Sensitivity of soil moisture field evolution to rainfall forcing

In this paper the temporal behaviour of soil moisture is modelled and statistically characterized by use of the zero‐dimensional model for soil moisture dynamics and the rectangular pulses Poisson process model for rainfall forcing. The mean, covariance and spectral density function of soil moisture (both instantaneous and locally averaged cases) are analytically derived to evaluate its sensitivity to the model parameters. Finally, the probability density function of soil moisture is derived to evaluate the effect of rainfall forcing. All the model parameters used have been tuned to the Monsoon '90 data. Results can be summarized as follows. (1) Only the soil moisture model parameters (η and nZ_r) are found to affect the autocorrelation function in a distinguishable manner. On the other hand, both the rainfall model parameter (θ) and the effective soil depth (nZ_r) are found to be of impact to the soil moisture spectrum. However, as the smoothing (or damping) effect of soil is so dominant, about ±20% variation of one parameter seems not to affect significantly the second‐order statistics of soil moisture. (2) More difference can be found by applying a longer averaging time, which is found to obviously decrease the variance but increase the correlation even though no overlapping between neighbouring soil moisture data was allowed. (3) Among rainfall model parameters, the arrival rate (λ) was found to be most important for the soil moisture evolution. When increasing the arrival rate of rainfall, the histogram of soil moisture shifts its peak to a certain value as well as becomes more concentrated around the peak. However, by decreasing the arrival rate of rainfall, a much smaller (almost to zero) mean value of soil moisture was estimated, even though the total volume of rainfall remained constant. This indicates that desertification may take place without decreasing the total volume of rainfall. Copyright © 2005 John Wiley & Sons, Ltd.     

Estimation of actual evaporation using precipitation and soil moisture records in arid climates

There is little knowledge available about infiltration and evaporation processes in wadi channels in arid regions. This work was conducted to determine the actual evaporation from bare soils in wadi channels in the south-western region of the Kingdom of Saudi Arabia. The estimation of soil evaporation is highly dependent on the availability of moisture in the upper layers of alluvial wadis, in which the areal rainfall, flood hydrograph and soil properties play a significant part. The study was conducted by estimating the actual evaporation using soil moisture data, precipitation and runoff depths in a representative basin. The results are compared with potential rates. The actual rates were 1.5 mm/day immediately after a rainy day and then decreased to 0.42 mm/day. The minimum rate was about 0.1–0.2 mm/day during the dry season. The potential rates were about 9.5 mm/day in June and July, decreasing to 3.5 mm/day in December and January.     

Determination of bare surface soil moisture from combined temporal evolution of land surface temperature and net surface shortwave radiation

Land surface soil moisture (SSM) is an important variable for hydrological, ecological, and meteorological applications. A multi‐linear model has recently been proposed to determine the SSM content from the combined diurnal evolution of both land surface temperature (LST) and net surface shortwave radiation (NSSR) with the parameters TN (the LST mid‐morning rising rate divided by the NSSR rising rate during the same period) and t_d (the time of daily maximum temperature). However, in addition to the problem that all the coefficients of the multi‐linear model depend on the atmospheric conditions, the model also suffers from the problems of the nonlinearity of TN as a function of the SSM content and the uncertainty of determining the t_d from the diurnal evolution of the LST. To address these problems, a modified multi‐linear model was developed using the logarithm of TN and normalizing t_d by the mid‐morning temperature difference instead of using the TN and t_d. Except for the constant term, the coefficients of all other variables in the modified multi‐linear model proved to be independent of the atmospheric conditions. Using the relevant simulation data, results from the modified multi‐linear model show that the SSM content can be determined with a root mean square error (RMSE) of 0.030m³/m³, provided that the constant term is known or estimated day to day. The validation of the model was conducted using the field measurements at the Langfang site in 2008 in China. A higher correlation is achieved (coefficient of determination: R² = 0.624, RMSE = 0.107m³/m³) between the measured SSM content and the SSM content estimated using the modified multi‐linear model with the coefficients determined from the simulation data. Another experiment is also conducted to estimate the SSM content using the modified model with the constant term calibrated each day by one‐spot measurements at the site. The estimation result has a relatively larger error (RMSE = 0.125m³/m³). Additionally, the uncertainty of the determination of the coefficients is analysed using the field measurements, and the results indicate that the SSM content obtained using the modified model accurately characterizes the surface soil moisture condition. Copyright © 2012 John Wiley & Sons, Ltd.     

