Bares, V.

Fencl, M.

Fidranska, H.

Stransky, D.

I-Revues

NOVATECH 2016 
1 
Microwave links potential for runoff prediction: Case 
study Letnany 
Le potentiel des ondes cellulaires pour la prévision des 
rejets de temps de pluie : étude de cas de Letnany 
 
David Stransky*, Helena Fidranska**, Martin Fencl* and Vojtech 
Bares*  
 
*Czech Technical University in Prague, Faculty of Civil Engineering, Thakurova 
7, 166 29 Prague, Czech Republic (stranskyd@fsv.cvut.cz) 
**Sweco Hydroprojekt, Taborska 31, 140 16 Prague, Czech Republic 
 
RÉSUMÉ 
La gestion des eaux pluviales en milieu urbain nécessite des données pluviométriques d’une 
résolution spatiale et temporelle élevée, qui ne sont souvent pas disponibles. Des données intégrées 
sur les taux de pluviométrie provenant d’ondes cellulaires (MWL) permettraient potentiellement de 
remédier à cette situation puisque le réseau MWL est très dense dans les zones urbaines. Cet article 
étudie le potentiel du système MWL en termes de prédiction du ruissellement en zone urbaine. Il 
compare la performance du modèle de ruissellement en utilisant les données pluviométriques dans six 
scénarios différents de suivi des précipitations dérivés de champs de précipitations générés à partir de 
modèles stochastiques : informations pluviométriques complètes (référence), taux de précipitations 
mesuré par le réseau MWL et taux de pluviométrie mesuré par quatre installations différentes de 
pluviomètres. L’article met l’accent sur la description de la variation spatiale des précipitations plutôt 
que sur les incertitudes de l’instrumentation proprement dite. Les données pluviométriques (150 
chutes de pluie) pour les six scénarios, ont été dérivées de champs de précipitations générés à partir 
de modèles stochastiques utilisés comme données de base pour un modèle calibré de ruissellement. 
La performance du modèle est évaluée en fonction des formes hydrographiques, des volumes de 
ruissellement, des pics de rejet et du décalage temporel des pics de rejet. Les résultats montrent le 
potentiel considérable de la méthode MWL qui, pour tous les paramètres intéressants, présente une 
similitude très étroite avec le scénario de référence. 
 
ABSTRACT 
Urban storm water management requires rainfall data of high spatial and temporal resolution which is 
often not available. Path-integrated rain rate information from cellular microwave links (MWL) has a 
great potential to improve this situation as the MWL network is very dense in urban areas. The paper 
investigates the MWL potential in terms of urban storm runoff prediction. It compares the rainfall-runoff 
model performance when using rain rate input from six different rainfall monitoring scenarios derived 
from stochastically generated rainfall fields: complete rainfall information (reference), rain rates as 
measured by MWL network and rain rates as measured by four different rain gauge layouts. The 
paper focuses on effect of rainfall spatial variation description rather than uncertainties in 
instrumentation itself. Rainfall data (150 rainfall events) for six scenarios were derived from 
stochastically generated rain fields used as an input to a calibrated rainfall-runoff model. Model 
performance is evaluated with respect to hydrograph shapes, runoff volumes, peak discharges and 
time shift of peak discharges. Results show a high potential of the MWL method which in all metrics of 
interest exhibit a very close similarity with the reference scenario. 
 
