Next Article in Journal
Topoclimatic Zoning and Representative Areas as Determined by an Automatic Weather Station (AWS) Network in the Atacama Region, Chile
Previous Article in Journal
Effectivity and Cost Efficiency of a Tax on Nitrogen Fertilizer to Reduce GHG Emissions from Agriculture
Previous Article in Special Issue
Impacts of Weather Types on Soil Erosion Rates in Vineyards at “Celler Del Roure” Experimental Research in Eastern Spain
 
 
atmosphere-logo
Article Menu

Article Menu

Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Relationship of Weather Types on the Seasonal and Spatial Variability of Rainfall, Runoff, and Sediment Yield in the Western Mediterranean Basin

by
D. Peña-Angulo
1,*,
E. Nadal-Romero
1,
J.C. González-Hidalgo
2,
J. Albaladejo
3,
V. Andreu
4,
H. Bahri
5,
S. Bernal
6,
M. Biddoccu
7,
R. Bienes
8,
J. Campo
4,
M.A. Campo-Bescós
9,
A. Canatário-Duarte
10,
Y. Cantón
11,12,
J. Casali
9,
V. Castillo
3,
E. Cavallo
7,
A. Cerdà
13,
P. Cid
14,
N. Cortesi
15,
G. Desir
16,
E. Díaz-Pereira
3,
T. Espigares
17,
J. Estrany
18,
J. Farguell
19,
M. Fernández-Raga
20,
C.S. Ferreira
21,
V. Ferro
22,
F. Gallart
23,
R. Giménez
9,
E. Gimeno
4,
J.A. Gómez
24,
A. Gómez-Gutiérrez
25,
H. Gómez-Macpherson
24,
O. González-Pelayo
26,
O. Kairis
27,
G.P. Karatzas
28,
S. Keesstra
29,30,
S. Klotz
31,
C. Kosmas
27,
N. Lana-Renault
32,
T. Lasanta
1,
J. Latron
23,
R. Lázaro
33,
Y. Le Bissonnais
34,
C. Le Bouteiller
31,
F. Licciardello
35,
J.A. López-Tarazón
36,37,
A. Lucía
38,
V.M. Marín-Moreno
39,
C. Marín
16,
M.J. Marqués
40,
J. Martínez-Fernández
41,
M. Martínez-Mena
3,
L. Mateos
24,
N. Mathys
31,
L. Merino-Martín
42,43,
M. Moreno-de las Heras
23,44,
N. Moustakas
27,
J.M. Nicolau
45,
V. Pampalone
46,
D. Raclot
34,
M.L. Rodríguez-Blanco
47,
J. Rodrigo-Comino
13,48,
A. Romero-Díaz
49,
J.D. Ruiz-Sinoga
50,
J.L. Rubio
4,
S. Schnabel
25,
J.M. Senciales-González
50,
A. Solé-Benet
33,
E.V. Taguas
39,
M.T. Taboada-Castro
51,
M.M. Taboada-Castro
52,
F. Todisco
53,
X. Úbeda
19,
E.A. Varouchakis
28,
L. Wittenberg
54,
A. Zabaleta
55 and
M. Zorn
56
add Show full author list remove Hide full author list
1
Instituto Pirenaico de Ecología, IPE-CSIC, 22700 Zaragoza, Spain
2
Departamento de Geografía, Universidad de Zaragoza, 50009 Zaragoza, Spain
3
Soil and water conservation research group, CEBAS-CSIC, 30100 Murcia, Spain
4
Department of Environmental Quality and Soils, Desertification Research Centre-CIDE (CSIC, UV, GV), Moncada, 46113 Valencia, Spain
5
National Research Institute for Rural Engineering, Water, and Forestry (INRGREF), Carthage University, Carthage 1054, Tunisia
6
Integrative Freshwater Ecology Group, Centre d’Estudis Avançats de Blanes (CEAB-CSIC), 17300 Blanes, Girona, Spain
7
Institute for Agricultural and Earthmoving Machines (IMAMOTER), National Research Council of Italy (CNR), 10135 Torino, Italy
8
Departamento Investigación Aplicada y Extensión Agraria, Instituto Madrileño de Investigación y Desarrollo Rural, Agrario y Alimentario (IMIDRA), 28800 Madrid, Spain
9
Department of Engineering, ISFOOD Institute, Public University of Navarre, 31006 Pamplona, Spain
10
Research Center for Natural Resources, Environment and Society (CERNAS), Polytechnic Institute of Castelo Branco, School of Agriculture, Castelo Branco, Portugal, Research Center GEOBIOTEC, UBI, 6201 Covilhã, Portugal
11
Department of Agronomy (Soil Science Area), University of Almeria. Engineering High School, 04120 Almeria, Spain
12
Centro de Investigación de Colecciones Científicas de la Universidad de Almería (CECOUAL), University of Almería, 04120 Almeria, Spain
13
Soil Erosion and Degradation Research Group, Department of Geography, University of Valencia, 46010 Valencia, Spain
14
Fall Creek Farm & Nursery, Tala 45300, Mexico
15
Department of Earth Sciences, Centro Nacional de Supercomputación, 08034 Barcelona, Spain
16
Departamento de Ciencias de la Tierra, Universidad de Zaragoza, 50009 Zaragoza, Spain
17
Departamento de Ciencias de la Vida, Unidad de Ecología, Universidad de Alcalá, 28801 Alcalá de Henares, Madrid, Spain
18
Department of Geography, Institute of Agroenvironmental and Water Economy Research -INAGEA, University of the Balearic Islands, 07122 Palma, Spain
19
Environmental Mediterranean Research Group (GRAM), Departament of Geography, University of Barcelona, 08007 Barcelona, Spain
20
Department of Physics, IMARENAB, University of Leon, 24071 Leon, Spain
21
Research Center for Natural Resources, Environment and Society (CERNAS), Polytechnic Institute of Coimbra, Agrarian School of Coimbra, 1349 Coimbra, Portugal
22
Department of Earth and Marine Science, University of Palermo, 90133 Palermo, Italy
23
Surface Hydrology and Erosion group, Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034 Barcelona, Spain
24
Instituto de Agricultura Sostenible (CSIC), 14004 Córdoba, Spain
25
INTERRA Research Institute, University of Extremadura, 06006 Cáceres, Spain
26
Department of Environment and Planning, Earth Surface Processes Team (ESP) Centre for Environmental and Marine Studies (CESAM), University of Aveiro Campus Universitario de Santiago, 3810 Aveiro, Portugal
27
Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 3800 Athens, Greece
28
School of Environmental Engineering, Technical University of Crete, 70013 Chania, Greece
29
Team Soil Water and Land Use, Wageningen Environmental Research, Wageningen UR, 6708 Wageningen, The Netherlands
30
Civil, Surveying and Environmental Engineering, The University of Newcastle, Callaghan 2308, Australia
31
University of Grenoble, INRAE, UR ETNA, 38000 Grenoble, France
32
Area of Geography, DCH, University of La Rioja, 26006 Logroño, Spain
33
Experimental Station of Arid Zones, EEZA-CSIC, 04120 Almería, Spain
34
LISAH, University Montpellier, INRAE, IRD, Institut Agro, 34 090 Montpellier, France
35
Department of Agriculture, Food and Environment, University of Catania, 95124 Catania, Italy
36
Fluvial Dynamics Research Group—RIUS, University of Lleida, 25003 Lleida, Spain
37
Institute for Environmental Science and Geography, University of Potsdam, 14476 Potsdam, Germany
38
Center for Applied Geosciences, Faculty of Science, Eberhard Karls Universität Tübingen, 72074 Tübingen, Germany
39
Departamento de Ingeniería Rural, University of Cordoba—ETSIAM Campus Rabanales, Leonardo Da Vinci Building, 14014 Córdoba, Spain
40
Departamento de Geología y Geoquímica, Universidad Autónoma de Madrid, 28049 Madrid, Spain
41
Instituto Hispano Luso de Investigaciones Agrarias, University of Salamanca, 37008 Villamayor, Spain
42
University of Montpellier, AMAP, INRAE, CIRAD, CNRS, IRD, PS2 TA/A51, 34 398, Montpellier CEDEX 5, France
43
CEFE, University Montpellier, CNRS, EPHE, IRD, University Paul Valéry Montpellier 3, 34 398, Montpellier, France
44
Department of Ecology, Desertification Research Centre-CIDE (CSIC, UV, GV), Moncada, 46113 Valencia, Spain
45
Department of Agriculture and Environmental Sciences, University of Zaragoza, 50009 Zaragoza, Spain
46
Department of Agriculture, Food and Forest Sciences, University of Palermo, 90133 Palermo, Italy
47
History, Art and Geography Department, GEAAT Group, University of Vigo, Campus as Lagoas, 36310 Ourense, Spain
48
Physical Geography, Trier University, 54296 Trier, Germany
49
Departamento de Geografía, Universidad de Murcia, Campus de La Merced, 30100 Murcia, Spain
50
Department of Geography, University of Málaga, 29016 Málaga, Spain
51
Faculty of Sciences, Centre for Advanced Scientific Research (CICA), University of A Coruna, 15001 A Coruña, Spain
52
ETSIIAA, Area of Soil Science and Soil Chemistry, University of Valladolid, 47002 Palencia, Spain
53
Agricultural and Biosystems Engineering Research Unit, Department of Agriculture-Food and Environmental Sciences, University of Perugia, 06121 Perugia, Italy
54
Department of Geography and Environmental Studies, University of Haifa, Haifa 3498838, Israel
55
Hydro-Environmental Processes Research Group, Science and Technology Faculty, University of the Basque Country, Leioa, Basque Country, 48940 Leioa, Spain
56
Geographical Institute, Research Centre of the Slovenian Academy of Sciences and Arts, 1000 Ljubljana, Slovenia
*
Author to whom correspondence should be addressed.
Atmosphere 2020, 11(6), 609; https://doi.org/10.3390/atmos11060609
Submission received: 8 May 2020 / Revised: 29 May 2020 / Accepted: 31 May 2020 / Published: 9 June 2020

