Surface microrelief changes affect the soil and water conservation benefits of rainwater harvesting tillage operation during rainfall events

Reservoir tillage (RT) improves the soil rainwater harvesting capacity and reduces soil erosion on cropland, but there is some debate regarding its effectiveness. The objective of this study was to further verify the effect of RT on soil erosion and explore the reasons for this effect by analysing microrelief changes during rainfall. Rainfall intensities of 60, 90, and 120 mm/hr and three slope degrees (5, 15, and 25°, representing gentle, medium, and steep slopes) were considered. A smooth surface (SS) served as the control. The microrelief changes were determined based on digital elevation models, which were measured using a laser scanner with a 2‐cm grid before and after rainfall events. The results showed that compared with the values for the SS, RT reduced both the runoff and sediment by approximately 10‐20% on the gentle slope; on the medium slope, although RT also reduced the runoff in the 90‐ and 120‐mm/hr intensity rainfall events, the sediment increased by 158.90% and 246.08%; on the steep slope, the sediment increased by 92.33 to 296.47%. Overall, when the runoff control benefit of RT was lower than 5%, there was no sediment control benefit. RT was effective at controlling soil loss on the gentle slopes but was not effective on the medium and steep slopes. This is because the surface depressions created by RT were filled in with sediment that eroded from the upslopes, and the surface microrelief became smoother, which then caused greater soil and water loss than that on an SS at the later rainfall stage.     

Evaluation of Terrestrial Laser Scanner and Structure from Motion photogrammetry techniques for quantifying soil surface roughness parameters over agricultural soils

The surface roughness of agricultural soils is mainly related to the type of tillage performed, typically consisting of oriented and random components. Traditionally, soil surface roughness (SSR) characterization has been difficult due to its high spatial variability and the sensitivity of roughness parameters to the characteristics of the instruments, including its measurement scale. Recent advances in surveying have greatly improved the spatial resolution, extent, and availability of surface elevation datasets. However, it is still unknown how new roughness measurements relates with the conventional roughness measurements such as 2D profiles acquired by laser profilometers. The objective of this study was to evaluate the suitability of Terrestrial Laser Scanner (TLS) and Structure from Motion (SfM) photogrammetry techniques for quantifying SSR over different agricultural soils. With this aim, an experiment was carried out in three plots (5 × 5 m) representing different roughness conditions, where TLS and SfM photogrammetry measurements were co-registered with 2D profiles obtained using a laser profilometer. Differences between new and conventional roughness measurement techniques were evaluated visually and quantitatively using regression analysis and comparing the values of six different roughness parameters. TLS and SfM photogrammetry measurements were further compared by evaluating multi-directional roughness parameters and analyzing corresponding Digital Elevation Models. The results obtained demonstrate the ability of both TLS and SfM photogrammetry techniques to measure 3D SSR over agricultural soils. However, profiles obtained with both techniques (especially SfM photogrammetry) showed a loss of high-frequency elevation information that affected the values of some parameters (e.g. initial slope of the autocorrelation function, peak frequency and tortuosity). Nevertheless, both TLS and SfM photogrammetry provide a massive amount of 3D information that enables a detailed analysis of surface roughness, which is relevant for multiple applications, such as those focused in hydrological and soil erosion processes and microwave scattering. © 2019 John Wiley & Sons, Ltd.     

Sub-grid scale parameterisation of 2D hydrodynamic models of inundation in the urban area

This paper presents preliminary results from a study considering the parameterisation of coarse-grid 2D flood models to take into account sub-grid scale flow patterns occurring in the urban area. A simulation of a severe flood in an urbanized coastal floodplain is first run using a fine grid that can resolve the flow around and between buildings. Next, the same model is run again using the same underlying topography, although stripped from any buildings, and a set of 7 values of the roughness parameter (Manning’s n), all larger than (or equal to) the value used in the original run. A further set of simulations is carried out using a five-fold increased grid cell size. It is found that while it may be possible to model the overall effects of the buildings using strongly increased roughness parameter values, using a coarse grid otherwise has implications related to the loss of information about the site topography that results in flood flow routes being incorrectly modelled.     

