The miombo woodland is the largest dry woodland formation in sub-Saharan Africa, covering an estimated area of 2.7–3.6 million km2. Compared to other global ecosystems, the miombo woodland demonstrates unique interactions between plant phenology and climate. For instance, it experiences an increase in the leaf area index (LAI) during the dry season. However, due to limited surface exchange observations in the miombo region, there is a lack of information regarding the effect of these properties on miombo woodland evaporation. It is crucial to have a better understanding of miombo evaporation for accurate hydrological and climate modelling in this region. Currently, the only available regional evaporation estimates are based on satellite data. However, the accuracy of these estimates is questionable due to the scarcity of field estimates with which to compare. Therefore, this study aims to compare the temporal dynamics and magnitudes of six satellite-based evaporation estimates – the Topography-driven Flux Exchange (FLEX-Topo) model, Global Land Evaporation Amsterdam Model (GLEAM), Moderate-Resolution Imaging Spectrometer (MODIS) MOD16 product, operational Simplified Surface Energy Balance (SSEBop) model, Thornthwaite–Mather climatic Water Balance (TerraClimate) dataset, and Water Productivity through Open access of Remotely sensed derived data (WaPOR) – during different phenophases in the miombo woodland of the Luangwa Basin, a representative river basin in southern Africa. The goal of this comparison is to determine if the temporal dynamics and magnitudes of the satellite-based evaporation estimates align with the documented feedback between miombo woodland and climate. In the absence of basin-scale field observations, actual evaporation estimates based on the multi-annual water balance (Ewb) are used for comparison. The results show significant discrepancies among the satellite-based evaporation estimates during the dormant and green-up and mid-green-up phenophases. These phenophases involve substantial changes in miombo species' canopy phenology, including the co-occurrence of leaf fall and leaf flush, as well as access to deeper moisture stocks to support leaf flush in preparation for the rainy season. The satellite-based evaporation estimates show the highest agreement during the senescence phenophase, which corresponds to the period of high temperature, high soil moisture, high leaf chlorophyll content, and highest LAI (i.e. late rainy season into the cool-dry season). In comparison to basin-scale actual evaporation, all six satellite-based evaporation estimates appear to underestimate evaporation. Satellite-based evaporation estimates do not accurately represent evaporation in this data-sparse region, which has a phenology and seasonality that significantly differ from the typical case in data-rich ground-truth locations. This may also be true for other locations with limited data coverage. Based on this study, it is crucial to conduct field-based observations of evaporation during different miombo species phenophases to improve satellite-based evaporation estimates in miombo woodlands. ... Read more

Through precipitation retention and evaporation (by both interception and transpiration), woodlands play a significant role in the global moisture cycle. Evaporation is the largest, but at the same time, the most difficult flux to observe in a woodland. Accounting for woodland evaporation is important for hydrological modelling for the efficient development and management of water resources. Assessing evaporation is a challenging undertaking that involves the use of a wide range of equipment and requires skilled personnel. Much work has been conducted on assessing evaporation in agricultural crops. Even satellite data-based models are largely structured to assess evaporation in agricultural crops to the exclusion of understanding evaporation dynamics in natural woodlands, especially in African ecosystems. However, evaporation in woodland surfaces accounts for a significant portion of the water cycle over the terrestrial land mass. Understanding the characteristics of woodland ecosystem evaporation like interception and transpiration, is key to monitoring climate impact on woodland ecosystems, which is important for hydrological modelling and the management of water resources at various scales. One of the key aspects to enable this understanding is the knowledge of woodland phenological interaction with climate variables and the seasonal environmental regimes. “Vegetation phenology” refers to the periodic biological life cycle events of plants, such as leaf flushing and senescence, and corresponding temporal changes in vegetation canopy cover. Solar radiation, temperature and water availability (i.e., rainfall and soil moisture) are some of the key environmental variables that influence plant phenology. The attributes of woodland phenology, solar radiation, temperature and water availability differ across the