Abstract

:
Rainfall is the key factor to understand soil erosion processes, mechanisms, and rates. Most research was conducted to determine rainfall characteristics and their relationship with soil erosion (erosivity) but there is little information about how atmospheric patterns control soil losses, and this is important to enable sustainable environmental planning and risk prevention. We investigated the temporal and spatial variability of the relationships of rainfall, runoff, and sediment yield with atmospheric patterns (weather types, WTs) in the western Mediterranean basin. For this purpose, we analyzed a large database of rainfall events collected between 1985 and 2015 in 46 experimental plots and catchments with the aim to: (i) evaluate seasonal differences in the contribution of rainfall, runoff, and sediment yield produced by the WTs; and (ii) to analyze the seasonal efficiency of the different WTs (relation frequency and magnitude) related to rainfall, runoff, and sediment yield. The results indicate two different temporal patterns: the first weather type exhibits (during the cold period: autumn and winter) westerly flows that produce the highest rainfall, runoff, and sediment yield values throughout the territory; the second weather type exhibits easterly flows that predominate during the warm period (spring and summer) and it is located on the Mediterranean coast of the Iberian Peninsula. However, the cyclonic situations present high frequency throughout the whole year with a large influence extended around the western Mediterranean basin. Contrary, the anticyclonic situations, despite of its high frequency, do not contribute significantly to the total rainfall, runoff, and sediment (showing the lowest efficiency) because of atmospheric stability that currently characterize this atmospheric pattern. Our approach helps to better understand the relationship of WTs on the seasonal and spatial variability of rainfall, runoff and sediment yield with a regional scale based on the large dataset and number of soil erosion experimental stations.

1. Introduction

It is well-known that there is a close relationship between atmospheric circulation and climatic variables (i.e., precipitation, snow accumulation, temperature) [1,2,3]. In addition, precipitation variability is a recognized characteristic of Mediterranean environments [4] and the relationship between rainfall and atmospheric circulation, and its spatial and temporal variability have been widely studied [5,6]. Also, recent research has achieved promising results in the relationship among atmospheric pattern, runoff, and sediment yield [7,8,9].
The studies of rainfall variability and its causes are of particular interest for hydrology and soil erosion research, because rainfall patterns directly affect runoff and soil erosion and its temporal distribution [10]. There are several studies that analyzed the relationships between rainfall and flood generation, runoff, erosion processes, and sediment yield [11,12,13], but few studies focused on their relationship with the atmospheric circulation patterns, being one of the leading controlling causes. Caspary [14] analyzed the relationships between the occurrence of floods in southwest Germany and westerly circulation patterns. Another example is the study by Quinn and Wilby [15] that analyzed the relationships between weather types and variations in multi-decadal floods in England, Scotland, and Wales since the 1870s. Recently, Mountreuil et al. [16] and Tylkowski [17] examined the storm surge events associated with erosion and its relationships with weather types.
In the Mediterranean region, different studies have analyzed WTs and environmental variables. Kostopoulou and Jones [18] investigated the relationships between atmospheric circulation patterns and surface climatic elements (temperature and precipitation) in the eastern Mediterranean basin. Fernandez-Raga et al. [19] studied the relation between the kinetic energy and other rainfall characteristic with the WTs in forest plantation in northern central Portugal. Furthermore, Grimalt et al. [20] determined a temporal analysis of the weather types for the western Mediterranean basin over the 1948–2009 period. On the other hand, Royé et al. [21] focused on the spatial and temporal patterns to cloud-to-ground lightning related to the circulation weather types over the northwest Iberian Peninsula. More specific research analyzing the synoptic situations associated with flood episodes were presented by Llasat et al. [22] in Catalonia (Spain) between 1840–1870. Also, Rodrigo-Comino et al. [23] focused on the identification of which WTs were associated to rainfall events were able to generate specific surface flows and soil loss rates in Málaga (Spain).
However, despite the fact that the marked seasonal variability of rainfall regime in Mediterranean areas clearly determines the hydrological and erosion response, few studies have been carried out to define these temporal patterns and the relationships between atmospheric conditions and the hydrological response. Gilabert and Llasat [24] analyzed the circulation weather types associated with extreme floods in Catalonia (North-eastern Spain) and established their temporal patterns. The previous study shows that most synoptic situations were pure cyclonic structures, in both extraordinary and catastrophic events in Catalonia.
Lastly, there are scarce contributions about the efficiency of the WTs related to rainfall events, hydrological responses, and sediment transport particularly at seasonal scale. For the Iberian Peninsula, Nadal-Romero et al. [7] calculated the efficiency of the WTs in sediment transport by means of magnitude-frequency analyses, i.e., ‘work done’ in physical concept (see the classical contribution of Wolman and Miller [25], Thornes and Brunsden [26], Wolman and Gerson [27], and Thorn [28]), and found that the most efficient WTs in sediment production were westerly flows, although spatial differences were identified.
Following the previous paragraphs, the main objective of this study was to analyze the seasonal variability of the relationships between rainfall, runoff, and sediment yield (SY, used to refer to erosion depths at a plot scale and sediment yield at a catchment scale) with weather types (WTs) in the western Mediterranean basin, specifically Portugal, Spain, and south France areas. The specific objectives were: (i) to detect the seasonal contribution of the different WTs in the magnitude of rainfall, runoff, and SY in the study sites; and (ii) to analyze the seasonal efficiency of the different WTs to result in rainfall event, hydrological responses and sediment production based on the relation frequency and magnitude of rainfall, runoff and SY, respectively. We hypothesized that: (i) there is a temporal (i.e., seasonal) and spatial pattern in the relationships between rainfall, runoff and SY with WTs in western Mediterranean basin; and (ii) these relationships vary seasonally and differ among rainfall, runoff, and SY, as well as the seasonal efficiency in terms of rainfall, runoff generation, and sediment fluxes of the different WTs. More specifically, we expect that some WTs, despite their high frequency, will contribute little to the generation of rainfall, runoff, and SY (i.e., they are not very effective), while other (low-frequency) WTs will show a very effective contribution to rainfall runoff and SY. We also expect that the efficiency of the WTs will be affected by season. To a certain extent, this study provides seasonal analyses of previous Mediterranean analyses regarding the relationships of hydrological and sediment response to different WTs in the Mediterranean region by Nadal-Romero et al. [7] and Peña-Angulo et al. [8].

2. Experiments

2.1. Data

A database of rainfall events with hydrological and SY information was compiled from a network of experimental plots and catchments (<50 km2) in the Mediterranean basin. From the database compiled by Peña-Angulo et al. [8], only those study sites with at least 3 years of data were included in this study (Table 1). In that sense, this investigation is focused on 8245 rainfall events obtained from 46 sites (29 catchments and 17 plots) from Portugal, Spain, and France during 1985–2015 period (Table 1). This dataset has involved the collaboration of many researchers, which have allowed us to compile the most extensive collection of real rainfall, surface hydrology and SY in Mediterranean basin at plot and catchment scales (for more details see Peña-Angulo et al. [8]).
The WTs classification relies on the daily sea level pressure dataset from NCEP/NCAR 40-year Reanalysis Project [29]. We used the WTs classification proposed by Jenkinson and Collinson [30], based on the original work of Lamb [31], following the approach suggested by Jones et al. [32], and Trigo and DaCamara [33] for the Iberian Peninsula. Furthermore, the 26 WTs of the original classification defines directional: north (N), northeast (NE), east (E), southeast (SE), south (S), southwest (SW), west (W), and northwest (NW); two WTs dominates by the strength of vorticity: anticyclonic (A) and cyclonic (C); and hybrid types (eight for each C or A). However, we decided to follow the methodology explained by Cortesi et al. [5] and Nadal et al. [6], aggregated in 10 classes. WTs were aggregated into 10 types, the original (A and C), and the combination of pure directional types with hybrid types accordingly to wind direction (NE, E, SE, S, SW, W, NW, and N).