Effect of depression storage capacity on overland‐flow generation for rough horizontal surfaces: water transfer distance and scaling

Overland‐flow triggering on rough surfaces was investigated using an understanding‐oriented model. The model was based on conditioned‐walker technique and developed to simulate and analyse the evolution of puddle connection on numerically generated rough surfaces. The percolation theory gave a theoretical framework to formalize model outputs and to study overland‐flow scaling. Overland‐flow triggering appeared consistent with a percolation process. A scale‐change exponent was suggested. New insights based on the concept of transfer distance of water were emphasized. Transfer distance enabled us to analyse the water redistribution inside a field and helped to define rainfall efficiency when infiltration occurred. Copyright © 2002 John Wiley & Sons, Ltd.     

Perspectives in using a remotely sensed dryness index in distributed hydrological models at the river‐basin scale

In a previous study a spatially distributed hydrological model, based on the MIKE SHE code, was constructed and validated for the 375 000 km² Senegal River basin in West Africa. The model was constructed using spatial data on topography, soil types and vegetation characteristics together with time‐series of precipitation from 112 stations in the basin. The model was calibrated and validated based on river discharge data from nine stations in the basin for 11 years. Calibration and validation results suggested that the spatial resolution of the input data in parts of the area was not sufficient for a satisfactory evaluation of the modelling performance. The study further examined the spatial patterns in the model input and output, and it was found that particularly the spatial resolution of the precipitation input had a major impact on the model response. In an attempt to improve the model performance, this study examines a remotely sensed dryness index for its relationship to simulated soil moisture and evaporation for six days in the wet season 1990. The index is derived from observations of surface temperature and vegetation index as measured by the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor. The correlation results between the index and the simulation results are of mixed quality. A sensitivity analysis, conducted on both estimates, reveals significant uncertainties in both. The study suggests that the remotely sensed dryness index with its current use of NOAA AVHRR data does not offer information that leads to a better calibration or validation of the simulation model in a spatial sense. The method potentially may become more suitable with the use of the upcoming high‐resolution temporal Meteosat Second Generation data. Copyright © 2002 John Wiley & Sons, Ltd.     

DTM resolution controls the accuracy of estimating surface runoff indicators in flat,lowland landscapes

Surface runoff plays an important role in contaminant transport, nutrient loss, soil erosion and peak discharges in streams and rivers. Because it is the result of a variety of complex hydrological processes, estimating surface runoff using physically based hydrological models is challenging. Upscaling of physical soil properties is necessary to cope with the limits of computational power in surface runoff modelling. In flat landscapes, the (micro)topographic surface controls the onset and progression of surface runoff on saturated soils during rain events. Therefore, its proper representation is crucial when attempting to model and predict surface runoff. In this study, the influence of microtopography (centimetre scale) on estimations of maximum depression storage (MDS), random roughness (RR) and the connectivity threshold (CT) is explored. These properties are selected because they often serve as surface runoff indicators in hydrological modelling. To characterize microtopography, a terrestrial laser scanner (TLS) is used to generate a digital terrain model (DTM) of the study site with a horizontal spatial resolution of 5 cm. MDS, RR and CT are then calculated and compared to the values generated from the publicly available Dutch national DTM dataset with a resolution of 50 cm. Our results show considerable differences in MDS, RR and CT when calculated for the different input resolution datasets. Using DTMs that do not sufficiently capture microtopography leads to underestimation of MDS and RR, and to overestimation of CT. Our findings indicate that surface runoff indicators, and thereby the surface runoff response of a saturated surface to rainfall events, are defined at scales smaller than the scales of typically available DTMs. Understanding surface runoff through modelling studies therefore requires a framework that accounts for this lack of information arising from using coarser resolution DTMs. We demonstrate a linear relationship between MDS values generated from the different resolution DTMs. This opens the possibility of using empirical scaling relationships between high- and lower-resolution DTMs to account for microtopography. Repetition of our measurements on similar surfaces would contribute to establishing such empirical scaling relationships. Our results should be seen as indicative of flat landscapes and surfaces where centimetre scale microtopography is relevant.     