KEYWORDS 
Telecommunication microwave links, quantitative precipitation estimates, rainfall monitoring, storm 
runoff prediction, urban hydrology 
SESSION 
2 
1 INTRODUCTION 
Rainfall is the main driver for urban runoff, and represents thus a crucial input for urban hydrology 
modelling. Uncertainties in rainfall measurements propagate directly to the predicted runoff (Fencl et 
al., 2013; Stransky et al., 2007). Runoff response in urban catchments is extremely sensitive to spatio-
temporal rainfall dynamics on very fine temporal and spatial scales (Berne et al., 2004; Schilling, 
1991). Actual state of national and regional rainfall measurement networks (even those specifically 
designed for urban hydrology tasks) is usually one order of magnitude sparser than optimal. A solution 
might be searched for in radar rainfall estimates, however, they are still affected by substantial errors 
(Berne and Krajewski, 2013) and the required high-resolution radar information is not always available. 
Recently, commercial microwave links (MWLs) from telecommunication networks have been 
suggested as a novel source of rainfall information (Leijnse et al., 2007; Messer et al., 2006), which 
could provide quantitative precipitation estimates (QPEs) on the radar-pixel scale or even finer 
resolutions. MWLs are point-to-point radio systems, which connect two remote locations, mostly at 
line-of-sight. They operate usually at millimetre wave lengths and rainfall drops represent a major 
source of the signal attenuation, and can provide path-average QPEs. 
The goal of this paper is to analyse (apart from instrumentation uncertainties) if using MWLs is a viable 
method compared to traditional methods using individual rain gauges (RG) or a network of them. A 
question raised is: Are path-average QPEs from MWLs comparable to point measurements from 
traditional network of RGs? 
 
2 MATERIAL AND METHODS 
2.1 Experimental catchment 
A district of Prague called Letnany (134 ha) was selected as an experimental catchment. The 
catchment is a mixture of residential (a housing estate), commercial and industrial areas. The 
catchment is drained by separate sewer system of the length of 18.2 km. There are no RGs 
permanently placed within the catchment. The nearest RG Ladvi is situated about 2 km west from the 
centre of the experimental catchment. The catchment is covered by 19 MWLs (Figure 1). 
 
Figure 1: Experimental catchment Letnany with MWL and different rain gauge layouts 
For purposes of presented study the experimental catchment was divided to 188 sub-catchments of 
average size 0.7 ha. 
2.2 Rainfall data 
One hundred fifty artificial rain events were generated by stochastic simulation of intermittent drop size 
distribution fields in time (Schleiss et al., 2012) with a pixel size of 100x100 meters (Figure 2) and time 
resolution 1 min. All scenarios described in chapter 2.3 are based on this data. 
2.3 Scenarios 
Six hypothetical scenarios with different rainfall information were studied (Table 1).  
NOVATECH 2016 
3 
 
Figure 2: Example of stochastically generated rain fields 
Table 1: Scenarios studied 
SCENARIO SCENARIO NAME SOURCE OF RAINFALL DATA 
A Reference 188 RGs placed in individual sub-catchments 
B MWLs 19 MWLs 
C Five RGs network of five rain gauges placed within the catchment (or in a 
close vicinity) 
D Three RGs network of three rain gauges placed within the catchment (or in a 
close vicinity) 
E One RG one rain gauge placed in the centre of catchment (as used for the 
rainfall-runoff model calibration) 
F Remote RG one rain gauge placed in the location of closest permanent RG Ladvi 
2.4 Simulations 
A calibrated rainfall-runoff model MIKE URBAN was used to simulate the scenarios described. In case 
of scenarios C and D, calculations were made for several different settings of RG network. Averaged 
values from these calculations (discharge Q, water depth h and velocity v) were used for further 
analysis. More than 2000 simulations were done in total. 
2.5 Performance criteria 
Simulation results were analysed at three cross sections (upper, middle and downstream part of the 
system). Comparison to reference scenario was done with respect to: 
• shape of the hydrograph: 
o correlation coefficient, 
o coefficient of determination, 
o least square method. 
• surcharge ratio (length of surcharged sewers related to the total length of the sewer system, in 
%) (Stransky and Fatka, 2005), 
• runoff volume V, 
• peak discharge Qmax and 
• time shift of peak discharges ∆T. 
 