2.2. Method

The analyses of the temporal variability of the three study variables (rainfall, runoff, and SY) due to the WTs, was done seasonally considering classical monthly aggregation (winter: December, January, and February; spring: March, April, May; summer: June, July, August; and autumn: September, October, November). Each of the 8245 daily events was associated with WTs for individual sites. For each site and daily events, the percentage of rainfall, runoff and SY produced was estimated over the whole period, and we obtained the total percentage in each season for each study site (see Annex Table 1 for more details). First, we checked seasonal differences in the percentage of rainfall, runoff and SY using boxplot and we applied Wilcoxon signed-rank test [73] between seasons for each study variable. After, we analyzed the spatial distribution of rainfall, runoff and SY in each season with maps and we obtained around 25% of the sites in each study variable. The value 25% represents a uniform distribution over the four seasons. Secondly, to identify temporal patterns of the relationships between rainfall, runoff, and SY with WTs, we calculated in each site the seasonal percentage of rainfall, runoff and SY produced by each WTs. The statistical distribution of the percentage of rainfall, runoff, and SY was represented in the boxplots. Then, the analysis of the spatial variability was carried out by mapping the percentage of rainfall, runoff and SY below and above 2.5% for the different WTs per each season and study site. The 2.5% value represents the uniform distribution of 10 WTs and four seasons.
We applied three specific analyses to detect the most efficient WTs in terms of generating the largest contribution (% of magnitude) of rainfall, runoff and SY in each season. First, we checked whether the frequency of rainfall events during the study period at each site responds to the frequency of the WTs with the aim to verify if the contribution of the WTs to rainfall were due to the frequency of the WTs or due to another cause (i.e., direction of the wind). This analysis was done by comparing the frequency of the WTs in the reference climate period (1981–2010, 30 years) with the frequency of the rainfall events in the study period (1985–2015, 30 years). Secondly, we obtained the frequency of the WTs in each season with the major contribution, more than 5% of magnitude of rainfall, runoff, and SY. Finally, we calculated an efficiency index in each study sites, following the methodology used in Nadal-Romero et al. [7]. The index is defined as the product of the contribution to rainfall, runoff, and sediment yield (% of magnitude) and frequency of rainfall events, hydrological responses and sediment production in the study period. High values for the index represent high efficiency of WTs, and low values mean WTs less efficiency. We obtained the mean of the efficient index in each season, WTs, and study variable. All analyses and figures were carried out using R software (R, version 3.2.3) [74].

3. Results

3.1. Temporal Relationships between Rainfall, Runoff, and Sediment Yield with Weather Types

The seasonal percentage of rainfall, runoff and SY is shown in the boxplots presented in Figure 1. Rainfall peaks in winter and autumn and shows the smallest contribution in summer. Rainfall shows significant differences between seasons, except between winter and autumn and for winter and spring. Runoff occurred mostly during winter and autumn, which, on average, accounted for more than 50% of the total runoff. Yet, the seasonal percentage of runoff was highly variable across sites, especially in winter and autumn, as indicated by the long whiskers of the box plots that could range from 0 to 80%. Runoff shows significant differences between seasons, except between winter and autumn. SY variability is very large for all the seasons and no significant differences were observed between the seasons, only occur between summer and autumn. The median SY percentage values of the seasons reach the highest contribution in autumn, followed by spring, winter, and summer.
Figure 2 shows the spatial distribution of the seasonal percentages of rainfall, runoff, and SY, below and above 25% of annual value. Sites with >25% rainfall in winter, spring and autumn show a fairly homogeneous spatial distribution, while on the contrary in summer, high rainfall contribution values are only reached in the northeastern inland region. Runoff follows a similar pattern in sites with >25% contribution in winter, spring and autumn, while in summer high values are only reached in the eastern area. Last, SY distribution shows less spatial coherence and high seasonal spatial variability: winter and spring show a fairly homogeneous spatial distribution, while for summer and autumn sites with >25% are mostly located in the eastern area.
The seasonal percentage contribution of rainfall, runoff and SY by different WTs are shown in Figure 3. The WTs with more generalized high percentage contribution are C (cyclonic) and W (west) types. The C type contributes to the three variables in all the seasons, reaching the lowest contributions in summer SY. The westerly types (W, NW, and SW) present a high contribution in rainfall and runoff for winter, spring, and autumn, and to a lesser extent in summer SY. The easterly types (E, NE, and SE) have a high contribution in summer rainfall and runoff, and also, in relative terms, in summer SY. North WT shows a high contribution for rainfall in spring and autumn, and for runoff and SY in spring. South WT contribution is mainly concentrated in spring in rainfall, runoff, and SY.
The seasonal percentage of rainfall, runoff, and SY produced under WTs shows a high spatial variability (Figure S1: rainfall, Figure S2: runoff, Figure S3: SY). Figure 4 is an example and shows the spatial distribution of rainfall, runoff, and SY below and above 2.5% under W and E types. In winter, and also in spring and autumn, westerly WTs produce preferably the highest rainfall and runoff values in the central-western areas, being no so clear for the SY response. Contrarily, easterly WTs predominate in summer, especially in the northeast and eastern part of the Iberian Peninsula. In general, the seasonal percentage of SY distribution accordingly to WTs is more heterogeneous than the observed in rainfall and runoff, suggesting a more complex relationship between SY and WTs than rainfall or runoff.

3.2. Seasonal Efficiency of Weather Types to Produce Rainfall, Runoff, and Sediment Yield

The analysis of the WT efficiency in rainfall, runoff, and SY shows great differences among them. Figure 5 shows the seasonal frequency distribution of each WTs during the reference climate period (1981–2010) and the rainfall events studied (1985–2015). The most frequent WTs during the climate reference period are A, N, NE, E, SE, and eventually C (summer), W, SW, and NW (winter). Differently, the WTs that show a high rainfall event frequency are C (spring), SW, W, and NW (winter), with noticeable contributions of NE and E through the year. The anticyclonic (A) WT is the dominant atmospheric pattern in the western Mediterranean area, although it does not correspond with a high frequency of rainfall events. This is a logic result, because A WT is usually associated with atmospheric stability, not only in summer season but also in winter. Contrarily, the low frequency of cyclonic (C) WT during the reference period is coupled with a high frequency of rainfall events, especially in spring and autumn, which is in line with its characteristic instability, sometimes associated to polar front depressions and to a lesser extent to low-pressure systems developed in the inland areas as a consequence of intense heating during warm season (i.e., thermal lows).
On the other hand, westerly flows (W, SW, and NW) show a moderate frequency in the reference climate period, but they appear to be very frequent in rainfall events, except in summer. The south WT shows a low frequency in the reference climate period and rainfall events during the year, except during autumn. For the easterly flows (E and NE) the frequency in the reference climate period and rainfall events is very similar. Lastly, the SE and N types show a high frequency in the reference climate period but a low frequency in rainfall events throughout the year.
These results are in agreement with the information shown in Figure 6, which represents the frequency of the WTs with major contributions (more than 5%) of rainfall, runoff, and SY in each season. The westerly flows (W and SW) show a high contribution, producing the maximum values in rainfall and runoff in winter and autumn. In addition, the S and SE types show maximum contributions in autumn. The C WT produces the highest contribution in spring and autumn, while the E and NE WTs produce the maximum values in summer. It should be highlighted that the low values related to SY contribution especially in winter, and the high contribution of C, SW, and E WTs in autumn.
The efficiency to produce rainfall, runoff and sediment discharge of each WTs varies substantially in each season (Figure 7). The westerly WTs (W and SW) are very efficient (low frequency and high contribution) in autumn and winter, and the NW type is also very efficient related to rainfall and runoff values in winter. The C type is very efficient related to rainfall and runoff in spring. On the other hand, the NE and E WTs are efficient in summer, and the E and S types in autumn. The A, N, and SE types show low efficient values in all variables and seasons.

