scholarly journals Spatiotemporal geostatistical analysis of precipitation combining ground and satellite observations

2021 ◽  
Author(s):  
Emmanouil A. Varouchakis ◽  
Dionissios T. Hristopulos ◽  
George P. Karatzas ◽  
Gerald A. Corzo Perez ◽  
Vitali Diaz
Keyword(s):  
Satellite Images ◽  
Geostatistical Analysis ◽  
Reference Period ◽  
Precipitation Data ◽  
Regression Kriging ◽  
Infrared Observation ◽  
Spatiotemporal Mapping ◽  
Time Period ◽  
Retrieval Algorithms

Abstract Precipitation data are useful for the management of water resources as well as flood and drought events. However, precipitation monitoring is sparse and often unreliable in regions with complicated geomorphology. Subsequently, the spatial variability of the precipitation distribution is frequently represented incorrectly. Satellite precipitation data provide an attractive supplement to ground observations. However, satellite data involve errors due to the complexity of the retrieval algorithms and/or the presence of obstacles that affect the infrared observation capability. This work presents a methodology that combines satellite and ground observations leading to improved spatiotemporal mapping and analysis of precipitation. The applied methodology is based on space–time regression kriging. The case study is referred to the island of Crete, Greece, for the time period of 2010–2018. Precipitation data from 53 stations are used in combination with satellite images for the reference period. This work introduces an improved spatiotemporal approach for precipitation mapping.

scholarly journals Constructing Damage Indices Based on Publicly Available Spatial Data: Exemplified by Earthquakes and Volcanic Eruptions in Indonesia

2021 ◽  
Author(s):  
Emmanuel Skoufias ◽  
Eric Strobl ◽  
Thomas Tveit
Keyword(s):  
Spatial Data ◽  
Volcanic Ash ◽  
Satellite Images ◽  
Fragility Curves ◽  
Volcanic Eruptions ◽  
Damage Indices ◽  
Damage Indicator ◽  
Time Period ◽  
Peak Ground Motion

AbstractThis article demonstrates the construction of earthquake and volcano damage indices using publicly available remote sensing sources and data on the physical characteristics of events. For earthquakes we use peak ground motion maps in conjunction with building type fragility curves to construct a local damage indicator. For volcanoes we employ volcanic ash data as a proxy for local damages. Both indices are then spatially aggregated by taking local economic exposure into account by assessing nightlight intensity derived from satellite images. We demonstrate the use of these indices with a case study of Indonesia, a country frequently exposed to earthquakes and volcanic eruptions. The results show that the indices capture the areas with the highest damage, and we provide overviews of the modeled aggregated damage for all provinces and districts in Indonesia for the time period 2004 to 2014. The indices were constructed using a combination of software programs—ArcGIS/Python, Matlab, and Stata. We also outline what potential freeware alternatives exist. Finally, for each index we highlight the assumptions and limitations that a potential practitioner needs to be aware of.

scholarly journals Estudo de Caso: Análise Sinótica de um Evento Extremo de Precipitação Ocorrida no Estado de Pernambuco entre os dias 17 A 19 de Junho de 2010 (Case Study: Synoptic Analysis of an Extreme Event of Precipitation in the Pernambuco State between ...)

2013 ◽  
Vol 6 (1) ◽  
pp. 066 ◽  
Author(s):  
Giordani Rafael Sodré
Keyword(s):  
Data Collection ◽  
Satellite Images ◽  
Meteorological Parameters ◽  
Weather Forecasting ◽  
Extreme Event ◽  
Reanalysis Data ◽  
Northeast Brazil ◽  
Precipitation Data ◽  
Climate Studies

