Data Processing for Assessment of Meteorological and Hydrological Drought
Abstract
Accurate and reliable data processing is of primary importance for drought assessment. It helps decision makers to lay out mitigation measures within the context of drought preparedness planning and water resources management. In order to understand meteorological and hydrological drought, we need to identify drought characteristics (duration, severity and spatial extent). Drought indices are essential tools quantifying drought severity and identifying its frequency and duration. For the calculation of drought indices, availability of long time series of undisturbed, good-quality observational data is essential. The studied area cover a Bulgarian part of the catchment of Struma River which is one of the largest Bulgarian rivers. The general aim of this research is to evaluate the occurrence of hydrological and meteorological droughts in Struma River basin and to show utilization of various indices for comparative analysis of meteorological and hydrological drought. Drought events are identified using the following indices—Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and Streamflow Drought Index (SDI) for time scales 6 and 12 months. Additionally to these indices, we use also Rainfall Anomaly Index (RAI) and introduce Streamflow Anomaly Index (SAI). The main investigated period is 1962–2016.
Domains
Computer Science [cs]Origin | Files produced by the author(s) |
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