African Center of Meteorological Applications for Development (ACMAD)The Soil Moisture Anomaly (SMA) dataset provides a measure of deviation in root-zone soil moisture conditions relative to the long-term climatological mean. Generated typically from hydrological models or satellite assimilation systems, this product highlights deficits or surpluses in soil water availability that are critical for agriculture and pastoralism. Because soil moisture integrates rainfall over time and accounts for evapotranspiration losses, SMA offers a more direct indicator of agricultural drought stress than precipitation deficits alone. This dataset is essential for monitoring the onset of agricultural drought, as soil moisture deficits often precede visible vegetation stress. It is widely used to assess potential yield reductions in rainfed agriculture and to monitor fodder availability in pastoral regions.acmad-soil-moisture-anomalyHumanitarian Data ExchangePublicAfrica - Monthly and dekadal Soil Moisture Anomaly (SMA)DatasetsAngolaBurundiBeninBurkina FasoBotswanaCentral African RepublicCôte d'IvoireCameroonDemocratic Republic of the CongoCongoComorosCabo VerdeDjiboutiAlgeriaEgyptEritreaWestern SaharaEthiopiaGabonGhanaGuineaGambiaGuinea-BissauEquatorial GuineaKenyaLiberiaLibyaLesothoMoroccoMadagascarMaliMozambiqueMauritaniaMauritiusMalawiNamibiaNigerNigeriaRwandaSudanSenegalSierra LeoneSomaliaSouth SudanSao Tome and PrincipeEswatiniSeychellesChadTogoTunisiaUnited Republic of TanzaniaUgandaSouth AfricaZambiaZimbabwe2012-01-01 to 2024-07-31