Utilizando parâmetros meteorológicos na investigação da atuação dos mecanismos atmosféricos moduladores da precipitação no período de inverno sobre o Nordeste Brasileiro (NEB), e caracterizar qual fenômeno modulou aprecipitação intensa ocorrida entre os dias 17/06/2010 e 19/06/2010 por meio de dados de reanálise do NCEP/NCAR, dados de precipitação da Plataforma de Coleta de Dados (PCD’s), do Instituto Nacional deMeteorologia (INMET) e imagens de satélite do Centro de Previsão de Tempo e Estudos Climáticos do Instituto Nacional de Pesquisas Espaciais (CPTEC/INPE). Observou-se através dos campos gerados pelo software Grads, as características atmosféricas propícias ao favorecimento da convecção sobre o NEB no mês de junho e em específico nos dias 17, 18 e 19 de junho onde foram registrados os valores mais elevados de precipitação, foi realizado o diagnóstico dos sistemas sinóticos atuantes nos três dias, em estudo, caracterizando as perturbações vindas de leste como o sistema responsável pela formação do complexo convectivo que atuou sobre o estado de Pernambuco. AbstractThe use of meteorological parameters is important to investigate its function on the atmospheric modulators mechanisms of precipitation during the winter over the Northeast Brazil (NEB). This study aimed to characterize the phenomena which modulates the intense precipitation occurred between the days 17 to 19/06/2010 through the reanalysis data of NCEP / NCAR precipitation data of the Platform for Data Collection (PCDs), the National Institutes of Meteorology (INMET) and satellite images of the Center for Weather Forecasting and Climate Studies, National Institute for Space Research (CPTEC / INPE). It was observed, through the fields generated by the software Grads, that the atmospheric characteristics that permit the convection over the NEB in June and, in particular, on days 17, 18 and 19 June when was we registered the highest values of precipitation, when the diagnosis of synoptic systems operating in three days was performed; itcharacterized the disturbances coming from the east, as the system responsible for the formation of convective complex that occurred on the State of Pernambuco.

scholarly journals The reasons women choose and stay in a geology major: a qualitative multi-case analysis

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Ron E. Gray ◽  
Alexis T. Riche ◽  
Isabel J. Shinnick-Gordon ◽  
James C. Sample
Keyword(s):  
Role Models ◽  
Critical Incident ◽  
Earth Science ◽  
Time Period ◽  
The Usa ◽  
Data Source ◽  
Introductory Classes ◽  
Iterative Coding ◽  
As Relationship

AbstractDespite earning half of all science and engineering undergraduate degrees between 2007 and 2016 in the USA, women were awarded only 39% of earth science degrees in the same time period. In order to better understand why women are both choosing and staying in geology programs, we conducted a multi-case study of nine current female undergraduate geology majors at a large public university in the USA within a department that is at gender parity among its undergraduate majors. The main data source was audio-recorded critical incident interviews of each participant. Data from the interviews were analyzed through an iterative coding process using codes adapted from previous studies that focused on factors both internal and external to the department. The students said that personal interests, influence by others outside of the department, and introductory classes attracted them to the geology program, but once declared, departmental factors such as relationship with faculty caused them to stay. We also found an emphasis on female role models, especially those teaching introductory courses. We believe this study offers important insights into the ways in which factors leading to recruitment and retention play out in the lived experiences of female geology majors.

scholarly journals Application of a Novel Hybrid Method for Flood Susceptibility Mapping with Satellite Images: A Case Study of Seoul, Korea

2021 ◽  
Vol 13 (14) ◽  
pp. 2786
Author(s):  
Roya Narimani ◽  
Changhyun Jun ◽  
Saqib Shahzad ◽  
Jeill Oh ◽  
Kyoohong Park
Keyword(s):  
High Risk ◽  
Hybrid Method ◽  
Satellite Images ◽  
Controlling Factors ◽  
Susceptibility Mapping ◽  
Low Risk ◽  
Flood Susceptibility ◽  
Flood Susceptibility Mapping ◽  
Flood Maps

This paper proposes a novel hybrid method for flood susceptibility mapping using a geographic information system (ArcGIS) and satellite images based on the analytical hierarchy process (AHP). Here, the following nine multisource environmental controlling factors influencing flood susceptibility were considered for relative weight estimation in AHP: elevation, land use, slope, topographic wetness index, curvature, river distance, flow accumulation, drainage density, and rainfall. The weight for each factor was determined from AHP and analyzed to investigate critical regions that are more vulnerable to floods using the overlay weighted sum technique to integrate the nine layers. As a case study, the ArcGIS-based framework was applied in Seoul to obtain a flood susceptibility map, which was categorized into six regions (very high risk, high risk, medium risk, low risk, very low risk, and out of risk). Finally, the flood map was verified using real flood maps from the previous five years to test the model’s effectiveness. The flood map indicated that 40% of the area shows high flood risk and thus requires urgent attention, which was confirmed by the validation results. Planners and regulatory bodies can use flood maps to control and mitigate flood incidents along rivers. Even though the methodology used in this study is simple, it has a high level of accuracy and can be applied for flood mapping in most regions where the required datasets are available. This is the first study to apply high-resolution basic maps (12.5 m) to extract the nine controlling factors using only satellite images and ArcGIS to produce a suitable flood map in Seoul for better management in the near future.

