Commemorating the 50th anniversary of the Freeze and Harlan (1969) Blueprint for a physically-based, digitally-simulated hydrologic response model

2020 ◽  
Author(s):  
Craig T. Simmons ◽  
Philip Brunner ◽  
Rene Therrien ◽  
Edward A. Sudicky
Keyword(s):  
Numerical Models ◽  
50Th Anniversary ◽  
Response Model ◽  
Hydrologic Response ◽  
Personal Communications ◽  
Rivers And Lakes ◽  
Challenges And Opportunities ◽  
Physically Based ◽  
Groundwater Exchange ◽  
Overland Runoff

<p>The year 2019 marked the 50th anniversary of a pioneering publication in hydrology. Allan Freeze and Richard Harlan published their <em>Blueprint for a physically-based, digitally-simulated hydrologic response model</em> (Freeze and Harlan, 1969) in <em>Journal of Hydrology</em>. Their vision was for a futuristic model that would integrate key processes and compartments in the hydrologic cycle: precipitation, evapotranspiration, overland runoff, infiltration and groundwater exchange (into and out of) surface water bodies, such as rivers and lakes. Today, the original Blueprint is a reality.</p><p>We recently published a paper in <em>Journal of Hydrology</em> to commemorate the 50 year anniversary of the original Blueprint paper (Simmons et al., 2019). In this talk, we present an overview of, and highlights from, this paper.</p><p>Through personal communications with Allan Freeze, we present the history and genesis of the Blueprint paper. We reflect on the uptake of the Blueprint into modern hydrology, the development of numerical models that enabled this, and the range of challenges being tackled by these models. Finally, we consider challenges and opportunities for the future of this area of modelling and hydrologic science.</p><p> </p><p><strong>Reference</strong></p><p>Simmons, C.T., Brunner, P., Therrien, R., and Sudicky, E.A., 2019. <em>Commemorating the 50th anniversary of the Freeze and Harlan (1969) Blueprint for a physically-based, digitally-simulated hydrologic response model</em>, Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2019.124309  </p>

A physically-based soil surface model and its combination with numerical models for predicting bare-soil evaporation rates

2021 ◽  
Author(s):  
Xiaocheng Liu ◽  
Chenming Zhang ◽  
Yue Liu ◽  
David Lockington ◽  
Ling Li
Keyword(s):  
Numerical Model ◽  
Surface Resistance ◽  
Numerical Models ◽  
Soil Column ◽  
Soil Surface ◽  
Bare Soil ◽  
Water Vapor Transport ◽  
Surface Model ◽  
Vapor Flow ◽  
Physically Based

<p>Estimation of evaporation rates from soils is significant for environmental, hydrological, and agricultural purposes. Modeling of the soil surface resistance is essential to estimate the evaporation rates from bare soil. Empirical surface resistance models may cause large deviations when applied to different soils. A physically-based soil surface model is developed to calculate the surface resistance, which can consider evaporation on the soil surface when soil is fully saturated and the vapor flow below the soil surface after dry layer forming on the top. Furthermore, this physically-based expression of the surface resistance is added into a numerical model that considers the liquid water transport, water vapor transport, and heat transport during evaporation. The simulation results are in good agreement with the results from six soil column drying experiments.  This numerical model can be applied to predict or estimate the evaporation rate of different soil and saturation at different depths during evaporation.</p>

Multiscale Simulations of Domains in Ferroelectrics

Domain Walls ◽  
2020 ◽  
pp. 311-339
Author(s):  
S. Liu ◽  
I. Grinberg ◽  
A. M. Rappe
Keyword(s):  
Density Functional ◽  
Large Scale ◽  
Mean Field Theory ◽  
Mean Field ◽  
Md Simulations ◽  
Relaxor Ferroelectrics ◽  
Ferroelectric Materials ◽  
Multiscale Simulations ◽  
Challenges And Opportunities ◽  
Physically Based

