Coping with Information Extraction from In-Situ Data Acquired in Natural Streams DOI Creative Commons
Özlem Baydaroğlu, Marian Muste, Atiye Cikmaz

и другие.

EarthArXiv (California Digital Library), Год журнала: 2024, Номер unknown

Опубликована: Янв. 20, 2024

Flood waves propagating in natural streams are highly complex flow situations with intricate dependencies among variables that still not well understood. The most relevant information for deciphering these is extracted from continuous in-situ measurements acquired through high sampling frequency special attention to the magnitude and timing of hydrograph peaks. new generation acoustic instruments can produce experimental evidence if useful nonlinear, nonstationary signals inherently noisy dataset on site. This study presents a screening protocol smoothen streamflow data unwanted influences noise generated by perturbations observational fluctuations. flexible robust combining quantitative (statistical fitness parameters) qualitative (domain expert judgments) evaluations. tested 18 smoothing methods applied 118 datasets identify optimal conditioning candidates. Sensitivity analyses conducted assess validity, generality, scalability procedures. main goal this analysis set mathematical foundation empirical results lead unified, general conclusions principles or protocols unsteady flows open channels, formulating practical guidance future acquisition processing, using better support numerical data-driven modeling efforts.

Язык: Английский

State-level multidimensional agricultural drought susceptibility and risk assessment for agriculturally prominent areas DOI
S M Samiul Islam, Serhan Yeşilköy, Özlem Baydaroğlu

и другие.

International Journal of River Basin Management, Год журнала: 2024, Номер unknown, С. 1 - 18

Опубликована: Фев. 13, 2024

Given the growing climate variability, quantifying droughts has gained significant importance, particularly in agriculturally concentrated areas such as Iowa. This study presents a novel approach for evaluating risk of agricultural drought, which combines geospatial methods with fuzzy logic algorithm. The integrates diverse array meteorological, physical, and social factors, yielding more comprehensive nuanced understanding impacts drought. covered sector within Corn Belt region Iowa formulated maps illustrating vulnerability drought timeframe spanning from 2015 to 2021. illustrate progress analysis, fully representing spatial temporal dimensions uniqueness this is ascribed its methodological framework, thorough assessment prior research inform assignment weights parameters logic-based index. findings demonstrate notable increase proportion Iowa's land area classified at a'very high' risk, rising 0.66% 5.39% 2018. upward trend suggests an escalating susceptibility conditions. Mid-Iowa western portion state exhibited increased 'high' 'extremely threats during period. accuracy our was validated using Kappa coefficient 75%. indicator potential be utilized context mitigation program monitoring. Moreover, methodology can modified implementation geographical across globe.

Язык: Английский

Процитировано

11
Coping with Information Extraction from In-Situ Data Acquired in Natural Streams DOI Creative Commons
Özlem Baydaroğlu, Marian Muste, Atiye Cikmaz

и другие.

EarthArXiv (California Digital Library), Год журнала: 2024, Номер unknown

Опубликована: Янв. 20, 2024

Flood waves propagating in natural streams are highly complex flow situations with intricate dependencies among variables that still not well understood. The most relevant information for deciphering these is extracted from continuous in-situ measurements acquired through high sampling frequency special attention to the magnitude and timing of hydrograph peaks. new generation acoustic instruments can produce experimental evidence if useful nonlinear, nonstationary signals inherently noisy dataset on site. This study presents a screening protocol smoothen streamflow data unwanted influences noise generated by perturbations observational fluctuations. flexible robust combining quantitative (statistical fitness parameters) qualitative (domain expert judgments) evaluations. tested 18 smoothing methods applied 118 datasets identify optimal conditioning candidates. Sensitivity analyses conducted assess validity, generality, scalability procedures. main goal this analysis set mathematical foundation empirical results lead unified, general conclusions principles or protocols unsteady flows open channels, formulating practical guidance future acquisition processing, using better support numerical data-driven modeling efforts.

Язык: Английский

Процитировано

4