4. Discussion

4.1. Seasonal Differences in the Contribution of Rainfall, Runoff, and Sediment Yield Produced by the Weather Types

The western Mediterranean basin is located in the transition between tropical and mid latitudes in which atmospheric dynamic interacts with a complex topography to produce a high spatio-temporal variability of rainfall, and where climate models recurrently show a very low capability to forecast and predict rainfall [75]. In this region, general results from previous studies have suggested the potential of using atmospheric patterns (i.e., weather types) to analyze spatial variability of rainfall [5], runoff, and SY [7,8,23], that could help us to understand the spatial variability on the response of natural systems [76].
We show that the spatial variability of rainfall strongly determines the spatial variability of the runoff and SY responses across the western Mediterranean basin. This influence holds through the year, though spatial patterns change across seasons. Our results are in line with previous studies showing that seasonal patterns of rainfall and runoff are highly variable depending on the study sites [77,78,79]. For example, Smetanova et al. [80] performed an analysis of the seasonal distribution of the sediment for different environments in the Mediterranean. The highest SY response occurs in spring and summer for catchments with oceanic climates, while catchments with semi-arid or dry climates experience minimum values in summer. Tuset et al. [81] identified in the northeast of the Iberian Peninsula (Ribera Salada catchment) that low runoff and sediment values are recorded in winter. Meanwhile the majority of runoff and sediment is produced in spring, while little runoff and high amount of sediment is produced in summer and autumn. Lana-Renault et al. [82] showed a strong seasonality in the hydrological response in the Arnás catchment (Central Pyrenees), with high responses during winter and spring, and low responses during summer and early autumn. At slope scale, the influence of rainfall intensity and distribution was also a key factor in soil erosion studies. Topographical measurements carried out in vineyards by Martínez-Casasnovas et al. [83], measurements carried out in the field with USLE research plots in arid [84], and wet climates [85] as well as by means of small research plots [86], show how relevant rainfall intensity and volume is to determine soil erosion rates.
This spatio-temporal variability in runoff and sediment patterns is well captured in the maps presented in this study. In addition, our results show that this variability can be associated, at least to some extent, with the occurrence of different weather types. These finding stresses that the seasonality of atmospheric conditions plays an important role on determining runoff and SY patterns, and thus, a better understanding of atmospheric circulation can help us to understand hydrology and sediment export in Mediterranean regions.
The high seasonal variability of rainfall, with high values in winter and autumn, and very low values in summer, is also reflected spatially. That means that the rainfall, runoff, and SY show a homogeneous spatial contribution in winter, and a high heterogeneity in summer, and the WTs help to explain their spatial and seasonal distribution. The westerly flows (SW and W) are frequent in winter and autumn, and also have a high contribution to rainfall, runoff, and SY throughout the territory. The westerly flows are usually loaded with moisture from the Atlantic Ocean (wet air masses and frontal systems governed by the North Atlantic Oscillation), which increases rainfall, and therefore runoff and SY from west to east across the Iberian Peninsula. Furthermore, these flows do not find a topographic barrier, and then they can affect extended inland areas except for the eastern Mediterranean coastland and south of France. On the other hand, the frequency of these westerly flows in summer is reduced as a consequence of the northerly migration of pressure systems [5]. During summer, the easterly flows (NE and E) predominate, in such a way that the greatest contribution of rainfall, runoff, and SY comes from these WTs, which have a limited spatial influence to inland by the effect of topographic barriers parallel to the coast. These easterly flows that come from the Mediterranean Sea have different origins: (i) sometimes are related to the presence of a thermal low over northwestern Africa; (ii) but most commonly are related with a low pressure system which has become completely displaced (cut-off) from westerly current and moves independently, particularly at the end of summer, spring, and autumn; and (iii) finally, these WTs sometimes originate by orographic depressions (as Ligura and Gulf of Lion low). In all the cases, these easterly flows find a mountain barrier parallel to the coast of the Iberian Peninsula from northeast to the southeast (the Catalan Coastland Range, the Iberian System, Subbetic Systems) that limit their influence exclusively to the Mediterranean coastland [5].
Some specific cases should be highlighted such as C (cyclonic) weather type, which is characterized by a homogeneous influence at the spatial level and through the year in the analyzed events, with two relative peaks in spring and autumn. Contrarily, the A (anticyclonic) type has very little spatial and seasonal influence. These observations are in agreement with the results obtained by Morán-Tejeda et al. [87] that analyzed the hydro-meteorological response of major floods in Spanish mountain rivers, and concluded that the floods were more frequent under cyclonic (26%), as well as under advection of westerly flows (26% of total floods) and easterly flows (22% of total floods).
The analysis of the spatial and temporal distribution of rainfall, runoff, and SY contributions under each WT showed important differences in the magnitude of the explored relationships. Despite the high spatial variability observed, the present research found some clear spatial associations between some WTs and rainfall, runoff, and SY during several specific seasons. Our research revealed that rainfall or runoff events can take place under any type of weather type, with seasonal and spatial patterns, although C and advection from SW and W (in winter and spring) and E and SE (in summer and autumn) are the most dominant WTs in the western and eastern of the study area, respectively. SY showed a high spatial and temporal variability, suggesting that is a more complex and locally dependent processes than runoff, as it is dependent also on relief, connectivity, and land cover and land management practices [86,88].

4.2. Seasonal Efficiency of the Different Weather Types Related to Rainfall, Runoff, and Sediment Yield

A crucial characteristic to determine the role played by the WTs on the temporal and seasonal variability in the study period is firstly provided by WTs comparison of the frequency between the whole climate reference period (1981–2010) and the rainfall events observed during the study period (1985–2015). These comparisons show that despite of the high frequency of the anticyclonic WT their contribution to rainfall, runoff, and SY is low, and presents the lowest frequent in runoff and sediment production. The high frequency of A type has also been also observed in other Mediterranean areas [5,6,20,89]. These authors also indicate that the seasonal rainfall contribution of A type is quite small compared to its frequency. The predominance of the A type is strongly related to the migration of the Azores anticyclone towards the Iberian Peninsula [90]. However, in summer, under anticyclone situations, high values of runoff and sediment production can be recorded locally in high mountain areas due to the capacity of mountain ranges for triggering convective activity at the local scale because of high isolated radiation [87]. These local processes cannot be detected in this study due to the coarse spatial resolution of the applied reanalysis grid.
The frequency of easterly (NE, SE, E) flows during the climate reference period is higher than the frequency of rainfall events. In addition, important seasonal differences can also be also observed. For example, N and NE are the most frequent WTs in summer. Gilabert and Llasat [24] also observed this seasonal pattern analyzing WTs associated with extreme floods in the northeastern Mediterranean. These authors suggested that in summer there is an increase of the frequency of NE WTs, due to the relatively cool air that favors instability of the air mass and promotes precipitation.
WT frequency analyses in rainfall, runoff, and SY reveal again the classical question about the temporal distribution of the processes, the relationship between rainfall and runoff, and those with sediment yield. The westerly and cyclonic situations in winter and autumn are those that have a higher frequency in rainfall events [91] due to frontal systems that transport air masses with moisture from the ocean to the Iberian Peninsula, while easterly WT predominance in spring and summer suggest different mechanisms. Summer events are associated with short, intense, and localized rainfalls, often associates to thermal convective lows and high rainfall intensity. Morán-Tejeda et al. [87] suggested that large rainfall amounts in the western Mediterranean basin are more intense and concentrated in events of a few hours, and have usually a convective origin due to the occurrence of cold depressions in the middle troposphere (cut-off-low) with advection of warm flows from the Mediterranean. Similar results were found in different areas of the Mediterranean basin by Ramos et al. (2014). Gilabert and Llasat [24] observed that floods were most common in autumn, followed by summer. Furthermore, in autumn, cyclonic situations were the most common, with more than 50% of the floods, while in summer accounted for approximately 40% of the floods.
The efficiency of each WTs in relation to rainfall, runoff, and SY varies substantially in each season. The westerly WTs are very efficient in autumn and winter, while easterly WTs are efficient in summer. There are a few studies that analyzed the efficient of the WTs related to the rainfall, runoff and SY. Nadal-Romero et al. [7,92] evaluated the efficiency of WTs on SY, and they found the most efficient WTs is westerly flow. We have found the westerly WTs are very efficient, but only in winter and autumn due to their high frequency, and the opposite in summer.
The results obtained in this study have encouraged further topics related to atmospheric patterns and the hydrological and sediment yield response. In that sense, future research should focus on: (i) evaluation the role play by extreme events and their relationships with different WTs; (ii) analyze the relationships between rainfall intensity and WTs; (iii) investigate different responses and WTs based on land use and land covers related to different runoff processes (infiltration excess overland flow and saturation excess overland flow).

