moisture accounting procedure is necessary for models using the CN method. For shallow soils and soils with low storage, the existing methods have limitations in their ability to reproduce the observed runoff. Therefore, a simple one‐parameter model based on the Soil Conservation Society CN procedure is developed for use in continuous hydrologic simulation. The sensitivity of the model parameter to runoff predictions was also analysed. In addition, the behaviour of the procedure developed and the existing continuous soil moisture accounting procedure used in hydrologic models, in combination with Penman–Monteith and Hargreaves evapotranspiration (ET) methods was also analysed. The new CN methodology, its behaviour and the sensitivity of the depletion coefficient (model parameter) were tested in four United States Geological Survey defined eight‐digit watersheds in different water resources regions of the USA using the SWAT model. In addition to easy parameterization for calibration, the one‐parameter model developed performed adequately in predicting runoff. When tested for shallow soils, the parameter is found to be very sensitive to surface runoff and subsurface flow and less sensitive to ET. Copyright © 2007 John Wiley & Sons, Ltd.     

Vegetation and soil carbon storage in China

This study estimated the current vegetation and soil carbon storage in China using a biogeochemical model driven with climate, soil and vegetation data at 0.5° latitude-longitude grid spatial resolution. The results indicate that the total carbon storage in China's vegetation and soils was 13.33 Gt C and 82.65 Gt C respectively, about 3% and 4% of the global total. The nationally mean vegetation and soil carbon densities were 1.47 kg C/m2 and 9.17 kg C/m2, respectively, differing greatly in various regions affected by climate, vegetation, and soil types. They were generally higher in the warm and wet Southeast China and Southwest China than in the arid Northwest China; whereas vegetation carbon density was the highest in the warm Southeast China and Southwest China, soil carbon density was the highest in the cold Northeast China and southeastern fringe of the Qinghai-Tibetan Plateau. These spatial patterns are clearly correlated with variations in the climate that regulates plant growth and soil organi     

The effect of conservation practices in sloped croplands on soil hydraulic properties and root‐zone moisture dynamics

Rain‐induced erosion and short‐term drought are the two factors that limit the productivity of croplands in the red soil region of subtropical China. The objective of this study was to estimate the effects of conservation practices on hydraulic properties and root‐zone water dynamics of the soil. A 3‐year experiment was performed on a slope at Xianning. Four treatments were evaluated for their ability to reduce soil erosion and improve soil water conditions. Compared with no practices (CK) and living grass strips (GS), the application of polyacrylamide (PAM) significantly reduced soil crust formation during intense rainfall, whereas rice straw mulching (SM) completely abolished soil crust formation. The SM and PAM treatments improved soil water‐stable aggregates, with a redistribution of micro‐aggregates into macro‐aggregates. PAM and SM significantly increased the soil water‐holding capacity. These practices mitigated the degradation of the soil saturated hydraulic conductivity (Ks) during intense rainfalls. These methods increased soil water storage but with limited effects during heavy rainfalls in the wet period. In contrast, during the dry period, SM had the highest soil water storage, followed by PAM and CK. Grass strips had the lowest soil water storage because of the water uptake during the vigorous grass growth. A slight decline in the soil moisture resulted in a significant decrease in the unsaturated hydraulic conductivity (Ku) of the topsoil. Therefore, the hydraulic conductivity in the field is governed by soil moisture, and the remaining soil moisture is more important than improving soil properties to resist short‐term droughts. As a result, SM is the most effective management practice when compared with PAM and GS, although they all protect the soil hydraulic properties during wet periods. These results suggest that mulching is the best strategy for water management in erosion‐threatened and drought‐threatened red soils. Copyright © 2014 John Wiley & Sons, Ltd.     

A simple water balance model adapted for soil water repellency: application on Portuguese burned and unburned eucalypt stands

Soil water repellency can impact soil hydrology, overland flow generation and associated soil losses. However, current hydrological models do not take it into account, which creates a challenge in repellency‐prone regions. This work focused on the adaptation for soil water repellency of a daily water balance model. Repellency is estimated from soil moisture content using site‐specific empirical relations and used to limit maximum soil moisture. This model was developed and tested using approximately 2 years of data from one long‐unburned and two recently burned eucalypt plantations in northern Portugal, all of which showed strong seasonal soil water repellency cycles. Results indicated important improvements for the burned plantations, with the Nash–Sutcliffe efficiency increasing from ?0.55 and ?0.49 to 0.55 and 0.65. For the unburned site, model performance was already good without the modification and efficiency only improved slightly from 0.71 to 0.74, mostly due to the better simulation of delayed soil wetting after dry periods. Results suggested that even a simple approach to simulate soil water repellency can markedly improve the performance of hydrological models in eucalypt forests, especially after fire. Copyright © 2015 John Wiley & Sons, Ltd.     

