TY - JOUR

T1 - Performance of nearest neighbour metrics for pluvial flood nowcasts in urban catchments

AU - Sämann, Robert

AU - Graf, Thomas

AU - Neuweiler, Insa

N1 - Funding Information: The authors acknowledge the financial support by the Federal Ministry of Education and Research of Germany in the framework of Geotechnologies (project number 03G0846A); Bora Shehu for the collection and generation of the precipitation samples and her discussion about the model validation; Julian Wahl from ITWH for providing the surface and pipe model.

PY - 2022/1

Y1 - 2022/1

N2 - Urban flood warning systems need fast response times between the rainfall forecast and the flood alarm. Flood forecasts from physically based numerical models usually need much computation time. Flood forecasts based on databases from previous events or pre-simulated events can speed up the process of decision making. This work introduces and compares four distance metrics for temporal rainfall patterns used in a nearest neighbour based forecast system for dynamic water levels and velocities during pluvial floods. The system uses a database of 960 pre-calculated flood events. The performance of each metric is evaluated by analysis of time-series of flow variables. For the error quantification,a procedure to find a small number of representative locations in an urban catchment is described. A new approach to quantify the similarity of dynamic flow fields is introduced, which makes use of particle transport tracking. The four distance metrics are tested on forecast for four exemplary pluvial flood events resulting from rainfall of durations between 15 and 50 min and return-periods between 10 and 100 years. The best metric is based on the temporal precipitation pattern and takes the response time of the drainage system into account. If the pattern has a very short duration, a simpler characterisation-metric can be used, which takes the total volume, peak intensity and peak position into account.

AB - Urban flood warning systems need fast response times between the rainfall forecast and the flood alarm. Flood forecasts from physically based numerical models usually need much computation time. Flood forecasts based on databases from previous events or pre-simulated events can speed up the process of decision making. This work introduces and compares four distance metrics for temporal rainfall patterns used in a nearest neighbour based forecast system for dynamic water levels and velocities during pluvial floods. The system uses a database of 960 pre-calculated flood events. The performance of each metric is evaluated by analysis of time-series of flow variables. For the error quantification,a procedure to find a small number of representative locations in an urban catchment is described. A new approach to quantify the similarity of dynamic flow fields is introduced, which makes use of particle transport tracking. The four distance metrics are tested on forecast for four exemplary pluvial flood events resulting from rainfall of durations between 15 and 50 min and return-periods between 10 and 100 years. The best metric is based on the temporal precipitation pattern and takes the response time of the drainage system into account. If the pattern has a very short duration, a simpler characterisation-metric can be used, which takes the total volume, peak intensity and peak position into account.

KW - Dynamic water level

KW - Ensemble selection

KW - Nearest neighbour

KW - Pluvial flood forecast

UR - http://www.scopus.com/inward/record.url?scp=85120787133&partnerID=8YFLogxK

U2 - 10.1016/j.jhydrol.2021.127225

DO - 10.1016/j.jhydrol.2021.127225

M3 - Article

AN - SCOPUS:85120787133

VL - 604

JO - Journal of hydrology

JF - Journal of hydrology

SN - 0022-1694

M1 - 127225

ER -