scholarly journals Using Sensor Data to Dynamically Map Large‐Scale Models to Site‐Scale Forecasts: A Case Study Using the National Water Model

2018 ◽  
Vol 54 (8) ◽  
pp. 5636-5653
Author(s):  
Kevin J. Fries ◽  
Branko Kerkez
Keyword(s):  
Large Scale ◽  
Sensor Data ◽  
Water Model ◽  
Scale Models ◽  
National Water

scholarly journals Evaluation of drought propagation in an ensemble mean of large-scale hydrological models

2012 ◽  
Vol 9 (7) ◽  
pp. 8375-8424 ◽  
Author(s):  
A. F. Van Loon ◽  
M. H. J. Van Huijgevoort ◽  
H. A. J. Van Lanen
Keyword(s):  
Large Scale ◽  
Dry Season ◽  
Hydrological Drought ◽  
Hydrological Models ◽  
Drought Characteristics ◽  
Snow Season ◽  
Scale Models ◽  
Ensemble Mean ◽  
Semi Arid

Abstract. Hydrological drought is increasingly studied using large-scale models. It is, however, not sure whether large-scale models reproduce the development of hydrological drought correctly. The pressing question is: how well do large-scale models simulate the propagation from meteorological to hydrological drought? To answer this question, we evaluated the simulation of drought propagation in an ensemble mean of ten large-scale models, both land-surface models and global hydrological models, that were part of the model intercomparison project of WATCH (WaterMIP). For a selection of case study areas, we studied drought characteristics (number of droughts, duration, severity), drought propagation features (pooling, attenuation, lag, lengthening), and hydrological drought typology (classical rainfall deficit drought, rain-to-snow-season drought, wet-to-dry-season drought, cold snow season drought, warm snow season drought, composite drought). Drought characteristics simulated by large-scale models clearly reflected drought propagation, i.e. drought events became less and longer when moving through the hydrological cycle. However, more differentiation was expected between fast and slowly responding systems, with slowly responding systems having less and longer droughts in runoff than fast responding systems. This was not found using large-scale models. Drought propagation features were poorly reproduced by the large-scale models, because runoff reacted immediately to precipitation, in all case study areas. This fast reaction to precipitation, even in cold climates in winter and in semi-arid climates in summer, also greatly influenced the hydrological drought typology as identified by the large-scale models. In general, the large-scale models had the correct representation of drought types, but the percentages of occurrence had some important mismatches, e.g. an overestimation of classical rainfall deficit droughts, and an underestimation of wet-to-dry-season droughts and snow-related droughts. Furthermore, almost no composite droughts were simulated for slowly responding areas, while many multi-year drought events were expected in these systems. We conclude that drought propagation processes are reasonably well reproduced by the ensemble mean of large-scale models in contrasting catchments in Europe and that some challenges remain in catchments with cold and semi-arid climates and catchments with large storage in aquifers or lakes. Improvement of drought simulation in large-scale models should focus on a better representation of hydrological processes that are important for drought development, such as evapotranspiration, snow accumulation and melt, and especially storage. Besides the more explicit inclusion of storage (e.g. aquifers) in large-scale models, also parametrisation of storage processes requires attention, for example through a global scale dataset on aquifer characteristics.

scholarly journals OntCheck: An Ontology-Driven Static Correctness Checking Tool for Component-Based Models

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Xi Lin ◽  
Hehua Zhang ◽  
Ming Gu
Keyword(s):  
Large Scale ◽  
Description Logic ◽  
Early Stage ◽  
Semantic Knowledge ◽  
Unified Framework ◽  
Domain Specific ◽  
Scale Models ◽  
Correctness Checking ◽  
Static Checking

Component-based models are widely used for embedded systems. The models consist of components with input and output ports linked to each other. However, mismatched links or assumptions among components may cause many failures, especially for large scale models. Binding semantic knowledge into models can enable domain-specific checking and help expose modeling errors in the early stage. Ontology is known as the formalization of semantic knowledge. In this paper we propose an ontology-driven tool for static correctness checking of domain-specific errors. two kinds of important static checking, semantic type and domain-restrcted rules, are fulfilled in a unified framework. We first propose a formal way to precisely describe the checking requirements by ontology and then separately check them by a lattice-based constraint solver and a description logic reasoner. Compared with other static checking methods, the ontology-based method we proposed is model-externally configurable and thus flexible and adaptable to the changes of requirements. The case study demonstrates the effectiveness of our method.

scholarly journals Evaluation of drought propagation in an ensemble mean of large-scale hydrological models

