Publications

Gumindoga, W; Murwira, A; Rwasoka, DT; Jahure, FB; Chikwiramakomo, L (2020). The spatio-temporal soil moisture variation along the major tributaries of Zambezi River in the Mbire District, Zimbabwe. JOURNAL OF HYDROLOGY-REGIONAL STUDIES, 32, 100753.

Abstract
This study uses the Surface Energy Balance System (SEBS) and the TOPographic driven MODEL (TOPMODEL) in estimating soil moisture for Mbire district in Zimbabwe and validates these estimates with ground based gravimetric measurements baseded on fifty-four soil moisture sampling sites. Five atmospherically corrected MODIS images for the period 2013were processed and used to estimate evapotransiration. The result of the relative evaporation from the SEBS algorithm was multiplied by the average of the porosity and the field capacity to get the spatial and temporal soil moisture estimates. The TOPMODEL rainfall-runoff model whose land surface inputs were obtained from remote sensing was calibrated with runoff data for the period ranging 2008-2013. After successful calibration the model was used to to simulate spatial and temporal soil moisture estimates and compare with insitu-measured soil moisture from the fifty-two sampling sites. An upscaling procedure to improve the comparison between soil moisture retrieval point measurements, remote sensing and TOPMODEL outputs was accomplished by the use of geostatistical tools. Land suitability analysis for flood recession farming was performed using soil moisture maps, distance from stream network, vertical channel distance, and land use/ cover datasets. The model performance indicators for TOPMODEL simulations show an acceptable match with measured discharge, (NSE = 0.765 and 0.812 and PBIAS= -6.04 % and -10.5 % for Manyame and Angwa sub catchments respectively). Results show that the SEBS approach show spatial and temporal soil moisture variability across the Mbire district simulated. There is a strong relationship (R-2 = 0.796) between upscaled insitu-based soil moisture measurements and SEBS based techniques for the period of March to July 2013. The study further revealed that there is a fair relationship (R-2 = 0.60) between upscaled ground soil moisture measurements and hydrological modelling (TOPMODEL) for the same period. TOPMODEL soil moisture increases towards the Angwa and Manyame river tributaries. Results also show that approximately 22800 ha of Mbire district has suitable to moderately suitable flood recession farming area. The study concludes that the use of geostatistical approaches, remote sensing and hydrologic models is promising in planning and management of soil moisture and water resources in data scarce and water limited environments.

DOI:
10.1016/j.ejrh.2020.100753

ISSN: