scholarly journals Models of Gully Erosion by Water

Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3293
Author(s):  
Aleksey Sidorchuk
Keyword(s):  
Time Series ◽  
Dynamic Model ◽  
Land Management ◽  
Surface Runoff ◽  
Model Calibration ◽  
Input Data ◽  
Gully Erosion ◽  
Water Runoff ◽  
Erosion Risk ◽  
Maximum Surface

The type of modelling of gully erosion for the projects of land management depend on the targets and degree of details of these projects, as well as on the availability of input data. The set of four models cover a broad range of possible applications. The most detailed information about predicted gullies, change of their depth, width, and volume throughout the gully lifetime is obtained with the gully erosion and thermoerosion dynamic model. The calculation requires the time series of surface runoff, catchment relief, and lithology and the complex of coefficients and parameters, some of which can be estimated only by model calibration on the measurements. The difficulty in obtaining some of these coefficients makes it necessary to use less complicated models. The stable gully model predicts final gully depths and widths and is useful for projects where only stable gully geometry is used. The modified area–slope approach is used in the two simplest models, where the position on the slopes of possible gullies is calculated without details of the gully geometry. One of these models calculates total erosion potential, taking into account all water runoff transforming a gully. The second calculates gully erosion risk, using the information about slope inclination, contributing area and maximum surface runoff.

scholarly journals Greenland liquid water runoff from 1979 through 2017

2020 ◽  
Author(s):  
Kenneth D. Mankoff ◽  
Andreas P. Ahlstrøm ◽  
William Colgan ◽  
Robert S. Fausto ◽  
Xavier Fettweis ◽  
...  
Keyword(s):  
Time Series ◽  
Liquid Water ◽  
Input Data ◽  
Climate Models ◽  
Volume Flow Rate ◽  
Sensitivity Study ◽  
Water Volume ◽  
Daily Maximum ◽  
Water Runoff ◽  
Runoff Water

Abstract. We provide high-resolution datasets of Greenland hydrologic outlets, basins, and streams, and a 1979 through 2017 time series of Greenland liquid water runoff for each outlet. Outlets, basins, and streams are derived from traditional hydrologic routing algorithms over the surface of a 100 m ArcticDEM digital elevation model (DEM) twice: Once to the ice margin and once to the coast. We then partition liquid water runoff from both ice and land from two regional climate models (RCMs; MAR and RACMO) into each basin and at each outlet location. The data include 18903 ice basins and outlets (614 basins greater than 10 km2), 30241 land basins and outlets (958 basins greater than 10 km2), major streams in each basin, and daily runoff water volume flow rate at each outlet from each of two RCMs. We perform a sensitivity study of outlet location change for every ice sheet location over a range of hydrologic routing assumptions and data sets. Annual runoff from the ice ranges from ~136 km3 in 1992 to ~785 km3 in 2012. Daily maximum ice runoff from one basin is as large as 4380 m3 s−1. Both ice runoff magnitude and variability increase over the time series. Land runoff contributes an additional ∼ 35 % to the ice runoff. Comparison with 9 basins instrumented with stream gauges shows a range of (dis)agreement from poor to excellent between our estimated discharge and observations. As part of the journal’s living archive option, and our goal to make an operational product, all input data, code, and results from this study will be updated as needed (when new input data are available, as new features are added, or to fix bugs) and made available at https://doi.org/10.22008/promice/data/freshwater_runoff/v01 (Mankoff, 2020) and at http://github.com/mankoff/freshwater.

scholarly journals Hydrological model calibration for derived flood frequency analysis using stochastic rainfall and probability distributions of peak flows

2014 ◽  
Vol 18 (1) ◽  
pp. 353-365 ◽  
Author(s):  
U. Haberlandt ◽  
I. Radtke
Keyword(s):  
Time Series ◽  
Frequency Analysis ◽  
Model Calibration ◽  
Hydrological Model ◽  
Probability Distributions ◽  
Flood Frequency ◽  
Rainfall Data ◽  
Flood Frequency Analysis ◽  
Peak Flows ◽  
Hourly Rainfall