On the temporal resolution of mass balance models for soluble chemicals in soils

A daily step model of chemical mass balance in the topsoil is presented and validated at the three experimental sites in Europe, and subsequently applied to perform two distinct numerical experiments. First, an experiment was run using hypothetic soluble chemicals with half‐lives ranging from 10^?1 to 10⁴, with a range of representative European climate and soil properties, assuming uniform constant emissions of the chemicals throughout the year. Chemical mass in soil from the daily step model calculations can be surrogated by the monthly step model consistently parameterized in terms of absolute values, patterns and inter‐monthly variability with decreasing accuracy at higher chemical half‐lives. Leaching fluxes can be also surrogated by the monthly step calculation, although with higher errors. Runoff is correct in the order of magnitude, but it shows only a weak correlation with the monthly mean of the daily model output. For leaching and runoff, the accuracy depends mainly on soil properties. Variability is well reproduced for both leaching and runoff. The second experiment represented a pulse emission of chemicals discharged on a single day in a 12‐month period. Results from the annual average mass of chemicals in the soil, annual runoff and leaching fluxes from the daily step model were compared with the results obtained from the experiment assuming constant‐removal rates for the year. The two values are within a factor of 10 for half‐lives longer than 10 days; therefore, it is possible to emulate the daily step model with a simple constant‐removal rate model for screening‐level assessment. The experiments suggest that simpler schemes may be a practical screening‐level approximation of detailed daily step models for both continuous and pulse emissions, two cases providing extreme bounds of variation to real world emissions. Copyright © 2010 John Wiley & Sons, Ltd.     

Evaluation of the temporal variations of groundwater storage and its interactions with climatic variables using GRACE data and hydrological models: A study from Turkey

Monitoring of the fluctuations of groundwater storage is particularly important in arid and semi-arid regions where water scarcity brings about various challenges. Remote sensing data and techniques play a preponderant role in developing solutions to environmental problems. The launch of Gravity Recovery and Climate Experiment (GRACE) satellites has eased the remote monitoring and evaluation of groundwater resources with an unprecedented precision over large scales. Within the scope of the current study, the latest release (RL06) of GRACE mass concentrations (Mascons) from Jet Propulsion Laboratory (JPL) dataset as well as Global Land Data Assimilation System (GLDAS) models of Noah and Catchment Land Surface Model (CLSM) were used to provide Groundwater Storage Anomalies (GWSA) over Turkey. The temporal interactions of the estimated GWSA with the climatic variables of precipitation and temperature (derived from the reanalysis datasets of CHELSA [Climatologies at High resolution for the Earth's Land Surface Areas] and FLDAS [the Famine Early Warning Systems Network Land Data Assimilation System], respectively) were investigated statistically. The results suggest that there is a descending trend (from 2003 to 2016) for Terrestrial Water Storage Anomalies (TWSA) and GWSA over Turkey with a total loss of 11 and 6 cm of water, respectively. The statistical analysis results also indicate that the monthly variations of GWSA over Turkey are highly correlated with precipitation and temperature at 2-month lag. The analysis of the climatology (long-term) values of monthly GWSA, precipitation and temperature also revealed high agreement between the variables.     

Sensitivity of model parameterizations for simulated latent heat flux at the snow surface for complex mountain sites

The snowcover energy balance is typically dominated by net radiation and sensible and latent heat fluxes. Validation of the two latter components is rare and often difficult to undertake at complex mountain sites. Latent heat flux, the focus of this paper, is the primary coupling mechanism between the snow surface and the atmosphere. It accounts for the critical exchange of mass (sublimation or condensation), along with the associated snowcover energy loss or gain. Measured and modelled latent heat fluxes at a wind‐exposed and wind‐sheltered site were compared to evaluate variability in model parameters. A well‐tested and well‐validated snowcover energy balance model, Snobal, was selected for this comparison because of previously successful applications of the model at these sites and because of the adjustability of the parameters specific to latent heat transfer within the model. Simulated latent heat flux and snow water equivalent (SWE) were not sensitive to different formulations of the stability profile functions associated with heat transfer calculations. The model parameters of snow surface roughness length and active snow layer thickness were used to improve latent heat flux simulations while retaining accuracy in the simulation of the SWE at an exposed and sheltered study site. Optimal parameters for simulated latent heat flux and SWE were found at the exposed site with a shorter roughness length and thicker active layer, and at the sheltered site with a longer roughness length and thinner active layer. These findings were linked to physical characteristics of the study sites and will allow for adoption into other snow models that use similar parameters. Physical characteristics of wind exposure and cover could also be used to distribute critical parameters in a spatially distributed modelling domain and aid in parameter selection for application to other watersheds where detailed information is not available. Copyright © 2012 John Wiley & Sons, Ltd.     

