2012 | OriginalPaper | Buchkapitel
Analysis of Trend and Periodicity in Long-Term Annual Rainfall Time Series of Nigeria
verfasst von : Deepesh Machiwal, Madan Kumar Jha
Erschienen in: Hydrologic Time Series Analysis: Theory and Practice
Verlag: Springer Netherlands
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Understanding trends and variations of current and historical hydroclimatic variables is pertinent to the future development and sustainable management of water resources of a particular region. Information regarding hydroclimatological issues is important within the context of global warming, water and energy cycles and the increasing demand for water due to population and economic growth (Sankarasubramanian and Vogel, 2003; Oguntunde et al., 2006). Changes in the climate system and land cover have been widely accepted to have important consequences for regional to global water resources management and conservation. The extent to which human alteration of earth’s environment affects the global hydrologic cycle is still largely unknown (Szilagyi, 2001). Valuable historical records of hydrologic patterns over complex drainage basins help to understand anthropogenic and climatic effects on large-scale terrestrial ecosystems (Vörösmarty and Sahagian, 2000). One of the very important necessities of research into climate change is to analyze and detect historical changes in the climatic system (Houghton et al., 1996). Rainfall is a principal element of the hydrological cycle, hence understanding its behaviour may be of profound social and economic significance. Detection of trends and oscillations in the rainfall time series yields important information for understanding the climate. However, rainfall changes are particularly hard to gauge, because rainfall is not uniform and varies considerably from place to place and time to time, even on small scales.