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Salif, K., Gil, M., Fatogoma, B., Emmanuel, P., Alain, D. and Eric, S. (2023) Building Tools for Further Investigating Acid Mining Production: Intercomparison of Four Hydrological Model Versions through a Scoring Technique on the Niger River Basin, in West Africa. Earth & Environmental Science Research & Reviews, 6, 566-594.
https://doi.org/10.33140/EESRR.06.04.02

has been cited by the following article:

• TITLE: Using Geostatistical Kriging for Hydrologic Models’ Parameters Estimation on Niger River Watersheds in West Africa

  AUTHORS: Salif Koné

  KEYWORDS: Hydrogeostatistics Practice, Niger River, SimulHyd, Hydrospace, GR2M, Hydrological Modelling

  JOURNAL NAME: International Journal of Modern Nonlinear Theory and Application, Vol.13 No.4, December 18, 2024

  ABSTRACT: Geostatistical Kriging is performed on hydrologic model parameters in a two-dimensional region—different from the geographical space—as a hydrospace. The x-axis in percent is a relative difference of soil characteristics between an embedded 12 watersheds in reference to a large one related to the Niger River in West Africa; noted var_WHC, it stands for Water Holding Capacity. The y-axis in percent, var_Nash, is a hydrologic model’s efficiency in two contexts: (a) calibrated model parameters on the reference watershed are injected in modelling on each sub-watershed in validation phase to produce a series of Nash values as references, (b) a second series of Nash values is produced in calibrations. SimulHyd which stands for Simulation of Hydrological Systems is applied along with a French hydrological model—Genie Rural with 2 parameters at Monthly time step. The built Nash-WHC hydrospace and its two variants, or hybrids, permit the krige of both hydrologic model’s parameters. The relative variation of upper module absolute ranges from 0.1% to 15.68%—the developed hydro-geostatistics practice is considered in reference to hydrological calibration. Accepted as hydrogeostatistics practice, it is applicable to ungauged watersheds to estimate hydrologic models’ parameters.