Latitudinal variations of CPI values of long-chain n-alkanes in surface soils:Evidence for CPI as a proxy of aridity

Carbon preference index (CPI) of long-chain n-alkanes preserved in surface soil increases gradually from southeastern China to the north margin of Loess Plateau.Along this latitudinal transect,the CPI value correlates to relative humidity,precipitation,and temperature with a negative linear relationship,respectively,whereas the correlation of CPI to temperature is relatively weak.In the Wuyi,Shennongjia,and Tianshan Mountains,CPI values do not change systemically with altitude increasing (or temperature decreasing).However,mean value of CPI for the individual mountain increases in turn from the humid mountain to the arid.These results jointly suggest that aridity (or humidity) is a dominate climate factor in altering soil CPI value.High CPI values of geological records therefore indicate the arid paleoclimate.Though long-chain n-alkanes in soil are derived mainly from leaf wax of terrestrial vascular plants,the regular latitudinal variations of soil CPI might not be caused by the change of vegetation.We speculate that increased long-chain n-alkanes from microbes and/or enhanced biodegradation in the humid climate lead to the decrease of soil CPI.     

Reconstructing the early 19th‐century Waal River by means of a 2D physics‐based numerical model

Suspended‐sediment concentration data are a missing link in reconstructions of the River Waal in the early 1800s. These reconstructions serve as a basis for assessing the long‐term effects of major interventions carried out between 1850 AD and the early 20th century. We used a 2D physics‐based morphodynamic model accounting for the influence of floodplain vegetation to fill in this gap. Historical discharge hydrographs were derived from a correlation between flow discharge records at Cologne and water level measurements of the Rhine branches in the Netherlands, taking into account the discharge distribution between the branches. Historical floodplain sedimentation rates were estimated using old cartographic information and recent geomorphologic field work. The computed historical sedimentation rates are found to be within the range of measured data, which suggests that fine suspended sediment concentrations in the early 1800s were comparable to contemporary ones. The computations show also how vegetation enhances the formation of natural levees close to the main channel and at the same time decreases the sedimentation rates in farther areas of the floodplain. A sensitivity analysis shows suspended sediment composition to have a strong influence on the resulting quantities and patterns of floodplain deposition. The reconstruction has also provided validation of the modelling tools to reproduce the effects of vegetation on sediment dynamics, enabling their implementation to study other cases. Copyright © 2010 John Wiley & Sons, Ltd.     

A 2.5D coupled FE-BE model for the prediction of railway induced vibrations

Ground vibrations induced by railway traffic at grade and in tunnels are often studied by means of two-and-half dimensional (2.5D) models that are based on a Fourier transform of the coordinate in the longitudinal direction of the track. In this paper, the need for 2.5D coupled finite element-boundary element models is demonstrated in two cases where the prediction of railway induced vibrations is considered. A recently proposed novel 2.5D methodology is used where the finite element method is combined with a boundary element method, based on a regularized boundary integral equation. In the formulation of the boundary integral equation, Green's functions of a layered elastic halfspace are used, so that no discretization of the free surface or the layer interfaces is required. In the first case, two alternative models for a ballasted track on an embankment are compared. In the first model, the ballast and the embankment are modelled as a continuum using 2.5D solid elements, whereas a simplified beam representation is adopted in the second model. The free field vibrations predicted by both models are compared to those measured during a passage of the TGVA at a site in Reugny (France). A very large difference is found for the free field response of both models that is due to the fact that the deformation of the cross section of the embankment is disregarded in the simplified representation. In the second case, the track and free field response due to a harmonic load in a tunnel embedded in a layered halfspace are considered. A simplified methodology based on the use of the full space Green's function in the tunnel–soil interaction problem is investigated. It is shown that the rigorous finite element-boundary element method is required when the distance between the tunnel and the free surface and the layer interfaces of the halfspace is small compared to the wavelength in the soil.     