This chapter focuses on recent studies of ferroelectrics, where large-scale molecular dynamics (MD) simulations using first-principles-based force fields played a central role in revealing important physics inaccessible to direct density functional theory (DFT) calculations but critical for developing physically-based free energy functional for coarse-grained phase-field-type simulations. After reviewing typical atomistic potentials of ferroelectrics for MD simulations, the chapter describes a progressive theoretical framework that combines DFT, MD, and a mean-field theory. It then focuses on relaxor ferroelectrics. By examining the spatial and temporal polarization correlations in prototypical relaxor ferroelectrics with million-atom MD simulations and novel analysis techniques, this chapter shows that the widely accepted model of polar nanoregions embedded in a non-polar matrix is incorrect for Pb-based relaxors. Rather, the unusual properties of theses relaxor ferroelectrics stem from the presence of a multi-domain state with extremely small domain sizes (2–10 nanometers), giving rise to a greater flexibility for polarization rotations and the ultrahigh dielectric and piezoelectric responses. Finally, this chapter discusses the challenges and opportunities for multiscale simulations of ferroelectric materials.

scholarly journals Coupling of structures using frequency response functions

2018 ◽  
Vol 211 ◽  
pp. 06005
Author(s):  
Tiago Silva ◽  
João Pereira
Keyword(s):  
Frequency Response ◽  
Numerical Models ◽  
Complete Response ◽  
Modal Identification ◽  
Response Model ◽  
Response Functions ◽  
Experimental Frequency ◽  
Frequency Response Functions ◽  
Structural Modifications ◽  
Combined Use

In the field of structural dynamics is common to predict the behaviour of a structure regarding structural modifications. In this context, the frequency based substructuring method is well-known to perform structural modifications based on the coupling of structures. This process gives the possibility to perform the study of a structure at the level of its components and then assess the response of the coupled system. In practice, it is impossible to attain an experimental complete response model, although one can simulate all the responses of a structure using numerical models. Hence, the substructuring process can be enhanced by the combined use of experimental and numerical responses, as it was demonstrated using numerically obtained frequency response functions. This work presents the enhancement of the frequency based substructuring method using a method to expand experimental frequency response functions over the entire set of degrees of freedom in a finite element model. This expansion process, known as modified Kidder’s method, considers that if one can only measure translations due to exciting force, it is possible to obtain the complete response model, including the rotational frequency response functions due to exciting moments. The combined use of the frequency based substructuring and the modified Kidder’s methods has several advantages, as it avoids modal identification or residual compensation. To evaluate the performance of the proposed procedure a numerical example of a beam structure is presented, and its results are discussed.

scholarly journals Forecasting Lightning Threat Using Cloud-Resolving Model Simulations

2009 ◽  
Vol 24 (3) ◽  
pp. 709-729 ◽  
Author(s):  
Eugene W. McCaul ◽  
Steven J. Goodman ◽  
Katherine M. LaCasse ◽  
Daniel J. Cecil
Keyword(s):  
Numerical Models ◽  
Wrf Model ◽  
Phase Region ◽  
General Character ◽  
Lightning Flash ◽  
Flash Rate ◽  
Spatial Coverage ◽  
Physically Based ◽  
Cloud Resolving Model ◽  
Near Term

Abstract Two new approaches are proposed and developed for making time- and space-dependent, quantitative short-term forecasts of lightning threats, and a blend of these approaches is devised that capitalizes on the strengths of each. The new methods are distinctive in that they are based entirely on the ice-phase hydrometeor fields generated by regional cloud-resolving numerical simulations, such as those produced by the Weather Research and Forecasting (WRF) model. These methods are justified by established observational evidence linking aspects of the precipitating ice hydrometeor fields to total flash rates. The methods are straightforward and easy to implement, and offer an effective near-term alternative to the incorporation of complex and costly cloud electrification schemes into numerical models. One method is based on upward fluxes of precipitating ice hydrometeors in the mixed-phase region at the −15°C level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domain-wide statistics of the peak values of simulated flash-rate proxy fields against domain-wide peak total lightning flash-rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. The blended solution proposed in this work is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Simulations of selected diverse North Alabama cases show that the WRF can distinguish the general character of most convective events, and that the methods employed herein show promise as a means of generating quantitatively realistic fields of lightning threat. However, because the models tend to have more difficulty in predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single simulations can be in error. Although these model shortcomings presently limit the precision of lightning threat forecasts from individual runs of current generation models, the techniques proposed herein should continue to be applicable as newer and more accurate physically based model versions, physical parameterizations, initialization techniques, and ensembles of forecasts become available.