diverse ecosystems globally, therefore, requires better understanding at a more local or regional level. Yet, evaporation of natural woodlands, especially in African ecosystems, with respect to phenological phases, are poorly characterised. This is largely because phenological studies have mainly focused on northern mid-latitude regions to the exclusion of other regions like the miombo of southern Africa. For increasing the predictive power of hydrological models, it is important to account for the interaction of woodland phenology with climate variables over the seasons and to characterise evaporation. This thesis aims at understanding the miombo woodland evaporation as a consequence of the vegetation phenological interaction with environmental and hydrological variables across seasons. Based on information in public domain, this study is the first independent field observation data-based characterisation of actual evaporation of the miombo woodland. The miombo is a heterogeneous woodland of the genus Brachystegia with the dominant species in the study location being Bauhinia petersenia, Brachystegia longifolia, Brachystegia boehmii, Brachystegia speciformis, Jubenerdia paninculata, Pericopsis angolensis, Uapaca kirkiana and Uapaca sansibarica. Unique phenological attributes are the simultaneous leaf fall, leaf flush and leaf colour changes that normally occur in the dry season between May and October. Most miombo woodland species are broad leaved and have developed dry season coping mechanisms such as deep rooting (capacity to access deep soil moisture and ground water) and vegetation water storage. The canopy closure is varied across the miombo woodland strata and is influenced by several factors including rainfall, soil type, soil moisture and nutrients, species diversity and temperature. These phenological attributes are species dependent, with varied response to phenological stimuli. This study sought to answer the question on the role of the phenology of the miombo woodland in the evaporation dynamics. The thesis also endeavoured to show how phenology, potentially, affects satellite-based evaporation estimates of the miombo woodland. The Luangwa Basin in southern Africa, a largely miombo woodland covered basin, was used as the study area. This basin was chosen because it is located in both the dry miombo woodland and wet miombo woodland in the Zambezian miombo woodland which is the largest strata of the miombo woodland. Furthermore, the Luangwa Basin is located in Zambia which is described as the country possibly with the highest diversity of trees and is said to be the centre of endemism for Brachystegia, with 17 species. To answer the questions on the importance of the phenology of the miombo woodland on the evaporation dynamics, the study used a coupled approach by applying both satellite data and field observations. Phenological changes of the miombo woodland across seasons were assessed using satellite-based data, the normalised difference vegetation index (NDVI) and leaf area index (LAI). Satellite-based data, land surface temperature (LST) and normalised difference infrared index (NDII), were used as proxies for climate variables canopy temperature and canopy vegetation water content. Point scale field estimates of evaporation across three different phenophases of the miombo woodland were obtained using the Bowen ratio distributed temperature sensing (BR-DTS) system. By measuring profiles of air temperature and wet bulb temperature, the evaporation could be estimated via the Bowen ratio method (BR-DTS). Six satellite-based evaporation estimates were compared across different phenophases of the miombo woodland. This was meant to observe the phenophases in which significant diferences in the trend and magnitude of satellite-based evaporation estimates occured. The general water balance approach was used to assess annual actual evaporation at basin scale. Consequently, satellite-based evaporation estimates were compared to the BR-DTS-based evaporation estimates at point scale and the water balance-based evaporation at basin scale. Results, based on satellite data, show that the phenology of the miombo woodland, i.e., changes in woodland canopy cover and photosynthetic activities, have a season-dependent correlation with climate variables. Woodland canopy cover, across phenophases and seasons, appear to be more influenced rather by water than temperature. This may explain the particular species-dependent buffering mechanisms during water limited conditions i.e., leaf shedding, deep rooting systems with access to ground water, and the vegetation water storage mechanisms. In agreement with available literature in public domain it appears there is little variation in canopy cover/closure (i.e., proxied by LAI) in wet miombo woodland in the dry season. At the wet miombo woodland site in Mpika, Zambia, the BR-DTS observations showed that, across the different phenophases, the actual evaporation trend and