Anthropogenic alterations in urban areas influence the thermal environment causing elevated atmospheric and subsurface temperatures. The subsurface urban heat island effect is observed in several cities. Often shallow urban aquifers exist with thermal anomalies that spread laterally and vertically, resulting in the long-term accumulation of heat. In this study, we develop an analytical heat flux model to investigate possible drivers such as increased ground surface temperatures (GSTs) at artificial surfaces and heat losses from basements of buildings, sewage systems, subsurface district heating networks, and reinjection of thermal wastewater. By modeling the anthropogenic heat flux into the subsurface of the city of Karlsruhe, Germany, in 1977 and 2011, we evaluate long-term trends in the heat flux processes. It revealed that elevated GST and heat loss from basements are dominant factors in the heat anomalies. The average total urban heat flux into the shallow aquifer in Karlsruhe was found to be ∼759 ± 89 mW/m(2) in 1977 and 828 ± 143 mW/m(2) in 2011, which represents an annual energy gain of around 1.0 × 10(15) J. However, the amount of thermal energy originating from the individual heat flux processes has changed significantly over the past three decades.
Abstract. Knowledge on water and energy fluxes is a key for urban planning and design. Nevertheless, hydrological data for urban environments is sparse and as a result, many processes are still poorly understood and thus inadequately represented within models. We contribute to reduce this shortcoming by providing a dataset, which includes time series of soil moisture and soil temperature measured underneath 18 different permeable pavements (PPs) and 4 urban greenspaces located within the city of Freiburg (Germany). Time series were recorded with a high temporal resolution of 10 min with a total of 65 individual soil moisture sensors and cover a measuring period of 2 entire years (Nov. 2016 – Oct. 2018). The recorded time series contain valuable information on the soil hydrological behavior and demonstrate the effect of surface properties and surrounding urban structures on soil temperatures. In addition, we performed double-ring infiltration experiments, which in combination with the soil moisture measurements yielded soil hydrological parameters for the PPs including porosity, field capacity and infiltration capacity. We present this unique dataset, which is a valuable source of information for studying urban water and energy cycles. We encourage its usage in various ways e.g. for model calibration and validation purposes, to study thermal regimes of cities and to derive urban water and energy fluxes. The dataset is freely available at the FreiDok plus data repository at https://freidok.uni-freiburg.de/data/149321 and https://doi.org/10.6094/UNIFR/149321 (Schaffitel et al., 2019).
Abstract. Water fluxes at the soil–atmosphere interface are a key piece of information for studying the terrestrial water cycle. However, measuring and modeling water fluxes in the vadose zone poses great challenges. While direct measurements require costly lysimeters, common soil hydrologic models rely on a correct parametrization, a correct representation of the involved processes, and the selection of correct initial and boundary conditions. In contrast to lysimeter measurements, soil moisture measurements are relatively cheap and easy to perform. Using such measurements, data-driven approaches offer the possibility to derive water fluxes directly. Here we present FluSM (fluxes from soil moisture measurements), which is a simple, parsimonious and robust data-driven water balancing framework. FluSM requires only a single input parameter (the infiltration rate) and is especially valuable for cases where the application of Richards-based models is critical. Since permeable pavements (PPs) present such a case, we apply FluSM on a recently published soil moisture data set to obtain the water balance of 15 different PPs over a period of 2 years. Consistent with findings from previous studies, our results show that vertical drainage dominates the water balance of PPs, while surface runoff plays only a minor role. An additional uncertainty analysis demonstrates the ability of the FluSM-approach for water balance studies, since input and parameter uncertainties only have a small effect on the characteristics of the derived water balances. Due to the lack of data on the hydrologic behavior of PPs under field conditions, our results are of special interest for urban hydrology.
Abstract. Knowledge of water and energy fluxes is key for urban planning and design. Nevertheless, hydrological data from urban environments are sparse, and, as a result, many processes are still poorly understood and thus inadequately represented within models. We contribute to reducing this shortfall by providing a dataset that includes time series of soil moisture and soil temperature measured underneath 18 different permeable pavements (PPs) and 4 urban green spaces located within the city of Freiburg (Germany). Time series were recorded with a high temporal resolution of 10 min using a total of 65 individual soil moisture sensors and covering a measurement period of 2 years (November 2016–October 2018). The recorded time series contain valuable information on the soil hydrological behavior of PPs and demonstrate the effect of surface properties and surrounding urban structures on soil temperatures. In addition, we performed double-ring infiltration experiments, which in combination with the soil moisture measurements yielded soil hydrological parameters for the PPs, including porosity, field capacity and infiltration capacity. We present this unique dataset, which is a valuable source of information for studying urban water and energy cycles. We encourage its usage in various ways, e.g., for model calibration and validation purposes, study of thermal regimes of cities, and derivation of urban water and energy fluxes. The dataset is freely available from the FreiDok plus data repository at https://freidok.uni-freiburg.de/data/151573 and https://doi.org/10.6094/UNIFR/151573 (Schaffitel et al., 2019).
Interactive comment on "A distributed soil moisture, temperature and infiltrometer dataset for permeable pavements and green spaces" by Axel Schaffitel et al. Axel Schaffitel et al.
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