Information and complexity measures applied to observed and simulated soil moisture time series

Abstract

Time series of soil moisture-related parameters provide important insights into the functioning of soil water systems. Analysis of patterns within such time series has been used in several studies. The objective of this work was to compare patterns in observed and simulated soil moisture contents to understand whether modelling leads to a substantial loss of information or complexity. The time series were observed at four plots in sandy soils within the USDA-ARS OPE3 experimental watershed, for a year; precipitation and evapotranspiration (ET) were measured and estimated, respectively, and used for soil water flow simulation with the HYDRUS-1D software. The information content measures are the metric entropy and the mean information gain, and complexity measures are the fluctuation complexity and the effective measure complexity. These measures were computed based on the binary encoding of soil moisture time series, and used probabilities of patterns, i.e. probabilities of joint or sequential appearance of symbol sequences. The information content of daily soil moisture time series was much smaller than that of rainfall data, and had higher complexity, indicating that soil worked essentially as an information filter. Information content and complexity decreased and increased with depth, respectively, demonstrating the increase in the information filtering action of soil. The information measures of simulated soil moisture content were close to those of the measurements, indicating the successful simulation of patterns in the data. The spatial variability of the information measures for simulated soil moisture content at all depths was less pronounced than the one of measured time series. Compared with precipitation and estimated ET, soil moisture time series had more structure and less randomness in this work. The information measures can provide useful complementary knowledge about model performance and patterns in observation and modelling results.

Citation Pan, F., Pachepsky, Y. A., Guber, A. K., & Hill, R. L. (2011) Information and complexity measures applied to observed and simulated soil moisture time series. Hydrol. Sci. J. 56(6), 1027–1039.     

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.     

Parametrization of the increase of the aeolian erosion threshold wind friction velocity due to soil moisture for arid and semi-arid areas

Large-scale simulation of the soil-derived dust emission in semi-arid regions needs to account for the influence of the soil moisture on the wind erosion threshold. Soil water retention consists of molecular adsorption on the soil grain surface and capillary forces between the grain. Interparticle capillary forces (characterized by the moisture tension) are the main factor responsible for the increase of the wind erosion threshold observed when the soil moisture increases. When the soil moisture content is close to but smaller than the maximum amount of adsorbed water, w′ (depending on the soil texture), these capillary forces are considered as not strong enough to significantly increase the erosion threshold. An expression of the moisture tension as a function of soil moisture and w′ is derived from retention curves. From this expression, a parametrization of the ratio of the wet to dry erosion thresholds has been developed as a function of soil moisture and soil texture. The coefficients of this parametrization have been determined by using experimental data from the literature. An empirical relationship between w′ and soil clay content has been established. The erosion threshold ratios simulated for different soil textures were found to be in good agreement with the experimental data.     

Soil water content vertical profiles under natural conditions: matching of experiments and simulations by a conceptual model

The prediction of soil moisture content, θ, as a function of depth, z, and time, t, is of fundamental importance for applications in many hydrological processes. The main objective of this paper is to provide an approach to solve this problem at a local scale in soils with vegetation. The matching of soil moisture vertical profiles observed under natural conditions in grassy plots and their simulations by a conceptual model is presented. Experimental measurements were performed in a plot located in Central Italy, complete with hydrometeorological sensors specifically set up and equipped with a time domain reflectometry system providing the water content, θ_e(z, t). A conceptual model framework earlier proposed for two‐layered soil vertical profiles was modified and adopted for simulations. The changes concern the incorporation of evapotranspiration, the reduction of the original model for applications also to homogeneous soil vertical profiles, and a correction for the differences existing between assumed and observed initial moisture contents. In the model calibration, it was found that the effects of vegetation could be represented adequately by a fictitious soil vertical profile with a more permeable upper layer of saturated hydraulic conductivity, K_s, independent of time. Then, for the validation events, the model simulations in the stages of both infiltration and redistribution/evapotranspiration reproduced appropriately θ_e(z, t) with typical values of root mean square error in the range 0.0017–0.0657. Similar results were obtained by applying the modified two‐layered model for simulations of experimental data observed in three other plots located in Northern Italy and Germany. For all four vegetated sites, the two‐layer profile better matched the experimental data than the assumption of a homogeneous profile. Thus, the conceptual approach based on a two‐layered scheme for representing θ(z, t) in soils with vegetation appears to be appropriate for many hydrological applications. Copyright © 2013 John Wiley & Sons, Ltd.     