3 RESULTS 
Results of the runoff simulations in the downstream profile of the sewer system are presented in Table 
2 and are similar with the results from the middle and upstream profiles. Average values of the 
SESSION 
4 
correlation coefficient, coefficient of determination and least square method, are presented. For the 
surcharge ratio, runoff volume and peak discharge, a number of runoff events (out of the total number 
of 150) exhibiting less than 10% error is given. Similarly, the number of runoff events with the time shift 
of Qmax less than 2 minutes is shown. 
Table 2. Comparison of the scenarios for the downstream profile 
SCENARIOS→ A B C D E F Reference MWLs Five RG Three RG One RG Remote RG 
Correlation coefficient Q 1.000 0.985 0.977 0.973 0.938 0.813 
Coef. of determination Q 1.000 0.971 0.957 0.952 0.898 0.736 
Least square method h 0.000 0.137 0.295 0.310 0.408 0.578 
Surcharge ratio 150 150 147 144 138 121 
Runoff volume V 150 111 102 102 58 35 
Peak discharge Qmax 150 104 98 99 45 31 
Time shift ∆T 150 111 112 110 83 35 
The runoff calculations based on MWLs (scenario B) exhibit the highest similarity with the reference 
scenario A (with exception of the time shift, where the five RGs scenario C performs slightly better). 
Scenarios B, C and D give very similar results, whereas using one RG within the catchment (scenario 
E) or in a remote location (scenario F) lead to a substantial error in the runoff prediction. 
 
4 CONCLUSIONS 
• using only one RG leads to substantial errors in runoff prediction even in a small catchment, 
• MWLs have a great potential to predict runoff with the same or a better performance than a 
network of RGs, 
• instrumentation uncertainties (especially relation between the signal attenuation and rainfall 
intensity)  must be further studied to enable the full exploitation of the theoretical potential of the 
MWLs method. 
 
5 ACKNOWLEDGEMENT 
This work was supported by the project of Czech Science Foundation (GACR) No. 14-22978S. Special 
thanks belong to Prazska Vodohospodarska spolecnost a.s. for providing us with rainfall-runoff model 
of the catchment and to Marc Schleiss for providing us with stochastically generated rain fields. 
 
LIST OF REFERENCES 
Berne, A., Delrieu, G., Creutin, J.-D., Obled, C. (2004). Temporal and spatial resolution of rainfall measurements 
required for urban hydrology. J. Hydrol.: Urban Hydrol. 299, 166–179. 
Berne, A., Krajewski, W.F. (2013). Radar for hydrology: Unfulfilled promise or unrecognized potential? Adv. Water 
Resour. 51, 357–366. 
Fencl, M., Rieckermann, J., Schleiss, M., Stránský, D., Bareš, V. (2013). Assessing the potential of using 
telecommunication microwave links in urban drainage modelling. Water Sci. Technol. 68, 1810–1818. 
Leijnse, H., Uijlenhoet, R., Stricker, J.N.M. (2007). Rainfall measurement using radio links from cellular 
communication networks. Water Resour. Res. 43. 
Messer, H., Zinevich, A., Alpert, P. (2006). Environmental Monitoring by Wireless Communication Networks. 
Science, 312, 713–713. 
Schilling, W. (1991). Rainfall data for urban hydrology: what do we need? Atmospheric Res. 27, 5–21. 
Schleiss, M., Jaffrain, J. and Berne, A. (2012). Stochastic simulation of intermittent DSD fields in time. Journal of 
Hydrometeorology 13 (2), 621–637. 
Stránský, D. and Fatka, P. (2005). Reliability and Safety of Sewer System. 10th International Conference on 
Urban Drainage (CD-ROM). Lyngby: Technical University of Denmark, BYG.DTU. 
Stransky, D., Bares, V., Fatka, P. (2007). The effect of rainfall measurement uncertainties on rainfall-runoff 
processes modelling. Water Sci. Technol. 55, 103–111. 


Le potentiel des ondes cellulaires pour la prévision des rejets de temps de pluie : étude de cas de Letnany

http://documents.irevues.inist.fr/bitstream/2042/60453/1/2C31-212STR.pdf

Le potentiel des ondes cellulaires pour la prévision des rejets de temps de pluie : étude de cas de Letnany

Abstract

Similar works

Full text

Available Versions

I-Revues