Influence of heterogeneity on unsaturated hydraulic properties: (1) local heterogeneity and scale effect

Spatial heterogeneity is ubiquitous in nature, which may significantly affect the soil hydraulic property curves. The models of a closed‐form functional relationship of soil hydraulic property curves (e.g. VG model or exponential model) are valid at point or local scale based on a point‐scale hydrological process, but how do scale effects of heterogeneity have an influence on the parameters of these models when the models are used in a larger scale process? This paper uses a two‐dimensional variably saturated flow and solute transport finite element model (VSAFT2) to simulate variations of pressure and moisture content in the soil flume under a constant head boundary condition. By changing different numerical simulation block sizes, a quantitative evaluation of parameter variations in the VG model, resulting from the scale effects, is presented. Results show that the parameters of soil hydraulic properties are independent of scale in homogeneous media. Parameters of α and n in homogeneous media, which are estimated by using the unsaturated hydraulic conductivity curve (UHC) or the soil water retention curve (WRC), are identical. Variations of local heterogeneities strongly affect the soil hydraulic properties, and the scale affects the results of the parameter estimations when numerical experiments are conducted. Furthermore, the discrepancy of each curve becomes considerable when moisture content becomes closer to a dry situation. Parameters estimated by UHC are totally different from the ones estimated by WRC. Copyright © 2012 John Wiley & Sons, Ltd.     

Simulated soil erosion from a semiarid typical steppe watershed using an integrated aeolian and fluvial prediction model

Total soil erosion is a result of both aeolian and fluvial processes, which is particularly true in semiarid regions. However, although physically interrelated, these two processes have conventionally been studied and modelled independently. Recently, a few researchers highlighted the importance and need of considering both processes in concert as well as their interactions, but they did not give specific modelling approaches or algorithms. The objectives of this study were to (1) formulate an integrated aeolian and fluvial prediction (IAFP) model, (2) parameterize the IAFP model for a semiarid steppe watershed located in northeastern China by using literature and historical data and (3) use the model to predict soil erosion in the watershed and assess the sensitivity of predicted erosion to environmental factors such as soil moisture and vegetation coverage. The results indicated that the IAFP model can capture the dynamic interactions between aeolian and fluvial erosion processes. For the study watershed, the model predicted a higher occurrence frequency of fluvial erosion than that of aeolian erosion and showed that these two processes almost equivalently contributed to the average total erosion of 0.07 mm year^?1 across the simulation period. The ‘existing’ vegetation cover can provide an overall good protection of the soils, although the vegetation cover was predicted to play a larger role in a drier than a wetter year as well as in controlling aeolian than fluvial erosion. In addition, soil erosion was predicted to be more sensitive to soil moisture than land coverage. A soil moisture level of 0.23–0.25 was determined to be the probable switch point from aeolian‐to fluvial‐dominant process or vice versa. Copyright © 2012 John Wiley & Sons, Ltd.     

Evaluation of the hydrology of the IBIS land surface model in a semi‐arid catchment

