Modeling the Semivariogram of Climatic Scenario around Rivers by Using Stream Network Mapping and Hydrological Indicator

L. Omolayo Agashua, B. Dorcas Oluyemi-Ayibiowu, N. Isioma Ihimekpen, E. Christopher Igibah


Precipitation erosivity propels detrimental hydrological happenings with substantial eco-friendly and socio-economic influences. The conception of the precipitation-vegetation interface is very vital for implementing acclimatization and mitigation techniques for terrestrial bionetworks. Numerous investigations have reconnoitered the spatial correlation of precipitation-vegetation context along the season-precipitation quantity gradient. Here, comprehensive scrutiny of spatio-temporal patterns of climatology-vegetation response to seasonal variability incongruities in River Ikpoba, southern Nigeria, using principal component scrutiny (PCS), semivariogram, cross-validation statistics, spatial distribution mapping, and hydrological indicators for multi-source climatic datasets for pre-impact flow (1913–1966) and post-impact flow (1967–2022). PCS outcomes reveal seven PCs whose eigenvalues were greater than one were hauled out of the twenty-five variables. The River Ikpoba water quality variables displayed a moderately strong rate of spatial reliance, which made it possible to create the spatial distribution map for the carefully chosen water quality variables. Results from further scrutiny of the river Ikpoba flow duration curve show the highest flow rate value between 900–1000cms for the month of October. The post-impact flow's highest value was 65cms in 2008, whereas the pre-impact flow was 64cms. Likewise, 90 days’ minimum highest flow rate was 250cms, 30 days was 1180cms, 7 days was 105cms, and 1 day was 105cms. Whereas the maximum for 1 day was 7200cms, 3 days’ value was 6400cms and 7 days' was 4500cms. This indicates that as the day progressed, the flow rate was increasing for a consecutive 30 days at a low flow rate, but at 90 days it declined. As the day progresses, the values for the maximum value decrease.


Doi: 10.28991/HEF-2022-03-01-02

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Distribution Mapping; Impact Flow; Spatial Reliance; Geostatistical; Contagions; Hydrological Indicator; River.


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DOI: 10.28991/HEF-2022-03-01-02


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