Abstract. Derived flood frequency analysis allows the estimation of design floods with hydrological modeling for poorly observed basins considering change and taking into account flood protection measures. There are several possible choices regarding precipitation input, discharge output and consequently the calibration of the model. The objective of this study is to compare different calibration strategies for a hydrological model considering various types of rainfall input and runoff output data sets and to propose the most suitable approach. Event based and continuous, observed hourly rainfall data as well as disaggregated daily rainfall and stochastically generated hourly rainfall data are used as input for the model. As output, short hourly and longer daily continuous flow time series as well as probability distributions of annual maximum peak flow series are employed. The performance of the strategies is evaluated using the obtained different model parameter sets for continuous simulation of discharge in an independent validation period and by comparing the model derived flood frequency distributions with the observed one. The investigations are carried out for three mesoscale catchments in northern Germany with the hydrological model HEC-HMS (Hydrologic Engineering Center's Hydrologic Modeling System). The results show that (I) the same type of precipitation input data should be used for calibration and application of the hydrological model, (II) a model calibrated using a small sample of extreme values works quite well for the simulation of continuous time series with moderate length but not vice versa, and (III) the best performance with small uncertainty is obtained when stochastic precipitation data and the observed probability distribution of peak flows are used for model calibration. This outcome suggests to calibrate a hydrological model directly on probability distributions of observed peak flows using stochastic rainfall as input if its purpose is the application for derived flood frequency analysis.

scholarly journals Sub-daily runoff simulations with parameters inferred at the daily time scale

2015 ◽  
Vol 12 (8) ◽  
pp. 7437-7467 ◽  
Author(s):  
J. E. Reynolds ◽  
S. Halldin ◽  
C. Y. Xu ◽  
J. Seibert ◽  
A. Kauffeldt
Keyword(s):  
Time Series ◽  
Numerical Method ◽  
Time Scales ◽  
Time Scale ◽  
Input Data ◽  
Flood Forecasting ◽  
Euler Method ◽  
Time Stepping ◽  
Parameter Values ◽  
Daily Time

Abstract. Concentration times in small and medium-sized watersheds (~ 100–1000 km2) are commonly less than 24 h. Flood-forecasting models then require data at sub-daily time scales, but time-series of input and runoff data with sufficient lengths are often only available at the daily time scale, especially in developing countries. This has led to a search for time-scale relationships to infer parameter values at the time scales where they are needed from the time scales where they are available. In this study, time-scale dependencies in the HBV-light conceptual hydrological model were assessed within the generalized likelihood uncertainty estimation (GLUE) approach. It was hypothesised that the existence of such dependencies is a result of the numerical method or time-stepping scheme used in the models rather than a real time-scale-data dependence. Parameter values inferred showed a clear dependence on time scale when the explicit Euler method was used for modelling at the same time steps as the time scale of the input data (1–24 h). However, the dependence almost fully disappeared when the explicit Euler method was used for modelling in 1 h time steps internally irrespectively of the time scale of the input data. In other words, it was found that when an adequate time-stepping scheme was implemented, parameter sets inferred at one time scale (e.g., daily) could be used directly for runoff simulations at other time scales (e.g., 3 or 6 h) without any time scaling and this approach only resulted in a small (if any) model performance decrease, in terms of Nash–Sutcliffe and volume-error efficiencies. The overall results of this study indicated that as soon as sub-daily driving data can be secured, flood forecasting in watersheds with sub-daily concentration times is possible with model-parameter values inferred from long time series of daily data, as long as an appropriate numerical method is used.

scholarly journals INFLUENCE OF SPATIAL AND TEMPORAL RESOLUTION ON TIME SERIES-BASED COASTAL SURFACE CHANGE ANALYSIS USING HOURLY TERRESTRIAL LASER SCANS

2021 ◽  
Vol V-2-2021 ◽  
pp. 137-144
Author(s):  
K. Anders ◽  
L. Winiwarter ◽  
H. Mara ◽  
R. C. Lindenbergh ◽  
S. E. Vos ◽  
...  
Keyword(s):  
Time Series ◽  
Temporal Resolution ◽  
Input Data ◽  
Laser Scanning ◽  
Poor Performance ◽  
Computational Effort ◽  
Spatial Extent ◽  
Change Analysis ◽  
Surface Change ◽  
Natural Surface

