Minna – The Human and Environmental Development Agenda (HEDA) on Wednesday predicted that this year’s rainfall will cease in parts of Niger state around November, particularly in three local government areas namely: Katcha, Agaie and Lapai.
Quoting NIMETs rainfall predictions for the year 2020, HEDA said the growing season across the state will end around October in Rijau, Mariga Agwara, Borgu and Kontagora Local Government Areas.
Speaking at a one-day seminar for 50 farmers drawn from the nine local government areas, Niger-South senatorial zone in Bida, Lead Facilitator HEDA, Malam Garba also explained that places like Suleja, Lapai Bida and Lavun are expected to have the longest period of rainfall period in the state for 170 days.
The total volume of rainfall for the state, according to Malam Garba, will range from 880 millimetres to 1, 350 milimetres in the southern part of the state.
Garba, however, lamented that “There currently exists a gap between States Agriculture Development authorities and the NIMET” and results in underutilisation of climate information services from the agency in policies, planning and programmes.”
He further advised that, “Timely reliable and useful climate information and early warning is critical to agriculture production and as well, livelihood protection for farmers in Niger state and Nigeria as a whole.
“Using the annual seasonal rainfall prediction produced by the Nigerian Meteorological Agency will help mitigate a lot of problems arising from the difficulty in planning because of weather nuance,” he pointed out.
Due to the COVID-19 pandemic and the need to respect the guidelines set out by the Presidential Task Force PTF especially Social and physical distancing the number of participants were reduced to only 50, but urged those present to share the knowledge acquired with fellow farmers in their respective localities.
The seminar was jointly organised by HEDA, NiMET, and the Community Action for Food Security Initiative to enlighten the farmers on how to effectively use NIMETs predictions to improve farming and agricultural production.