Support for this research was provided by the project HIDROCAES (CGL2011-27574-C02-01). E. Nadal-Romero is “Juan de la Cierva” researcher and Nicola Cortesi is FPI-PhD student both supported by Spanish Ministry of Economy and Competition. Weather Types and Erosion in a Mediterranean Mountain area (Central Spanish Pyrenees) Estela Nadal-Romero, Nicola Cortesi and Carlos González-Hidalgo University of Zaragoza, Geography and Land Management, Zaragoza (Spain) estelanr@unizar.es Weather types A A.E A.N A.NE A.NW A.S A.SE A.SW A.W C C.E C.N C.NE C.NW C.S C.SE C.SW C.W E N NE NW S SE SW W Day Frequency (%) 0 5 10 15 20 25 Araguás (2005-2012). Total days: 2421 Weather types A A.E A.N A.NE A.NW A.S A.SE A.SW A.W C C.E C.N C.NE C.NW C.S C.SE C.SW C.W E N NE NW S SW W Number of floods 0 10 20 30 40 50 60 n = 253 WTs A A.E A.N A.NE A.NW A.S A.SE A.SW A.W C C.E C.N C.NE C.NW C.S C.SE C.SW C.W E N NE NW S SE SW W Total suspended sediment yield (Mg) by WT 0 10 0 0 2000 3000 4000 5000 Frecuency (%) Product of magnitude and frequency 0 50 10 0 150 200 250 300 350 SY Frequency of floods Product of magnitude and frequency 0 0.05 0.10 0.15 0.20 0.25 Weather types A A.E A.N A.NE A.NW A.S A.SE A.SW A.W C C.E C.N C.NE C.NW C.S C.SE C.SW C.W E N NE NW S SE SW W Rainy days 0 20 40 60 80 10 0 Araguás (2005-2012). Rainy days: 612 WTs and precipitation in the Araguás catchment Introduction Acknowledgments Methods and analyses Previous researches in the Iberian Peninsula (IP) have analyzed the relationship between precipitations and specific WTs (Cortesi et al., 2012). The strong relationship detected between WTs and precipitation in the IP, coupled with the well-known relationship between storm-flow and soil erosion with precipitation, led us to suggest the hypothesis that there could be some links between WTs and flow and erosion. We analyze the relationship between the Weather Types (WTs) and floods, storm-flows and sediments in a Mediterranean mountain landscape. The daily circulation Weather Types affecting the IP are characterized through the use of a set of indices (NCAR project) who take into account physical and geometrical considerations adopted by Trigo and DaCamara (2000). These indices re-calculated by Cortesi et al. in 2012 were computed using Sea Level Pressure values (SPL) obtained for the 16 grid points (Fig. 1). 26 different Weather Types (WTs) were defined on a daily level; 8 WTs are purely directional types (NE, E, SE, S, SW, W, NW and N); 2 WTs are dominated by the strength of vorticity (Cyclonic C and Anti-cyclonic A types); and 16 other WTs are hybrid types (8 for each C or A hybrid). To ensure about the representativeness of the Araguás dataset temporal frame (2005-2012), we have analyzed WTs and precipitation from Araguás database and a longer database (1989-2011) from Jaca (AEMet). Daily values of precipitation, storm-flow and total sediment yield from Araguás catchment (October 2005 to May 2012) were associated with daily WTs. Cortesi N, Trigo R, González-Hidalgo JC, Ramos AM. 2012. High resolution reconstruction of monthly precipitation of Iberian Peninsula using circulation weather types. Hydrology and Earth System Science Discussion 9 (6): 6935-6977. Trigo RM, DaCamara C. 2000. Circulation weather types and their influence on the precipitation regime in Portugal. International Journal of Climatology 20 (13): 1559-1581. o The most frequent WTs during the study period were the Anti-cyclonic (21.4%), E (11.4%) and Cyclonic (7.4%) (Fig. 2). o The most frequent rainy days correspond to NW, W and C (Fig. 3 and Table 1). o The most probable rainy days would occur under Anti-cyclonic conditions, followed by Cyclonic and NW (Table 1; column 4). o The highest % of rainfall were recorded in the N.W (16.9%), C (15.1%) and W (13.6%). o The highest mean values were recorded in the C.W (9.5 mm) and C.NW (6.15 mm), but also C.N and C.SW produced rainfall events with mean values over 6 mm. WT Total days Day frequency (%) Rainy days Rainfall Probab. % rain Total rainfall/ total days (1) (2) (3) (4) (5) (6) A 519 21.4 46 0.4073 5.3 0.48 A.E 73 3.0 1 0.0012 0.3 