## 5 Conclusions  
This study applied the FVM-Godunov model to solve 2D shallow-water equations, in order to simulate the surface flow. The ghost-cell approach was integrated into the model, in order to maintain a uniform solution in both the interior and boundary cells. The model is demonstrated by simulating the surface runoff on a given catchment, by considering parameters such as infiltration, the roughness coefficient, and the rainfall intensity. The computed results were validated with the observed data on the catchment of Grand-Ouaga in Burkina Faso. The main conclusions are as follows:  
1. The model adapts to both the topography and the field data. The model is sensitive to several parameters, including infiltration rate, rainfall, and surface slopes. Furthermore, the model can predict the flow propagation on a given catchment and provide the water height/discharge at the outlet. As expected, runoff intensity increases with rainfall intensity, but this is not in a linear fashion; more intense rainfall produces proportionally more severe flooding. 2. When the estimated final value infiltration is moderated, there is an increase in the rate of water infiltration in the catchment, which reduces the quantity of water that converges toward the outlet. This leads to a decrease in surface runoff; water tends to accumulate in the already saturated zone. 3. The results proposed in the validation section show good agreement between the measured data and the simulated model. These results reveal that the parameters collected on the field and the rainfall intensity registered with the rain gauge  
Figure 12: Rainfall intensity (**a**) and comparative study of the water height (**b**) during the flood of 18 to 22 July 2016.  
present the results close to reality. However, it was acknowledged that the study needs improvement, which can help the model to simulate values closer to the observed values. 4. The consideration of a constant and uniform value of the infiltration coefficient and the Manning coefficients in each land-cover type of the watershed also increases the risk of overestimating the results, since these different coefficients should not be considered constant. Hence, there is a need to take samples in the field with the appropriate equipment. 5. Further elaboration of the model is required. For example, parameters such as evaporation, evapotranspiration, and water flow rate that are present in the study area will be considered in a subsequent study in order to improve the reach and accuracy of the final results. Although these parameters have been integrated into the numerical equations in this paper, their effects have yet to be analyzed. Conceptualization, A.J.E. ; data curation, A.J.E. ; formal analysis, S.L.Z.A. ; funding acquisition, L.Z. ; investigation, A.J.E., H.F. and Y.C. ; methodology, H.F. and S.L.Z.A. ; project administration, B.K. ; resources, Y.C. ; software, A.J.E. ; supervision, L.Z. ; validation, Y.C. ; writing--original draft, L.Z. and B.K. ; writing--review and editing, B.K. All authors have read and agreed to the published version of the manuscript. The authors gratefully acknowledge the financial support given for this research by the National Natural Science Foundation of China (Grant Nos. 51839008 and 51679066), Fok Ying Tong Education Foundation (Grant No. 161068), and the China Scholar Council (File No. 201806715024). [PERSON], Ph.D Professor, College of Water Conservancy and Hydropower Engineering, Hohai University; 1 Xikang Road, Nanjing, China; 210098. His research interests include hydraulic transients in pipe system, hydraulics in Hydropower/Pump/Pumped Storage Station, Transient Flow in Urban Storm Sewers. As principal investigator, [PERSON] was awarded 25 research grants and 2 travel grants, including: 3 funds (general, young, international exchange) from National Natural Science Foundation of China, 1 fund from Fok Ying Tong Education Foundation, and Specialized Research Fund for the Doctoral Program of Higher Education of China, etc.