scholarly journals Validation of the EROSION-3D Model through Measured Bathymetric Sediments

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1082
Author(s):  
Zuzana Németová ◽  
David Honek ◽  
Silvia Kohnová ◽  
Kamila Hlavčová ◽  
Monika Šulc Michalková ◽  
...  
Keyword(s):  
3D Model ◽  
Slovak Republic ◽  
Model Performance ◽  
Scientific Work ◽  
Erosion And Deposition ◽  
Small Reservoir ◽  
Rainfall Events ◽  
Erosion Processes ◽  
Physically Based ◽  
Model Point

The testing of a model performance is important and is also a challenging part of scientific work. In this paper, the results of the physically-based EROSION-3D (Jürgen Schmidt, Berlin, Germany) model were compared with trapped sediments in a small reservoir. The model was applied to simulate runoff-erosion processes in the Svacenický Creek catchment in the western part of the Slovak Republic. The model is sufficient to identify the areas vulnerable to erosion and deposition within the catchment. The volume of sediments was measured by a bathymetric field survey during three terrain journeys (in 2015, 2016, and 2017). The results of the model point to an underestimation of the actual processes by 30% to 80%. The initial soil moisture played an important role, and the results also revealed that rainfall events are able to erode and contribute to a significant part of sediments.

Modelling of impacts of erosion processes on agricultural landscapes due to intensive rainfall events

2020 ◽  
Author(s):  
Silvia Kohnová ◽  
Zuzana Németová
Keyword(s):  
Soil Erosion ◽  
Soil Degradation ◽  
Agricultural Land ◽  
Assessment Methods ◽  
Rainfall Events ◽  
Degradation Processes ◽  
Erosion Processes ◽  
Erosion Models ◽  
Physically Based ◽  
Physically Based Models

<p>At present, the occurrence of extreme precipitation events is becoming more and more frequent and therefore it is important to quantify their impact on the landscape and soil degradation processes. Until now a wide range of soil erosion models have been developed and many significant studies performed to evaluate soil erosion processes at local and regional level, but there are still many modeling principles that suffer from a range of problems. The general problem in soil erosion modelling lies in the validation and verification of the methodologies used. The validation of erosion models is a very complicated and complex process due to lack of suitable sites, financial demands and due to the high temporal and spatial variability. The paper points to validate the physically and event-based Erosion-3D model predominantly developed to calculate the amounts of soil loss, surface runoff, and depositions resulting from natural and design rainfall events. In the study two different erosion assessment methods were chosen in order to compare diverse evaluation approaches. Both water erosion assessment methods used have certain advantages and disadvantages, but nowadays the use of physically-based models, which are a younger generation of models, are regarded to be a more innovative and effective technique for the evaluation of complex runoff-erosion processes, deposition and transport processes. The significant contribution of physically-based models is seen in their more precise representation of the erosion and deposition processes, a more proper calculation of the erosion, deposition and sediment yields and the application of more complicated characteristics, including fluctuating soil conditions and surface properties in comparison with empirical models. The validation of the models was performed based on the continuous rainfall events for the period selected (2015, 2016 and 2017). The extreme rainfall events occurring during the period were chosen and their serious impact on the agricultural land was modeled. The modelled sediment data were compared with the measured sediment deposition data obtained by a bathymetry survey of the Svacenicky Creek polder. The polder is situated in the middle of the Myjava hill lands in the western part of Slovakia and the bathymetry measurement were conducted using a hydrographical survey using the EcoMapper Autonomous Underwater Vehicle (AUV) device. The results of the study include a comparison between the modelled and measured data and an assessment of the impact of the intensive rainfall events on the investigated territory.</p><p>Key words: intensive rainfall events, agricultural land, soil degradation processes, hydrological extremes, physically-based model</p>

scholarly journals Optimal parameters for the Green-Ampt infiltration model under rainfall conditions

2015 ◽  
Vol 63 (2) ◽  
pp. 93-101 ◽  
Author(s):  
Li Chen ◽  
Long Xiang ◽  
Michael H. Young ◽  
Jun Yin ◽  
Zhongbo Yu ◽  
...  
Keyword(s):  
Model Performance ◽  
Sensitivity Analyses ◽  
Richards Equation ◽  
Optimal Parameters ◽  
Rainfall Events ◽  
Infiltration Model ◽  
Physically Based ◽  
Close Fit ◽  
Infiltration Processes ◽  
Meansquare Error

