The effect of the choice of time resolution on the prediction of deep drainage rates in rocky covers

2020 ◽  
Author(s):  
Thomas Baumgartl ◽  
Mandana Shaygan
Keyword(s):  
Time Series ◽  
Water Balance ◽  
Numerical Modelling ◽  
Water Flow ◽  
Input Data ◽  
Pore System ◽  
Deep Drainage ◽  
Time Step ◽  
Rainfall Events ◽  
Hourly Data

<p><span>Numerical modelling is a tool allowing the prediction of water flow and water balance based on material properties and time dependent input information at defined boundaries. Long time series are often required for a well informed assessment of the performance of a site. It has been shown that covers as a preferred option constructed in semi-arid and arid climates on mine sites to manage water flows and to prevent deep drainage have a characteristic bi-modal pore system largely caused by a large fraction of coarse rocks. Bi-modal water retention curves have been established for such covers which have proven to describe the response to precipitation with higher accuracy. Meteorological data as input information are in many cases only available on a daily basis if time series over decades are used for modelling. For a bi-modal pore system with often very high values for saturated hydraulic conductivity, a daily time-step may be to large to capture numerically the response in water flow. The objective of the presented work is the comparison of modelled deep drainage data for a specific cover design where hourly data are compared with daily input data. The latter were aggregated from the hourly information. </span></p><p><span>The results from the numerical modelling showed that for environments with high intensity rainfall events the calculated amount of deep drainage was by up to 10% smaller for the aggregated daily input data compared to the hourly data.</span></p><p><span>The presentation will inform which rainfall events contributed primarily to the difference in the water balance parameters and to which extent a generalisation can be made on the choice or requirement to choose an appropriate time step for specific climatic conditions.</span></p>

scholarly journals 2DVD Data Revisited: Multifractal Insights into Cuts of the Spatiotemporal Rainfall Process

2015 ◽  
Vol 16 (2) ◽  
pp. 548-562 ◽  
Author(s):  
Auguste Gires ◽  
Ioulia Tchiguirinskaia ◽  
Daniel Schertzer ◽  
Alexis Berne
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Empirical Evidence ◽  
Heavy Rainfall ◽  
Resolution Time ◽  
Time Step ◽  
Measuring Device ◽  
Rainfall Events ◽  
Heavy Rainfall Events ◽  
Very High

Abstract Data collected during four heavy rainfall events that occurred in Ardèche (France) with the help of a 2D video disdrometer (2DVD) are used to investigate the structure of the raindrop distribution in both space and time. A first type of analysis is based on the reconstruction of 36-m-height vertical rainfall columns above the measuring device. This reconstruction is obtained with the help of a ballistic hypothesis applied to 1-ms time step series. The corresponding snapshots are analyzed with the help of universal multifractals. For comparison, a similar analysis is performed on the time series with 1-ms time steps, as well as on time series of accumulation maps of N consecutive recorded drops (therefore with variable time steps). It turns out that the drop distribution exhibits a good scaling behavior in the range 0.5–36 m during the heaviest portion of the events, confirming the lack of empirical evidence of the widely used homogenous assumption for drop distribution. For smaller scales, drop positions seem to be homogeneously distributed. The notion of multifractal singularity is well illustrated by the very high-resolution time series.

A model of the energy system of lactating and pregnant cows

1984 ◽  
Vol 38 (3) ◽  
pp. 351-362 ◽  
Author(s):  
J. M. Bruce ◽  
P. J. Broadbent ◽  
J. H. Topps
Keyword(s):  
Time Series ◽  
Food Intake ◽  
Environmental Factors ◽  
Dairy Cow ◽  
Input Data ◽  
Deterministic Model ◽  
Live Weight ◽  
Energy System ◽  
Nutritional Management ◽  
Time Step

ABSTRACT1. A deterministic model and computer program of the energy system of lactating and pregnant cows have been developed.2. Input data for cow, nutritional, management and environmental factors are required.3. The output of milk production, live weight and heat production is a time series, with a weekly time-step.4. Suckler and dairy cow examples are given to illustrate the use of the model to evaluate the effects of quality, quantity and pattern of food intake, and shelter.

scholarly journals Analysis of MNF and FAVAD Models for Leakage Characterization by Exploiting Smart-Metered Data: The Case of the Gorino Ferrarese (FE-Italy) District

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 643
Author(s):  
Irene Marzola ◽  
Stefano Alvisi ◽  
Marco Franchini
Keyword(s):  
Time Series ◽  
Water Balance ◽  
Water Consumption ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Utilities ◽  
Time Step ◽  
Minimum Night Flow ◽  
The Relationship ◽  
District Metered Area

Leakages in water distribution systems have great economic and environmental impacts and are a major issue for water utilities. In this work, the water balance and the Minimum Night Flow (MNF) method for evaluating the amount of water loss, as well as the power and Fixed and Variable Area Discharge (FAVAD) equations for analyzing the relationship between leakage and pressure, were applied to a fully monitored District Metered Area (DMA) located in Gorino Ferrarese (FE, Italy). Time series of (a) the water consumption of each user, (b) the DMA inflow, and (c) the pressure at the DMA inlet point were monitored with a 5 min time step. The results of an analysis carried out by exploiting the collected time series highlighted that: (a) The application of the MNF method based on literature values can lead to significant inaccuracies in the presence of users with irregular consumption, and (b) the estimation of the parameters of the power and FAVAD equations is highly affected by the amounts and types of observed data used.

