Mr Martin M. Chari

Level of Study: 
PhD
Department: 
Geography & Environmental Science
Topic: 
Enhancing adaptive capacities of farmers to climate-induced rainfall variabilities by mapping remotely sensed soil moisture in Raymond Mhlaba Local Municipality, Eastern Cape Province, South Africa
Abstract: 

Soil moisture is critical in addressing key scientific and practical challenges in today’s world such as food security, sustainable planning and management of water resources because of its strong influence on hydrological and meteorological processes. The global agricultural community needs timely and regular information on soil moisture variability and spatial trends in order to meet growing food demands in a changing climate by maximizing crop production. However, efforts to realise this objective continue to be undermined by lack of adequate because in situ soil moisture measurement is expensive, time consuming and labour intensive. These limitations are further aggravated by difficulties in providing data at appropriate spatial scales because ground sensors are rarely distributed to cover critical agricultural areas in inaccessible localities where efficient use of water is required because of its scarcity. This study attempts to bridge this gap by providing a replicable, practically implementable, adaptable and cost-effective methodology to timeously provide useful information by mapping soil moisture patterns at appropriate spatial scales in order to enhance the effectiveness of agricultural decision-making. This study seeks to do this by using a multi-step index of soil moisture derived from remotely sensed Sentinel 2 imagery to; map and rank on a scale ranging from low, medium to high; all farming areas with varying levels of soil moisture in Raymond Mhlaba Municipality which is situated in South Africa’s Eastern Cape Province. Results of this initiative will strongly suggest that this improvised methodology can go a long way in securitising the production of adequate food supplies under deteriorating climatic conditions by cost-effectively providing reliable soil moisture information for data-scarce areas at appropriate temporal and spatial scales