5. Conclusions

This study presents spatial and temporal patterns in the relationships between WTs, rainfall, runoff, and sediment yield in the western Mediterranean basin. Overall, the main results of this study can be summarized as follows:
The most frequent WTs is the anticyclonic, however it tends to produce a small number of rainfall events, and does not significantly contribute to the rainfall, runoff, and sediment yield (low efficiency).
Westerly WTs (NW, W, and SW) predominate throughout the western Mediterranean basin and generate the highest rainfall, runoff, and sediment yield during the cold period (winter and autumn).
Easterly WTs (NE, E, and SE) dominate rainfall, runoff, and sediment yield production during the warmer seasons (spring and summer).
The spatial influence of the westerly WTs is particularly large, except in the eastern study area, during the cold period, and decreases in summer. Cyclonic WTs spread their influence over extensive areas of the western Mediterranean region. The easterly WTs predominate during the warm period and it is located on the Mediterranean coast of the study area. Other WTs provide a more localized contribution over relative narrow areas.
Similar patterns for rainfall and runoff configurations were observed for sediment yield, although the last was influenced by a very marked spatial and temporal variability.
This study indicates that the WTs analyses offer a high potential research for the design of water resources management and soil erosion measurements, because they play a key role on determining rainfall, runoff, and sediment yield response and its temporal and spatial patterns. Finally, the results suggest that the WTs approach could be a useful tool for soil erosion modelling research and climate model scenarios.

Supplementary Materials

The following are available online at https://www.mdpi.com/2073-4433/11/6/609/s1, Table S1: Seasonal distribution of the percentage of rainfall, runoff, and sediment yield in each study site; Figure S1: Spatial distribution of the percentage of rainfall in the weather types for each season; Figure S2: Spatial distribution of the percentage of runoff in the weather types for each season; Figure S3 Spatial distribution of the percentage of sediment yield in the weather types for each season.

Author Contributions

Conceptualization, D.P.-A., E.N.-R., and J.C.G.-H.; Data curation, J.A., V.A., H.B., S.B., M.B., R.B., J.C. (Julian Campo), M.A.C.-B., A.C.-D., Y.C., J.C. (Javier Casali), V.C., E.C., A.C., P.C., N.C., G.D., E.D.-P., T.E., J.E., J.F., M.F.-R., C.S.F., V.F., F.G., R.G., E.G., J.A.G., A.G.-G., H.G.-M., O.G.-P., O.K., G.K., K.S., S.K., C.K., N.L.-R., T.L., J.L., R.L., Y.L.B., C.L.B., F.L., J.A.L.-T., A.L., V.M.M.-M., C.M., M.J.M., J.M.-F., M.M.-M., L.M., M.N., L.M.-M., M.M.-d.l.H., N.M., J.M.N., V.P., D.R., M.L.R.-B., J.R.-C., A.R.-D., J.D.R.-S., J.L.R., S.S., J.M.S.-G., A.S.-B., E.V.T., M.M.T.-C., M.T.T.-C., F.T., X.Ú., E.A.V., L.W., A.Z., and M.Z.; Formal analysis, D.P.-A., E.N.-R., J.C.G.-H. and N.C.; Investigation, D.P.-A., E.N.-R., and J.C.G.-H.; Methodology, D.P.-A., E.N.-R., and J.C.G.-H.; Writing—original draft, D.P.-A., E.N.-R., and J.C.G.-H.; Writing—review and editing, D.P.-A., E.N.-R., J.C.G.-H., J.A., V.A., H.B., S.B., M.B., R.B., J.C., M.A.C.-B., A.C.-D., Y.C., J.C., V.C., E.C., A.C., P.C., N.C., G.D., E.D.P., T.E., J.E., J.F., M.F.-R., C.S.F., V.F., F.G., R.G., E.G., J.A.G., A.G.-G., H.G.-M., O.G.-P., O.K., G.K., K.S., S.K., C.K., N.L.-R., T.L., J.L., R.L., Y.L.B., C.L.B., F.L., J.A.L.-T., A.L., V.M.M.-M., C.M., M.J.M., J.M.-F., M.M.-M., L.M., M.N., L.M.-M., M.M.-d.l.H., N.M., J.M.N., V.P., D.R., M.L.R.-B., J.R.-C., A.R.-D., J.D.R.-S., J.L.R., S.S., J.M.S.-G., A.S.-B., E.V.T., M.M.T.-C., M.T.T.-C., F.T., X.Ú., E.A.V., L.W., A.Z., and M.Z. All authors have read and agreed to the published version of the manuscript.

Funding

Spanish Government (Ministry of Economy and Competitiveness, MINECO) and FEDER Projects: CGL2014 52135-C3-3-R, ESP2017-89463-C3-3-R, CGL2014-59946-R, CGL2015-65569-R, CGL2015-64284-C2-2-R, CGL2015-64284-C2-1-R, CGL2016-78075-P, GL2008-02879/BTE, LEDDRA 243857, RECARE-FP7, CGL2017-83866-C3-1-R, and PCIN-2017-061/AEI. Dhais Peña-Angulo received a “Juan de la Cierva” postdoctoral contract (FJCI-2017-33652 Spanish Ministry of Economy and Competitiveness, MEC). Ana Lucia acknowledge the "Brigitte-Schlieben-Lange-Programm". The “Geoenvironmental Processes and Global Change” (E02_17R) was financed by the Aragón Government and the European Social Fund. José Andrés López-Tarazón acknowledges the Secretariat for Universities and Research of the Department of the Economy and Knowledge of the Autonomous Government of Catalonia for supporting the Consolidated Research Group 2014 SGR 645 (RIUS- Fluvial Dynamics Research Group). Artemi Cerdà thank the funding of the OCDE TAD/CRP JA00088807. José Martínez-Fernandez acknowledges the project Unidad de Excelencia CLU-2018-04 co-funded by FEDER and Castilla y León Government. Ane Zabaleta is supported by the Hydro-Environmental Processes consolidated research group (IT1029-16, Basque Government). This paper has the benefit of the Lab and Field Data Pool created within the framework of the COST action CONNECTEUR (ES1306).

