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Modeling the influence of daily temperature and precipitation extreme indices on vegetation dynamics in Katsina State using statistical downscaling model (SDM)

journal contribution
submitted on 2023-12-19, 05:43 and posted on 2024-01-11, 08:23 authored by Mohammad Hadi Ahmad, Ahmed Abubakar, Mohd Yusoff Ishak, Samir Shehu Danhassan, Zhang Jiahua, Juha M. Alatalo

Climate change significantly impacts local, regional, and global vegetation changes. These changes have continued to threaten ecosystems, especially in dryland areas where moisture is scarce, and the livelihoods of rural communities are at risk because of such changes, as well as their capacity to provide outputs and sustain the livelihoods of rural communities. This study aims to derive a simulation model of vegetation conditions concerning daily temperature and extreme precipitation indices in Katsina State, Nigeria. This study uses remote sensing and Geographic Information System (GIS)-based analysis, time series analysis of precipitation, maximum and minimum temperature, and twenty-four indices defined by the Expert Team on Climate Change Detection to evaluate the influence of Temp and precipitation extreme indices on vegetation dynamics/NDVI. The results indicate that the statistical downscaling model (SDSM) is performing satisfactorily in predicting maximum and minimum temperatures, along with precipitation, for the time horizon of the simulation. Mean precipitation of 1.98 mm (RCP2.6), 2.03 mm (RCP4.5), and 2.07 mm (RCP8.5) was revealed in the study area. Tmax and Tmin were projected under low emissions at 20.1 0C and 14.25 0C (RCP2.6), 20.13 °C and 14.26 0C (RCP4.5), and 20.15 0C and 14.27 0C (RCP8.5) respectively. All the scenarios present increasing minimum and maximum temperatures and decreasing precipitation, except for RCP8.5, which predicted a more adverse trend. However, in Katsina State, the Normalized Difference Vegetation Index (NDVI), precipitation, Tmax, and Tmin, extreme temperature and precipitation indices, and drought indices successfully demonstrated spatial and temporal variability.

Other Information

Published in: Ecological Indicators
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.ecolind.2023.110979

Funding

Open Access funding provided by the Qatar National Library.

History

Language

  • English

Publisher

Elsevier

Publication Year

  • 2023

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Qatar University
  • Environmental Science Center - QU

Geographic coverage

Nigeria