The contribution of numerical models to our understanding of the Phanerozoic CO2 history

2020 ◽  
Author(s):  
Yves Godderis ◽  
Yannick Donnadieu
Keyword(s):  
Carbon Cycle ◽  
Numerical Models ◽  
Continental Drift ◽  
Ice Age ◽  
Mountain Range ◽  
Climatic Trend ◽  
Carbon Cycle Model ◽  
Physically Based ◽  
Continental Weathering ◽  
The Many

<p>Our understanding of the geological regulation of the carbon cycle has been deeply influenced by the contribution of Bob Berner with his well-known model GEOCARB. Here, we will present a fundamentally different carbon cycle model that explicitly accounts for the effect of the paleogeography using physically based climate simulations and using 22 continental configurations spanning the whole Phanerozoic (GEOCLIM, geoclimmodel.wordpress.com). We will show that several key features of the Phanerozoic climate can be simply explained by the modulation of the carbon cycle by continental drift with the notable exception of the Late Paleozoic Ice Age, which is explained by the intense weathering of the Hercynian mountain range. In particular, the continental drift may have strongly impacted the runoff intensity as well as the weathering flux during the transition from the hot Early Cambrian world to the colder Ordovician world. Another fascinating example is the large atmospheric CO<sub>2</sub> decrease simulated during the Triassic owing to the northward drift of Pangea exposing large continental area to humid sub-tropics and boosting continental weathering. Conversely, our model fails to reproduce the climatic trend of the last 100 Ma. This is due to the highly dispersed continental configurations of the last 100 Ma that optimize the consumption of CO<sub>2</sub> through continental weathering. This discrepancy may be reduced if we account for a larger influence of the Earth degassing flux on the atmospheric CO<sub>2</sub> evolution, which could come from the increase contribution of the pelagic component on the oceanic crust on the global carbonate flux and from the many sub-marine LIPs occurring during the Late Cretaceous.</p><p> </p>

scholarly journals Simulating the influence of snow surface processes on soil moisture dynamics and streamflow generation in an alpine catchment

2017 ◽  
Vol 21 (8) ◽  
pp. 4053-4071 ◽  
Author(s):  
Nander Wever ◽  
Francesco Comola ◽  
Mathias Bavay ◽  
Michael Lehning
Keyword(s):  
Soil Moisture ◽  
Snow Cover ◽  
Soil Water ◽  
Water Flux ◽  
Response Model ◽  
Hydrologic Response ◽  
Model Framework ◽  
Flood Risks ◽  
Soil Water Flux

Abstract. The assessment of flood risks in alpine, snow-covered catchments requires an understanding of the linkage between the snow cover, soil and discharge in the stream network. Here, we apply the comprehensive, distributed model Alpine3D to investigate the role of soil moisture in the predisposition of the Dischma catchment in Switzerland to high flows from rainfall and snowmelt. The recently updated soil module of the physics-based multilayer snow cover model SNOWPACK, which solves the surface energy and mass balance in Alpine3D, is verified against soil moisture measurements at seven sites and various depths inside and in close proximity to the Dischma catchment. Measurements and simulations in such terrain are difficult and consequently, soil moisture was simulated with varying degrees of success. Differences between simulated and measured soil moisture mainly arise from an overestimation of soil freezing and an absence of a groundwater description in the Alpine3D model. Both were found to have an influence in the soil moisture measurements. Using the Alpine3D simulation as the surface scheme for a spatially explicit hydrologic response model using a travel time distribution approach for interflow and baseflow, streamflow simulations were performed for the discharge from the catchment. The streamflow simulations provided a closer agreement with observed streamflow when driving the hydrologic response model with soil water fluxes at 30 cm depth in the Alpine3D model. Performance decreased when using the 2 cm soil water flux, thereby mostly ignoring soil processes. This illustrates that the role of soil moisture is important to take into account when understanding the relationship between both snowpack runoff and rainfall and catchment discharge in high alpine terrain. However, using the soil water flux at 60 cm depth to drive the hydrologic response model also decreased its performance, indicating that an optimal soil depth to include in surface simulations exists and that the runoff dynamics are controlled by only a shallow soil layer. Runoff coefficients (i.e. ratio of rainfall over discharge) based on measurements for high rainfall and snowmelt events were found to be dependent on the simulated initial soil moisture state at the onset of an event, further illustrating the important role of soil moisture for the hydrological processes in the catchment. The runoff coefficients using simulated discharge were found to reproduce this dependency, which shows that the Alpine3D model framework can be successfully applied to assess the predisposition of the catchment to flood risks from both snowmelt and rainfall events.