Modification of the Penman method for computing bare soil evaporation

The Penman equation, which calculates potential evaporation, was modified by Staple (1974, Soil Science Society of America Proceedings 38 : 837) to include in it the relative vapour pressure h_s of an unsaturated soil to predict actual evaporation from a soil surface. This improved the prediction when the difference between the temperature of the soil surface and ambient air is relatively small. The objectives of this study were (i) to revise it further using the actual temperature of the soil surface and air to provide the upper boundary condition in computing evaporative flux from the soil surface and (ii) to determine the range of water content for which the modified form of the Penman equation is applicable. The method adopted was tested by a series of outdoor experiments with a clay soil. The method of Staple (1974) overestimated the rate of evaporation above the water content 0·14 m³ m^?3 (up to 30% deviation), whereas the new method agreed well with the measured rates (maximum 7% deviation). Below 0·14 m³ m^?3 water content, both methods underestimated, but the Staple (1974) method deviated more from the measured values: the deviations were above 70% and around 30% for the Staple (1974) and the new methods respectively. Although the new method provided accurate solutions for a wider range of water content from saturation to the lower limit of the liquid phase of a particular soil, the modification did not respond to the vapour phase of the soil moisture. Therefore, in the dry range (i.e. in the vapour phase in which the flow was entirely as vapour), either resistance models or a Fickian equation should be used. Although the effect of salinity on the measured rates was significant, the model erroneously calculated the same rates for both saline and non‐saline conditions. The effect of soil texture can easily be accounted by defining appropriate matric potential water content ψ_m(θ) and soil relative humidity water content h_s(θ) relationships. Copyright © 2007 John Wiley & Sons, Ltd.     

Improving the estimation of hydrothermal state variables in the active layer of frozen ground by assimilating <Emphasis Type="Italic">in situ</Emphasis> observations and SSM/I data

The active layer of frozen ground data assimilation system adopts the SHAW (Simulteneous Heat and Water) model as the model operator. It employs an ensemble kalman filter to fuse state variables predicted by the SHAW model with in situ observation and the SSM/I 19 GHz brightness temperature for the purpose of optimizing model hydrothermal state variables. When there is little water movement in the frozen soil during the winter season, the unfrozen water content depends primarily on soil temperature. Thus, soil temperature is the crucial state variable to be improved. In contrast, soil moisture is heavily influenced by precipitation during the summer season. The simulation accuracy of soil moisture has a strong and direct impact on the soil temperature. In this case, the crucial state variable to be improved is soil moisture. One-dimensional assimilation experiments that have been carried out at AMDO station show that land data assimilation method can improve the estimation of hydrothermal state variables in the soil by fusing model information and observation information. The reasonable model error covariance matrix plays a key role in transferring the optimized surface state information to the deep soil, and it provides improved estimations of whole soil state profiles. After assimilating the 4-cm soil temperature by in situ observation, the soil temperature RMSE (Root Mean Square Error) of each soil layer decreased by 0.96°C on average relative to the SHAW simulation. After assimilating the 4-cm soil moisture in situ observation, the soil moisture RMSE of each soil layer decreased by 0.020 m³·m⁻³. When assimilating the SSM/I 19 GHz brightness temperature, the soil temperature RMSE of each soil layer during the winter decreased by 0.76°C, while the soil moisture RMSE of each soil layer during the summer decreased by 0.018 m³·m⁻³.     