Acknowledgments

This research was supported by projects funded by Spanish and FEDER, the “Brigitte-Schlieben-Lange-Programm”; the Governments of Spanish Autonomous Region of Aragón, Catalonia, Castilla-León and Basque Country. José Andrés López-Tarazón acknowledges the Secretariat for Universities and Research of the Department of the Economy and Knowledge of the Autonomous Government of Catalonia for supporting the Consolidated Research Group 2014 SGR 645 (RIUS- Fluvial Dynamics Research Group). Artemi Cerdà thank the funding of the OCDE TAD/CRP JA00088807. José Martínez-Fernandez acknowledges the project Unidad de Excelencia CLU-2018-04 co-funded by FEDER and Castilla y León Government. Ane Zabaleta is supported by the Hydro-Environmental Processes consolidated research group (IT1029-16, Basque Government). This paper has the benefit of the Lab and Field Data Pool created within the framework of the COST action CONNECTEUR (ES1306).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Esteban, P.; Jones, P.D.; Mases, M.; Martín-Vide, J. Atmospheric circulation patterns related to heavy snowfall days in Andorra, Pyrenees. Int. J. Clim. 2005, 25, 319–329. [Google Scholar] [CrossRef]
  2. Peña-Angulo, D.; Trigo, R.M.; Cortesi, N.; Gonzalez-Hidalgo, J.C. The influence of weather types on the monthly average maximum and minimum temperatures in the Iberian Peninsula. Atmos. Res. 2016, 217–230. [Google Scholar] [CrossRef]
  3. Sánchez-Benítez, A.; García-Herrera, R.; Vicente-Serrano, S.M. Revisiting rainfall variability, trends and drivers in the Canary Islands. Int. J. Climatol. 2017, 37, 3565–3576. [Google Scholar] [CrossRef]
  4. Lionello, P.; Boscoso, R.; Malanotte-Rizzoli, P. Mediterranean Climate Variability; Elsevier: Amsterdam, The Netherlands, 2006; p. 438. [Google Scholar]
  5. Cortesi, N.; Trigo, R.M.; González-Hidalgo, J.C.; Ramos, A.M. Modelling monthly rainfallwith circulation weather types for a dense network of stations over Iberia. Hydrol. Earth Syst. Sci. 2013, 17, 665–678. [Google Scholar] [CrossRef] [Green Version]
  6. Ramos, A.M.; Cortesi, N.; Trigo, R. Circulation weather types and spatial variability of daily rainfallin the Iberian Peninsula. Front. Earth Sci. 2014, 2, 25–45. [Google Scholar] [CrossRef] [Green Version]
  7. Nadal-Romero, E.; Gonzalez-Hidalgo, J.C.; Cortesi, N.; Desir, G.; Gómez, J.A.; Lasanta, T.; Lucía, A.; Marin, C.; Martínez-Murillo, J.; Pacheco, E.; et al. Relationship of runoff, erosion and sediment yield to weather types in the Iberian Peninsula. Geomorphology 2015, 228, 372–381. [Google Scholar] [CrossRef] [Green Version]
  8. Peña-Angulo, D.; Nadal-Romero, E.; Gonzalez-Hidalgo, J.C.; Albaladejo, J.; Andreu, V.; Bagarello, V.; Bahri, H.; Batalla, R.J.; Bernal, S.; Bienes, R.; et al. Spatial variability of the relationships of runoff and sediment yield with weather types throughout the Mediterranean basin. J. Hydrol. 2019, 571, 390–405. [Google Scholar] [CrossRef] [Green Version]
  9. Fernández-Raga, M.; Fraile, R.; Palencia, C.; Marcos, E.; Castañón, A.; Castro, A. The Role of Weather Types in Assessing the Rainfall Key Factors for Erosion in Two Different Climatic Regions. Atmosphere 2020, 11, 443. [Google Scholar] [CrossRef]
  10. Langbein, W.B.; Schumm, S.A. Yield of sediment in relation to mean annual precipitation. Trans. Am. Geophys. Union 1958, 39, 1076. [Google Scholar] [CrossRef] [Green Version]
  11. Andrade, C.; Santos, J.A.; Pinto, J.G.; Corte-Real, J. Large-scale atmospheric dynamics of the wet winter 2009–2010 and its impact on hydrology in Portugal. Clim. Res. 2011, 46, 29–41. [Google Scholar] [CrossRef] [Green Version]
  12. Auffray, A.; Clavel, A.; Jourdain, S.; Ben Daoud, A.; Sauquet, E.; Lang, M.; Obled, C.; Panthou, G.; Gautheron, A.; Gottardi, F.; et al. Reconstructing the hydrometeorological scenario of the 1859 flood of the Isere River. Houille Blanche-Revue Int. de l’eau 2011, 1, 44–50. [Google Scholar] [CrossRef] [Green Version]
  13. Nadal-Romero, E.; Peña-Angulo, D.; Regüés, D. Rainfall, run-off, and sediment transport dynamics in a humid mountain badland area: Long-term results from a small catchment. Hydrol. Process. 2018, 32, 1588–1606. [Google Scholar] [CrossRef]
  14. Caspary, H.J. Die Winterhochwasser 1990, 1993 und 1995 in Südwestdeutschland-Signale einer bereits eingetretenen Klimaänderung. In Klimänderung und Wasserwirtschaft; Bechteler, W., Günthert, F.A., Kleeberg, H.-B., Eds.; Internationales Symposium am: Puerto Vallarta, Mexico, 1995; Volume 27, p. 28. [Google Scholar]
  15. Wilby, R.; Quinn, N. Reconstructing multi-decadal variations in fluvial flood risk using atmospheric circulation patterns. J. Hydrol. 2013, 487, 109–121. [Google Scholar] [CrossRef]
  16. Montreuil, A.-L.; Elyahyioui, J.; Chen, M. Effect of Large-Scale Atmospheric Circulation and Wind on Storm Surge Occurrence. J. Coast. Res. 2016, 75, 755–759. [Google Scholar] [CrossRef]
  17. Tylkowski, J. The temporal and spatial variability of coastal dune erosion in the Polish Baltic coastal zone. Baltica 2018, 30, 97–106. [Google Scholar] [CrossRef]
  18. Kostopoulou, E.; Jones, P. Comprehensive analysis of the climate variability in the eastern Mediterranean. Part II: Relationships between atmospheric circulation patterns and surface climatic elements. Int. J. Clim. 2007, 27, 1351–1371. [Google Scholar] [CrossRef]
  19. Fernández-Raga, M.; Fraile, R.; Keizer, J.; Teijeiro, M.E.V.; Castro, A.; Palencia, C.; Calvo, A.; Koenders, J.; Marques, R.L.D.C. The kinetic energy of rain measured with an optical disdrometer: An application to splash erosion. Atmos. Res. 2010, 96, 225–240. [Google Scholar] [CrossRef]
  20. Grimalt, M.; Tomas, M.; Garau, G.A.; Martin-Vide, J.; Moreno-García, M. Determination of the Jenkinson and Collison’s weather types for the western Mediterranean basin over the 1948–2009 period. Temporal analysis. Atmósfera 2013, 26, 75–94. [Google Scholar] [CrossRef] [Green Version]
  21. Royé, D.; Lorenzo, N.; Martin-Vide, J. Spatial–temporal patterns of cloud-to-ground lightning over the northwest Iberian Peninsula during the period 2010–2015. Nat. Hazards 2018, 92, 857–884. [Google Scholar] [CrossRef]
  22. Llasat, M.-C.; Barriendos, M.; Barrera, A.; Rigo, T.; Barrera-Escoda, A. Floods in Catalonia (NE Spain) since the 14th century. Climatological and meteorological aspects from historical documentary sources and old instrumental records. J. Hydrol. 2005, 313, 32–47. [Google Scholar] [CrossRef]
  23. Rodrigo-Comino, J.; Senciales, J.M.; Sillero-Medina, J.; Gyasi-Agyei, Y.; Ruiz-Sinoga, J.D.; Ries, J.B. Analysis of Weather-Type-Induced Soil Erosion in Cultivated and Poorly Managed Abandoned Sloping Vineyards in the Axarquía Region (Málaga, Spain). Air Soil Water Res. 2019, 12, 1–11. [Google Scholar] [CrossRef]
  24. Gilabert, J.; Llasat, M.C. Circulation weather types associated with extreme flood events in Northwestern Mediterranean. Int. J. Clim. 2017, 38, 1864–1876. [Google Scholar] [CrossRef]
  25. Wolman, M.G.; Miller, J.P. Magnitude and frequency of forces in geomorphic processes. J. Geol. 1960, 68, 54–74. [Google Scholar] [CrossRef] [Green Version]
  26. Thornes, J.B.; Brunsden, D. Geomorphology and time. Earth Surf. Process. Landf. 1977, 3, 211–212. [Google Scholar]
  27. Wolman, M.G.; Gerson, R. Relative scales of time and effectiveness of climate in watershed geomorphology. Earth Surf. Process. Landf. 1978, 3, 189–208. [Google Scholar] [CrossRef]
  28. Thorn, C.E. An Introduction to Theoretical Geomorphology; Unwin Hyman: London, UK, 1988. [Google Scholar]
  29. Kalnay, E.; Kanamitsu, M.; Kistler, R.; Collins, W.; Deaven, D.; Gandin, L.; Iredell, M.; Saha, S.; White, G.; Woollen, J.; et al. The NMC/NCAR 40-Year Reanalysis Project. Bull. Am. Meteorol. Soc. 1996, 77, 437–471. [Google Scholar] [CrossRef] [Green Version]
  30. Jenkinson, A.F.; Collison, F.P. An Initial Climatology of Gales over the North Sea, Synoptic Climatology Branch Memorandum; Meteorological Office: Bracknell, UK, 1977.
  31. Lamb, H.H. British Isles Weather Types and a Register of Daily Sequence of Circulation Patterns, 1861-1971 (Geophysical Memoir); HMSO: London, UK, 1972; Volume 116.
  32. Jones, P.D.; Hulme, M.; Briffa, K.R. A comparison of Lamb circulation types with an objective classification scheme. Int. J. Clim. 1993, 13, 655–663. [Google Scholar] [CrossRef]
