|Urban Water Interfaces (UWI)
|Deutsche Forschungsgemeinschaft (DFG)
|Project partner of the UWI research training group
Dr. Alby Duarte Rocha
Dr. Basem Aljoumani
|Prof. Dr. Birgit Kleinschmit
UWI is an interdisciplinary and international collaboration to advance the understanding of urban water interfaces by promoting innovative research to predict changes and anticipate future scenarios to improve water management and systems. To achieve this aim, the Technische Universität Berlin (TUB) and the Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB) stablished a unified framework of natural and technical interfaces to assess the quantitative impact of climate change on urban water systems. Multiple domains with natural and technical interfaces are considered, such as water surfaces, urban soils and vegetation, aquifers and sediments, water treatment and sewer systems.
The UWI project is organized in four common interfaces:
Doctoral students and research assistants (Postdoc) currently work on their own research projects, but also in common activities and interactions between projects and common topics.
Interfaces in urban watersheds
The research projects described below are part of the “interfaces in urban watersheds” common topic and they are focused on heat and vapor fluxes at the soil-vegetation-atmosphere interface in urban areas. The main aim of these research projects is to understand and model the relationship between evapotranspiration and urban landcover. To accomplish this, different modelling approaches using a combination of remote sensing and ancillary datasets are used to determine evapotranspiration rates at local and regional urban scales.
This project focuses on the fusion of remote sensing, machine learning, and climatological data to better model and understand heat and vapor fluxes (evapotranspiration, air temperature) in a heterogeneous urban environment. The main aims of this project are to 1) model and characterize the seasonal and diurnal variation of heat and vapor fluxes of urban vegetation using a combination of remote sensing (satellite, UAV) and field-based data; 2) validate modelled evapotranspiration (ET) estimates with in-situ ET estimates; and 3) to upscale ET estimates of urban vegetation spatially (urban scale) and temporally (multi-year) using satellite data, machine learning, and other modelling approaches (flux footprint modelling, Penman-Monteith). In the first phase of this project, urban air temperature at nighttime was accurately spatially modelled one day in advance at a high resolution by combining satellite data, crowdsourced weather data, and machine learning (Vulova et al. 2020). In the second phase of this project, a novel approach combining remote sensing, flux footprint modelling, and deep learning and machine learning is being applied to model urban ET. This approach can be applied to spatially upscale urban ET at a high resolution in the future. Furthermore, thermal and multispectral images collected in an urban research garden (the Steglitz Urban Ecohydrological Observatory), along with other field measurements (Leaf Area Index, soil moisture, stomatal conductance) will be used to model and validate ET estimates of urban vegetation at a local scale.
Modelling of evapotranspiration of urban vegetation using thermal and optical remote sensing - a physically-based approach using SCOPE model
This study aims to assess the feasibility to use the Soil-Canopy-Observation of Photosynthesis and Energy fluxes (SCOPE) model to predict evapotranspiration (ET) accurately in an urban environment. SCOPE model accounts for a wide range of surface-atmosphere interactions as it integrates radiative transfer and energy balance models (Tol et al., 2009). It will also evaluate the contributions of different remote sensing data, such as optical and thermal images from UAV and satellite platform to improve ET predictions with SCOPE models. This project will explore which of the four ET limiting factors (light, temperature, CO2 and water) is more critical for estimation purely based on remote sensing data.
Analyzing and predicting evaporation, infiltration, runoff, and solute transport of different paved urban soils
This associated project will collaborate with the UWI colleagues focusing on four objectives: (1) Estimating evaporation from different urban paved surfaces; (2) Investigating urban rainfall-runoff relationships and their effects on the variations of dissolved metals in roadside soils; (3) Assessing the impacts of rainfall intensity and duration on the soil solution salt concentration and soil moisture under different urban pavement types; and (4) Uncertainty assessment of solute transport under different urban pavement types.