Filtreler

20252
Filtreleri Sıfırla

Ayarlar

Yazar: Terzi, Tolga Barış × WoS Q: Q2 ×

Arama Sonuçları

Listeleniyor 1 - 2 / 2
  • Küçük Resim
    Yayın
    DroughtStats: a comprehensive software for drought monitoring and analysis
    (Springer Science and Business Media Deutschland GmbH, 2025-01) Terzi, Tolga Barış; Önöz, Bihrat
    The significance of drought monitoring and prediction systems has grown substantially due to the escalating impacts of climate change. However, existing tools for drought analysis face several limitations, including restricted functionality to single-variable indices, reliance on predefined probability distributions, lack of flexibility in choosing distributions, and the need for advanced programming expertise. These constraints hinder comprehensive and accurate drought assessments. This study introduces DroughtStats, a novel, user-friendly software designed to overcome these challenges and enhance drought analysis capabilities. DroughtStats integrates advanced statistical tools to analyze hydrometeorological data, compute both single-variable and multivariable drought indices using empirical and parametric methods, and evaluate drought characteristics with improved accuracy. Notably, it supports a broader range of probability distributions, performs copula-based analyses, and estimates potential evapotranspiration using multiple methods, including Penman–Monteith. Additionally, DroughtStats can analyze the relationship between different datasets using techniques like copula-based Kendall’s tau. By addressing the limitations of existing tools, DroughtStats provides a more flexible and comprehensive approach to drought monitoring. Its versatility and global applicability are demonstrated through a case study in Turkey’s Çoruh River Basin (CRB), where drought indices based on precipitation and streamflow are calculated to characterize drought conditions. The results show that DroughtStats can successfully identify and characterize drought events at various time scales, providing valuable insights into drought severity, frequency, and recovery, and offering a reliable tool for ongoing drought monitoring and management.
  • Küçük Resim
    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, Bihrat
    Drought 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.