Improving Operational Efficiency Using Automated Time Analysis for Multi-Well Pad Fracturing

2021 ◽  
Author(s):  
Fahd Siddiqui ◽  
Mohammadreza Kamyab ◽  
Michael Lowder
Keyword(s):  
Real Time ◽  
Operational Efficiency ◽  
Permian Basin ◽  
Potential Cost ◽  
Time Period ◽  
Cloud Server ◽  
The Us ◽  
Single Well ◽  
Complete Automation

Abstract The economic success of unconventional reservoirs relies on driving down completion costs. Manually measuring the operational efficiency for a multi-well pad can be error-prone and time-prohibitive. Complete automation of this analysis can provide an effortless real-time insight to completion engineers. This study presents a real-time method for measuring the time spent on each completion activity, thereby enabling the identification and potential cost reduction avenues. Two data acquisition boxes are utilized at the completion site to transmit both the fracturing and wireline data in real-time to a cloud server. A data processing algorithm is described to determine the start and end of these two operations for each stage of every well on the pad. The described method then determines other activity intervals (fracturing swap-over, wireline swap-over, and waiting on offset wells) based on the relationship between the fracturing and wireline segments of all the wells. The processed data results can be viewed in real-time on mobile or computers connected to the cloud. Viewing the full operational time log in real-time helps engineers analyze the whole operation and determine key performance indicators (KPIs) such as the number of fractured stages per day, pumping percentage, average fracture, and wireline swap-over durations for a given time period. In addition, the performance of the day and night crews can be evaluated. By plotting a comparison of KPIs for wireline and fracturing times, trends can be readily identified for improving operational efficiency. Practices from best-performing stages can be adopted to reduce non-pumping times. This helps operators save time and money to optimize for more efficient operations. As the number of wells increases, the complexity of manual generation of time-log increases. The presented method can handle multi-well fracturing and wireline operations without such difficulty and in real-time. A case study is also presented, where an operator in the US Permian basin used this method in real-time to view and optimize zipper operations. Analysis indicated that the time spent on the swap over activities could be reduced. This operator set a realistic goal of reducing 10 minutes per swap-over interval. Within one pad, the goal was reached utilizing this method, resulting in reducing 15 hours from the total pad time. The presented method provides an automated overview of fracturing operations. Based on the analysis, timely decisions can be made to reduce operational costs. Moreover, because this method is automated, it is not limited to single well operations but can handle multi-well pad completion designs that are commonplace in unconventionals.

scholarly journals Evaluation of Integrated Assessment Model hindcast experiments: A case study of the GCAM 3.0 land use module

2017 ◽  
Author(s):  
Abigail C. Snyder ◽  
Robert P. Link ◽  
Katherine V. Calvin
Keyword(s):  
Integrated Assessment ◽  
Structural Changes ◽  
Spatial Scales ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Land Allocation ◽  
Time Period ◽  
Skill Scores ◽  
Performance Benchmarks

Abstract. Hindcasting experiments (conducting a model forecast for a time period in which observational data is available) are rarely undertaken in the Integrated Assessment Model (IAM) community. When they are undertaken, the results are often evaluated using global aggregates or otherwise highly aggregated skill scores that mask deficiencies. We select a set of deviation based measures that can be applied at different spatial scales (regional versus global) to make evaluating the large number of variable-region combinations in IAMs more tractable. We also identify performance benchmarks for these measures, based on the statistics of the observational dataset, that allow a model to be evaluated in absolute terms rather than relative to the performance of other models at similar tasks. This is key in the integrated assessment community, where there often are not multiple models conducting hindcast experiments to allow for model intercomparison. The performance benchmarks serve a second purpose, providing information about the reasons a model may perform poorly on a given measure and therefore identifying opportunities for improvement. As a case study, the measures are applied to the results of a past hindcast experiment focusing on land allocation in the Global Change Assessment Model (GCAM) version 3.0. We find quantitative evidence that global aggregates alone are not sufficient for evaluating IAMs, such as GCAM, that require global supply to equal global demand at each time period. Additionally, the deviation measures examined in this work successfully identity parametric and structural changes that may improve land allocation decisions in GCAM. Future work will involve implementing the suggested improvements to the GCAM land allocation system identified by the measures in this work, using the measures to quantify performance improvement due to these changes, and, ideally, applying these measures to other sectors of GCAM and other land allocation models.

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