2012 ◽  
Vol 16 (11) ◽  
pp. 4057-4078 ◽  
Author(s):  
A. F. Van Loon ◽  
M. H. J. Van Huijgevoort ◽  
H. A. J. Van Lanen
Keyword(s):  
Large Scale ◽  
Dry Season ◽  
Hydrological Drought ◽  
Hydrological Models ◽  
Drought Characteristics ◽  
Snow Season ◽  
Scale Models ◽  
Ensemble Mean ◽  
Semi Arid

Abstract. Hydrological drought is increasingly studied using large-scale models. It is, however, not sure whether large-scale models reproduce the development of hydrological drought correctly. The pressing question is how well do large-scale models simulate the propagation from meteorological to hydrological drought? To answer this question, we evaluated the simulation of drought propagation in an ensemble mean of ten large-scale models, both land-surface models and global hydrological models, that participated in the model intercomparison project of WATCH (WaterMIP). For a selection of case study areas, we studied drought characteristics (number of droughts, duration, severity), drought propagation features (pooling, attenuation, lag, lengthening), and hydrological drought typology (classical rainfall deficit drought, rain-to-snow-season drought, wet-to-dry-season drought, cold snow season drought, warm snow season drought, composite drought). Drought characteristics simulated by large-scale models clearly reflected drought propagation; i.e. drought events became fewer and longer when moving through the hydrological cycle. However, more differentiation was expected between fast and slowly responding systems, with slowly responding systems having fewer and longer droughts in runoff than fast responding systems. This was not found using large-scale models. Drought propagation features were poorly reproduced by the large-scale models, because runoff reacted immediately to precipitation, in all case study areas. This fast reaction to precipitation, even in cold climates in winter and in semi-arid climates in summer, also greatly influenced the hydrological drought typology as identified by the large-scale models. In general, the large-scale models had the correct representation of drought types, but the percentages of occurrence had some important mismatches, e.g. an overestimation of classical rainfall deficit droughts, and an underestimation of wet-to-dry-season droughts and snow-related droughts. Furthermore, almost no composite droughts were simulated for slowly responding areas, while many multi-year drought events were expected in these systems. We conclude that most drought propagation processes are reasonably well reproduced by the ensemble mean of large-scale models in contrasting catchments in Europe. Challenges, however, remain in catchments with cold and semi-arid climates and catchments with large storage in aquifers or lakes. This leads to a high uncertainty in hydrological drought simulation at large scales. Improvement of drought simulation in large-scale models should focus on a better representation of hydrological processes that are important for drought development, such as evapotranspiration, snow accumulation and melt, and especially storage. Besides the more explicit inclusion of storage in large-scale models, also parametrisation of storage processes requires attention, for example through a global-scale dataset on aquifer characteristics, improved large-scale datasets on other land characteristics (e.g. soils, land cover), and calibration/evaluation of the models against observations of storage (e.g. in snow, groundwater).

scholarly journals Leishmaniasis and Climate Change—Case Study: Argentina

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Oscar Daniel Salomón ◽  
María Gabriela Quintana ◽  
Andrea Verónica Mastrángelo ◽  
María Soledad Fernández
Keyword(s):  
Public Health ◽  
Climate Change ◽  
Large Scale ◽  
Local Level ◽  
Point Of View ◽  
Mitigation Strategies ◽  
Vector Borne Diseases ◽  
Scale Models ◽  
Vector Borne

Vector-borne diseases closely associated with the environment, such as leishmaniases, have been a usual argument about the deleterious impact of climate change on public health. From the biological point of view interaction of different variables has different and even conflicting effects on the survival of vectors and the probability transmission of pathogens. The results on ecoepidemiology of leishmaniasis in Argentina related to climate variables at different scales of space and time are presented. These studies showed that the changes in transmission due to change or increase in frequency and intensity of climatic instability were expressed through changes in the probability of vector-human reservoir effective contacts. These changes of contact in turn are modulated by both direct effects on the biology and ecology of the organisms involved, as by perceptions and changes in the behavior of the human communities at risk. Therefore, from the perspective of public health and state policy, and taking into account the current nonlinear increased velocity of climate change, we concluded that discussing the uncertainties of large-scale models will have lower impact than to develop-validate mitigation strategies to be operative at local level, and compatibles with sustainable development, conservation biodiversity, and respect for cultural diversity.

scholarly journals The Earth Model Column Collaboratory (EMC<sup>2</sup>) v1.1: An Open-Source Ground-Based Lidar and Radar Instrument Simulator and Subcolumn Generator for Large-Scale Models

