The regional early warning system for rainfall-induced landslides operating in Campania (Italy): performance evaluation of two warning strategies

Transcription

1 1st IMEKO TC-4 International Workshop on Metrology for geotechnics March 2016, Benevento (Italy) The regional early warning system for rainfall-induced landslides operating in Campania (Italy): performance evaluation of two warning strategies Michele Calvello, Gaetano Pecoraro, Luca Piciullo University of Salerno (Italy)

2 Landslide early warning systems (LEWS) 1. Risk analysis 2. Risk assessment 3. Risk management Risk mitigation by early warning Fell et al. (2005). A framework for landslide risk assessment and management. In: Landslide Risk Management, ISBN-13:

3 Landslide early warning systems (LEWS) Categories of LEWSs local systems and regional systems Warning systems operating at regional scale for rainfall-induced landslides (ReLEWS) assess the probability of occurrence of landslides, over appropriately-defined homogeneous alert zones of relevant extension, through the prediction and monitoring of meteorological variables Every Italian region has developed a ReLEWS over its territory, typically within a wider-purpose critical weather conditions warning system (DPCM 27/2/2004) The objectives of LEWSs should be defined considering the scale of analysis and the type of landslides. (Calvello and Piciullo, 2015) All the 21 ReLEWS have been independently designed and they are independently managed by the regional civil protection agencies Calvello M., Piciullo L. (2015). Citywide early warning systems for rainfall-induced landslides. Slopes and Geohazards, Proc. XVI ECSMGE, Vol. 4, p DPCM 27/02/2004, Indirizzi operativi per la gestione organizzativa e funzionale del sistema di allertamento nazionale, statale e regionale per il rischio idrogeologico ed idraulico ai fini di protezione civile. Italian national law.

4 Landslide early warning systems (LEWS) Categories of LEWSs local systems and regional systems Warning systems operating at regional scale for rainfall-induced Actors and issues System effectiveness landslides (ReLEWS) Risk perception People Managers Scientists Model performance Components RE = rainfall events LE = landslide events WE = warning events ReCoL = regional correlation law ReLWaM = regional landslide warning model ReLEWS = regional landslide early warning system

5 Objective of the paper Evaluation of the technical performance of the landslide warning system operating, at regional scale, in the Campania region. The EDuMaP method (Calvello and Piciullo, 2016) is employed to compare two warning strategies adopted by the warning system operating in the Campania region, based on cumulated rainfall thresholds over different lengths of time. M. Calvello, L. Piciullo (2016) Assessing the performance of regional landslide early warning models: the EDuMaP method. Nat. Hazards Earth Syst. Sci., vol.16, No.1, 2016, pp

6 The regional EWS for rainfall-induced landslides operating in the Campania region Managed by the regional civil protection agency as part of the regional warning system developed to deal with extreme weather conditions and with the so-called hydraulic and hydrogeological risks (i.e. floods and landslides) Rainfall monitoring network km 2 (8 warning zones, 551 municipalities) 154 rain gauges, 1 meteorological radar Landslide risk scenario Occurrence of shallow landslides and debris flows Warning strategies: precursors and thresholds 1. Warning zones predicted rainfall at 6, 12 and 24 hours 2. Municipalities ITALY cumulative monitored rainfall over 24, 48 and 72 hours Province Warning zone Rain gauge Km D.P.G.R. n /06/2005, Decreto del Presidente della Giunta Regionale della Campania: Il Sistema di Allertamento Regionale per il rischio Idrogeologico e Idraulico ai fini di protezione civile. Italian regional law.

7 The EDuMaP method (Calvello and Piciullo, 2016) The EDuMaP method assesses, in three steps, the performance of the warning model employed by an early warning system M.Calvello, L.Piciullo, Assessing the performance of regional landslide early warning models: the EDuMaP method Nat. Hazards Earth Syst. Sci., vol.16, No.1, 2016, pp

8 The EDuMaP method (Calvello and Piciullo, 2016) Step 1. Preliminary identification of landslide and warning events from analyses carried out on landslide and warning databases. M.Calvello, L.Piciullo, Assessing the performance of regional landslide early warning models: the EDuMaP method Nat. Hazards Earth Syst. Sci., vol.16, No.1, 2016, pp

9 The EDuMaP method (Calvello and Piciullo, 2016) Step 1. The results of the analysis on the landslide and warning databases depend on the values assumed by ten input parameters. Parameters of the events analysis Symbol Relevant for 1. Warning levels W lev Classification of WE 2. Landslide density criterion L den(k) Classification of LE 3. Lead time t LEAD Identification of WE 4. Landslide typology L typ Identification of LE 5. Minimum interval between Landslide Events Dt LE Identification of LE 6. Over time t OVER Identification of LE 7. Area of analysis A Temporal analyses of LE and WE 8. Spatial discretization adopted for warnings DA (k) Temporal analyses of LE and WE 9. Time frame of analysis DT Temporal analyses of LE and WE 10. Temporal discretization of analysis Dt Temporal analyses of LE and WE M.Calvello, L.Piciullo, Assessing the performance of regional landslide early warning models: the EDuMaP method Nat. Hazards Earth Syst. Sci., vol.16, No.1, 2016, pp

