Integrating GIS and remote sensing for land use/land cover mapping and groundwater potential assessment for climate-smart cocoa irrigation in Ghana

Abstract

Although Ghana is a leading global cocoa producer, its production and yield have experienced declines in recent years due to various factors, including long-term climate change such as increasing temperatures and changing rainfall patterns, as well as drought events. With the increasing exposure of cocoa-producing regions to extreme weather events, the vulnerability of cocoa production is also expected to rise. Supplemental irrigation for cocoa farmers has emerged as a viable adaptation strategy to ensure a consistent water supply and enhance yield. However, understanding the potential for surface and groundwater irrigation in the cocoa-growing belt remains limited. Consequently, this study aims to provide decision-support maps for surface and groundwater irrigation potential to aid planning and investment in climate-smart cocoa irrigation. Utilizing state-of-the-art geospatial and remote sensing tools, data, and methods, alongside in-situ groundwater data, we assess the irrigation potential within Ghana's cocoa-growing areas. Our analysis identified a total area of 22,126 km2 for cocoa plantations and 125.2 km2 for surface water bodies within the cocoa-growing regions. The multi-criteria analysis (MCA) revealed that approximately 80% of the study area exhibits moderate to very high groundwater availability potential. Comparing the MCA output with existing borehole locations demonstrated a reasonable correlation, with about 80% of existing boreholes located in areas with moderate to very high potential. Boreholes in very high potential areas had the highest mean yield of 90.7 l/min, while those in low groundwater availability potential areas registered the lowest mean yield of 58.2 l/min. Our study offers a comprehensive evaluation of water storage components and their implications for cocoa irrigation in Ghana. While groundwater availability shows a generally positive trend, soil moisture and surface water have been declining, particularly in the last decade. These findings underline the need for climate-smart cocoa irrigation strategies that make use of abundant groundwater resources during deficit periods. A balanced conjunctive use of surface and groundwater resources could thus serve as a sustainable solution for maintaining cocoa production in the face of climate change.

Review of Applications of Remote Sensing towards Sustainable Agriculture in the Northern Savannah Regions of Ghana

“…To forestall similar challenges in the Upper West Region, Diabene et al [93] used RS-derived land use and land cover and slope data as key parameters to identify potential areas of small reservoirs for the implementation of the agricultural water management intervention of the government of Ghana. Similarly, Akpoti et al [94] used land cover data to assess the irrigation potential of Ghana's cocoa-growing areas. The study finds a total area of 22,126 km 2 for cocoa plantations and 125.2 km 2 for smallholder reservoirs within cocoa-growing regions.…”

Runoff Management based Water Harvesting for Better Water Resources Sustainability: A Comprehensive Review

“…It allows decision-makers to consider an array of factors, such as hydrological characteristics, environmental impacts, socio-economic aspects, and technical feasibility, when evaluating potential dam sites [139]. Through the integration of GIS and remote sensing technologies, spatial data can be leveraged to enhance the accuracy and objectivity of the analysis [140]. Furthermore, MCA provides a transparent and systematic approach, which is particularly valuable when dealing with complex and controversial decisions.…”

Lake bottom relief reconstruction and water volume estimation based on the subsidence rate of the post-mining area (Bytom, Southern Poland)

“…Geoinformation methods facilitate research on changes in the Earth’s topography, land cover or processes (e.g. 42 , 43 ). In this case, the Geographic Information System (GIS) may be based on the usage or the generation of digital elevation models (DEMs), which, thanks to interpolation algorithms, allow for obtaining digital terrain models (DTMs) and their derivatives.…”