Repository logo

Browsing by Subject "drought"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • thumbnail.journal.alt
    Item type:Article, Access status: Open Access ,
    Drought assessment and forecasting according to the Köppen–Geiger climate classification using GRACE and MERRA observations
    (Wydawnictwa AGH, 2026) Birylo, Monika
    Prolonged and recurrent droughts are a problem of the 21st century. Agriculture, grazing, fires, logging, and mining make soil susceptible to permanent degradation. However, well-managed land can recover from long drought cycles. Because drought is increasingly affecting larger areas, continuous monitoring and risk assessment are essential. Satellite-based models provide global observations of the Earth and enable their assessment using indices, thereby supporting the classification of the examined areas. In this study, the Combined Climatological Deviation Index (CCDI) and the Water Storage Deficit Index (WSDI) were calculated to evaluate drought sensitivity in Europe, within its climatic zones according to the Köppen–Geiger classification. Based on the research, it was concluded that almost all areas show a tendency towards drying, and the predictions indicate that the current drought conditions and their pace will continue. The CCDI and WSDI are very useful in studies of drought in Europe.
  • thumbnail.journal.alt
    Item type:Article, Access status: Open Access ,
    Geospatial analysis of the impact of flood and drought hazards on crop land and its relationship with human migration at the district level in Uttar Pradesh, India
    (Wydawnictwa AGH, 2021) Islam, Zubairul; Singh, Sudhir Kumar
    The main objective was to explore the connection between flood and drought hazards and their impact on crop land and human migration. The Flood and Drought effect on Cropland Index (FDCI), hot spot analysis and the Global Regression Analysis method was applied for the identification of the relationship between human migration and flood and drought hazards. The spatial pattern and hot and cold spots of FDCI, spatial autocorrelation and Getis-OrdGi* statistic techniques were used respectively. The FDCI was taken as an explanatory variable and human migration was taken as a dependent variable in the environment of the geographically weighted regression (GWR) model which was applied to measure the impact of flood and drought hazards on human migration. FDCI suggests a z-score of 4.9, which shows that the impact of flood and drought frequency on crop land is highly clustered. In the case of the hot spots analysis, out of seventy districts in Uttar Pradesh twenty-one were classified as hot spot and eight were classified as cold spots with a confidence level of 90 to 99%. Hot spot indicate maximum and cold spots show minimum impact of flood and drought hazards on crop land. The impact of flood and drought hazards on human migration show that there are fourteen districts where migration out is far more than predicted while there are ten districts where migration out is far lower.