magnitude appeared to be more associated with the available energy than the changes in the woodland canopy cover. Further analysis showed that the net radiation has a greater influence on actual evaporation as it accounted for more variations in the actual evaporation compared to the changes in the woodland canopy cover (i.e., NDVI). The energy partitioning showed that available energy expenditure varied with phenological season. In the green down phenophase during the cool dry season the available energy was largely partitioned as sensible heat flux. As the temperature and net radiation begun to increase in the early dormant phenophase during the late cool dry season (July August) the available energy appeared to be equally partitioned between sensible and latent heat flux. In the late dormant phenophase during the early warm pre-rainy season (i.e., September) available energy was largely partitioned as latent heat flux. In the green-up phenophase during the late pre-warm rainy season (i.e., October) and early rainy season (i.e., November to December) the avialable energy was largely partitioned as latent heat flux. During the rain days the available energy appeard to be equally partition between latent and sensible heat flux. It appears that as the net radiation and canopy cover increased the available energy was largely partitioned as latent heat flux during the dry season. A remarkable observation was the continued rising trend of actual evaporation even during the lowest woodland canopy cover period in August and September. The rising trend in actual evaporation during the dry season may be due to the developed dry season water stress buffering mechanism such as deep rooting with access to moisture in deep soils and possibly access to ground water. The trend of the BR-DTS-based actual evaporation of the miombo woodland in the dry season points to the interaction between hydro-climate variables (i.e., precipitation linked soil moisture and net radiation) and the plant phenology. When compared to field observations, at point scale, all satellite-based evaporation estimates underestimated actual evaporation of a wet miombo woodland in the dry season and part of the early rainy season. Substantial underestimations were in the dormant and the green-up phenophases. Additionally, except for the WaPOR, the trends of all other satellite-based evaporation estimates differed from that of field observations. Plausible explanations for the behaviour (trend and magnitude) of satellite-based evaporation estimates in the dry season include the non-integration of soil moisture directly into the modelling of transpiration and the optimisation of the rooting depth. For instance, the use of proxies such as the NDVI and LST for soil moisture in surface energy balance models, such as SSEBop, results in uncertainities as the proxies are unable to take into account other factors that influence the sensible heat flux. In MOD16 the use of relative humidity and vapour pressure difference as proxies for soil moisture may be a source of uncertainty in estimating transpiration. On the other hand it has been observed that direct integration of soil moisture in the MOD16 algorithm appeared to improve the accuracy of actual evaporation estimates. This may explain why the WaPOR which integrate soil moisture stress in the algorithm appeared to have a smilar trend to field observations and also had higher estimates of actual evaporation compared to the other satellite-based evaporation estimates. It has also been shown that optimising the rooting depth improves the accuracy of transpiration estimates in vegetation with a dry season. Most miombo woodland species are deep rooting with access to deep soil moisture and potentially groundwater. Therefore, direct integration of soil moisture into the algorithms for the satellite-based evaporation estimates and optimising the rooting depth is likely to improve the accuracy of actual evaporation estimates for the miombo woodland. The phenophase-based comparison at pixel scale in dry miombo woodland and wet miombo woodland and at the Luangwa Basin miombo woodland scale showed similar results. In all three scenarios substantially high coefficients of variation in actual evaporation estimates among satellite-based evaporation estimates were observed in the water limited, high temperature and low woodland canopy cover conditions in the dormant phenophase. The coefficients of variation in actual evaporation estimates were also substantially high in the green-up phenophase at the boundary between the dry season and the rainy season. The lowest coefficients of variation in actual evaporation estimates were observed in water abundant, high temperature, high leaf chlorophyll content and high woodland canopy cover during the maturity/peak phenophase. The high coefficients of variation in actual evaporation estimates, among satellite-based evaporation estimates, in the dormant and green-up phenophases, points