Abstract. Near-continuously acquired terrestrial laser scanning (TLS) data contains valuable information on natural surface dynamics. An important step in geographic analyses is to detect different types of changes that can be observed in a scene. For this, spatiotemporal segmentation is a time series-based method of surface change analysis that removes the need to select analysis periods, providing so-called 4D objects-by-change (4D-OBCs). This involves higher computational effort than pairwise change detection, and efforts scale with (i) the temporal density of input data and (ii) the (variable) spatial extent of delineated changes. These two factors determine the cost and number of Dynamic Time Warping distance calculations to be performed for deriving the metric of time series similarity. We investigate how a reduction of the spatial and temporal resolution of input data influences the delineation of twelve erosion and accumulation forms, using an hourly five-month TLS time series of a sandy beach. We compare the spatial extent of 4D-OBCs obtained at reduced spatial (1.0 m to 15.0 m with 0.5 m steps) and temporal (2 h to 96 h with 2 h steps) resolution to the result from highest-resolution data. Many change delineations achieve acceptable performance with ranges of ±10 % to ±100 % in delineated object area, depending on the spatial extent of the respective change form. We suggest a locally adaptive approach to identify poor performance at certain resolution levels for the integration in a hierarchical approach. Consequently, the spatial delineation could be performed at high accuracy for specific target changes in a second iteration. This will allow more efficient 3D change analysis towards near-realtime, online TLS-based observation of natural surface changes.

scholarly journals Simulation of the Occurrence of Water Runoff in Soils Under Cultivation of Industrial Tomato Irrigated by Center Pivot

2019 ◽  
Vol 11 (7) ◽  
pp. 48
Author(s):  
Diogo. H. M. Moraes ◽  
José Alves Júnior ◽  
Marcio Mesquita ◽  
Adão. W. P. Evangelista ◽  
Derblai Casaroli ◽  
...  
Keyword(s):  
Surface Runoff ◽  
Irrigation System ◽  
Numerical Technique ◽  
Irrigation Management ◽  
Water Runoff ◽  
Clayey Soils ◽  
Infiltration Capacity ◽  
Tomato Crop ◽  
Center Pivot ◽  
Different Types

The tomato crop is almost totally irrigated. Among the irrigation methods utilized, mechanized sprinkling by center pivot stands out in tomato cultivation. A cultural treatment used in the tomato is the synchronization of the irrigations with the applications of the pesticides since with the leaf wetting the plants become unprotected and susceptible to diseases. In an attempt to reduce pesticide applications, growers seek to increase the time between irrigations, however, there are limitations, inherent to the soil and the irrigation system itself. The objective of this work was to simulate the soil water runoff tendency for irrigation management in the tomato crop, simulating three different types of soils (sandy, medium and clayey), three declines (0, 5 and 10%), and two types of deflectors (I-Wob and Spray). For this, four pivot sizes (25, 50, 75 and 100 ha) were defined and the methodology of maximum allowable precipitation estimated by the Newton-Raphson numerical technique was used to verify the different runoff conditions. The results showed that clayey soils are more susceptible when compared to medium and sandy soils, to surface runoff. Pivots of 100, 75 and 50 ha present greater susceptibility to runoff, with 25 ha being the best suitability for infiltration capacity in both soils. There is a percentage reduction of the maximum allowable rainfall of 40.74 % (±1.54) when the terrain is plan and pass to have 5% inclination and 22.99% (±1.47) between 5 and 10 %. I-Wob type deflectors have a better distribution of application, a consequently better relation with the maximum allowable precipitation intensity and less possibility of the surface runoff.

THE INFLUENCE OF IMPROVED PLACEMENT OF FLOW-REGULATING FOREST BELTS ON THE FORMATION OF SURFACE RUNOFF OF MELTWATER

2021 ◽  
Author(s):  
A.I. Petelko ◽  
Keyword(s):  
Surface Runoff ◽  
Scientific Research ◽  
Soil Freezing ◽  
Water Runoff ◽  
Combined Design ◽  
Spring Runoff ◽  
Natural Factors ◽  
Melt Water ◽  
Forest Belts ◽  
Snow Deposition

The materials of scientific research for a number of years on the formation of melt water runoff on autumn plowing with stock-regulating forest belts of a combined design with low-growing shrubs are presented. It was revealed that the spring runoff depends on the main natural factors: moisture, soil freezing and snow deposition.