A DETERMINISTIC PARAMETRIC WATER-BALANCE MODEL

1973 ◽  
Vol 4 (3) ◽  
pp. 191-205
Author(s):  
HARALD GRIP
Keyword(s):  
Time Series ◽  
Water Balance ◽  
Input Data ◽  
Deterministic Model ◽  
Water Balance Model ◽  
Balance Model ◽  
Output Data ◽  
Mean Values ◽  
Initial Values ◽  
Recession Curve

A simple deterministic model, that needs little input-data, is derived. It is based on an analysis of the recession curve, where new considerations are introduced. Input data consist of time-series of precipitation, initial values of storage in upper and lower soil-storages and in interception storage, and initial runoff. Output data are time-series of evapotranspiration, interception, upper and lower soil-storages and runoff, all given as 2-hour mean values.

scholarly journals Accounting for hydro-climatic and water use variability in the assessment of past and future water balance at the basin scale

2015 ◽  
Vol 371 ◽  
pp. 43-48 ◽  
Author(s):  
J. Fabre ◽  
D. Ruelland ◽  
A. Dezetter ◽  
B. Grouillet
Keyword(s):  
Time Series ◽  
Water Balance ◽  
Water Use ◽  
Water Demand ◽  
Climatic Conditions ◽  
Climate Change Scenarios ◽  
Climate Trends ◽  
Time Step ◽  
Basin Scale ◽  
Water Uses

Abstract. This study assesses water stress by 2050 in river basins facing increasing human and climatic pressures, by comparing the impacts of various combinations of possible future socio-economic and climate trends. A modelling framework integrating human and hydro-climatic dynamics and accounting for interactions between resource and demand at a 10-day time step was developed and applied in two basins of different sizes and with contrasted water uses: the Herault (2500 km2, France) and the Ebro (85 000 km2, Spain) basins. Natural streamflow was evaluated using a conceptual hydrological model (GR4j). A demand-driven reservoir management model was designed to account for streamflow regulations from the main dams. Urban water demand was estimated from time series of population and monthly unit water consumption data. Agricultural water demand was computed from time series of irrigated area, crop and soil data, and climate forcing. Indicators comparing water supply to demand at strategic resource and demand nodes were computed. This framework was successfully calibrated and validated under non-stationary human and hydro-climatic conditions over the last 40 years before being applied under four combinations of climatic and water use scenarios to differentiate the impacts of climate- and human-induced changes on streamflow and water balance. Climate simulations from the CMIP5 exercise were used to generate 18 climate scenarios at the 2050 horizon. A baseline water use scenario for 2050 was designed based on demographic and local socio-economic trends. Results showed that projected water uses are not sustainable under climate change scenarios.

scholarly journals Simulation of Daily Mean Soil Temperatures for Agricultural Land Use Considering Limited Input Data

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 441
Author(s):  
Philipp Grabenweger ◽  
Branislava Lalic ◽  
Miroslav Trnka ◽  
Jan Balek ◽  
Erwin Murer ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Input Data ◽  
Agricultural Land ◽  
Soil Column ◽  
Soil Conditions ◽  
Snow Layer ◽  
Time Step ◽  
Soil Temperatures ◽  
Dimensional Simulation ◽  
Limited Input Data

A one-dimensional simulation model that simulates daily mean soil temperature on a daily time-step basis, named AGRISOTES (AGRIcultural SOil TEmperature Simulation), is described. It considers ground coverage by biomass or a snow layer and accounts for the freeze/thaw effect of soil water. The model is designed for use on agricultural land with limited (and mostly easily available) input data, for estimating soil temperature spatial patterns, for single sites (as a stand-alone version), or in context with agrometeorological and agronomic models. The calibration and validation of the model are carried out on measured soil temperatures in experimental fields and other measurement sites with various climates, agricultural land uses and soil conditions in Europe. The model validation shows good results, but they are determined strongly by the quality and representativeness of the measured or estimated input parameters to which the model is most sensitive, particularly soil cover dynamics (biomass and snow cover), soil pore volume, soil texture and water content over the soil column.

scholarly journals Assessing dry weather flow contribution in TSS and COD storm events loads in combined sewer systems

2011 ◽  
Vol 63 (12) ◽  
pp. 2983-2991 ◽  
Author(s):  
M. Métadier ◽  
J. L. Bertrand-Krajewski
Keyword(s):  
Time Series ◽  
Oxygen Demand ◽  
Seasonal Effect ◽  
Storm Events ◽  
Combined System ◽  
Time Step ◽  
Urban Catchment ◽  
Sewer Systems ◽  
Continuous Discharge