  33. Trigo, R.M.; DaCamara, C. Circulation weather types and their influence on the rainfallregime in Portugal. Int. J. Climatol. 2000, 20, 1559–1581. [Google Scholar] [CrossRef]
  34. Nadal-Romero, E.; Lasanta, T.; García-Ruiz, J.M. Runoff and sediment yield from land under various uses in a Mediterranean mountain area: Long-Term results from an experimental station. Earth Surf. Process. Landf. 2012, 38, 346–355. [Google Scholar] [CrossRef]
  35. Zabaleta, A.; Martínez, M.; Uriarte, J.A.; Antigüedad, I. Factors controlling suspended sediment yield during runoff events in small headwater catchments of the Basque Country. Catena 2007, 71, 179–190. [Google Scholar] [CrossRef]
  36. Bienes, R.; Guerrero-Campo, J.; Aroca, J.A.; Gómez, B.; Nicolau, J.M.; Espigares, T. Evolución del coeficiente de escorrentía en campos agrícolas del centro de España con diferentes usos del suelo. Ecología 2001, 15, 23–36. [Google Scholar]
  37. Bienes, R.; Moré, A.; Marqués, M.J.; Moreiro, S.; Nicolau, J.M. Efficiency of different plant cover to control water erosion in central Spain. In: A. Faz Cano R, Ortíz Silla AR, Mermut (Eds.), Sustainable Use and Management of Soils. Arid and Semiarid Regions. Adv. Geoecol. 2005, 36, 155–162. [Google Scholar]
  38. Nadal-Romero, E.; Regüés, D. Geomorphological dynamics of subhumid mountain badland areas—weathering, hydrological and suspended sediment transport processes: A case study in the Araguás catchment (Central Pyrenees) and implications for altered hydroclimatic regimes. Prog. Phys. Geogr. 2010, 4, 123–150. [Google Scholar] [CrossRef]
  39. Díaz, E.; Roldán, A.; Castillo, V.; Albaladejo, J. Plant colonization and biomass production in a Xeric Torriorthent amended with urban refuse. Land Degrad. Dev. 2017, 8, 245–255. [Google Scholar] [CrossRef]
  40. Romero Díaz, A.; Cammeraat, L.H.; Vacca, A.; Kosmas, C. Soil erosion at experimental sites in three Mediterranean countries: Italy, Greece and Spain. Earth Surf. Process. Landf. 1999, 24, 1243–1256. [Google Scholar] [CrossRef]
  41. Lana-Renault, N.; Latron, J.; Karssenberg, D.; Serrano-Muela, P.; Regüès, D.; Bierkens, M.F.P. Differences in stream flow in relation to changes in land cover: A comparative study in two sub-Mediterranean mountain catchments. J. Hydrol. 2011, 411, 366–378. [Google Scholar] [CrossRef] [Green Version]
  42. Desir, G.; Marin, C. Factors controlling the erosion rates in a semi-arid zone (Bardenas Reales, NE Spain). Catena 2007, 71, 31–40. [Google Scholar] [CrossRef]
  43. Martínez-Mena, M.; López, J.; Almagro, M.; Boix-Fayos, C.; Albaladejo, J. Effect of water erosion and cultivation on the soil carbon stock in a semiarid area of South-East Spain. Soil Tillage Res. 2008, 99, 119–129. [Google Scholar] [CrossRef]
  44. Estrany, J.; Garcia, C.; Batalla, R.J. Suspended sediment transport in a small Mediterranean agricultural catchment. Earth Surf. Process. Landf. 2009, 34, 929–940. [Google Scholar] [CrossRef]
  45. Rodríguez-Blanco, M.; Taboada-Castro, M.; Taboada-Castro, M. Linking the field to the stream: Soil erosion and sediment yield in a rural catchment, NW Spain. Catena 2013, 102, 74–81. [Google Scholar] [CrossRef]
  46. Cantón, Y.; Domingo, F.; Solé-Benet, A.; Puigdefábregas, J.; Castilla, M.Y.C. Hydrological and erosion response of a badlands system in semiarid SE Spain. J. Hydrol. 2001, 252, 65–84. [Google Scholar] [CrossRef]
  47. Duarte, A.C. Water pollution induced by rainfed and irrigated agriculture in Mediterranean environment at basin scale. Ecohydrol. Hydrobiol. 2011, 11, 35–46. [Google Scholar] [CrossRef]
  48. Gómez, J.A.; Vanwalleghem, T.; De Hoces, A.; Taguas, E. Hydrological and erosive response of a small catchment under olive cultivation in a vertic soil during a five-year period: Implications for sustainability. Agric. Ecosyst. Environ. 2014, 188, 229–244. [Google Scholar] [CrossRef]
  49. Gimeno-García, E.; Andreu, V.; Rubio, J.L. Influence of vegetation recovery on water erosion at short and medium-term after experimental fires in a Mediterranean shrubland. Catena 2007, 69, 150–160. [Google Scholar] [CrossRef] [Green Version]
  50. Cid, P.; Gomez-Macpherson, H.; Boulal, H.; Mateos, L. Catchment scale hydrology of an irrigated cropping system under soil conservation practices. Hydrol. Process. 2016, 30, 4593–4608. [Google Scholar] [CrossRef] [Green Version]
  51. Desir, G.; Sirvent, J.; Gutierrez, M.; Sancho, C. Sediment yield from gypsiferous degraded areas in the middle Ebro basin (NE, Spain). Phys. Chem. Earth 1995, 20, 385–393. [Google Scholar] [CrossRef]
  52. Casalí, J.; Gastesi, R.; Álvarez-Mozos, J.; De Santisteban, L.; Lersundi, J.D.V.D.; Gimenez, R.; Larrañaga, A.; Goñi, M.; Agirre, U.; Campo-Bescós, M.A.; et al. Runoff, erosion, and water quality of agricultural watersheds in central Navarre (Spain). Agric. Water Manag. 2008, 95, 1111–1128. [Google Scholar] [CrossRef]
  53. Sirvent, J.; Desir, G.; Gutierrez, M.; Sancho, C.; Benito, G. Erosion rates in badland areas recorded by collectors, erosion pins and profilometer techniques (Ebro Basin, NE-Spain). Geomorphology 1997, 18, 61–75. [Google Scholar] [CrossRef]
  54. Cambon, J.P.; Esteves, M.; Klotz, S.; Le Bouteiller, C.; Legout, C.; Liebault, F.; Mathys, N.; Meunier, M.; Olivier, J.E.; Richard, D. Observatoire hydrosedimentaire de montagne Draix-Bleone. Irstea 2015. [Google Scholar] [CrossRef]
  55. Hernandez-Santana, V.; Martínez-Fernández, J. TDR measurement of stem and soil water content in two Mediterranean oak species. Hydrol. Sci. J. 2008, 53, 921–931. [Google Scholar] [CrossRef]
  56. Lana-Renault, N.; López-Vicente, M.; Nadal-Romero, E.; Ojanguren, R.; Llorente, J.; Errea, P.; Regüès, D.; Ruiz, P.; Khorchani, M.; Arnáez, J.; et al. Catchment based hydrology under post farmland abandonment scenarios. Cuad. Investig. Geográfica 2018, 44, 503. [Google Scholar] [CrossRef] [Green Version]
  57. Casalí, J.; Giménez, R.; Diez, J.; Álvarez-Mozos, J.; Lersundi, J.D.V.D.; Goñi, M.; Campo-Bescós, M.A.; Chahor, Y.; Gastesi, R.; López, J.J. Sediment production and water quality of watersheds with contrasting land use in Navarre (Spain). Agric. Water Manag. 2010, 97, 1683–1694. [Google Scholar] [CrossRef]
  58. Andreu, V.; Imeson, A.; Rubio, J. Temporal changes in soil aggregates and water erosion after a wildfire in a Mediterranean pine forest. Catena 2001, 44, 69–84. [Google Scholar] [CrossRef] [Green Version]
  59. Taguas, E.; Ayuso, J.; Pérez, R.; Giráldez, J.; Gómez, J.A. Intra and inter-annual variability of runoff and sediment yield of an olive micro-catchment with soil protection by natural ground cover in Southern Spain. Geoderma 2013, 206, 49–62. [Google Scholar] [CrossRef]
  60. Molénat, J.; Raclot, D.; Zitouna, R.; Andrieux, P.; Coulouma, G.; Feurer, D.; Grunberger, O.; Lamachère, J.; Bailly, J.-S.; Belotti, J.; et al. OMERE: A Long-Term Observatory of Soil and Water Resources, in Interaction with Agricultural and Land Management in Mediterranean Hilly Catchments. Vadose Zone J. 2018, 17, 180086. [Google Scholar] [CrossRef] [Green Version]
  61. Martínez-Mena, M.; Rogel, J.Á.; Castillo, V.M.; Albaladejo, J. Organic carbon and nitrogen losses influenced by vegetation removal in a semiarid mediterranean soil. Biogeochemistry 2002, 61, 309–321. [Google Scholar] [CrossRef]
  62. Estrany, J.; Garcia, C.; Batalla, R.J. Groundwater control on the suspended sediment load in the Na Borges River, Mallorca, Spain. Geomorphology 2009, 106, 292–303. [Google Scholar] [CrossRef]
  63. Taguas, E.; Guzmán, E.; Guzmán, G.; Vanwalleghem, T.; Gomez, J. Characteristics and importance of rill and gully erosion: a case study in a small catchment of a marginal olive grove. Cuad. Investig. Geográfica 2015, 41, 107. [Google Scholar] [CrossRef] [Green Version]
  64. Castillo, V.M.; Gómez-Plaza, A.; Martínez-Mena, M. The role of antecedent soil water content in the runoff response of semiarid catchments: a simulation approach. J. Hydrol. 2003, 284, 114–130. [Google Scholar] [CrossRef]
  65. Boix-Fayos, C.; Martínez-Mena, M.; Calvo-Cases, A.; Arnau-Rosalén, E.; Albaladejo, J.; Castillo, V.M. Causes and underlying processes of measurement variability in field erosion plots in Mediterranean conditions. Earth Surf. Process. Landf. 2006, 32, 85–101. [Google Scholar] [CrossRef]
