3 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 3 / 3
Yayın Advanced drought analysis using a novel copula-based multivariate index: a case study of the Ceyhan River Basin(Springer Science and Business Media Deutschland GmbH, 2025-02) Terzi, Tolga Barış; Önöz, BihratDrought is a severe natural disaster that poses significant risks to both social and ecological systems. Detecting drought is challenging due to its gradual development, which makes it difficult to identify and predict, often resulting in significant impacts on the affected regions. Therefore, accurate and dependable monitoring of drought conditions is essential for the development and implementation of effective mitigation strategies. Drought indices play a crucial role in monitoring drought conditions, with single-variable indices commonly employed in the literature to evaluate drought severity. While these indices are typically effective at characterizing the specific type of drought for which they were designed, they often fall short in offering a comprehensive view of overall drought conditions. The multivariate standardized drought index (MSDI) is a comprehensive tool that assesses drought conditions by integrating multiple hydrometeorological variables. Widely employed in the literature in both parametric and empirical forms, the MSDI is recognized for its effectiveness in detecting drought in an integrated manner. This study focuses on a particular challenge related to the calculation of MSDI using copula families. The novel methodology introduced in this paper involves selecting the most suitable copula family for each data subset using AIC and BIC criteria. Rather than applying a single copula family to the entire dataset, this approach utilizes multiple copula families for different subsets, thereby ensuring optimal modeling for each distinct group of data. The Ceyhan River Basin (CRB) is used as a case study to apply the proposed methodology. The drought characteristics of the basin are analyzed using both the newly developed MSDI and conventional single-variable indices, and the performance of the new methodology is evaluated. The application of this approach in the CRB demonstrated its effectiveness in identifying both concurrent and isolated occurrences of meteorological and hydrological droughts, thereby facilitating a more integrated and precise assessment of drought characteristics. Results indicated that the proposed MSDI detected drought events that were overlooked by single-variable indices and improved classification accuracy over the conventional MSDI.Yayın Drought analysis in the Seyhan River Basin based on standardized drought indices using a new approach considering seasonality(Springer Science and Business Media Deutschland GmbH, 2025-01) Terzi, Tolga Barış; Önöz, BihratDrought is a significant natural disaster with adverse effects on both social and ecological systems. Unlike other natural disasters, drought develops slowly and gradually, complicating its early detection and often resulting in severe impacts on affected regions. Consequently, accurate and dependable drought monitoring is essential for devising effective mitigation strategies. Standardized drought indices are vital tools in drought monitoring, providing a means to quantify and characterize drought events. Most standardized drought indices utilize the Standardized Precipitation Index (SPI) method, which is valued for its simplicity and flexibility. However, this study contends that the SPI method lacks several critical elements, particularly in practice, such as determining the most suitable probability distribution for hydrometeorological variables. Therefore, this study proposes a novel methodology for calculating standardized drought indices and assesses its performance against conventional and nonparametric standardized indices, employing various methods capable of capturing complex dependencies. The novel methodology involves identifying the best-fit probability distributions for each data group through various goodness-of-fit tests. This approach ensures that each group is modeled optimally, considering the seasonal variations inherent to each group. The Seyhan River Basin has been chosen as a case study for the proposed methodology. The drought characteristics of the basin are analyzed using indices derived from the new methodology, the conventional SPI method, and the nonparametric method. Additionally, trend analyses were performed on the calculated indices to identify any directional changes in drought patterns within the Seyhan River Basin. The performance of the proposed methodology was evaluated by analyzing its relationship with nonparametric standardized indices and comparing it to the relationship between conventional standardized indices and nonparametric standardized indices. The results show that the newly proposed methodology outperforms the conventional SPI method across various dependence measures, suggesting it captures the underlying data structure more effectively than the SPI method.Yayın Global exposure of population and land-use to meteorological droughts under different warming levels and SSPs: A CORDEX based study(John Wiley and Sons Ltd, 2021-12) Spinoni, Jonathan; Barbosa, Paulo; Bucchignani, Edoardo; Cassano, John; Cavazos, Tereza; Cescatti, Alessandro; Christensen, Jens Hesselbjerg; Christensen, Ole Bossing; Coppola, Erika; Evans, Jason; Forzieri, Giovanni; Geyer, Beate; Giorgi, Filippo; Jacob, Daniela; Katzfey, Jack; Koenigk, Torben; Laprise, Rene; Lennard, Christopher John; Kurnaz, Mehmet Levent; Li, Delei; Llopart, Marta; McCormick, Niall; Naumann, Gustavo; Nikulin, Grigory; Öztürk, Tuğba; Panitz, Hans-Jurgen; da Rocha, Rosmeri Porfirio; Solman, Silvina Alicia; Syktus, Jozef; Tangang, Fredolin; Teichmann, Claas; Vautard, Robert; Vogt, Jurgen Valentin; Winger, Katja; Zittis, George; Dosio, AlessandroGlobal warming is likely to cause a progressive drought increase in some regions, but how population and natural resources will be affected is still underexplored. This study focuses on global population and land-use (forests, croplands, pastures) exposure to meteorological drought hazard in the 21st century, expressed as frequency and severity of drought events. As input, we use a large ensemble of climate simulations from the Coordinated Regional Climate Downscaling Experiment, population projections from the NASA-SEDAC dataset, and land-use projections from the Land-Use Harmonization 2 project for 1981-2100. The exposure to drought hazard is presented for five SSPs (SSP1-SSP5) at four Global Warming Levels (GWLs, from 1.5 to 4 degrees C). Results show that considering only Standardized Precipitation Index (SPI; based on precipitation), the combination SSP3-GWL4 projects the largest fraction of the global population (14%) to experience an increase in drought frequency and severity (vs. 1981-2010), with this value increasing to 60% if temperature is considered (indirectly included in the Standardized Precipitation-Evapotranspiration Index, SPEI). With SPEI, considering the highest GWL for each SSP, 8 (for SSP2, SSP4, and SSP5) and 11 (SSP3) billion people, that is, more than 90%, will be affected by at least one unprecedented drought. For SSP5 (fossil-fuelled development) at GWL 4 degrees C, approximately 2 center dot 10(6) km(2) of forests and croplands (respectively, 6 and 11%) and 1.5 center dot 10(6) km(2) of pastures (19%) will be exposed to increased drought frequency and severity according to SPI, but for SPEI, this extent will rise to 17 center dot 10(6) km(2) of forests (49%), 6 center dot 10(6) km(2) of pastures (78%), and 12 center dot 10(6) km(2) of croplands (67%), with mid-latitudes being the most affected areas. The projected likely increase of drought frequency and severity significantly increases population and land-use exposure to drought, even at low GWLs, thus extensive mitigation and adaptation efforts are needed to avoid the most severe impacts of climate change.