The role of landscape morphology on soil moisture variability in semi-arid ecosystems

Previous studies on semi-arid ecosystems have shown high values of soil moisture variability (SMV) primarily induced by the combined effects of non-uniform precipitation, incoming solar radiation, and soil and vegetation properties. However, the relative impact of these various factors on SMV has been difficult to evaluate due to limited availability of field data. In addition, only a limited number of studies have analysed the role of landscape morphology on SMV. Here we use numerical simulations of a simple hydrological model, the Bucket Grassland Model, to systematically analyse the effect of each contributing factor on SMV on two different landscape morphologies. The two different landform morphologies represent landscapes dominated respectively by either diffusive erosion or fluvial erosion processes. We conducted various simulations driven by a stochastically generated 100-year climate time series, which is long enough to capture climatic fluctuations, in order to understand the effect of various soil moisture controlling factors on the spatiotemporal SMV. Our modelling results show that the fluvial dominated landscapes promote higher spatial SMV than the diffusive dominated ones. Further, the role of landform morphology on SMV is more pronounced in regions where the spatial variability of incoming solar radiation and precipitation is high.     

The role of overland flow and subsurface flow on the spatial distribution of soil moisture in the topsoil

Many investigations show relationships between topographical factors and the spatial distribution of soil moisture in catchments. However, few quantitative analyses have been carried out to elucidate the role of different hydrological processes in the spatial distribution of topsoil moisture in catchments. A spatially distributed rainfall—runoff model was used to investigate contributions of subsurface matric flow, macropore flow and surface runoff to the spatial distribution of soil moisture in a cultivated catchment. The model results show that lateral subsurface flow in the soil matrix or in macropores has a minor effect on the spatial distribution of soil moisture. Only when a perched groundwater table is maintained long enough, which is only possible if the subsurface is completely impermeable, may a spatial distribution in moisture content occur along the slope. Surface runoff, producing accumulations of soil moisture in flat flow paths of agricultural origin (field boundaries), was demonstrated to cause significant spatial variations in soil moisture within a short period after rainfall (<2 days). When significant amounts of surface runoff are produced, wetter moisture conditions will be generated at locations with larger upstream contributing areas. Copyright © 2001 John Wiley & Sons, Ltd.     

Analysis of soil moisture dynamics beneath olive trees

Olive cultivation is a widespread land use in Mediterranean climates. The proper implementation of soil and water conservation practices in groves requires detailed knowledge of the governing hydrological processes. In this work topsoil moisture dynamics under wet and dry conditions and across a small catchment was investigated in the inter row (IR) and directly under the olive tree canopies (UC). We do this using a sensor network (11 stations) and a simple bucket model which was calibrated (June, 2011–2012) and validated (June, 2012–2013). During most of the year the normalized soil moisture contents (s) were greater in the IR than under UC, with an average normalized soil moisture difference of 0.12. The difference between UC and IR normalized soil moisture followed a seasonal pattern, reaching a maximum near 0.30 during spring. An analysis of the normalized soil moisture probability density functions (pdfs) was bimodal, showing characteristic dominant wet and dry soil moisture states, with the highest probability densities for the dry state. Overall the spatial variability of soil moisture was lower UC than in the IR. This was a result of the soil moisture buffering capacity of the canopy with respect to rainfall and evaporation, in addition to observed differences in soil properties. Hourly soil moisture data were successfully modelled (R² > 0.85), both UC and in the IR, yet with the inclusion of a simple formulation for canopy interception for the former. The results provide insight into how olive trees change hydrological processes in their neighbourhood. Copyright © 2016 John Wiley & Sons, Ltd.     