Calibration of an integrated land surface process and radiobrightness (LSP/R) model during summertime

In this study, a soil vegetation and atmosphere transfer (SVAT) model was linked with a microwave emission model to simulate microwave signatures for different terrain during summertime, when the energy and moisture fluxes at the land surface are strong. The integrated model, land surface process/radiobrightness (LSP/R), was forced with weather and initial conditions observed during a field experiment. It simulated the fluxes and brightness temperatures for bare soil and brome grass in the Northern Great Plains. The model estimates of soil temperature and moisture profiles and terrain brightness temperatures were compared with the observed values. Overall, the LSP model provides realistic estimates of soil moisture and temperature profiles to be used with a microwave model. The maximum mean differences and standard deviations between the modeled and the observed temperatures (canopy and soil) were 2.6 K and 6.8 K, respectively; those for the volumetric soil moisture were 0.9% and 1.5%, respectively. Brightness temperatures at 19 GHz matched well with the observations for bare soil, when a rough surface model was incorporated indicating reduced dielectric sensitivity to soil moisture by surface roughness. The brightness temperatures of the brome grass matched well with the observations indicating that a simple emission model was sufficient to simulate accurate brightness temperatures for grass typical of that region and surface roughness was not a significant issue for grass-covered soil at 19 GHz. Such integrated SVAT-microwave models allow for direct assimilation of microwave observations and can also be used to understand sensitivity of microwave signatures to changes in weather forcings and soil conditions for different terrain types.     

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.     

An analysis of soil moisture dynamics using multi-year data from a network of micrometeorological observation sites

Soil moisture data, obtained from four AmeriFlux sites in the US, were examined using an ecohydrological framework. Sites were selected for the analysis to provide a range of plant functional type, climate, soil particle size distribution, and time series of data spanning a minimum of two growing seasons. Soil moisture trends revealed the importance of measuring water content at several depths throughout the rooting zone; soil moisture at the surface (0–10 cm) was approximately 20–30% less than that at 50–60 cm. A modified soil moisture dynamics model was used to generate soil moisture probability density functions at each site. Model calibration results demonstrated that the commonly used soil matric potential values for finding the vegetation stress point and field content may not be appropriate, particularly for vegetation adapted to a water-controlled environment. Projections of future soil moisture patterns suggest that two of the four sites will become severely stressed by climate change induced alterations to the precipitation regime.     

Influence of soil moisture hysteresis on the functioning of capillary barriers

Previous experimental studies of capillary barriers have identified highly hysteretic soil moisture retention characteristics in the materials used. In this study, numerical modelling is used to analyse the role of soil moisture hysteresis in capillary barrier functioning. Comparisons between published experimental results and model simulations indicate that soil moisture hysteresis was a necessary inclusion in the modelling approach to adequately reproduce pore water pressure distributions and the timing of breakthrough occurrences. Under hypothetical intermittent infiltration and evaporation conditions, the predicted volumetric water content in the moisture retention layer was significantly different for hysteretic and non‐hysteretic models. The hysteresis effect was found to be dependent on the nature of infiltration–evaporation cycling, although the predicted volume of flow through the hysteretic barrier was lower than that of the non‐hysteretic case, regardless of the nature of the cyclic upper boundary conditions. For practical engineering designs, where the water leakage through the barrier is the primary concern, the inclusion of soil moisture hysteresis in numerical modelling is needed. Copyright © 2009 John Wiley & Sons, Ltd.     

青藏高原北部活动层土壤热力特性的研究

利用2003年10月～2004年9月期间高原北部可可西里(QT01)、北麓河(QT02)、开心岭(QT05)、通天河(QT06)等地活动层土壤温度梯度、土壤热通量及土壤水分的观测资料,计算了高原北部活动层土壤的导热率、土壤容积热容量、导温率等土壤热力参数.结果显示,QT02、QT05、QT06三站导热率、导温率夏秋季节较大而冬季较小,容积热容量则相反,表现为秋冬季节大而夏季较小;QT01站导热率表现为春季大,夏季较小;表层土壤粒度较小及较低的土壤湿度是冬季导热率较小的可能原因;冻土的热力特征参量可描述为相应深度的温度、体积含冰量及土壤盐度的函数,土壤含水量是融土热特征参数的主要影响因子;土壤水分含量小于某一临界值时,导温率随土壤水分含量的增大而增大,反之则减小.     

