5 research outputs found

    Meteorological Drought Analysis and Return Periods over North and West Africa and Linkage with El Niño−Southern Oscillation (ENSO)

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    Droughts are one of the world’s most destructive natural disasters. In large regions of Africa, droughts can have strong environmental and socioeconomic impacts. Understanding the mechanism that drives drought and predicting its variability is important for enhancing early warning and disaster risk management. Taking North and West Africa as the study area, this study adopted multi-source data and various statistical analysis methods, such as the joint probability density function (JPDF), to study the meteorological drought and return years across a long term (1982−2018). The standardized precipitation index (SPI) was used to evaluate the large-scale spatiotemporal drought characteristics at 1−12-month timescales. The intensity, severity, and duration of drought in the study area were evaluated using SPI−12. At the same time, the JPDF was used to determine the return year and identify the intensity, duration, and severity of drought. The Mann-Kendall method was used to test the trend of SPI and annual precipitation at 1−12-month timescales. The pattern of drought occurrence and its correlation with climate factors were analyzed. The results showed that the drought magnitude (DM) of the study area was the highest in 2008−2010, 2000−2003, and 1984−1987, with the values of 5.361, 2.792, and 2.187, respectively, and the drought lasting for three years in each of the three periods. At the same time, the lowest DM was found in 1997−1998, 1993−1994, and 1991−1992, with DM values of 0.113, 0.658, and 0.727, respectively, with a duration of one year each time. It was confirmed that the probability of return to drought was higher when the duration of drought was shorter, with short droughts occurring more regularly, but not all severe droughts hit after longer time intervals. Beyond this, we discovered a direct connection between drought and the North Atlantic Oscillation Index (NAOI) over Morocco, Algeria, and the sub-Saharan countries, and some slight indications that drought is linked with the Southern Oscillation Index (SOI) over Guinea, Ghana, Sierra Leone, Mali, Cote d’Ivoire, Burkina Faso, Niger, and Nigeria

    Suitability mapping for rice cultivation in Benue State, Nigeria using satellite data

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    With rising population, decline in soil productivity and land-based conflicts, the per-capita land availability for cultivation is rapidly decreasing within Benue State, a largely agrarian and small-holder setting. This study attempts a local-level support for the actualisation of Sustainable Development Goal Number 2 (“end hunger, achieve food security and improved nutrition, and promote sustainable agriculture”) by 2030. Using Multi-Criteria Decision Making (MCDM) method, remote sensing data from Climate Research Unit (CRU) and in-situ data from Nigeria Meteorological Agency (NIMET) were analyzed by GIS techniques to map the suitability of rice cultivation in the study area, with the integration of Normalized Difference Vegetation Index (NDVI), land cover, slope, temperature, precipitation and soil parameters (cation exchange capacity, pH, bulk density, organic carbon). We apply the various statistical parameters that include mean spatial NDVI; correlation coefficient, standard deviation and Root Mean Square (RMS) between CRU and NIMET data. Spatial regression trend analysis is conducted between CRU precipitation and NDVI and between CRU temperature and NDVI from 1985 to 2015. The results reveal that NDVI in highly suitable rice planting regions is higher than marginally suitable regions except in the months of October and November, which shows that the highly suitable regions will yield better than the marginally suitable regions during the dry season. Additionally, NDVI is seasonally bimodal in response to precipitation, meaning that vegetation vigor is more dependent on precipitation than temperature. Finally, the correlation coefficient, standard deviation and RMS between CRU and NIMET precipitation data shows 0.42, 108, and 110, respectively, while these three factors between CRU and NIMET temperature data shows 0.88, 1.60, and 0.86, respectively. In conclusion, the MCDM approach reveals that upland is more suitable for rice cultivation in Benue State when comparing with the area provided by the Global Land Cover and National Mappings Organization (GLCNMO) data

    Spatio-temporal analysis of drought and return periods over the East African region using Standardized Precipitation Index from 1920 to 2016

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    © 2020 Elsevier B.V. East African region is susceptible to drought due to high variation in monthly precipitation. Studying drought at regional scale is vital since droughts are considered a ‘creeping’ disaster by nature with devasting and extended impact often requiring long periods to reverse the recorded damages. This study assessed drought exceedance and return years over East Africa from 1920 to 2016 using Climate Research Unit (CRU) precipitation data records. Meteorological drought, where precipitation is the central quantity of interest, was adopted in the work. Standardize Precipitation Index (SPI) was used to study long term meteorological droughts and also to assess drought magnitude, frequency, exceedance probability and return years using Joint Probability Density Function (JPDF). Also, Mann-Kendall trend analysis was applied to precipitation and SPI to investigate the trend changes. Results showed that years with high drought magnitude ranged from 1920−22, 1926−29, 1942−46 and 1947−51 with values corresponding to 2.2, 3.2, 3.4 and 2.6, respectively while years with low drought magnitude ranged from 1930−31, 1988−89 and 2001−02 with values as 0.2, 0.12 and 0.15, respectively. The longest droughts occurred from 1926−29, 1937−41, 1942−46, 1947−51, 1952−56, and 1958−61 with values in years as 3, 4, 4, 4, 4, and 3 years, respectively, while the shortest droughts occurred in time period of 1 year and ranged from 1930−31, 1964−65, 1979−80, 1981−82, 1983−84, 1988−89, 1991−92, 1993−94, 1996−97 and 2001−02. Also, it was demonstrated that probability of drought occurrence is high when severity is low and such droughts occur at short time intervals and not all severest drought took longer periods. The SPI trends indicate high positive (negative) pixels above (below) the zero-trend mark, indicating that drought prevails in both low and high elevation areas up to 2000 m. There was no direct link between ENSO and drought but arguably the association of drought in most El Niño and La Niña years suggests that the impact of ENSO cannot be ruled out since peak ENSO events occur during October to March periods which coincides with the short (SON) and long (MAM) rainy seasons of East Africa. The study is particularly relevant in being able to depict continuous and synoptic drought condition all over East Africa, providing vital information to farmers and policy makers, using very cost-effective method
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