Case study: Hydraulic modeling of runoff processes in Ghanaian inland valleys

The inland valleys of West Africa are strategic in terms of food security and poverty alleviation, but scientific studies on hydrologic processes happening in these environments have not been well documented. Modeling approaches presented in this paper are an attempt to better comprehend hydraulic phenomena occurring in inland valleys. An inland valley situated in the Northern Region of Ghana is set as the study site. The inland valley comprises well-drained uplands and hydromorphic valley bottoms. There are several earthen dams across the valley bottoms, which are at the same time seasonal wetlands cultivated to rice during the rainy season. A finite volume model for the shallow water equations is developed to numerically simulate surface runoff flows in the valley bottoms during flood events. Innovation is necessitated to handle a series of different hydraulic phenomena. Flux-splitting and data reconstruction techniques are used to achieve stable computation in the complex topography of the valley bottoms. Standard problems of oblique hydraulic jump and dam break flows are used to test the accuracy of the numerical model. The Manning's roughness coefficient is determined from calibration in another Ghanaian watershed located in the Eastern Region. Using actually observed time series data of rainfall intensity, surface flows during the rainfall events are simulated in the computational domain representing the valley bottoms of the study area. Observed data of water levels in the dams are compared to predictions, and discrepancies between them are examined from the hydrological point of view. In the case of a hypothetical flood event, cascading collapses of the dams and flooding of cultivated fields are reproduced

Pathogen and heavy metal contamination in urban agroecosystems of northern Ghana: Influence of biochar application and wastewater irrigation

Gefördert im Rahmen des Projekts DEALBundesministerium für Wirtschaftliche Zusammenarbeit und Entwicklung. Grant Number: 031A242-A,B; Bundesministerium für Bildung und Forschung. Grant Number: 031A242-A,