2021 ◽  
Author(s):  
Israel Silber ◽  
Robert C. Jackson ◽  
Ann M. Fridlind ◽  
Andrew S. Ackerman ◽  
Scott Collis ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Climate Models ◽  
Earth Model ◽  
Model Output ◽  
The Earth ◽  
Scale Models ◽  
Flexible Framework ◽  
Ground Based Lidar

Abstract. Climate models are essential for our comprehensive understanding of Earth's atmosphere and can provide critical insights on future changes decades ahead. Because of these critical roles, today's climate models are continuously being developed and evaluated using constraining observations and measurements obtained by satellites, airborne, and ground-based instruments. Instrument simulators can provide a bridge between the measured or retrieved quantities and their sampling in models and field observations while considering instrument sensitivity limitations. Here we present the Earth Model Column Collaboratory (EMC2), an open-source ground-based lidar and radar instrument simulator and subcolumn generator, specifically designed for large-scale models, in particular climate models, but also applicable to high-resolution model output. EMC2 provides a flexible framework enabling direct comparison of model output with ground-based observations, including generation of subcolumns that may statistically represent finer model spatial resolutions. In addition, EMC2 emulates ground-based (and air- or space-borne) measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. The simulator uses either single particle or bulk particle size distribution lookup tables, depending on the selected scheme approach, to perform the forward calculations. To facilitate model evaluation, EMC2 also includes three hydrometeor classification methods, namely, radar- and sounding-based cloud and precipitation detection and classification, lidar-based phase classification, and a Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) lidar simulator emulator. The software is written in Python, is easy to use, and can be straightforwardly customized for different models, radars and lidars. Following the description of the logic, functionality, features, and software structure of EMC2, we present a case study of highly supercooled mixed-phase cloud based on measurements from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE). We compare observations with the application of EMC2 to outputs from four configurations of the NASA Goddard Institute for Space Studies (GISS) climate model (ModelE3) in single-column model (SCM) mode and from a large-eddy simulation (LES) model. We show that two of the four ModelE3 configurations can form and maintain highly supercooled precipitating cloud for several hours, consistent with observations and LES. While our focus is on one of these ModelE3 configurations, which performed slightly better in this case study, both of these configurations and the LES results post-processed with EMC2 generally provide reasonable agreement with observed lidar and radar variables. As briefly demonstrated here, EMC2 can provide a lightweight and flexible framework for comparing the results of both large-scale and high-resolution models directly with observations, with relatively little overhead and multiple options for achieving consistency with model microphysical or radiation scheme physics.

Evaluating Baseflow Simulation in the National Water Model: A Case Study in the Northern High Plains Region, USA

2021 ◽  
Vol 57 (2) ◽  
pp. 267-280 ◽  
Author(s):  
Ritesh Karki ◽  
Joseph M. Krienert ◽  
Minki Hong ◽  
David R. Steward
Keyword(s):  
Water Model ◽  
High Plains ◽  
National Water

scholarly journals Calibration and uncertainty issues of a hydrological model (SWAT) applied to West Africa

2006 ◽  
Vol 9 ◽  
pp. 137-143 ◽  
Author(s):  
J. Schuol ◽  
K. C. Abbaspour
Keyword(s):  
West Africa ◽  
Model Calibration ◽  
Large Scale ◽  
Assessment Tool ◽  
Hydrological Models ◽  
Scale Models ◽  
Distributed Hydrological Models ◽  
Water Assessment ◽  
River Niger

Abstract. Distributed hydrological models like SWAT (Soil and Water Assessment Tool) are often highly over-parameterized, making parameter specification and parameter estimation inevitable steps in model calibration. Manual calibration is almost infeasible due to the complexity of large-scale models with many objectives. Therefore we used a multi-site semi-automated inverse modelling routine (SUFI-2) for calibration and uncertainty analysis. Nevertheless, the question of when a model is sufficiently calibrated remains open, and requires a project dependent definition. Due to the non-uniqueness of effective parameter sets, parameter calibration and prediction uncertainty of a model are intimately related. We address some calibration and uncertainty issues using SWAT to model a four million km2 area in West Africa, including mainly the basins of the river Niger, Volta and Senegal. This model is a case study in a larger project with the goal of quantifying the amount of global country-based available freshwater. Annual and monthly simulations with the "calibrated" model for West Africa show promising results in respect of the freshwater quantification but also point out the importance of evaluating the conceptual model uncertainty as well as the parameter uncertainty.