This paper evaluates the Integrated BIosphere Simulator (IBIS) land surface model using daily soil moisture data over a 3‐year period (2005–2007) at a semi‐arid site in southeastern Australia, the Stanley catchment, using the Monte Carlo generalized likelihood uncertainty estimation (GLUE) approach. The model was satisfactorily calibrated for both the surface 30 cm and full profile 90 cm. However, full‐profile calibration was not as good as that for the surface, which results from some deficiencies in the evapotranspiration component in IBIS. Relatively small differences in simulated soil moisture were associated with large discrepancies in the predictions of surface runoff, drainage and evapotranspiration. We conclude that while land surface schemes may be effective at simulating heat fluxes, they may be ineffective for prediction of hydrology unless the soil moisture is accurately estimated. Sensitivity analyses indicated that the soil moisture simulations were most sensitive to soil parameters, and the wilting point was the most identifiable parameter. Significant interactions existed between three soils parameters: porosity, saturated hydraulic conductivity and Campbell ‘b’ exponent, so they could not be identified independent of each other. There were no significant differences in parameter sensitivity and interaction for different hydroclimatic years. Even though the data record contained a very dry year and another year with a very large rainfall event, this indicated that the soil model could be calibrated without the data needing to explore the extreme range of dry and wet conditions. IBIS was much less sensitive to vegetation parameters. The leaf area index (LAI) could affect the mean of daily soil moisture time series when LAI < 1, while the variance of the soil moisture time series was sensitive to LAI > 1. IBIS was insensitive to the Jackson rooting parameter, suggesting that the effect of the rooting depth distribution on predictions of hydrology was insignificant. Copyright © 2014 John Wiley & Sons, Ltd.     

Long‐term effects of revegetation on soil hydrological processes in vegetation‐stabilized desert ecosystems

Planting of sand‐binding vegetation in the Shapotou region on the southeastern edge of the Tengger Desert began in 1956. The revegetation programme successfully stabilized formerly mobile dunes in northern China, permitting the operation of the Baotou‐Lanzhou railway. Long‐term monitoring has shown that the revegetation programme produced various ecological changes, including the formation of biological soil crusts (BSCs). To gain insight into the role of BSCs in both past ecological change and current ecological evolution at the revegetation sites, we used field measurements and HYDRUS‐1D model simulations to investigate the effects of BSCs on soil hydrological processes at revegetated sites planted in 1956 and 1964 and at an unplanted mobile dune site. The results demonstrate that the formation of BSCs has altered patterns of soil water storage, increasing the moisture content near the surface (0–5 cm) while decreasing the moisture content in deeper layers (5–120 cm). Soil evaporation at BSC sites is elevated relative to unplanted sites during periods when canopy coverage is low. Rainfall infiltration was not affected by BSCs during the very dry period that was studied (30 April to 30 September 2005); during periods with higher rainfall intensity, differences in infiltration may be expected due to runoff at BSC sites. The simulated changes in soil moisture storage and hydrological processes are consistent with ongoing plant community succession at the revegetated sites, from deep‐rooted shrubs to more shallow‐rooted herbaceous species. Copyright © 2009 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.     

Differences in soil moisture in two Middle Eastern oak forests: Comparing the effects of trees and soil composition

The incidence of large rain events in Mediterranean ecosystems vary among years. Summer aridity is interpreted as a resetting event, eliminating previous soil‐moisture dynamics. The dynamics of soil moisture and retention are critical to tree survival, particularly in dry regions. This study examines the long‐term soil water content (θ_V) dynamics in two distinct locations within the forest, under the canopy and forest clearing, within two diverse oak forests: subhumid mixed oak forests (MG) and semiarid monospecific oak woodlands (YE). Plots were established at small‐scale catchments and soil water contents were measured during 2010–2013, at three depths in the two different locations. Cumulative rainfall was used as an independent proxy for θ_V analysis. A novel bell‐bilogistic mathematical model of wetting, saturation, and drying arms was developed. We aimed to study the θ_V distribution differences between soil profiles giving the large climatic gradient between the two forested sub basins, the differences in vegetation traits along with soil attributes. We further aimed at determining the role of an individual tree in regulating soil‐moisture dynamics. We hypothesized the occurrence of distinct responses between sites in all soil‐moisture indices with higher θ_V at the wetter site. We tested the hypothesis that seasonal cumulative rainfall dictates the variations in soil‐moisture regimes throughout contiguous years. Annual rainfall was higher than long‐term average throughout the study. Soil profiles under the canopies at both sites were consistently wetter. Infiltration and depletion constants were higher at MG whereas maximum soil moisture was higher at YE. Homogenous recharge patterns were seen at MG although YE evinced more variation. Oaks had no effect on recharge at MG compared with the forest clearing. Soil properties primarily affected the wetting arm whereas vegetation composition regulated the drying arm. Mixed‐stands characterized by ever‐green and deciduous species may maintain favourable soil‐moisture conditions, in comparison with other mixed stand morphologies. The increasing role of slacking forces in infiltration process may alter the interaction between trees and herbaceous vegetation.     