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.     

基于土壤墒情抗差的降雨径流预报模型——设计与实验流域应用

本文旨在将实时监测得到的土壤墒情转化为流域水文模型可以直接使用的土壤含水量,论证将实时土壤墒情资料用于实时预报的可行性;利用实时监测土壤墒情,改进传统的模型结构,设计基于实测土壤墒情的降雨径流水文预报模型.采用土壤含水量误差抗差估计技术以抵御观测资料粗差的影响,提高系统的稳定性;并在此基础上提出了土壤含水量系统响应修正方法,以提高模型计算精度.将该模型应用于实验流域——宝盖洞流域进行应用检验,洪水模拟合格率达到92.3%,整体模拟精度达到甲级.     

Sensitivity of hydrological variables to climate change in the Haihe River basin,China

Using the defined sensitivity index, the sensitivity of streamflow, evapotranspiration and soil moisture to climate change was investigated in four catchments in the Haihe River basin. Climate change contained three parts: annual precipitation and temperature change and the change of the percentage of precipitation in the flood season (P_f). With satisfying monthly streamflow simulation using the variable infiltration capacity model, the sensitivity was estimated by the change of simulated hydrological variables with hypothetical climatic scenarios and observed climatic data. The results indicated that (i) the sensitivity of streamflow would increase as precipitation or P_f increased but would decrease as temperature increased; (ii) the sensitivity of evapotranspiration and soil moisture would decrease as precipitation or temperature increased, but it to P_f varied in different catchments; and (iii) hydrological variables were more sensitive to precipitation, followed by P_f, and then temperature. The nonlinear response of streamflow, evapotranspiration and soil moisture to climate change could provide a reference for water resources planning and management under future climate change scenarios in the Haihe River basin. Copyright © 2011 John Wiley & Sons, Ltd.     

An overview of hydrometeorological datasets from a small agricultural catchment (Nučice) in the Czech Republic

We introduce the freely available web-based Water in an Agricultural Landscape—NUčice Database (WALNUD) dataset that includes both hydrological and meteorological records at the Nučice experimental catchment (0.53 km²), which is representative of an intensively farmed landscape in the Czech Republic. The Nučice experimental catchment was established in 2011 for the observation of rainfall–runoff processes, soil erosion processes, and water balance of a cultivated landscape. The average altitude is 401 m a.s.l., the mean land slope is 3.9%, and the climate is humid continental (mean annual temperature 7.9°C, annual precipitation 630 mm). The catchment is drained by an artificially straightened stream and consists of three fields covering over 95% of the area which are managed by two different farmers. The typical crops are winter wheat, rapeseed, and alfalfa. The installed equipment includes a standard meteorological station, several rain gauges distributed across the basin, and a flume with an H-type facing that is used to monitor stream discharge, water turbidity, and basic water quality indicators. Additionally, the groundwater level and soil water content at various depths near the stream are recorded. Recently, large-scale soil moisture monitoring efforts have been introduced with the installation of two cosmic-ray neutron sensors for soil moisture monitoring. The datasets consist of observed variables (e.g. measured precipitation, air temperature, stream discharge, and soil moisture) and are available online for public use. The cross-seasonal, open access datasets at this small-scale agricultural catchment will benefit not only hydrologists but also local farmers.     

Soil moisture influenced the variability of air temperature and oasis effect in a large inland basin of an arid region

