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.@en

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. @en

The rapid development of free and open-access hydrological models and coupling framework tools continues to present more opportunities for coupled model development for improved assessment of floodplain hydrology. In this study, we set up an Upper Zambezi hydrological model and a fully spatially hydrological-hydrodynamic coupled model for the Barotse Floodplain using GLOFRIM (GLObally applicable computational FRamework for Integrated hydrological– hydrodynamic Modelling). The hydrological and hydrodynamic models used are WFLOW and LISFLOOD-FP, respectively. The simulated flows generated by the wflow model for the upstream gauge stations before the Barotse Floodplain were quite similar and closely matched the observed flow as indicated by the evaluation statistics; Chavuma, nse = 0.738; kge = 0.738; pbias = 2.561 and RSR = 0.511; Watopa, nse = 0.684; kge = 0.816; pbias = 10.577 and RSR = 0.557; and Lukulu, nse = 0.736; kge = 0.795; pbias = 10.437 and RSR = 0.509. However, even though the wflow hydrological model was able to simulate the upstream hydrology very well, the results at the floodplain outlet gauge stations did not quite match the observed monthly flows at Senanga gauge station as indicated by the evaluation statistics: nse = 0.132; kge = 0.509; pbias = 37.740 and RSR = 0.9233. This is mainly because the representation of both floodplain channel hydrodynamics and vertical hydrological processes is necessary to correctly capture floodplain dynamics. Thus, the need for an approach that saves as a basis for developing fully spatially distributed coupled hydrodynamic and hydraulic models’ assessments for groundwater dependent tropical floodplains such as the Barotse floodplain, in closing the gap between hydrology and hydrodynamics in floodplain assessments. A fully coupled model has the potential to be used in implementing adaptive wetland management strategies for water resources allocation, environmental flow (eflows), flood control, land use and climate change impact assessments.

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