Abstract The Green-Ampt (GA) model is widely used in hydrologic studies as a simple, physically-based method to estimate infiltration processes. The accuracy of the model for applications under rainfall conditions (as opposed to initially ponded situations) has not been studied extensively. We compared calculated rainfall infiltration results for various soils obtained using existing GA parameterizations with those obtained by solving the Richards equation for variably saturated flow. Results provided an overview of GA model performance evaluated by means of a root-meansquare- error-based objective function across a large region in GA parameter space as compared to the Richards equation, which showed a need for seeking optimal GA parameters. Subsequent analysis enabled the identification of optimal GA parameters that provided a close fit with the Richards equation. The optimal parameters were found to substantially outperform the standard theoretical parameters, thus improving the utility and accuracy of the GA model for infiltration simulations under rainfall conditions. A sensitivity analyses indicated that the optimal parameters may change for some rainfall scenarios, but are relatively stable for high-intensity rainfall events.

Sensitivity analysis of soil parameters and their impact on runoff-erosion processes

2020 ◽  
Vol 15 (1) ◽  
pp. 53-64
Author(s):  
David Honek ◽  
Zuzana Németová ◽  
Silvia Kohnová ◽  
Monika Šulc Michalková
Keyword(s):  
Sensitivity Analysis ◽  
3D Model ◽  
Soil Parameters ◽  
Erosion Processes ◽  
Initial Soil ◽  
Physically Based ◽  
Correct Determination ◽  
Variable Influence ◽  
Crucial Part

Abstract The modeling of soil erosion processes is affected by several factors that reflect the physical-geographic conditions of the study site together with the land use linkage. The soil parameters are significant in the modeling of erosion and also runoff processes. The correct determination of a soil's parameters becomes a crucial part of the model's calibration. This paper deals with a sensitivity analysis of seven soil input parameters to the physically-based Erosion 3D model. The results show the variable influence of each soil parameter. The Erosion 3D model is very sensitive to initial soil moisture, bulk density, and erodibility.

scholarly journals Sensitivity and Performance Analyses of the Distributed Hydrology–Soil–Vegetation Model Using Geomorphons for Landform Mapping

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2032
Author(s):  
Pâmela A. Melo ◽  
Lívia A. Alvarenga ◽  
Javier Tomasella ◽  
Carlos R. Mello ◽  
Minella A. Martins ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Overland Flow ◽  
Hydrological Model ◽  
Model Performance ◽  
Soil Parameters ◽  
Vegetation Model ◽  
Landform Classification ◽  
Physically Based ◽  
And Performance ◽  
Streamflow Simulation

Landform classification is important for representing soil physical properties varying continuously across the landscape and for understanding many hydrological processes in watersheds. Considering it, this study aims to use a geomorphology map (Geomorphons) as an input to a physically based hydrological model (Distributed Hydrology Soil Vegetation Model (DHSVM)) in a mountainous headwater watershed. A sensitivity analysis of five soil parameters was evaluated for streamflow simulation in each Geomorphons feature. As infiltration and saturation excess overland flow are important mechanisms for streamflow generation in complex terrain watersheds, the model’s input soil parameters were most sensitive in the “slope”, “hollow”, and “valley” features. Thus, the simulated streamflow was compared with observed data for calibration and validation. The model performance was satisfactory and equivalent to previous simulations in the same watershed using pedological survey and moisture zone maps. Therefore, the results from this study indicate that a geomorphologically based map is applicable and representative for spatially distributing hydrological parameters in the DHSVM.

scholarly journals Derivation and evaluation of landslide-triggering thresholds by a Monte Carlo approach

2014 ◽  
Vol 18 (12) ◽  
pp. 4913-4931 ◽  
Author(s):  
D. J. Peres ◽  
A. Cancelliere
Keyword(s):  
Monte Carlo ◽  
Slope Stability ◽  
Power Law ◽  
Rainfall Intensity ◽  
Antecedent Rainfall ◽  
Rainfall Events ◽  
Physically Based ◽  
Power Law Equation ◽  
Triggering Rainfall ◽  
Landslide Triggering