Soil moisture plays a significant role in land-atmosphere interactions. Changing fractions of latent and sensible heat fluxes caused by soil moisture variations can affect near-surface air temperature, thus influencing the oasis's cooling effect in arid regions. In this study, the framework for the evaporative fraction (EF) dependence on soil moisture is used to analyse the impacts of soil moisture variation on near-surface air temperature and the oasis effect. The result showed that soil moisture's contribution rate to EF was significantly higher than that of EF to temperature. Under the interaction of temperature sensitivity to EF and EF to soil moisture, the ∂T/∂ϴ presented a similar tempo-spatial variation with both of the above. It was most significant in oasis areas during summer (−1.676), while it was weaker in plain desert areas during the autumn (−0.071). In the study region, the effect of soil moisture variation on air temperature can reach 0.018–0.242 K for different land-cover types in summer. The maximum variation of soil moisture in summer can alter air temperature by up to 0.386 K. The difference in temperature variability between the oasis and desert areas promoted the formation of the oasis effect. For different oasis, the multi-year average oasis cold effect index (OCI) ranged from −1.36 to −0.26 K. In comparison, the average summer OCI ranged from −1.38 to −0.29 K. The lower bound of the cooling effect of oasis ranged from −4.97 to −1.69 K. The analysis framework and results of this study will provide a new perspective for further research on the evolution process of the oasis effect and water–heat balance in arid areas.     

Simulating pan‐Arctic runoff with a macro‐scale terrestrial water balance model

A terrestrial hydrological model, developed to simulate the high‐latitude water cycle, is described, along with comparisons with observed data across the pan‐Arctic drainage basin. Gridded fields of plant rooting depth, soil characteristics (texture, organic content), vegetation, and daily time series of precipitation and air temperature provide the primary inputs used to derive simulated runoff at a grid resolution of 25 km across the pan‐Arctic. The pan‐Arctic water balance model (P/WBM) includes a simple scheme for simulating daily changes in soil frozen and liquid water amounts, with the thaw–freeze model (TFM) driven by air temperature, modelled soil moisture content, and physiographic data. Climate time series (precipitation and air temperature) are from the National Centers for Environmental Prediction (NCEP) reanalysis project for the period 1980–2001. P/WBM‐generated maximum summer active‐layer thickness estimates differ from a set of observed data by an average of 12 cm at 27 sites in Alaska, with many of the differences within the variability (1σ) seen in field samples. Simulated long‐term annual runoffs are in the range 100 to 400 mm year^?1. The highest runoffs are found across northeastern Canada, southern Alaska, and Norway, and lower estimates are noted along the highest latitudes of the terrestrial Arctic in North America and Asia. Good agreement exists between simulated and observed long‐term seasonal (winter, spring, summer–fall) runoff to the ten Arctic sea basins (r = 0·84). Model water budgets are most sensitive to changes in precipitation and air temperature, whereas less affect is noted when other model parameters are altered. Increasing daily precipitation by 25% amplifies annual runoff by 50 to 80% for the largest Arctic drainage basins. Ignoring soil ice by eliminating the TFM sub‐model leads to runoffs that are 7 to 27% lower than the control run. The results of these model sensitivity experiments, along with other uncertainties in both observed validation data and model inputs, emphasize the need to develop improved spatial data sets of key geophysical quantities (particularly climate time series) to estimate terrestrial Arctic hydrological budgets better. Copyright © 2003 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.     

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.     

On the estimation of antecedent wetness conditions in rainfall–runoff modelling

The analysis of the physical processes involved in a conceptual model of soil water content balance is addressed with the objective of its application as a component of rainfall–runoff modelling. The model uses routinely measured meteorological variables (rainfall and air temperature) and incorporates a limited number of significant parameters. Its performance in estimating the soil moisture temporal pattern was tested through local measurements of volumetric water content carried out continuously on an experimental plot located in central Italy. The analysis was carried out for different periods in order to test both the representation of infiltration at the short time‐scale and drainage and evapotranspiration processes at the long time‐scale. A robust conceptual model was identified that incorporated the Green–Ampt approach for infiltration and a gravity‐driven approximation for drainage. A sensitivity analysis was performed for the selected model to assess the model robustness and to identify the more significant parameters involved in the principal processes that control the soil moisture temporal pattern. The usefulness of the selected model was tested for the estimation of the initial wetness conditions for rainfall–runoff modelling at the catchment scale. Specifically, the runoff characteristics (runoff depth and peak discharge) were found to be dependent on the pre‐event surface soil moisture. Both observed values and those estimated by the model gave good results. On the contrary, with the antecedent wetness conditions furnished by two versions of the antecedent precipitation index (API), large errors were obtained. Copyright © 2007 John Wiley & Sons, Ltd.