0.17 A.N 74 3.1 15 0.0189 2.5 1.56 A.NE 56 2.3 4 0.0038 0.9 0.71 A.NW 68 2.8 30 0.0348 5.0 3.48 A.S 15 0.6 3 0.0008 0.4 1.28 A.SE 39 1.6 0 0.0000 0.0 0.04 A.SW 24 1 2 0.0008 0.2 0.32 A.W 54 2.2 19 0.0175 1.9 1.68 C 179 7.4 77 0.2352 15.1 3.95 C.E 47 1.9 11 0.0088 1.5 1.54 C.N 30 1.2 20 0.0102 3.8 5.88 C.NE 30 1.2 12 0.0061 1.4 2.23 C.NW 19 0.8 12 0.0039 2.5 6.15 C.S 19 0.8 1 0.0003 0.2 0.38 C.SE 24 1 7 0.0029 0.8 1.58 C.SW 13 0.5 9 0.0020 1.7 6.05 C.W 23 0.9 20 0.0078 4.7 9.50 E 277 11.4 21 0.0992 2.7 0.45 N 138 5.7 52 0.1224 7.4 2.52 NE 171 7.1 32 0.0934 3.4 0.93 NW 146 6.0 90 0.2242 16.9 5.45 S 36 1.5 7 0.0043 1.1 1.46 SE 151 6.2 6 0.0155 0.6 0.18 SW 75 3.1 31 0.0397 6.3 3.94 W 121 5.0 84 0.1734 13.6 5.30 TOTAL 2421 612  The analyses of daily precipitation and WTs during 1989-2011 (Jaca Station) ensure the representativeness of the results obtained in the Araguás catchment from 2005-2012, and corroborate the strong association between the defined WTs and precipitation. Table 1. WT, rainy days and precipitation from Araguás catchment (2005-2012) Fig. 2. Day Frequency (%) for WTs in the Araguás catchment Fig. 3. Rainy days for WTs in the Araguás catchment WTs, storm-flow and sediment in the Araguás catchment o From October 2005, a total of 253 flood events were identified in the Araguás catchment. o The most frequent WTs in which flood events occurred were C, NW and W (Fig. 4). o Three WTs (SW, NW and W) produced 55.3% of total storm-flow in 95 floods (Table 2, columns 1 and 3). o Three WTs (SW, A and W) produced 72% of total SY in only 70 flood events (Table 2, columns 5 and 1). Fig. 4. Contribution from different WTs to flood generation during the period October 2005-May 2012 WT Floods Flood freq. (%) % Flow Mean Flow (mm) % SY Mean SY(Mg) (1) (2) (3) (4) (5) (6) A 14 5.5 12.7 3.3 24.5 233.6 A.E 1 0.4 2.4 8.5 1 137.9 A.N 4 1.6 1.5 1.4 0.8 26.2 A.NE 1 0.4 0.1 0.2 0.5 60.6 A.NW 11 4.3 1.3 0.4 2.8 34.2 A.W 4 1.6 2.2 2.0 1.4 46.7 C 49 19.4 5.9 0.4 6.0 16.4 C.E 3 1.2 0.5 0.6 0.2 10.4 C.N 10 4.0 3.2 1.1 0.6 7.4 C.NE 2 0.8 0.2 0.3 0.0 0.9 C.NW 8 3.2 0.6 0.3 0.7 11.0 C.S 1 0.4 0.1 0.2 0.0 5.1 C.SE 2 0.8 0.2 0.4 0.0 1.3 C.SW 4 1.6 0.7 0.6 0.2 5.4 C.W 9 3.6 1.9 0.7 1.2 18.0 E 7 2.8 0.8 0.4 0.1 1.4 N 18 7.1 8.6 1.7 2.9 21.8 NE 4 1.6 0.8 0.7 0.4 14.1 NW 39 15.4 13.3 1.2 8.9 30.3 S 6 2.4 1.1 0.7 0.2 5.0 SW 19 7.5 28.8 5.5 30.5 214.3 W 37 14.6 13.2 1.3 17 61.4 TOTAL 253 100 100 100 Time (min) 0 200 400 600 800 10 0 0 1200 14 0 0 Q (l s -1 km -2 ) 0 10 0 0 2000 3000 4000 5000 SSC (g l -1 ) 0 200 400 600 800 10 0 0 Q (l s-1 km-2) SSC (g l-1) 10 March 2006 Rainfall (mm) 0 1 2 3 4 Rainfall: 36 mm Storm-flow: 16.95 mm Storm-flow coefficient: 0.47 Sediment yield: 6787.56 Mg Km2 29 October 2005 Rainfall (mm) 0 1 2 3 4 5 6 Time (min) 0 200 400 600 800 10 0 0 12 0 0 Q (l s -1 ) 0 500 10 0 0 1500 2000 2500 SSC (g l -1 ) 0 10 0 200 300 400 500 600 70 0 Q (l s-1) SSC (g l-1) Storm-flow: 9.82 mm Storm-flow coefficient: 0.35 Sediment Yield: 4972.79 Mg Km2 Anti-cyclonic South-Westerly Table 2. WT, floods, storm-flow and SY from Araguás catchment (2005-2012) Fig. 6. Seasonal contribution from different WTs to rainfall, storm-flow and suspended sediment yield during flood events recorded in the Araguás catchment. WTs have been grouped by wind direction and Anti-cyclonic and Cyclonic types where not shown in the graphics Fig. 8. Magnitude, frequency and work done by suspended sediment yield according to 26 WTs Fig. 7. Hyetograph, hydrograph, and sedigraph for the events occurring on 10 March 2006 (A flow pattern) and 29 October 2005 (SW flow pattern) Seasonal differences in % of rainfall, storm-flow and SYwere observed (Fig. 6) o In winter and spring NW and W flows predominate. o In autumn, rainfall and storm-flow are produced mostly by NW and SW but SYis produced nearby under SW direction flow. o In summer N and W flows predominate and the occurrence of convection processes. Fig. 8 shows magnitude-frequency distribution and “work done” according to the 26 WTs. The most efficient WTs in SY were W and SW Fig. 1. Grid formed by 16 dots from which the values of SLP are obtained