Streamflow predictability in the Saskatchewan/Nelson River basin given macroscale estimates of the initial soil moisture status

Abstract

Soil moisture estimates obtained over large spatial areas will become increasingly available through current and upcoming satellite missions and from numerous land surface parameterization schemes run at global- and continental-scale resolutions. The goal of this research was to evaluate the potential for using macroscale estimates of soil moisture for enhancing streamflow forecasts. Towards this research objective, monthly streamflow estimates were obtained from over 50 gauge locations within the Nelson basin, Canada, for the period 1979–1999. For each streamflow record, multiple linear regression models were used to remove components of the streamflow signal related to previous streamflow, climate teleconnections (e.g. ENSO and AO) and snow water equivalence. Correlations were then assessed between the macroscale soil moisture estimates and the residuals of the multiple linear regression analysis over lead times of one, two and three months. At the one- and two-month lead time, statistically significant relationships between soil moisture and the residuals of streamflow are observed over a large proportion of the gauging locations. The number of catchments with statistically significant relationships decreases significantly after two months and particularly in the months of April—June. This study demonstrates that available macroscale estimates of soil moisture have the potential to enhance streamflow prediction, although further study is suggested to improve upon the soil moisture estimates and their application in a forecast system.     

Modelling spatio-temporal soil moisture dynamics in mountain tundra

Soil moisture has a fundamental influence on the processes and functions of tundra ecosystems. Yet, the local dynamics of soil moisture are often ignored, due to the lack of fine resolution, spatially extensive data. In this study, we modelled soil moisture with two mechanistic models, SpaFHy (a catchment-scale hydrological model) and JSBACH (a global land surface model), and examined the results in comparison with extensive growing-season field measurements over a mountain tundra area in northwestern Finland. Our results show that soil moisture varies considerably in the study area and this variation creates a mosaic of moisture conditions, ranging from dry ridges (growing season average 12 VWC%, Volumetric Water Content) to water-logged mires (65 VWC%). The models, particularly SpaFHy, simulated temporal soil moisture dynamics reasonably well in parts of the landscape, but both underestimated the range of variation spatially and temporally. Soil properties and topography were important drivers of spatial variation in soil moisture dynamics. By testing the applicability of two mechanistic models to predict fine-scale spatial and temporal variability in soil moisture, this study paves the way towards understanding the functioning of tundra ecosystems under climate change.     

NIR-red spectral space based new method for soil moisture monitoring

Drought is a complex natural disaster that occurs frequently. Soil moisture has been the main issue in remote monitoring of drought events as the most direct and important variable describing the drought. Spatio-temporal distribution and variation of soil moisture evidently affect surface evapotranspiration, agricultural water demand, etc. In this paper, a new simple method for soil moisture monitoring is de- veloped using near-infrared versus red (NIR-red) spectral reflectance space. First, NIR-red spectral reflectance space is established using atmospheric and geometric corrected ETM data, which is manifested by a triangle shape, in which different surface covers have similar spatial distribution rules. Next, the model of soil moisture monitoring by remote sensing (SMMRS) is developed on the basis of the distribution characteristics of soil moisture in the NIR-red spectral reflectance space. Then, the SMMRS model is validated by comparison with field measured soil moisture data at different depths. The results showed that satellite estimated soil moisture by SMMRS is highly accordant with field measured data at 5 cm soil depth and average soil moisture at 0―20 cm soil depths, correlation coef- ficients are 0.80 and 0.87, respectively. This paper concludes that, being simple and effective, the SMMRS model has great potential to estimate surface moisture conditions.     

Temporal and spatial changes of soil moisture and its response to temperature and precipitation over the Tibetan Plateau

ABSTRACT

The temporal and spatial characteristics of soil moisture over the Tibetan Plateau (TP) were analysed to explore the relative contributions of temperature and precipitation to soil moisture change. Non-significant changes in soil moisture were observed for the TP over the period 1950–2010, while a seasonal cycle was evident, with higher values in summer and smaller values in winter. The soil moisture showed obvious spatial heterogeneity, with higher values in the south than in the north of the TP. The soil moisture fluctuated with time, jointly influenced by precipitation and temperature changes, with precipitation the dominant factor, while temperature regulated the relationship between soil moisture and precipitation. The relative contribution of precipitation to soil moisture changes was over 80%, except for winter in which temperature was the dominant factor, with a relative contribution of more than 70%. Because of the sharp increase in temperature in winter, the uneven spatial distribution of soil moisture over the TP might harm the fragile ecological environment.     

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.     

