This work presents a technique for debris-flow (DF) forecasting able to be used in the framework of DF early warning systems at regional scale. The developed system is applied at subbasin scale and is based on the concepts of fuzzy logic to combine two ingredients: (i) DF subbasin susceptibility assessment based on geomorphological variables and (ii) the magnitude of the rainfall situation as depicted from radar rainfall estimates. The output of the developed technique is a three-class warning (“low”, “moderate” or “high”) in each subbasin when a new radar rainfall map is available.
The developed technique has been applied in a domain in the eastern Pyrenees (Spain) from May to October 2010. The warning level stayed “low” during the entire period in 20 % of the subbasins, while in the most susceptible subbasins the warning level was at least “moderate” for up to 10 days.
Quantitative evaluation of the warning level was possible in a subbasin where debris flows were monitored during the analysis period. The technique was able to identify the three events observed in the catchment (one debris flow and two hyperconcentrated flow events) and produced no false alarm.
Intense and/or prolonged precipitation is the main agent triggering mass movement hazards like
landslides and debris flows (DF). These phenomena result in loss of life and goods in mountainous areas.
During the last 2–3 decades, there has been a tendency towards increasing the number of operational
landslide and DF early warning systems
In EWSs, hazard assessment for rainfall-induced DFs (either triggered by landslides or by erosion
and material entrainment into the flow) is based on combining (i) information about DF susceptibility
in the area under consideration and (ii) measurements and forecasts of rainfall
Study area:
DF susceptibility assessment is usually performed by relating the occurrence of DF with a number of
variables controlling DF initiation to identify the locations more prone to future events. In general,
it is agreed that including detailed information of these variables leads to improved DF susceptibility
assessment. However, the availability of very high-resolution information of certain variables at regional
scale is limited and, consequently, susceptibility mapping at these scales is based on simplified approaches.
Several of these variables are based on GIS-retrieved watershed morphometrics derived from
digital elevation models (DEMs) and sometimes include more specific geological or soil information
Rainfall inputs are another fundamental element of DF EWSs.
The magnitude of the rainfall situation (i.e., its potential to trigger shallow landslides or DFs) is,
in many cases, assessed by comparison of event rainfall with a critical rainfall threshold.
These thresholds are frequently obtained for different event durations and computed
(i) based on statistical analyses of regional records
Our area of study is in the central-eastern Pyrenees, where landslides and DFs are
common processes. There are several case studies
The main objective of this work was to develop a technique for DF warning that can be used in the framework of an operational EWS. The developed approach has been designed to fulfill the following conditions:
Real-time operation at regional scale: to keep the computational cost of the
technique into reasonable limits, we have divided our analysis domain into
subbasins of less than 50 km Simple outputs: the system has been designed to qualitatively assess DF
hazard in all the subbasins of the monitored domain by issuing a three-class
traffic-light code for warning levels “low”, “moderate” and “high”. Flexibility: the structure of the developed technique allows simple
implementation in new study areas and integration of approaches
to assess DF susceptibility or the magnitude of the rainfall situation alternative to
those implemented in this study.
The paper is organized as follows: Sect.
The study has been carried out in two subdomains in the central-eastern
Pyrenees (zones “A” and “B” in Fig.
The analysis of the susceptibility of the subbasins to the occurrence of DF
events is based on a number of geomorphological variables derived from the
DEM. These variables have been related to the occurrence of DF in the
subbasins of the analysis domain (see Sect.
The rainfall data used in this study are radar quantitative precipitation
estimate (QPE) maps of 30 min rainfall accumulations with a resolution of
1 km. These maps have been produced with the Integrated Tool for
Hydrometeorological Forecasting
The analyzed period is the debris-flow season of 2010 from 1 May to 31 October.
In the study area this was a rather wet period, with rainfall
accumulations over 600 mm in some areas and without significant snow events.
The comparison between radar rainfall estimates and rain gauge observations
shows no systematic bias and a root mean square relative error of 15 %
for the 159 rain gauges within the radar coverage (Fig.
The main goal of this work is to develop a flexible approach to classify DF
warnings into three levels (“low”, “moderate” and “high”) at regional scale
that can be implemented in real time in the framework of an EWS. The
developed technique (a schematic diagram is shown in Fig.
DF susceptibility based on geomorphologic variables (Sect. the magnitude of the rainfall situation as depicted from radar QPE
(Sect.
The combination of these two ingredients is done through a fuzzy rule to determine the warning level when a new radar QPE map is available.
Schematic diagram of the proposed technique for DF warning at subbasin scale.
The approach applied for assessing DF susceptibility is based on the
relationship between geomorphological characteristics and the occurrence of
DFs at subbasin scale. In the study area,
The overlapping area between the pdf curves for non-reactive and reactive
subbasins has been used to assess the skill of these geomorphological
variables to discriminate between reactive and non-reactive subbasins. This
is a very simple and intuitive criterion
Histograms for the four geomorphological variables used for
susceptibility assessment.