Test of statistical means for the extrapolation of soil depth point information using overlays of spatial environmental data and bootstrapping techniques

Hydrological modelling depends highly on the accuracy and uncertainty of model input parameters such as soil properties. Since most of these data are field surveyed, geostatistical techniques such as kriging, classification and regression trees or more sophisticated soil‐landscape models need to be applied to interpolate point information to the area. Most of the existing interpolation techniques require a random or regular distribution of points within the study area but are not adequate to satisfactorily interpolate soil catena or transect data. The soil landscape model presented in this study is predicting soil information from transect or catena point data using a statistical mean (arithmetic, geometric and harmonic mean) to calculate the soil information based on class means of merged spatial explanatory variables. A data set of 226 soil depth measurements covering a range of 0–6·5 m was used to test the model. The point data were sampled along four transects in the Stubbetorp catchment, SE‐Sweden. We overlaid a geomorphology map (8 classes) with digital elevation model‐derived topographic index maps (2–9 classes) to estimate the range of error the model produces with changing sample size and input maps. The accuracy of the soil depth predictions was estimated with the root mean square error (RMSE) based on a testing and training data set. RMSE ranged generally between 0·73 and 0·83 m ± 0·013 m depending on the amount of classes the merged layers had, but were smallest for a map combination with a low number of classes predicted with the harmonic mean (RMSE = 0·46 m). The results show that the prediction accuracy of this method depends on the number of point values in the sample, the value range of the measured attribute and the initial correlations between point values and explanatory variables, but suggests that the model approach is in general scale invariant. Copyright © 2009 John Wiley & Sons, Ltd.     

Evaluating explicit and implicit routing for watershed hydro‐ecological models of forest hydrology at the small catchment scale

This paper explores the behaviour and sensitivity of a watershed model used for simulating lateral soil water redistribution and runoff production. In applications such as modelling the effects of land‐use change in small headwater catchments, interactions between soil moisture, runoff and ecological processes are important. Because climate, soil and canopy characteristics are spatially variable, both the pattern of soil moisture and the associated outflow must be represented in modelling these processes. This study compares implicit and explicit routing approaches to modelling the evolution of soil moisture pattern and spatially variable runoff production. It also addresses the implications of using different landscape partitioning strategies. This study presents the results of calibration and application of these different routing and landscape partitioning approaches on a 60 ha forested watershed in Western Oregon. For comparison, the different approaches are incorporated into a physically based hydro‐ecological model, RHESSys, and the resulting simulated soil moisture, runoff production and sensitivity to unbiased error are examined. Results illustrate that both routing approaches can be calibrated to achieve a reasonable fit between observed and modelled outflow. Calibrated values for effective watershed hydraulic conductivity are higher for the explicit routing approach, which illustrates differences between the two routing approaches in their representation of internal watershed dynamics. The explicit approach illustrates a seasonal shift in drainage organization from watershed to more local control as climate goes from a winter wet to a summer dry period. Assumptions used in the implicit approach maintain the same pattern of drainage organization throughout the season. The implicit approach is also more sensitive to random error in soil and topographic input information, particularly during wetter periods. Comparison between the two routing approaches illustrates the advantage of the explicit routing approach, although the loss of computational efficiency associated with the explicit routing approach is noted. To compare different strategies for partitioning the landscape, the use of a non‐grid‐based method of partitioning is introduced and shown to be comparable to grid‐based partitioning in terms of simulated soil moisture and runoff production. Copyright © 2001 John Wiley & Sons, Ltd.     

Comparing the performance of a 2‐D finite element and a 2‐D finite volume model of floodplain inundation using airborne SAR imagery

The performances of a finite volume model (SFV) and finite element model (TELEMAC‐2D) in reproducing inundation on a 16 km reach of the river Severn, United Kingdom, are compared. Predicted inundation extents are compared with 4 airborne synthetic aperture radar images of a major flood event in November 2000, and these are used to calibrate 2 values of Manning's n for the channel and floodplain. The four images are shown to have different capacities to constrain roughness parameters, with the image acquired at low flow rate doing better in determining these parameters than the image acquired at approximately peak flow. This is assigned to the valley filling nature of the flood and the associated insensitivity of flood extent to changes in water level. The level of skill demonstrated by the models, when compared with inundation derived using a horizontal water free surface, also increases as flow rate drops. The two models show markedly different behaviours to the calibration process, with TELEMAC showing less sensitivity and lower optimum values for Manning's n than SFV. When the models are used in predictive mode, calibrated against one image and predicting another, SFV performs better than TELEMAC. Copyright © 2007 John Wiley & Sons, Ltd.     