AutoSS: A Deep Learning-Based Soft Sensor for Handling Time-Series Input Data

2021 ◽  
Vol 6 (3) ◽  
pp. 6100-6107
Author(s):  
Nicolo Bargellesi ◽  
Alessandro Beghi ◽  
Mirco Rampazzo ◽  
Gian Antonio Susto
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Input Data ◽  
Handling Time ◽  
Soft Sensor

Monitoring of water table dynamics in peatlands with OPTRAM: Towards globally applicable algorithms in Google Earth Engine using Landsat and Sentinel-2

2021 ◽  
Author(s):  
Iuliia Burdun ◽  
Michel Bechtold ◽  
Viacheslav Komisarenko ◽  
Annalea Lohila ◽  
Elyn Humphreys ◽  
...  
Keyword(s):  
Time Series ◽  
Water Table ◽  
Input Data ◽  
Short Wave ◽  
Google Earth ◽  
Google Earth Engine ◽  
Short Wave Infrared ◽  
Northern Peatlands ◽  
Sentinel 2

<p>Fluctuations of water table depth (WTD) affect many processes in peatlands, such as vegetation development and emissions of greenhouse gases. Here, we present the OPtical TRApezoid Model (OPTRAM) as a new method for satellite-based monitoring of the temporal variation of WTD in peatlands. OPTRAM is based on the response of short-wave infrared reflectance to the vegetation water status. For five northern peatlands with long-term in-situ WTD records, and with diverse vegetation cover and hydrological regimes, we generate a suite of OPTRAM index time series using (a) different procedures to parametrise OPTRAM (peatland-specific manual vs. globally applicable automatic parametrisation in Google Earth Engine), and (b) different satellite input data (Landsat vs. Sentinel-2). The results based on the manual parametrisation of OPTRAM indicate a high correlation with in-situ WTD time-series for pixels with most suitable vegetation for OPTRAM application (mean Pearson correlation of 0.7 across sites), and we will present the performance differences when moving from a manual to an automatic procedure. Furthermore, for the overlap period of Landsat and Sentinel-2, which have different ranges and widths of short-wave infrared bands used for OPTRAM calculation, the impact of the satellite input data to OPTRAM will be analysed. Eventually, the challenge of merging different satellite missions in the derivation of OPTRAM time series will be explored as an important step towards a global application of OPTRAM for the monitoring of WTD dynamics in northern peatlands.</p>

scholarly journals Modelling of Surface Runoff on the Yamal Peninsula, Russia, Using ERA5 Reanalysis

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2099
Author(s):  
Tatiana Matveeva ◽  
Aleksey Sidorchuk
Keyword(s):  
Surface Runoff ◽  
Industrial Development ◽  
Meteorological Data ◽  
Reanalysis Data ◽  
Gully Erosion ◽  
Yamal Peninsula ◽  
Weather Forecasts ◽  
Main Input ◽  
The Cost ◽  
The Yamal Peninsula

The Yamal peninsula is a territory of active industrial development as it contains several rich fields of natural condensed gas and oil. The density of the gullies net on the Yamal peninsula is one of the highest in the Russian Arctic. The natural environment or constructions can be potentially damaged by gully erosion and the cost of such damage is high. The models of gully erosion require surface runoff estimates. The hydrological model was developed for surface runoff estimation during the spring snow thaw and summer rains. In the conditions of Arctic climate with deep permafrost, the losses in runoff are limited to evaporation, as soil permeability is negligible. The model was calibrated on the available measurements. The meteorological base for hydrological calculations was ERA5 reanalysis, the fifth generation of European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalyses, validated on the meteorological data. The deviations of reanalysis data from the measurements cause the errors in the results of surface runoff calculation. The daily surface runoff can vary in the range of 18–30% due to ERA5 errors in air temperature and snow cover depth. As the daily surface runoff is the main input to the models of gully erosion, these errors must be taken into account in the modelling of gully erosion on the Yamal peninsula.

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