Among the 18 analyzed geomorphological variables, the subbasin maximum, mean
and minimum heights (respectively,
To guarantee the independence of the variables, only one height variable has
been used (
The four variables (
Membership functions used to assess the susceptibility of the
subbasins based on
In general, the design of the membership functions implies a certain
degree of subjectivity, and consequently they are usually defined as simple
curves. The most common membership functions are triangular, trapezoidal,
piecewise linear or Gaussian that reproduce the user's knowledge of the
problem
For each of the variables used to assess subbasin susceptibility (
The database presented previously has been used to estimate the proportion of
subbasins of type
These curves
Description of the geomorphological variables used for DF susceptibility assessment
and weight estimated with Eq. (
The weights used to combine the membership degree of the four variables,
With this method, similar weights have been obtained for
The susceptibility classifier produces three maps with the membership degree of each subbasin to the three susceptibility classes (“low”, “moderate” and `high”). Since the assessment of subbasin susceptibility is based on static geomorphological variables, these maps are used as static information.
Figure
Beyond what has been explained about the design of the membership functions
in Sect.
Classification of DF subbasin susceptibility in the study area.
The second element of the developed technique is the characterization of the
rainfall situation in terms of its potential to trigger DFs. We have adopted
the results obtained with the physically based model of
Example of the curves used for diagnosing the percent of subbasin unstable area based on rainfall duration and mean intensity. This case is for an antecedent rain of 40 mm.
In our study, radar rainfall estimates have been used to obtain the values of
AR,
It has to be noted that the model of
The subbasin unstable area computed with the model of
The membership functions used for this variable are also piecewise linear
(see Fig.
Membership function for the unstable area used in the assessment of the magnitude of the rainfall event. The green, orange and red lines correspond, respectively, to the membership functions for the classes “weak”, “moderate” and “severe” rainfall situation.
Similarly as for the susceptibility classifier, this classifier produces
three
maps with the membership degree
For the implementation of this module, decisions have been made regarding the
rainfall product and the definition of rainfall event. We have chosen to use
30 min accumulations aggregated over the area of each subbasin. This seems
to be a good compromise to capture the rapid evolution of local convective
phenomena affecting small areas at a reasonable computational cost. On the
other hand, the definition of rainfall event plays an important role in the
performance of the slope stability model of
Example of the implementation of the developed technique over the
analysis domain on 23 July 2010 at 01:30 UTC:
Finally, it is worth pointing out that each subbasin is treated independently. Consequently, in different subbasins rainfall events start and end at different times, with different conditions of antecedent rainfall, and the computation of the unstable area uses different rainfall intensities and event durations.
The DF warning level,
For example, in subbasins with “low” susceptibility (
Evaluating the three expressions of Eq. (
Figure
The developed classifier has been implemented in two subdomains in the eastern Pyrenees in the period 1 May–31 October 2010. The presentation of the results focuses first on an overall analysis of the warning level obtained with the developed technique along the analyzed period; in the second part, its performance is evaluated for specific subbasins during selected heavy rain events.
Figure
Rule used to derive the DF warning level from the combination of subbasin DF susceptibility and the magnitude of the rainfall situation.
Number of days for which the warning level in the period 1 May to
31 October 2010 was
The results obtained for the analysis period show that in some basins the warning level was “high” for a significant number of days and, consequently, we would expect some DF occurrence. However, validation of these results is difficult, because no systematic DF records are available in the area of study for the analysis period. Furthermore, in some of the cases there might be DF occurrence but with no impact on people or goods. Thus, very little information remains for validation of our results.
The only alternative for quantitative analysis of the results has been focusing on a few subbasins where DF records exist. Next section focuses on the results obtained in a subbasin where DFs were systematically monitored during the analysis period.
This section analyzes the performance of the developed technique in the
catchment of the Rebaixader torrent (a “moderately” susceptible subbasin
located in zone A near the village of Senet, Lleida, Spain; Fig.
Scatterplot of 24 h accumulations recorded with the Senet rain gauge (located in the Rebaixader catchment) and the Creu del Vent radar in the period from 1 May to 31 October 2010.
Time series of 30 min rain rate observed with the Barruera and
Senet rain gauges (blue and red solid lines, respectively) during five rainfall
events in the Rebaixader catchment. The two dashed lines correspond to the
radar QPE collocated with the two rain gauges. The top color bar shows the
time series of the warning level obtained in the Rebaixader subbasin: green,
orange and red correspond, respectively, to DF warning level “low”,
“moderate” and “high”. The orange and red triangles on the
Rainfall observations in the catchment are recorded with a rain gauge
collocated with the geophones (hereafter referred to as the Senet rain gauge).
A second rain gauge exists 6 km from the catchment, in the nearby village of
Barruera. During the studied period, the Senet and the Barruera rain gauges
accumulated 748 and 699 mm, respectively, whereas radar estimated 696
and 668 mm. The scatterplots of radar vs. rain gauge daily accumulations show
remarkable agreement (see Fig.
During the analysis period the monitoring system detected three significant
cases: one debris flow and two hyperconcentrated flows (also called debris
floods); the latter can also be hazardous for persons and infrastructure
This section analyzes the results obtained in the catchment for five
illustrative rainfall events, including the four cases for which the obtained
warning level was either “moderate” or `high” during the analysis period (see
Table
Summary of the results obtained in the Rebaixader subbasin
for the events presented in Sect.