Abstract. Assessment of landslide-triggering rainfall thresholds is useful for early warning in prone areas. In this paper, it is shown how stochastic rainfall models and hydrological and slope stability physically based models can be advantageously combined in a Monte Carlo simulation framework to generate virtually unlimited-length synthetic rainfall and related slope stability factor of safety data, exploiting the information contained in observed rainfall records and field-measurements of soil hydraulic and geotechnical parameters. The synthetic data set, dichotomized in triggering and non-triggering rainfall events, is analyzed by receiver operating characteristics (ROC) analysis to derive stochastic-input physically based thresholds that optimize the trade-off between correct and wrong predictions. Moreover, the specific modeling framework implemented in this work, based on hourly analysis, enables one to analyze the uncertainty related to variability of rainfall intensity within events and to past rainfall (antecedent rainfall). A specific focus is dedicated to the widely used power-law rainfall intensity–duration (I–D) thresholds. Results indicate that variability of intensity during rainfall events influences significantly rainfall intensity and duration associated with landslide triggering. Remarkably, when a time-variable rainfall-rate event is considered, the simulated triggering points may be separated with a very good approximation from the non-triggering ones by a I–D power-law equation, while a representation of rainfall as constant–intensity hyetographs globally leads to non-conservative results. This indicates that the I–D power-law equation is adequate to represent the triggering part due to transient infiltration produced by rainfall events of variable intensity and thus gives a physically based justification for this widely used threshold form, which provides results that are valid when landslide occurrence is mostly due to that part. These conditions are more likely to occur in hillslopes of low specific upslope contributing area, relatively high hydraulic conductivity and high critical wetness ratio. Otherwise, rainfall time history occurring before single rainfall events influences landslide triggering, determining whether a threshold based only on rainfall intensity and duration may be sufficient or it needs to be improved by the introduction of antecedent rainfall variables. Further analyses show that predictability of landslides decreases with soil depth, critical wetness ratio and the increase of vertical basal drainage (leakage) that occurs in the presence of a fractured bedrock.

scholarly journals Inverse distributed hydrological modelling of Alpine catchments

2006 ◽  
Vol 10 (3) ◽  
pp. 395-412 ◽  
Author(s):  
H. Kunstmann ◽  
J. Krause ◽  
S. Mayr
Keyword(s):  
Parameter Estimation ◽  
Hydrological Model ◽  
Model Performance ◽  
Horizontal Resolution ◽  
Nonlinear Parameter ◽  
Model Complexity ◽  
Distributed Hydrological Model ◽  
Nonlinear Parameter Estimation ◽  
Estimated Parameters ◽  
Physically Based

Abstract. Even in physically based distributed hydrological models, various remaining parameters must be estimated for each sub-catchment. This can involve tremendous effort, especially when the number of sub-catchments is large and the applied hydrological model is computationally expensive. Automatic parameter estimation tools can significantly facilitate the calibration process. Hence, we combined the nonlinear parameter estimation tool PEST with the distributed hydrological model WaSiM. PEST is based on the Gauss-Marquardt-Levenberg method, a gradient-based nonlinear parameter estimation algorithm. WaSiM is a fully distributed hydrological model using physically based algorithms for most of the process descriptions. WaSiM was applied to the alpine/prealpine Ammer River catchment (southern Germany, 710 km2 in a 100×100 m2 horizontal resolution. The catchment is heterogeneous in terms of geology, pedology and land use and shows a complex orography (the difference of elevation is around 1600 m). Using the developed PEST-WaSiM interface, the hydrological model was calibrated by comparing simulated and observed runoff at eight gauges for the hydrologic year 1997 and validated for the hydrologic year 1993. For each sub-catchment four parameters had to be calibrated: the recession constants of direct runoff and interflow, the drainage density, and the hydraulic conductivity of the uppermost aquifer. Additionally, five snowmelt specific parameters were adjusted for the entire catchment. Altogether, 37 parameters had to be calibrated. Additional a priori information (e.g. from flood hydrograph analysis) narrowed the parameter space of the solutions and improved the non-uniqueness of the fitted values. A reasonable quality of fit was achieved. Discrepancies between modelled and observed runoff were also due to the small number of meteorological stations and corresponding interpolation artefacts in the orographically complex terrain. Application of a 2-dimensional numerical groundwater model partly yielded a slight decrease of overall model performance when compared to a simple conceptual groundwater approach. Increased model complexity therefore did not yield in general increased model performance. A detailed covariance analysis was performed allowing to derive confidence bounds for all estimated parameters. The correlation between the estimated parameters was in most cases negligible, showing that parameters were estimated independently from each other.

scholarly journals Rainfall-runoff modelling in a catchment with a complex groundwater flow system: application of the Representative Elementary Watershed (REW) approach

2005 ◽  
Vol 2 (3) ◽  
pp. 639-690 ◽  
Author(s):  
G. P. Zhang ◽  
H. H. G. Savenije
Keyword(s):  
River Basin ◽  
Overland Flow ◽  
Model Performance ◽  
Source Area ◽  
Subsurface Water ◽  
Watershed Hydrology ◽  
Rainfall Runoff ◽  
Data Set ◽  
Physically Based ◽  
Infiltration Excess