scholarly journals Short-term forecasting of the chloride content in the mineral waters of the Ustroń Health Resort using SARIMA and Holt-Winters models

2015 ◽  
Vol 3 (4) ◽  
pp. 57-65
Author(s):  
Dominika Dąbrowska ◽  
Marek Sołtysiak ◽  
Jan Waligóra
Keyword(s):  
Water Quality ◽  
Mineral Water ◽  
Numerical Models ◽  
Moving Average ◽  
Forecast Accuracy ◽  
Chloride Content ◽  
Mineral Waters ◽  
Health Resort ◽  
Physically Based ◽  
Short Term Forecasting

Abstract The Ustroń S.A. Health Resort (southern Poland) uses iodide-bromide mineral waters taken from Middle and Upper Devonian limestones and dolomites with a mineralisation range of 110-130 g/dm3 for curative purposes. Two boreholes - U-3 and U3-A drilled in the early 1970s were exploited. The aim of this paper is to estimate changes in mineral water quality of the Ustroń Health Resort by taking into consideration chloride content in the water from the U-3 borehole. The data has included the results of monthly analyses of chlorides from 2005 to 2015 during the tests carried out by the Mining Department of the Health Resort. The triple exponential smoothing (ETS) function and the Seasonal Autoregressive Integrated Moving Average (SARIMA) method of modelling time series were used for the calculations. The ability to properly forecast mineral water quality can result in a good status of the exploitation borehole and a limited number of failures in the exploitation system. Because of the good management of health resorts, it is possible to acquire more satisfied customers. The main goal of the article involves the real-time forecast accuracy, obtained results show that the proposed methods are effective for such situations. Presented methods made it possible to obtain a 24-month point and interval forecast. The results of these analyses indicate that the chloride content is forecast to be in the range of 72 to 83 g/l from 2015 to 2017. While comparing the two methods of analysis, a narrower range of forecast values and, therefore, greater accuracy were obtained for the ETS function. The good performance of the ETS model highlights its utility compared with complicated physically based numerical models.

Stochastic Behavior of Complex Submerged Systems

1995 ◽  
Author(s):  
Mohammed M. Ettouney ◽  
Raymond P. Daddazio ◽  
Najib N. Abboud
Keyword(s):  
Structural Dynamics ◽  
Uncertain Systems ◽  
Numerical Models ◽  
Computational Technique ◽  
Stochastic Behavior ◽  
Acoustic Performance ◽  
Entire Structure ◽  
Internal Structures ◽  
Physically Based ◽  
Total Structure

Abstract Acoustic performance is an important issue in naval applications. The structural dynamics of internal systems strongly effects the acoustic performance of the entire structure. Due to the complexity of the internal structures, it is difficult to construct numerical models of sufficient fidelity to represent the essential physics of the system. Hence the complexity of internal systems essentially introduces uncertainty into the total structure. This paper develops a stochastic computational technique which can account for the uncertainties of the problem using physically based definitions of the governing statistical properties of the uncertain systems.

Sign in / Sign up

Export Citation Format

Share Document