Estimating growing-season root zone soil moisture from vegetation index-based evapotranspiration fraction and soil properties in the Northwest Mountain region,USA

A soil moisture retrieval method is proposed, in the absence of ground-based auxiliary measurements, by deriving the soil moisture content relationship from the satellite vegetation index-based evapotranspiration fraction and soil moisture physical properties of a soil type. A temperature–vegetation dryness index threshold value is also proposed to identify water bodies and underlying saturated areas. Verification of the retrieved growing season soil moisture was performed by comparative analysis of soil moisture obtained by observed conventional in situ point measurements at the 239-km² Reynolds Creek Experimental Watershed, Idaho, USA (2006–2009), and at the US Climate Reference Network (USCRN) soil moisture measurement sites in Sundance, Wyoming (2012–2015), and Lewistown, Montana (2014–2015). The proposed method best represented the effective root zone soil moisture condition, at a depth between 50 and 100 cm, with an overall average R² value of 0.72 and average root mean square error (RMSE) of 0.042.     

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.     

Impact of soil moisture heterogeneity length scale and gradients on daytime coupled land‐cloudy boundary layer interactions

Using a coupled large‐eddy simulation–land surface model framework, the impact of two‐dimensional soil moisture heterogeneity on the cloudy boundary layer under varied free‐atmosphere stabilities is investigated. Specifically, the impacts of soil moisture heterogeneity length scale and heterogeneity in terms of soil moisture gradients on micrometeorological states, surface fluxes, boundary layer characteristics, and cloud development are examined. The results show that mesoscale circulations due to surface heterogeneity in soil moisture play an important role in transferring water vapour within the boundary layer and in regulating cloud distribution at the entrainment zone, which, in turn, provides feedbacks on boundary layer/surface energy budgets. The initial domain‐averaged soil moisture is identical for all homogenous and heterogeneous cases; however, the soil moisture heterogeneity in gradient and length scale between dry and wet regions has a significant impact on the estimates of near‐surface micrometeorological properties and surface fluxes, which further affect the boundary layer states and characteristics. Both liquid water potential temperature and liquid water mixing ratio increase with an increasing soil moisture gradient, whereas the amount of specific humidity decreases. Heterogeneity length scale and free atmosphere stability also amplify these impacts on the boundary layer structure and cloud formation. In a low atmospheric stability condition that potentially allows for a deeper boundary layer and a higher entrainment rate, cloud base height and cloud thickness significantly increase as the soil moisture gradient and length scale increase. Analysis to differentiate the influences of surface heterogeneity type (i.e. length scale vs gradient) shows that in general soil moisture gradient provides a larger impact than heterogeneity length scale, although the heterogeneity length scale is large enough to initiate circulation features responsible for differences in the coupled system between homogeneous and heterogeneous soil moisture cases. Copyright © 2012 John Wiley & Sons, Ltd.     

The effect of biological soil crusts on soil moisture dynamics under different rainfall conditions in the Tengger Desert,China

Rainfall is considered as the dominant water replenishment in desert ecosystems, and the conversion of rainfall into soil water availability plays a central role in sustaining the ecosystem function. In this study, the role of biological soil crusts (BSCs), typically formed in the revegetated desert ecosystem in the Tengger Desert of China, in converting rainfall into soil water, especially for the underlying soil moisture dynamics, was clarified by taking into account the synthetic effects of BSCs, rainfall characteristics, and antecedent soil water content on natural rainfall conditions at point scale. Our results showed that BSCs retard the infiltration process due to its higher water holding capacity during the initial stage of infiltration, such negative effect could be offset by the initial wet condition of BSCs. The influence of BSCs on infiltration amount was dependent on rainfall regime and soil depth. BSCs promoted a higher infiltration through the way of prolonged water containing duration in the ground surface and exhibited a lower infiltration at deep soil layer, which were much more obvious under small and medium rainfall events for the BSCs area compared with the sand area. Generally, the higher infiltration at top soil layer only increased soil moisture at 0.03 m depth; in consequence, there was no water recharge for the deep soil, and thus, BSCs had a negative effect on soil water effectiveness, which may be a potential challenge for the sustainability of the local deep‐rooted vegetation under the site specific rainfall conditions in northwestern China.     