Abstract. Based on the Representative Elementary Watershed (REW) approach, the modelling tool REWASH (Representative Elementary WAterShed Hydrology) has been developed and applied to the Geer river basin. REWASH is deterministic, semi-distributed, physically based and can be directly applied to the watershed scale. In applying REWASH, the river basin is divided into a number of sub-watersheds, so called REWs, according to the Strahler order of the river network. REWASH describes the dominant hydrological processes, i.e. subsurface flow in the unsaturated and saturated domains, and overland flow by the saturation-excess and infiltration-excess mechanisms. Through flux exchanges among the different spatial domains of the REW, surface and subsurface water interactions are fully coupled. REWASH is a parsimonious tool for modelling watershed hydrological response. However, it can be modified to include more components to simulate specific processes when applied to a specific river basin where such processes are observed or considered to be dominant. In this study, we have added a new component to simulate interception using a simple parametric approach. Interception plays an important role in the water balance of a watershed although it is often disregarded. In addition, a refinement for the transpiration in the unsaturated zone has been made. Finally, an improved approach for simulating saturation overland flow by relating the variable source area to both the topography and the groundwater level is presented. The model has been calibrated and verified using a 4-year data set, which has been split into two for calibration and validation. The model performance has been assessed by multi-criteria evaluation. This work is the first full application of the REW approach to watershed rainfall-runoff modelling in a real watershed. The results demonstrate that the REW approach provides an alternative blueprint for physically based hydrological modelling.

scholarly journals Numerical modeling of blowing and drifting snow in Alpine terrain

2001 ◽  
Vol 47 (156) ◽  
pp. 97-110 ◽  
Author(s):  
Peter Gauer
Keyword(s):  
Field Measurements ◽  
Erosion And Deposition ◽  
Mountainous Regions ◽  
Boundary Layer Equations ◽  
Trajectory Calculations ◽  
Drifting Snow ◽  
Physically Based ◽  
Turbulent Closure ◽  
Snow Distribution ◽  
Two Layer Model

AbstractIn mountainous regions, snow transport due to wind significantly influences snow distribution and, as a result, avalanche danger. A physically based numerical two-layer model is developed to simulate blowing and drifting snow in Alpine terrain. One layer describes the driving-wind field and the transport in suspension. The description is based on the atmospheric boundary-layer equations, using ane−∊model for the turbulent closure. The second layer describes the transport due to saltation, including erosion and deposition of snow. Here, conservation equations for mass and momentum are formulated for the mixture of snow and air. Particle trajectory calculations are used to parameterize quantities characterizing the saltation layer. Both layers are mutually coupled by boundary conditions. A two-way coupling between particles and airflow is taken into account. Comparisons between simulation results and field measurements around an Alpine crest show encouraging results.

scholarly journals Study on the effect of rainfall spatial variability on runoff modelling

2018 ◽  
Vol 20 (3) ◽  
pp. 577-587 ◽  
Author(s):  
Jun Zhang ◽  
Dawei Han ◽  
Yang Song ◽  
Qiang Dai
Keyword(s):  
Spatial Distribution ◽  
Spatial Variability ◽  
Spatial Information ◽  
Model Performance ◽  
Moran’S I ◽  
Image Size ◽  
Moran's I ◽  
Rainfall Events ◽  
Lumped Model ◽  
Distributed Models

Abstract Rainfall spatial variability was assessed to explore its influence on runoff modelling. Image size, coefficient of variation (Cv) and Moran's I were chosen to assess for rainfall spatial variability. The smaller the image size after compression, the less complex is the rainfall spatial variability. The results showed that due to the drawing procedure and varied compression methods, a large uncertainty exists for using image size to describe rainfall spatial variability. Cv quantifies the variability between different rainfall values without considering rainfall spatial distribution and Moran's I describes the spatial autocorrelation between gauges rather than the values. As both rainfall values and spatial distribution have an influence on runoff modelling, the combination of Cv and Moran's I was further explored. The results showed that the combination of Cv and Moran's I is reliable to describe rainfall spatial variability. Furthermore, with the increase of rainfall spatial variability, the hydrological model performance decreases. Moreover, it is difficult for a lumped model to cope with rainfall events assigned with complex rainfall spatial variability since spatial information is not taken into consideration (i.e. the VIC model used in this study). Therefore, it is recommended to apply distributed models that can deal with more spatial input information.

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