Abstract. Evapotranspiration (ET) is one of the most important components in the water cycle. However, there are relatively few direct measurements of ET available (e.g. using flux towers). Nevertheless, various disciplines, ranging from hydrology to agricultural and climate sciences, require information on the spatial and temporal distribution of ET at regional and global scales. Due to the limited data availability, attention has turned toward satellite-based products to fill observational gaps. Various data products, including remote sensing (RS) products, have been developed and provide a large range of ET estimations. Across Africa, only a limited number of flux towers are available; hence, they are insufficient for the systematic evaluation of the available ET products. Thus, in this study, we conduct a methodological evaluation of nine existing RS-derived ET products as well as other available ET products in order to evaluate their reliability at the basin scale. A general water balance (WB) approach is used, where ET is equal to precipitation minus discharge for long-term averages. Firstly, ET products are compared with WB-inferred ET (ETWB) for basins that do not show long-term trends. The ET products and the calculated ETWB are then evaluated against the Budyko equation, which is used as a reference condition. The spatial characteristics of the ET products are finally assessed via the analysis of selected land cover elements across Africa: forests, irrigated areas and water bodies. Additionally, a cluster analysis is conducted to identify similarities between individual ET products. The results show that CMRSET, SSEBop and WaPOR rank highest in terms of the estimation of the long-term average mean ET across basins, with low biases and good spatial variability across Africa. GLEAM consistently ranks lowest in most evaluation criteria, although it has the longest available time period. Each product shows specific advantages and disadvantages. Depending on the study in question, at least one product should be suitable for a particular requirement. The reader should bear in mind that many products suffer from a large bias. Based on the evaluation criteria in this study, the three highest ranked products, CMRSET, SSEBop and WaPOR, would suit many users' needs due to the low biases and good spatial variability across Africa.
The assessment of water withdrawals for irrigation is essential for managing water resources in cultivated tropical catchments. These water withdrawals vary seasonally, driven by wet and dry seasons. A land use map is one of the required inputs of hydrological models used to estimate water withdrawals in a catchment. However, land use maps provide typically static information and do not represent the hydrological seasons and related cropping seasons and practices throughout the year. Therefore, this study assesses the value of seasonal land use maps in the quantification of water withdrawals for a tropical cultivated catchment. We developed land use maps for the main seasons (long rains, dry, and short rains) for the semi-arid Kikuletwa catchment, Tanzania. Three Landsat 8 images from 2016 were used to develop seasonal land use land cover (LULC) maps: March (long rains), August (dry season), and October (short rains). Quantitative and qualitative observation data on cropping systems (reference points and questionnaires/surveys) were collected and used for the supervised classification algorithm. Land use classifications were done using 20 land use and land cover classes for the wet season image and 19 classes for the dry and short rain season images. Water withdrawals for irrigated agriculture were calculated using (1) the static land use map or (2) the three seasonal land use maps. Clear differences in land use can be seen between the dry and the other seasons and between rain-fed and irrigated areas. A difference in water withdrawals was observed when seasonal and static land use maps were used. The highest differences were obtained for irrigated mixed crops, with an estimation of 572 million m3/year when seasonal dynamic maps were used and only 90 million m3/year when a static map was used. This study concludes that detailed seasonal land use maps are essential for quantifying annual irrigation water use of catchment areas with distinct dry and wet seasonal dynamics.
A tool called WetSpa-Urban was developed to respond to the need for precise runoff estimations in an increasingly urbanized world. WetSpa-Urban links the catchment model WetSpa-Python to the urban drainage model Storm Water Management Model (SWMM). WetSpa-Python is an open-source, fully distributed, process-based model that accurately represents surface hydrological processes but does not simulate hydraulic structures. SWMM is a well-known open-source hydrodynamic tool that calculates pipe flow processes in an accurate manner while runoff is calculated conceptually. Merging these tools along with certain modifications, such as improving the efficiency of surface runoff calculation and simulating flow at the sub-catchment level, makes WetSpa-Urban suitable for event-based and continuous rainfall–runoff modeling for urban areas. WetSpa-Urban was applied to the Watermaelbeek catchment in Brussels, Belgium, which recently experienced rapid urbanization. The model efficiency was evaluated using different statistical methods, such as Nash–Sutcliffe efficiency and model bias. In addition, a statistical investigation, independent of time, was performed by applying the box-cox transformation to the observed and simulated values of the flow peaks. By speeding up the simulation of the hydrological processes, the performance of the surface runoff calculation increased by almost 130%. The evaluation of the simulated 10 minute flow versus the observed flow at the outlet of the catchment for 2015 reached a Nash–Sutcliffe efficiency of 0.86 and a bias equal to 0.06.
Abstract. Evapotranspiration (ET) is one of the most important components in the water cycle. However, there are relatively few direct measurements of ET (using flux towers), whereas various disciplines ranging from hydrology to agricultural and climate sciences, require information on the spatial and temporal distribution of ET at regional and global scale. Due to limited data availability, attention has turned toward satellite based products to fill observational gaps. Various remote sensing data products have been developed, providing a large range of ET estimations. Across Africa only a limited number of flux towers are available which are insufficient for systematic evaluation of remotely sensed (RS) derived ET products. Thus we propose a methodology for evaluating RS derived ET data at the basin scale using a general water balance (WB) approach, where ET is equal to precipitation minus discharge for long-term annual averages. Firstly, RS ET products are compared with WB inferred ET for basins without long-term trends present. The RS products are then assessed according to spatial characteristics through analysing two land cover elements across Africa, irrigated areas and water bodies. A cluster analysis is also conducted to identify similarities between individual ET products. Finally, the RS products are evaluated against the Budyko equation. The results show that CMRSET, SSEBop and WaPOR rank highest in terms of estimation of long-term annual average mean ET across basins with low biases. Along with ETMonitor, the same three products rank highest in spatial distribution of ET patterns across Africa. GLEAM and MOD16 consistently rank the lowest in most criteria evaluation. Many of the products analysed in this study can be trusted depending on the study under question, keeping in mind some of these products have large biases in magnitude estimation. However our recommendation would be the three highest ranked products being CMRSET, SSEBop and WaPOR.
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