to the challenge of estimating the actual evaporation of the miombo woodland in the dry season and early rainy season. The same scenario emerged as was observed at point scale, with reference to field observations, in which satellite-based evaporation estimates which directly integrate soil moisture in their algorithm appeared to have higher estimates of actual evaporation in the dormant phenophase in the dry season. For instance, the FLEX-Topo and WaPOR integrate soil moisture in their algorithms. Compared to each other the FLEX-Topo and WaPOR appeared to have no statistically significant (p-value > 0.5) differences in their trends and mean estimates of actual evaporation in the dormant phenophase in the dry season. Compared to the FLEX-Topo and WaPOR the other four satellite-based evaporation estimates, GLEAM, MOD16, SSEBop and TerraClimate showed statisticantly significant (p-value < 0.05) differences in the trend and mean estimates of actual evaporation in the dormant phenophase in the dry season. Considering the canopy phenology and the associated physiological adaptation of the miombo woodland plants in the dry season, it appears that the direct integration of the soil moisture in the algorithms and optimising the rooting depth is likely to improve the accuracy of the satellite-based evaporation estimates. In the maturity/peak phenophase(s) during the mid-rainy season, compared to other satellite-based evaporation estimates, the MOD16 appeared to have significantly (p-value < 0.05) higher estimates of actual evaporation. The plausible explanation for this observation could be that the interception module of MOD16 is more responsive to the miombo woodland phenology. The wet miombo woodland intercepts between 17-20 percent of rainfall annually. Compared to the general annual water balance-based actual evaporation all six satellite-based evaporation estimates underestimated actual evaporation of the Luangwa Basin. The implication of this observation is that satellite-based evaporation estimates likely underestimates evaporation even in non-miombo woodland such as the mopane woodland that are also part of the larger Luangwa Basin vegetation landscape. However, for a comprehensive overview of the performance of the satellite-based evaporation estimates there is need for vegetation type and land-cover type based assessments of actual evaporation for the Luangwa Basin. At both point and basin scale-based assessments, there was a negative linear relationship between the spatial resolution of satellite-based evaporation estimates and the estimated actual evaporation. Satellite-based evaporation estimates with fine spatial resolutions showed lower underestimates compared to those with coarser resolutions. The implication is that the finer the spatial resolution the lower the underestimation. However, at both assessment scales, the linear relationships between the spatial resolutions and the evaporation estimates were statistically insignificant (i.e., p-value > 0.05). The reason for this outcome is exhibited in that some satellite-based evaporation estimates with relatively coarser spatial resolutions, i.e., SSEBop at both point and basin scale and TerraClimate at basin scale, underestimated less compared to MOD16 which had a finer spatial resolution. Furthermore, at basin scale a coarser spatial resolution estimate FLEX-Topo and a finer spatial resolution estimate WaPOR showed similar magnitude of actual evaporation in the dormant phenophase in the dry season. The implication of this observation is that other factors (i.e., heterogeneity in the landscape, model structure, processes and inputs) influence more the estimated actual evaporation rather than the spatial resolutions of the satellite-based evaporation estimates. Consequently, it appears that satellite-based estimates at finer spatial resolution with the structure, processes and inputs that couple canopy transpiration with the root zone storage, taking into account the vertical upward (beyond 2.5 m) and horizontal moisture flux as well as the canopy phenological changes, are likely to provide actual evaporation estimates that reflect actual conditions of the miombo woodland. This is demonstrated by the WaPOR estimates which appears to include these aspects in simulating actual evaporation. The field-based actual evaporation assessments were conducted in the wet miombo woodland. It is possible that the phenological response to changes in hydrological and climate regimes in the drier miombo woodland are different from the observations at the Mpika site. Therefore, there is need for similar observations to be performed in the drier miombo woodland and to compare the results. However, this thesis has demonstrated the importance of understanding and incorporating the canopy phenology and dry season physiological adaptation (i.e., deep rooting) of the miombo woodland in modelling actual evaporation. Additionally, for basins with heterogenous woodland types like the Luangwa, it is important to conduct actual evaporation assessments in the different vegetation types. This is likely to give a more representative understanding of basin scale evaporation dynamics. Nevertheless, this study has provided a foundation on which other studies can build towards a more comprehensive understanding of the actual evaporation dynamics in this unique woodland. ... Read more