Soil temperature and soil moisture dynamics in winter and spring under heavy snowfall conditions in North-Eastern Japan

Warm winters and high precipitation in north-eastern Japan generate snow covers of more than three meters depth and densities of up to 0.55 g cm⁻³. Under these conditions, rain/snow ratio and snowmelt have increased significantly in the last decade under increasing warm winters. This study aims at understanding the effect of rain-on-snow and snowmelt on soil moisture under thick snow covers in mid-winter, taking into account that snowmelt in spring is an important source of water for forests and agriculture. The study combines three components of the Hydrosphere (precipitation, snow cover and soil moisture) in order to trace water mobility in winter, since soil temperatures remained positive in winter at nearly 0.3°C. The results showed that soil moisture increased after snowmelt and especially after rain-on-snow events in mid-winter 2018/2019. Rain-on-snow events were firstly buffered by fresh snow, increasing the snow water equivalent (SWE), followed by water soil infiltration once the water storage capacity of the snowpack was reached. The largest increase of soil moisture was 2.35 vol%. Early snowmelt increased soil moisture with rates between 0.02 and 0.035 vol% hr⁻¹ while, rain-on-snow events infiltrated snow and soil faster than snowmelt and resulted in rates of up to 1.06 vol% hr⁻¹. These results showed the strong connection of rain, snow and soil in winter and introduce possible hydrological scenarios in the forest ecosystems of the heavy snowfall regions of north-eastern Japan. Effects of rain-on-snow events and snowmelt on soil moisture were estimated for the period 2012–2018. Rain/snow ratio showed that only 30% of the total precipitation in the winter season 2011/2012 was rain events while it was 50% for the winter 2018/2019. Increasing climate warming and weakening of the Siberian winter monsoons will probably increase rain/snow ratio and the number of rain-on-snow events in the near future.     

Comparison of SMOS,modelled and in situ long-term soil moisture series in the northwest of Spain

ABSTRACT

This work aimed to evaluate the capability of modelled vs in situ soil moisture observations in the northwest of Spain for a period of four years (2010–2013) in order to validate the SMOS L2 product. Comparisons were performed for a set of representative stations of the Soil Moisture Measurement Stations network of the University of Salamanca (REMEDHUS) at both point and area scales. The SMOS series showed good correlation with the modelled series, better than that obtained with the in situ observations (0.77 vs 0.68 average correlation coefficients). However, some underestimation or overestimation of the SMOS series, related to the soil characteristics, was observed with respect to both the in situ and the modelled series. The SMOS data normalization produced a notable improvement in the results, highlighting the capability of the modelled data to validate the SMOS soil moisture series. This research provides a solid foundation for the future validation of SMOS at large scales, overcoming the spatial representativeness issues arising from the use of in situ point measurements.

Editor M.C. Acreman; Associate editor N. Verhoest     

Obstacles to long‐term soil moisture monitoring with heated distributed temperature sensing

The field deployment of a heated distributed temperature sensor (DTS) for over three years has revealed two obstacles to estimating soil moisture (θ) that may hamper subsurface DTS applications as well as use of other subsurface thermal probes. The first observed obstacle was a hysteretic response of the DTS sensor. The relationship between θ and the temperature response (?T) within the cable was not only dependent on θ of the soil, but also on the previous wetting and drying cycles leading to that state. The second observed obstacle was soil structure healing. Soil structure healing causes the relationship between ?T and θ to evolve through time; this calibration curve becomes flatter, or less sensitive, as the surrounding soil makes better contact with the cable. Effects of the hysteretic response of the instrument and soil structure healing are largely the result of small gaps between the cable and soil. These small gaps can be approximated by a contact resistance between the cable and soil. In this article we characterize the occurrence of hysteretic and soil structure healing effects from field data and parameterize contact resistance by simulating heat transfer using a numerical modelling approach Copyright © 2015 John Wiley & Sons, Ltd.     

Measurement of soil moisture change in spatially heterogeneous weathered soils using a capacitance probe

A capacitance probe has been employed to measure the spatial and temporal change of soil moisture in a weathered soil profile with heterogeneous texture characteristics. Measurements were made to a depth of 2 m at intervals of 2 cm. The field work was carried out during a wetting-up period in a subtropical monsoonal environment in the Middle Hills of Nepal. Calibrations of the frequency readings against gravimetric and volumetric soil moisture are compared. It was found that the frequency reading correlates much better with the volumetric soil moisture. Although the soil is spatially heterogeneous in its particle size, porosity and bulk density, it was found that a single regression equation can be used to represent the relationship between the frequency reading of the capacitance probe and volumetric soil moisture. The results demonstrate that the capacitance probe enables the investigation of soil moisture variation temporally and spatially at high resolution and can measure a wide moisture range. © 1998 John Wiley & Sons, Ltd.