Continuous high resolution long term turbidity measurements along with continuous discharge measurements are now recognised as an appropriate technique for the estimation of in sewer total suspended solids (TSS) and Chemical Oxygen Demand (COD) loads during storm events. In the combined system of the Ecully urban catchment (Lyon, France), this technique is implemented since 2003, with more than 200 storm events monitored. This paper presents a method for the estimation of the dry weather (DW) contribution to measured total TSS and COD event loads with special attention devoted to uncertainties assessment. The method accounts for the dynamics of both discharge and turbidity time series at two minutes time step. The study is based on 180 DW days monitored in 2007–2008. Three distinct classes of DW days were evidenced. Variability analysis and quantification showed that no seasonal effect and no trend over the year were detectable. The law of propagation of uncertainties is applicable for uncertainties estimation. The method has then been applied to all measured storm events. This study confirms the interest of long term continuous discharge and turbidity time series in sewer systems, especially in the perspective of wet weather quality modelling.

scholarly journals Stationary and Non-Stationary Frameworks for Extreme Rainfall Time Series in Southern Italy

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1477 ◽  
Author(s):  
Davide De Luca ◽  
Luciano Galasso
Keyword(s):  
Time Series ◽  
Climate Models ◽  
Southern Italy ◽  
Regional Climate ◽  
Data Series ◽  
Rainfall Time Series ◽  
Annual Maximum ◽  
Data Set ◽  
Maximum Rainfall ◽  
Rainfall Events

This study tests stationary and non-stationary approaches for modelling data series of hydro-meteorological variables. Specifically, the authors considered annual maximum rainfall accumulations observed in the Calabria region (southern Italy), and attention was focused on time series characterized by heavy rainfall events which occurred from 1 January 2000 in the study area. This choice is justified by the need to check if the recent rainfall events in the new century can be considered as very different or not from the events occurred in the past. In detail, the whole data set of each considered time series (characterized by a sample size N > 40 data) was analyzed, in order to compare recent and past rainfall accumulations, which occurred in a specific site. All the proposed models were based on the Two-Component Extreme Value (TCEV) probability distribution, which is frequently applied for annual maximum time series in Calabria. The authors discussed the possible sources of uncertainty related to each framework and remarked on the crucial role played by ergodicity. In fact, if the process is assumed to be non-stationary, then ergodicity cannot hold, and thus possible trends should be derived from external sources, different from the time series of interest: in this work, Regional Climate Models’ (RCMs) outputs were considered in order to assess possible trends of TCEV parameters. From the obtained results, it does not seem essential to adopt non-stationary models, as significant trends do not appear from the observed data, due to a relevant number of heavy events which also occurred in the central part of the last century.

A Novel Solution to Compute Stress Time Series in Nonlinear Hydro-Structure Simulations

2015 ◽  
Author(s):  
Fabien Bigot ◽  
François-Xavier Sireta ◽  
Eric Baudin ◽  
Quentin Derbanne ◽  
Etienne Tiphine ◽  
...  
Keyword(s):  
Time Series ◽  
Frequency Domain ◽  
Time Domain ◽  
Hot Spot ◽  
Structural Response ◽  
Container Ship ◽  
Time Step ◽  
Computation Cost ◽  
Hull Girder ◽  
Non Linear

Ship transport is growing up rapidly, leading to ships size increase, and particularly for container ships. The last generation of Container Ship is now called Ultra Large Container Ship (ULCS). Due to their increasing sizes they are more flexible and more prone to wave induced vibrations of their hull girder: springing and whipping. The subsequent increase of the structure fatigue damage needs to be evaluated at the design stage, thus pushing the development of hydro-elastic simulation models. Spectral fatigue analysis including the first order springing can be done at a reasonable computational cost since the coupling between the sea-keeping and the Finite Element Method (FEM) structural analysis is performed in frequency domain. On the opposite, the simulation of non-linear phenomena (Non linear springing, whipping) has to be done in time domain, which dramatically increases the computation cost. In the context of ULCS, because of hull girder torsion and structural discontinuities, the hot spot stress time series that are required for fatigue analysis cannot be simply obtained from the hull girder loads in way of the detail. On the other hand, the computation cost to perform a FEM analysis at each time step is too high, so alternative solutions are necessary. In this paper a new solution is proposed, that is derived from a method for the efficient conversion of full scale strain measurements into internal loads. In this context, the process is reversed so that the stresses in the structural details are derived from the internal loads computed by the sea-keeping program. First, a base of distortion modes is built using a structural model of the ship. An original method to build this base using the structural response to wave loading is proposed. Then a conversion matrix is used to project the computed internal loads values on the distortion modes base, and the hot spot stresses are obtained by recombination of their modal values. The Moore-Penrose pseudo-inverse is used to minimize the error. In a first step, the conversion procedure is established and validated using the frequency domain hydro-structure model of a ULCS. Then the method is applied to a non-linear time domain simulation for which the structural response has actually been computed at each time step in order to have a reference stress signal, in order to prove its efficiency.

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