This event produced a large part of the rainfall accumulated over the
catchment in the month of May. Figure
Although the comparison between radar and rain gauge observations in Barruera
(Fig.
During this event a local convective rainstorm affected the basin for around
4 h (see Fig.
The DF warning level changed to “high” on 11 July 2010 at 12:30 UTC, lasting until the end of the event. This coincides almost exactly with the geophone signal, which started at 12:43 UTC.
During this event the obtained DF warning level was “moderate” or “high” in a
large number of subbasins due to numerous convective cells developing and
crossing the entire analysis domain (a characteristic rainfall intensity map
for this event is shown in Fig.
A short period of intense rainfall affected the Rebaixader catchment at the
beginning of the event (21 July 2010, 18:00–21:00 UTC). However,
Fig.
This same event probably produced DFs in many other subbasins. In particular,
M. Hürlimann (personal communication, 2012) reported DFs in the Erill
torrent, a catchment with frequent DF activity, and in the Port Ainé
catchment (subbasins 2 and 3 in Fig.
In the Erill subbasin, the DF warning level changed to “moderate” on
22 July 2010 at 17:00 UTC (Fig.
In the Rebaixader subbasin, the signal of the geophones was associated with a
debris flood starting on 9 October 2010 at 20:59 UTC, coinciding with heavy
rainfall intensities over the basin (Fig.
Same as Fig.
A technique for issuing DF warnings using radar rainfall maps has been developed and implemented into two subdomains in the central-eastern Pyrenees. We have opted for a simple and flexible fuzzy logic technique that classifies the DF warning level into “low”, “moderate” and “high” based on two ingredients: (i) the DF susceptibility of the subbasins and (ii) the magnitude of the rainfall situation.
The performance of the technique has been demonstrated for the warm season of 2010. For this period, the technique estimated “moderate” and “high” warnings in many of the subbasins of the analysis domain, especially related to a few intense rainfall events. This analysis also confirmed the expected correspondence between the areas with a large number of days with “moderate” and “high” DF warnings and the areas with susceptible subbasins affected by large amounts of precipitation.
The lack of extensive reports of DF occurrence in the area makes
the systematic verification of the DF warning level estimated with the
technique over the entire domain impossible. Geophone records of a monitoring system
were available in a “moderately” susceptible subbasin, which allowed studying
the performance of the developed technique during the DF season of 2010. In
this subbasin, the technique did not produce any false alarm, showing the
behavior of the technique in events with moderate rainfall intensities for
which no DF activity was reported and issued significant warnings during all
the reported cases. The results are very positive in situations of DFs: this
is the case of the event of 11 July 2010 in the Rebaixader subbasin (the
timing of the delivered DF hazard warning matches geophone records), and the
case occurred in the Erill catchment during the night of 22–23 July 2010, for
which the warning level was “high”. The exact timing of the latter event is
unknown, but the obtained warning level seems consistent with the time series
of rainfall in the basin. Finally, for all the debris flood cases in the
Rebaixader catchment, the warning level turned into “moderate” with some
delay with respect to geophone records. This is due to the fact that the
intensity–duration curves of
The high space–time resolution of radar QPE products fits the requirements of
DF early warning systems: they provide at least one rainfall measurement in
each subbasin, which cannot be guaranteed with operational rain gauge networks
at regional scale. However, it is fundamental to guarantee the quality of QPE
products
In this work, we have used two data sets available in the analysis domain.
The geomorphological variables derived by The results of the model of
One of the advantages of the developed technique is that its modules can be
replaced easily. In this sense, other methods for assessing DF susceptibility
Finally, in the context of a DF EWS, it would be necessary to implement the
developed methodology for DF warning with high-resolution rainfall forecasts
to extend the lead time to take effective action. The lead times of NWP models
(typically, beyond 1 day) enable earlier preparedness and allow preparing
effective emergency and response plans. However, DFs are sometimes triggered
by small-scale rainfall systems that are not well resolved by most available
NWP systems. At these scales, radar-based nowcasting techniques
We acknowledge the Catalan Weather Service (SMC) for providing the radar data and rain gauge observations and the Catalan Water Agency for providing rain gauge observations. We thank the contribution of Clara Unzeta, who worked on a preliminary version of this study in the context of her civil engineering undergraduate project. We are also indebted with V. Medina, G. Chevalier, F. Bregoli and A. Bateman (Sediment Transport Research Group, Technical University of Catalonia) for providing the data used in the susceptibility analysis and the intensity-duration curves obtained with the slope stability model. This work has been done in the framework of the EC project IMPRINTS (FP7-ENV-2008-1 IMPRINTS 226555) and the Spanish project ProFEWS (CGL2010-15892). The debris-flow monitoring is funded by the Spanish project DEBRISTART (CGL2011-23300). The first author is supported with a grant from the Ramón y Cajal Program of the Spanish Ministry of Economy and Competitiveness (RYC2010-06521). Edited by: A. Günther Reviewed by: J.-P. Malet and one anonymous referee