A comparison of two numerical models for the prediction of vibrations from underground railway traffic

Two prediction models for calculating vibration from underground railways are developed: the pipe-in-pipe model and the coupled periodic finite element–boundary element (FE–BE) model.The pipe-in-pipe model is a semi-analytical three-dimensional model that accounts for the dynamic interaction between the track, the tunnel and the soil. The continuum theory of elasticity in cylindrical coordinates is used to model two concentric pipes: an inner pipe to represent the tunnel wall and an outer pipe to represent the surrounding soil. The tunnel and soil are coupled accounting for equilibrium of stresses and compatibility of displacements at the tunnel–soil interface. This method assumes that the tunnel is invariant in the longitudinal direction and the problem is formulated in the frequency–wavenumber domain using a Fourier transformation. A track, formulated as an Euler–Bernoulli beam, is then coupled to this model. Results are transformed to the space domain using the inverse Fourier transform.The coupled periodic FE–BE model is based on a subdomain formulation, where a boundary element method is used for the soil and a finite element method for the tunnel. The Craig–Bampton substructuring technique is used to efficiently incorporate the track in the tunnel. The periodicity of the tunnel is exploited using the Floquet transformation to formulate the track–tunnel–soil interaction problem in the frequency–wavenumber domain and to compute the wave field radiated into the soil.An invariant concrete tunnel, embedded in a homogeneous full space is analyzed using both approaches. The pipe-in-pipe model offers an exact solution to this problem, which is used to validate the coupled periodic FE–BE model. The free field response due to a harmonic load in the tunnel is predicted and results obtained with both models are compared. The advantages and limitations of both models are highlighted. The coupled periodic FE–BE model has a greater potential as it can account for the complex periodic geometry of the tunnel and the layering in a soil medium. The effect of coupling a floating slab to the tunnel–soil system is also studied with both models by calculating the insertion gain.     

Lessons from the 2003 Tokachi-oki, Japan, earthquake for prediction of long-period strong ground motions and sloshing damage to oil storage tanks

The 2003 Tokachi-oki earthquake (M _w 8.0) in northern Japan generated large-amplitude long-period (4–8 s) ground motions in the Yufutsu sedimentary basin, causing severe damage to seven large oil storage tanks with floating roof structures because of severe sloshing of oil. The 30,000–40,000-m³ tanks having suffered the severe damage such as fires and sinking of floating roofs experienced the sloshing with large amplitudes exceeding 3 m in which the fundamental mode was predominant. The second mode of sloshing was also excited in the 110,000-m³ tanks in which their floating roofs sank into oil, indicating that the higher modes of sloshing as well as the fundamental mode should be considered in damage prediction. The strong ground motion recordings demonstrated the earthquake dependency of predominant periods and the substantial spatial variation of the long-period shaking observed within the Yufutsu basin, meaning the necessity of source- and site-specific prediction of long-period strong ground motions. The two-dimensional numerical modeling suggested the importance of detailed structures of soft near-surface sediments as well as deep basin structure for accurate prediction of long-period strong ground motions in deep sedimentary basins.     

A multi-objective calibration approach using in-situ soil moisture data for improved hydrological simulation of the Prairies

ABSTRACT

Traditionally, hydrological models are only calibrated to reproduce streamflow regime without considering other hydrological state variables, such as soil moisture and evapotranspiration. Limited studies have been performed on constraining the model parameters, despite the fact that the presence of a large number of parameters may provide large degree of freedom, resulting in equifinality and poor model performance. In this study, a multi-objective optimization approach is adopted, and both streamflow and soil moisture data are calibrated simultaneously for an experimental study basin in the Saskatchewan Prairies in western Canada. The results of this study show that the multi-objective calibration improves model fidelity compared to the single objective calibration. Moreover, the study demonstrates that single objective calibration performed against only streamflow can fairly mimic the streamflow hydrograph but does not yield realistic estimation of other fluxes such as evapotranspiration and soil moisture (especially in deeper soil layers).