Afghanistan: Combined Drought Indicator (CDI)

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About this dataset

The Combined Drought Indicator (CDI) dataset identifies different drought classes and their extent, focusing on vegetated areas (at risk, affected, and recovering). It integrates three complementary indicators — Standardized Precipitation Index (SPI), Soil Moisture Index Anomaly (SMA), and FAPAR anomaly — to capture meteorological, agricultural, and vegetation drought conditions. The dataset consists of raster maps with a spatial resolution of ~5 km at the Equator, using WGS84 (EPSG:4326) as the coordinate system. Data are available from 2012 to the present, updated every 10 days, which is suitable for monitoring short-term crop stress. Produced operationally by the European Drought Observatory (EDO), the CDI maps are freely accessible online. Recent updates include: CDIv3 (March 2023): integration of static crop masks to limit analysis to active growing seasons. CDIv4 (June 2024): introduction of dynamic snow masks and a new soil moisture input based on EFAS v5. More: https://drought.emergency.copernicus.eu/data/factsheets/factsheet_combinedDroughtIndicator_v4.pdf

Documentation

Combined Drought Indicator (CDI) The Combined Drought Indicator (CDI) integrates anomalies of precipitation, soil moisture, and vegetation greenness (see CDI Conceptual Framework, Table 2a). It uses three drought indicators and two thematic masks implemented in EDO. 1. Drought Indicators a. Standardized Precipitation Index (SPI) A well-known indicator recommended by the World Meteorological Organization (WMO) for meteorological drought monitoring. Quantifies the deviation of accumulated precipitation over a given timescale compared to a reference baseline (McKee et al., 1993; Edwards and McKee, 1997). CDI uses two timescales: SPI-1 (30 days) – indicates Extreme Meteorological Drought when value < -2 SPI-3 (90 days) – indicates Moderate Meteorological Drought when value < -1 Calculated using ERA5 (European ReAnalysis 5th Generation) precipitation data (Hersbach et al., 2017). b. Soil Moisture Index Anomaly (SMI) Derived from anomalies of estimated daily soil moisture content, expressed as a standardized Soil Moisture Index (SMI). SMI is a product of the JRC LISFLOOD hydrological model (de Roo et al., 2000; Laguardia and Niemeyer, 2008). The current SMI product is based on EFAS (European Flood Awareness System) version 5.0, operational since 20 September 2023. c. FAPAR Anomaly FAPAR (Fraction of Absorbed Photosynthetically Active Radiation) measures the fraction of incoming solar radiation absorbed by vegetation for photosynthesis. Satellite-derived FAPAR anomalies effectively detect and assess drought impacts on various land cover types (Gobron et al., 2005). 2. Thematic Masks a. Crop Masks Address seasonal shifts from vegetation to bare soil after harvest that affect FAPAR anomalies. Prevents misinterpretation of bare-soil signals as drought stress. Comprises 10-day gridded binary maps, where each pixel indicates presence or absence of crops during the growing season. Ensures that analysis of negative FAPAR anomalies in cropland areas is restricted to the growing season (see Table 2b). b. Snow Masks Prevent unreliable soil moisture readings under snow cover. The snow mask functions similarly to the crop mask, excluding affected pixels from CDI computations. Implemented through a dynamic snow cover masking process, using 10-day gridded binary maps that identify the presence or absence of snow. When snow is detected, corresponding soil moisture and FAPAR anomalies are excluded from the CDI (see Table 2c).

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