10 The EDuMaP method (Calvello and Piciullo, 2016) Step 2. The duration matrix report the time associated with the occurrence of landslide events in relation to the occurrence of warning events. d ij = T time ij M.Calvello, L.Piciullo, Assessing the performance of regional landslide early warning models: the EDuMaP method Nat. Hazards Earth Syst. Sci., vol.16, No.1, 2016, pp

11 The EDuMaP method (Calvello and Piciullo, 2016) Step 3. The assessment of the performance is based on the definition of a series of performance criteria and indicators applied to the duration matrix. M.Calvello, L.Piciullo, Assessing the performance of regional landslide early warning models: the EDuMaP method Nat. Hazards Earth Syst. Sci., vol.16, No.1, 2016, pp

12 00:00 02:00 04:00 06:00 08:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 24:00 hour of day early late early late late Regional landslide EWS performance Metrology for geotechnics 2016, Benevento (Italy). Prof. Michele Calvello The case study Test area and data bases Warning zone 3 (WZ3) km 2, 109 municipalities WZ3 north Time frame of analysis Rainfall measurements (source: regional civil protection agency) 44 rain gauges rainfall recorded every 10 minutes Campania Km WZ3 south Warning zone #3 (WZ3) Rain gauges Landslides Cava dè Tirreni (Cava) Cava dè Tirreni rain gauge (Cava rg) Landslides (source: FraneItalia project) news from on-line journalistic sources 2622 landslides in Italy for the years (213 in Campania region, 89 in WZ3) NIGHT MORNING AFTERN. EVEN. t L uncertainty 1 hour 2-4 hours 4-8 hours 24 hours 69 rainfall-induced phenomena Information on time of landslide occurrence

13 The case study Simulations and events analysis ID A rain gauges rainfall thresholds C-C Cava Cava rg 24, 48, 72 h Z3s-C WZ3 south Cava rg 24, 48, 72 h WE 4(VH) 4 3(H) 3 Z3-C WZ3 Cava rg 6, 12, 24 h Z3-one WZ3 one of 44 6, 12, 24 h 2(M) 2 1 2(S) 0 J F M A M J J A S O N D (I) -1 4(L) -2 LE WE 4(VH) 4 3(H) 3 2(M) 2 1 2(S) 0 J F M A M J J A S O N D (I) -1 4(L) -2 LE WE 4(VH) 4 3(H) 3 2(M) 2 1 2(S) 0 J F M A M J J A S O N D 3(I) -1 4(L) -2 LE WE 4(VH) 4 3(H) 3 2(M) 2 1 J F M A M J J A S O N D 2(S) (I) -1 4(L) -2 LE

14 Warning events Warning events Warning events Warning events Regional landslide EWS performance Metrology for geotechnics 2016, Benevento (Italy). Prof. Michele Calvello The case study Performance evaluation (C-C) 2(M) 3(H) 4(VH) (Z3s-C) Landslide events 2(S) 3(I) 4(L) Landslide events 2(S) 3(I) 4(L) Duration matrices and performance criteria 100% 100% 80% 60% 40% %FA %MA %TN 80% 60% 40% 20% 20% %CA 0% 0% C-C Z3s-C Z3-C Z3-one C-C Z3s-C Z3-C Z3-one %P %R %Y %G (M) Main positive and negative performance indicators 3(H) 4(VH) (Z3-C) 2(M) 3(H) 4(VH) (Z3-one) 2(M) 3(H) Landslide events 2(S) 3(I) 4(L) Landslide events (S) 3(I) 4(L) Indicator Symbol Formula Efficiency index Odds ratio Error rate Index of severity of false alerts Probability of serious nolandslides mistakes Ieff OR ER IFA PSM-NL (CA+TN)/S ij d ij (excluding d11) (CA+TN) /(MA+FA) (Red+Pur)/S ij d ij (excluding d11) (PUR&FA) / FA Pur/S ij d ij (for i=2-4, j=1) 1,0 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0,1 0,0 0,50 0,40 0,30 0,20 0,10 Ieff. OR C-C Z3s-C Z3-C Z3-one ER IFA PSM-NL 4(VH) ,00 C-C Z3s-C Z3-C Z3-one

15 Concluding remarks On the case study The comparison among the four simulations give some preliminary indications on what rainfall monitoring and warning strategies work better in the test area, yet further work, and other data, are surely needed to improve the reliability of the findings. On the performed analysis The EDuMaP method is a useful tool to evaluate the effect, in terms of performance, produced by different warning strategies within early warning systems for rainfall-induced landslides.