Application of Multi-Variant Statistical Drought Indices on Characterization and Quantification of Drought Conditions and its Effects on Agriculture in Mubi Area, North-East Nigeria

Abstract

This present research work aimed to apply multi-variant statistical drought indices on characterization and quantification of drought conditions and its effects on agriculture in Mubi area, North-east Nigeria. Five different drought indices were adopted namely; Rainfall Seasonality Index (RSI), Rainfall Decile Index (RDI), Percent Normal Precipitation (PNP), Threshold Level Method (TLM) and Rainfall Anomaly Index (RAI) and also effectiveness test of the indices was also assessed. The rainfall data was obtained from Adamawa state university, Mubi Agro-meteorological station from the 2004-2020 and also data on causes and effects of drought were derived using questionnaires where One Hundred and Eighty (180) farmers were randomly selected and subjected to descriptive statistical analysis. The results obtained revealed that the suitable index for drought identification in the area is in order of TLM >RDI, >PN>RSI >RAI. Meanwhile, for the quantification >PN > RSI >TLM> RSI > TLM >RAI. In addition, the highly effective indices with ETV > 0.4 are PN, RSI and TLM with three combinations, RSI and TLM for double indices. Among the single index the PN, RSI and RDI are found to be highly effective respectively. In addition, deforestation (45%) and overgrazing (30 %) are the major causes of drought scenarios in the area that occurred mostly in 2009-2014 affecting crop yields (35 %) and pest and diseases outcrop (20 %). The farmers’ uses early maturing crops (35 %) and early planting (20 %) are found to major mitigation strategies adopted in the area. Thus, the adoption of the highly effective identified indices (PN, RSI and TLM and RSI and TLM) should therefore be adopted in the region towards understanding the drought conditions for sustainable agricultural production and mitigation strategies. Farmers in the area should be train on the drought mitigation.

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