scholarly journals PERFORMANCE INVESTIGATION OF A HANDHELD 3D SCANNER TO DEFINE GOOD PRACTICES FOR SMALL ARTEFACT 3D MODELING

2017 ◽  
Vol XLII-2/W5 ◽  
pp. 427-434 ◽  
Author(s):  
E. Lachat ◽  
T. Landes ◽  
P. Grussenmeyer
Keyword(s):  
Large Scale ◽  
Accuracy Assessment ◽  
Specific Treatment ◽  
Point Clouds ◽  
Practical Case ◽  
3D Scanner ◽  
Scale Models ◽  
3D Scanners ◽  
Handheld Scanner

Handheld 3D scanners can be used to complete large scale models with the acquisition of occluded areas or small artefacts. This may be of interest for digitization projects in the field of Cultural Heritage, where detailed areas may require a specific treatment. Such sensors present the advantage of being easily portable in the field, and easily usable even without particular knowledge. In this paper, the Freestyle<sup>3D</sup> handheld scanner launched on the market in 2015 by FARO is investigated. Different experiments are described, covering various topics such as the influence of range or color on the measurements, but also the precision achieved for geometrical primitive digitization. These laboratory experiments are completed by acquisitions performed on engraved and sculpted stone blocks. This practical case study is useful to investigate which acquisition protocol seems to be the more adapted and leads to precise results. The produced point clouds will be compared to photogrammetric surveys for the purpose of their accuracy assessment.

Predictive Usage Mining for Sustainability of Complex Systems Design

2014 ◽  
Author(s):  
Jungmok Ma ◽  
Harrison M. Kim
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Systems Design ◽  
Sensor Data ◽  
Period Analysis ◽  
Dynamic Lca ◽  
Segmentation Analysis ◽  
Usage Patterns ◽  
New Perspective

A new perspective of dynamic LCA (life cycle assessment) is proposed with the predictive usage mining for sustainability (PUMS) algorithm. By defining usage patterns as trend, seasonality, and level from a time series of usage information, predictive LCA can be conducted in a real time horizon. Large-scale sensor data of product operation is analyzed in order to mine usage patterns and build a usage model for LCA. The PUMS algorithm consists of handling missing and abnormal values, seasonal period analysis, segmentation analysis, time series analysis, and predictive LCA. A newly developed segmentation algorithm can distinguish low activity periods and help to capture patterns more clearly. Furthermore, a predictive LCA method is formulated using a time series usage model. Finally, generated data is used to do predictive LCA of agricultural machinery as a case study.

A Family With Autosomal-Dominant Progressive Sensorineural Hearing Loss

1996 ◽  
Vol 5 (1) ◽  
pp. 23-32 ◽  
Author(s):  
Chris Halpin ◽  
Barbara Herrmann ◽  
Margaret Whearty
Keyword(s):  
Speech Production ◽  
Hearing Aids ◽  
Role Models ◽  
Speech Intelligibility ◽  
Large Scale ◽  
Speech Language Pathology ◽  
The Family ◽  
Patient Will ◽  
Language Pathology

The family described in this article provides an unusual opportunity to relate findings from genetic, histological, electrophysiological, psychophysical, and rehabilitative investigation. Although the total number evaluated is large (49), the known, living affected population is smaller (14), and these are spread from age 20 to age 59. As a result, the findings described above are those of a large-scale case study. Clearly, more data will be available through longitudinal study of the individuals documented in the course of this investigation but, given the slow nature of the progression in this disease, such studies will be undertaken after an interval of several years. The general picture presented to the audiologist who must rehabilitate these cases is that of a progressive cochlear degeneration that affects only thresholds at first, and then rapidly diminishes speech intelligibility. The expected result is that, after normal language development, the patient may accept hearing aids well, encouraged by the support of the family. Performance and satisfaction with the hearing aids is good, until the onset of the speech intelligibility loss, at which time the patient will encounter serious difficulties and may reject hearing aids as unhelpful. As the histological and electrophysiological results indicate, however, the eighth nerve remains viable, especially in the younger affected members, and success with cochlear implantation may be expected. Audiologic counseling efforts are aided by the presence of role models and support from the other affected members of the family. Speech-language pathology services were not considered important by the members of this family since their speech production developed normally and has remained very good. Self-correction of speech was supported by hearing aids and cochlear implants (Case 5’s speech production was documented in Perkell, Lane, Svirsky, & Webster, 1992). These patients received genetic counseling and, due to the high penetrance of the disease, exhibited serious concerns regarding future generations and the hope of a cure.

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