The trend and magnitude of actual evaporation across the phenophases of miombo woodlands are unknown. This is because estimating evaporation in African woodland ecosystems continues to be a challenge, as flux observation towers are scant if not completely lacking in most ecosystems. Furthermore, significant phenophase-based discrepancies in both trend and magnitude exist among the satellitebased evaporation estimates (i.e. Global Land Evaporation Amsterdam Model (GLEAM), moderate resolution imaging spectroradiometer (MODIS), operational simplified surface energy balance (SSEBop), and water productivity through open-access remotely sensed derived data (WaPOR)), making it difficult to ascertain which of the estimates are close to field conditions. Despite the many limitations with estimation of evaporation in woodlands, the development and application of the distributed temperature system (DTS) is providing deepened insights and improved accuracy in woodland energy partitioning for evaporation assessment. In this study, the Bowen ratio distributed temperature sensing (BRDTS) approach is used to partition available energy and estimate actual evaporation across three canopy phenophases of the miombo woodland, covering the entire 2021 dry season (May–October) and early rain season (November– December) at a representative site in Mpika in Zambia, southern Africa. To complement the field experiment, four satellite-based evaporation estimates are compared to the field observations. Our results show that actual evaporation of the miombo woodland appears to follow the trend of the net radiation, with the lowest values observed during the phenophase with the lowest net radiation in the cool dry season and the highest values during the phenophase with peak net radiation in the early rainy season. It appears the continued transpiration during the driest period in the dormant phenophase (with lowest canopy cover and photosynthetic activities) may be influenced by the species-dependent adapted physiological attributes such as access to moisture in deep soils (i.e. due to deep rooting), plant water storage, and the simultaneous leaf fall and leaf flush among miombo plants. Of the four satellite-based evaporation estimates, only the WaPOR has a similar trend to the field observations across the three phenophases. However, all four satellitebased estimates underestimate the actual evaporation during the dormant and green-up phenophases. Large coefficients of variation in actual evaporation estimates among the satellite-based estimates exist in the dormant and green-up phenophases and are indicative of the difficulty in estimating actual evaporation in these phenophases. The differences between field observations and satellite-based evaporation estimates can be attributed to the model structure, processes, and inputs. ... Read more

Understanding the canopy cover relationship with canopy water content and canopy temperature in the Miombo ecosystem is important for studying the consequences of climate change. To better understand these relationships, we studied the satellite data-based land surface temperature (LST) as proxy for canopy temperature, leaf area index (LAI), and the normalized difference vegetation index (NDVI) as proxies for canopy cover. Meanwhile, the normalized difference infrared index (NDII) was used as a proxy for canopy water content. We used several statistical approaches including the correlated component regression linear model (CCR.LM) to understand the relationships. Our results showed that the most determinant factor of variations in the canopy cover was the interaction between canopy water content (i.e., NDII) and canopy temperature (i.e., LST) with coefficients of determination (R²) ranging between 0.67 and 0.96. However, the coefficients of estimates showed the canopy water content (i.e., NDII) to have had the largest percentage of the interactive effect on the variations in canopy cover regardless of the proxy used i.e., LAI or NDVI. From 2009-2018, the NDII (proxy for canopy water content) showed no significant (at alpha level 0.05) trend. However, there was a-n significant upward trend in LST (proxy for canopy temperature) with a magnitude of 0.17 °C/year. Yet, the upward trend in LST did not result in significant (at alpha level 0.05) downward changes in canopy cover (i.e., proxied by LAI and NDVI). This result augments the observed least determinant factor characterization of temperature (i.e., LST) on the variations in canopy cover as compared to the vegetation water content (i.e., NDII). ... Read more