Testing of observation operators designed to estimate profile soil moisture from surface measurements

The accurate estimation of profile soil moisture is usually difficult due to the associated costs, strong spatiotemporal variability, and nonlinear relationship between surface and profile moisture. Here, we used data sets from the Soil and Climate Analysis Network to test how reliably observation operators developed based on the cumulative distribution function matching method can predict profile soil moisture from surface measurements. We first analysed how temporal resolution (hourly, daily, and weekly) and data length (half year, 1 year, 2 years, and 4 years) affected the performance of observation operators. The results showed that temporal resolution had a negligible influence on the performance of observation operators. However, a leave‐one‐year‐out cross‐validation showed that data length affected the performance of observation operators; a 2‐year interval was identified as the most suitable duration due to its low uncertainty in prediction accuracy. The robustness of the observation operators was then tested in three primary climates (humid continental, humid subtropical, and semiarid) of the continental United States, with the exponential filter employed as an independent method. The results indicated that observation operators reliably predicted profile soil moisture for most of the tested stations and performed almost equally well as the exponential filter method. The presented results verified the feasibility of using the cumulative distribution function matching method to predict profile soil moisture from surface measurements.     

Modelling soil moisture in a high‐latitude landscape using LiDAR and soil data

Soil moisture has a pronounced effect on earth surface processes. Global soil moisture is strongly driven by climate, whereas at finer scales, the role of non‐climatic drivers becomes more important. We provide insights into the significance of soil and land surface properties in landscape‐scale soil moisture variation by utilizing high‐resolution light detection and ranging (LiDAR) data and extensive field investigations. The data consist of 1200 study plots located in a high‐latitude landscape of mountain tundra in north‐western Finland. We measured the plots three times during growing season 2016 with a hand‐held time‐domain reflectometry sensor. To model soil moisture and its temporal variation, we used four statistical modelling methods: generalized linear models, generalized additive models, boosted regression trees, and random forests. The model fit of the soil moisture models were R² = 0.60 and root mean square error (RMSE) 8.04 VWC% on average, while the temporal variation models showed a lower fit of R² = 0.25 and RMSE 13.11 CV%. The predictive performances for the former were R² = 0.47 and RMSE 9.34 VWC%, and for the latter R² = 0.01 and RMSE 15.29 CV%. Results were similar across the modelling methods, demonstrating a consistent pattern. Soil moisture and its temporal variation showed strong heterogeneity over short distances; therefore, soil moisture modelling benefits from high‐resolution predictors, such as LiDAR based variables. In the soil moisture models, the strongest predictor was SAGA (System for Automated Geoscientific Analyses) wetness index (SWI), based on a 1 m² digital terrain model derived from LiDAR data, which outperformed soil predictors. Thus, our study supports the use of LiDAR based SWI in explaining fine‐scale soil moisture variation. In the temporal variation models, the strongest predictor was the field‐quantified organic layer depth variable. Our results show that spatial soil moisture predictions can be based on soil and land surface properties, yet the temporal models require further investigation. Copyright © 2017 John Wiley & Sons, Ltd.     

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

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

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.     

Identification of optimal soil hydraulic functions and parameters for predicting soil moisture

Abstract

The accuracy of six combined methods formed by three commonly-used soil hydraulic functions and two methods to determine soil hydraulic parameters based on a soil hydraulic parameter look-up table and soil pedotransfer functions was examined for simulating soil moisture. A novel data analysis and modelling approach was used that eliminated the effects of evapotranspiration so that specific sources of error among the six combined methods could be identified and quantified. By comparing simulated and observed soil moisture at six sites of the USDA Soil Climate Analysis Network, we identified the optimal soil hydraulic functions and parameters for predicting soil moisture. Through sensitivity tests, we also showed that adjusting only the soil saturated hydraulic conductivity, K_s , is insufficient for representing important effects of macropores on soil hydraulic conductivity. Our analysis illustrates that, in general, soil hydraulic conductivity is less sensitive to K_s than to the soil pore-size distribution parameter.

Editor D. Koutsoyiannis; Associate editor D. Hughes

Citation Pan, F., McKane, R.B. and Stieglitz, M., 2012. Identification of optimal soil hydraulic functions and parameters for predicting soil moisture. Hydrological Sciences Journal, 57 (4), 723–737.     

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.