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Space-time modelling of seasonal soil moisture for improved crop production – the case of the Guinea savannah region, Ghana

dc.contributor.advisorSauer, Daniela Prof. Dr.
dc.contributor.authorNketia, Kwabena Abrefa
dc.titleSpace-time modelling of seasonal soil moisture for improved crop production – the case of the Guinea savannah region, Ghanade
dc.contributor.refereeKappas, Martin Prof. Dr.
dc.description.abstractengThe upsurge in advocacy for food security in SSA implies the urgent need for improved sustainable adaptation measures that can boost food-crop production. This is of utmost concern, because, over the past decades, food security targets in SSA have remained unmet due to food-crop production limitations. One of the key adaptation measures which is identified to address these food-crop production limitations has been the urgent call for DSM. DSM is essential to address concerns on site-specific soil information that guides fertilizer application, improve data availability of soil fertility parameters and fill the gaps of spatially explicit soil maps. SSA is one of the regions in the world with a large terra incognita ahead of its DSM initiatives. Thus far, there is a paucity of data omission on seasonal SM and SWS, which reflect the size of water reservoir of agricultural soils and its water storage adequacy. It is imperative that such critical soil information is made available. This is because, studies have demonstrated that in rain-fed agriculture, which dominates the agricultural landscape of SSA, ~50% of total crop yield loss can be implicated by weather-induced water stress. Already, studies are reporting declining crop yields due to water-deficit conditions. Against this backdrop, meeting the globally-projected 60% increase in food demand by 2050, of which SSA is deemed to play a pivotal role, is recognized as a major challenge. This thesis fills the knowledge gap by employing state of the art approaches on spatio-temporal scale analyses in order to complement existing DSM initiatives, which guide sustainable agriculture, crop intensification, modelling agricultural systems and site-specific farm management recommendations. We investigated and modelled the spatio-temporal seasonal SM and SWS of arable benchmark soils of the Guinea savannah zone of Ghana. The Guinea savannah zone is of importance because, it is a key reminiscent of the arable landscapes of SSA. To make our findings useful to the SSA region, this research specifically targeted smallholder farming communities, as they constitute ~80% of the farmers in the region. Also, these farmers have farm sizes < 1 ha that can easily adopt improved management practices. Here, we selected major arable benchmark soils along three main soil toposequences of the Guinea savannah zone. Specific objectives undertaken to fill the knowledge gap were to: (1) design a new soil sampling stratification that adequately represented the soil toposequences, defined local structures and accounted for localized spatial autocorrelation in explaining SM and SWS variability, (2) analyze and assess the spatio-temporal dynamics of SM of soils of the area, (3) investigate the potentials for using high-spatial and -temporal resolution remote sensing images to estimate SM at detailed scale and (4) functionally map, at 100 m spatial resolution, the four-dimensional root zone SWS of soils of the Guinea savannah zone. Addressing these specific objectives, key implications that can improve food-crop production, especially for the Guinea savannah zone, are recommended. Firstly, SM and SWS in the shallow soil depths (≤ 15 cm) were highly variable, unstable and consistently dry as compared to the bottom soil layers (≥ 20 cm). These observed high temporal instability were as a result of, on the one hand, the influence of internal soil factors such as clay and silt contents, and bulk density, and on the other hand, external factors such as slope, precipitation and evapotranspiration. In the bottom layer soils, clay content increased with increasing soil depth which kept SM and SWS for longer periods by promoting time-stable wet cluster of locations. Secondly, time-stable locations where crop water requirements can be met during crop growing periods is explicitly identified for use. An outcome of this research is that almost all benchmark soils of the Guinea savannah zone (except for the Kumayili series) have SWS potentials that match the water requirements of at least some drought-tolerant crops of the area. Furthermore, we found that the use of high spatial resolution multi-temporal radar and optical remote sensing images opens new perspective to estimate and adequately understand the spatio-temporal variabilities of SM in sparse in situ measurements network. This finding brings the advantage over existing SM and SWS point-based analysis and also improves the use of SM and SWS information in semi-arid farming landscapes. Also, the estimation of SM at detailed spatio-temporal global scales while preserving a short revisit time is possible. Through this thesis, we connected several scales of analyses and initiatives regarding an improved food-crop production system in SSA. Possible adoptable recommendations drawn from this thesis include, e.g., the possibility and practicability to either prolong the existing major single farming window and the identification of locations and durations where additional crop-specific farming is applicable. In addition, the outcomes of the thesis can be used to enhance the adaptive capacity of smallholder farmers to increase food-crop production, yields, income and diversify livelihood alternatives of the local farming communities. Therefore, the findings from this thesis forms a core support system that is necessary to guide the implementation of drought-adaptation measures, dual farming system and complement existing DSM initiatives around the
dc.contributor.coRefereeDittrich, Christoph Prof. Dr.
dc.contributor.thirdRefereeErasmi, Stefan Dr.
dc.contributor.thirdRefereeHerbold, Steffen PD Dr.
dc.contributor.thirdRefereeFaust, Heiko Prof. Dr.
dc.subject.engsoil moisturede
dc.subject.engsoil water storagede
dc.subject.engspatio-temporal variabilityde
dc.subject.engsub-Saharan Africade
dc.subject.engWest Africade
dc.subject.engGuinea savanna zonede
dc.subject.engensemble-based machine learningde
dc.subject.engfood securityde
dc.affiliation.instituteFakultät für Geowissenschaften und Geographiede
dc.subject.gokfullGeographie (PPN621264008)de

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