Assessing wet and dry periods using Standardized Precipitation Index Fractal (SPIF) and polygons: A novel approach
| dc.authorid | 0000-0001-9846-8581 | |
| dc.contributor.author | Şen, Zekâi | |
| dc.date.accessioned | 2024-03-08T06:48:33Z | |
| dc.date.available | 2024-03-08T06:48:33Z | |
| dc.date.issued | 2024 | |
| dc.department | İstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, İnşaat Mühendisliği Bölümü | |
| dc.description.abstract | In the open literature, there are numerous studies on the normal and extreme (flood and drought) behavior of wet and dry periods based on the understanding of the standard precipitation index (SPI), which provides a series of categorizations by considering the standard normal (Gaussian) probability distribution function (PDF). The numerical meaning of each categorization assessment is quite lacking in terms of future predictions of wet and dry period duration based on historical records. This paper presents a new approach for calculating possible formations of future wet and dry period durations based on historical records through an effective fractal geometric forecasting approach. The essence of the proposed methodology is based on the number of dry periods (steps) of non-overlapping monthly duration along consecutive broken line paths in the SPI classification for wet and dry period durations. It has been observed that the plot of periods on double logarithmic paper falls along a straight line against the number of such periods, implying a power function, which is the essence of fractal geometry. Extending the empirically derived straight line provides the number of periods that may occur in the future over a range of SPI levels. This methodology is referred to as SPI fractal (SPIF), and the classic SPI classification is converted into SPIF wet and dry polygons, which provide additional information about the drought period number within a valid polygonal area, compared to the classic SPI results. The wet and dry period features of any hydro-meteorology time series are constrained in SPIF polygons. The application of the methodology was carried out on monthly rainfall records on the European side of the Istanbul Florya meteorological station in Turkey. | |
| dc.identifier.citation | Şen, Z. (2024). Assessing wet and dry periods using Standardized Precipitation Index Fractal (SPIF) and polygons: A novel approach. Water (Switzerland), 16(4). https://dx.doi.org/10.3390/w16040592 | |
| dc.identifier.doi | 10.3390/w16040592 | |
| dc.identifier.issn | 2073-4441 | |
| dc.identifier.issue | 4 | |
| dc.identifier.scopus | 2-s2.0-85185556545 | |
| dc.identifier.scopusquality | Q1 | |
| dc.identifier.uri | https://dx.doi.org/10.3390/w16040592 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12511/12347 | |
| dc.identifier.volume | 16 | |
| dc.identifier.wos | 001172674800001 | en_US |
| dc.identifier.wosquality | Q2 | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.institutionauthor | Şen, Zekâi | |
| dc.language.iso | en | |
| dc.publisher | Multidisciplinary Digital Publishing Institute (MDPI) | |
| dc.relation.ispartof | Water (Switzerland) | en_US |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.rights | Attribution 4.0 International | * |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | * |
| dc.subject | Double Logarithm | |
| dc.subject | Dry | |
| dc.subject | Fractal | |
| dc.subject | Gauss | |
| dc.subject | Probability | |
| dc.subject | Standard Precipitation Index | |
| dc.subject | Wet | |
| dc.title | Assessing wet and dry periods using Standardized Precipitation Index Fractal (SPIF) and polygons: A novel approach | |
| dc.type | Article |