  66. Outeiro, L.; Úbeda, X.; Farguell, J. The impact of agriculture on solute and suspended sediment load on a Mediterranean watershed after intense rainstorms. Earth Surf. Process. Landf. 2010, 35, 549–590. [Google Scholar] [CrossRef]
  67. Martínez Fernández, J.; Sánchez Martín, N.; Rodríguez Ruiz, M.; Scaini, A. Dinámica de la humedad del suelo en una cuenca agrícola del sector central de la cuenca del Duero. Cuad. Investig. Geográfica 2010, 38, 75–90. [Google Scholar] [CrossRef] [Green Version]
  68. Cerda, A.; Rodrigo-Comino, J.; Giménez-Morera, A.; Keesstra, S. An economic, perception and biophysical approach to the use of oat straw as mulch in Mediterranean rainfed agriculture land. Ecol. Eng. 2017, 108, 162–171. [Google Scholar] [CrossRef] [Green Version]
  69. Latron, J.; Llorens, P.; Gallart, F. The Hydrology of Mediterranean Mountain Areas. Geogr. Compass 2009, 3, 2045–2064. [Google Scholar] [CrossRef]
  70. Latron, J.; Llorens, P.; Soler, M.; Poyatos, R.; Rubio, C.M.; Muzylo, A.; Martínez-Carreras, N.; Delgado, J.; Regüés, D.; Catari, G.; et al. Hydrology in a Mediterranean mountain environment—The Vallcebre research basins (northeastern Spain). I. 20 years of investigations of hydrological dynamics. In Status and Perspectives of Hydrology in Small Basins; IAHS Publication: Clausthal-Zellerfeld, Germany, 2009; Volume 336, pp. 38–43. [Google Scholar]
  71. Schnabel, S.; Gómez-Gutiérrez, Á. The role of interannual rainfall variability on runoff generation in a small dry sub-humid watershed with disperse tree cover. Cuad. Investig. Geográfica 2013, 39, 259. [Google Scholar] [CrossRef] [Green Version]
  72. Bernal, S.; Sabater, F. Changes in discharge and solute dynamics between hillslope and valley-bottom intermittent streams. Hydrol. Earth Syst. Sci. 2012, 16, 1595–1605. [Google Scholar] [CrossRef] [Green Version]
  73. Dalgaard, P. Introductory Statistics with R; Springer Science and Business Media LLC: Berlin/Heidelberg, Germany, 2008; pp. 99–100. [Google Scholar]
  74. R Development Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2013. [Google Scholar]
  75. Lionello, P.; Giorgi, F. Winter precipitation and cyclones in the Mediterranean region: Future climate scenarios in a regional simulation. Adv. Geosci. 2007, 12, 153–158. [Google Scholar] [CrossRef] [Green Version]
  76. Fernández-González, S.; Del Rio, S.; Castro, A.; Peñas, A.; Fernández-Raga, M.; Calvo, A.; Fraile, R. Connection between NAO, weather types and precipitation in León, Spain (1948–2008). Int. J. Clim. 2011, 32, 2181–2196. [Google Scholar] [CrossRef] [Green Version]
  77. Kosmas, C.; Danalatos, N.; Cammeraat, E.; Chabart, M.; Diamantopoulos, J.; Farand, R.; Gutiérrez, L.; Jacob, A.; Marques, H.; Martínez-Fernández, J.; et al. The effect of land use on runoff and soil erosion rates under Mediterranean conditions. Catena 1997, 29, 45–59. [Google Scholar] [CrossRef]
  78. Latron, J.; Gallart, F. Runoff generation processes in a small Mediterranean research catchment (Vallcebre, Eastern Pyrenees). J. Hydrol. 2008, 358, 206–220. [Google Scholar] [CrossRef]
  79. Lana-Renault, N.; Regüès, D. Seasonal patterns of suspended sediment transport in an abandoned farmland catchment in the Central Spanish Pyrenees. Earth Surf. Process. Landf. 2009, 34, 1291–1301. [Google Scholar] [CrossRef]
  80. Smetanová, A.; Le Bissonnais, Y.; Raclot, D.; Zema, D.A.; Licciardello, F.; Le Bouteiller, C.; Latron, J.; Rodríguez-Caballero, E.; Mathys, N.; Klotz, S.; et al. Temporal variability and time compression of sediment yield in small Mediterranean catchments: Impacts for land and water management. Soil Use Manag. 2018, 34, 388–403. [Google Scholar] [CrossRef]
  81. Tuset, J.; Vericat, D.; Batalla, R. Rainfall, runoff and sediment transport in a Mediterranean mountainous catchment. Sci. Total. Environ. 2016, 540, 114–132. [Google Scholar] [CrossRef]
  82. Lana-Renault, N.; Latron, J.; Regüés, D. Streamflow response and water-table dynamics in a sub-Mediterranean research catchment (Central Pyrenees). J. Hydrol. 2007, 347, 497–507. [Google Scholar] [CrossRef]
  83. Martı́nez-Casasnovas, J.; Ramos, M.C.; Ribes-Dasi, M. Soil erosion caused by extreme rainfall events: mapping and quantification in agricultural plots from very detailed digital elevation models. Geoderma 2002, 105, 125–140. [Google Scholar] [CrossRef]
  84. Mohamadi, M.A.; Kavian, A. Effects of rainfall patterns on runoff and soil erosion in field plots. Int. Soil Water Conserv. Res. 2015, 3, 273–281. [Google Scholar] [CrossRef] [Green Version]
  85. Anache, J.A.A.; Wendland, E.; Oliveira, P.T.S.; Flanagan, D.C.; Nearing, M.A. Runoff and soil erosion plot-scale studies under natural rainfall: A meta-analysis of the Brazilian experience. Catena 2017, 152, 29–39. [Google Scholar] [CrossRef]
  86. Cerdà, A. The influence of geomorphological position and vegetation cover on the erosional and hydrological processes on a Mediterranean hillslope. Hydrol. Process. 1998, 12, 661–671. [Google Scholar] [CrossRef]
  87. Morán-Tejeda, E.; Fassnacht, S.R.; Lorenzo-Lacruz, J.; López-Moreno, J.; García, C.; Alonso-González, E.; Collados-Lara, A. Hydro-Meteorological Characterization of Major Floods in Spanish Mountain Rivers. Water 2019, 11, 2641. [Google Scholar] [CrossRef] [Green Version]
  88. Keesstra, S.; Zema, D.A.; Saco, P.M.; Parsons, A.; Pöppl, R.; Masselink, R.; Cerda, A. The way forward: Can connectivity be useful to design better measuring and modelling schemes for water and sediment dynamics? Sci. Total. Environ. 2018, 644, 1557–1572. [Google Scholar] [CrossRef]
  89. Russo, A.; Sousa, P.; Durão, R.; Ramos, A.; Salvador, P.; Linares, C.; Díaz, R.; Trigo, R. Saharan dust intrusions in the Iberian Peninsula: Predominant synoptic conditions. Sci. Total. Environ. 2020, 717, 137041. [Google Scholar] [CrossRef]
  90. Russo, A.; Trigo, R.M.; Martins, H.; Mendes, M.T. NO2, PM10 and O3 urban concentrations and its association with circulation weather types in Portugal. Atmos. Environ. 2014, 89, 768–785. [Google Scholar] [CrossRef]
  91. Fernández-Raga, M.; Castro, A.; Marcos, E.; Palencia, C.; Fraile, R. Weather types and rainfall microstructure in Leon, Spain. Int. J. Clim. 2016, 37, 1834–1842. [Google Scholar] [CrossRef]
  92. Teale, N.G.; Quiring, S.M.; Ford, T.W. Association of synoptic-scale atmospheric patterns with flash flooding in watersheds of the New York City water supply system. Int. J. Clim. 2016, 37, 358–370. [Google Scholar] [CrossRef]
Figure 1. Seasonal distribution of the percentage of rainfall, runoff, and sediment yield. The ends of the box are the upper and lower quartiles, so the box spans the interquartile range, the median is marked by a vertical line inside the box, and the whiskers are the two lines outside the box that extend to the highest and lowest observations. The significant value at p < 0.05 (***) and not significance (-) of Wilcoxon signed-rank test are paired remarked between winter and spring, winter and summer, winter and autumn, spring and summer, spring and autumn, and summer and autumn.
Figure 1. Seasonal distribution of the percentage of rainfall, runoff, and sediment yield. The ends of the box are the upper and lower quartiles, so the box spans the interquartile range, the median is marked by a vertical line inside the box, and the whiskers are the two lines outside the box that extend to the highest and lowest observations. The significant value at p < 0.05 (***) and not significance (-) of Wilcoxon signed-rank test are paired remarked between winter and spring, winter and summer, winter and autumn, spring and summer, spring and autumn, and summer and autumn.
Atmosphere 11 00609 g001
Figure 2. Spatial distribution of the percentage of rainfall, runoff, and sediment yield for each season in the study sites, and the number of sites with values higher or lower than 25%.
Figure 2. Spatial distribution of the percentage of rainfall, runoff, and sediment yield for each season in the study sites, and the number of sites with values higher or lower than 25%.
Atmosphere 11 00609 g002
Figure 3. Seasonal distribution of the percentage of rainfall, runoff and sediment yield for the different WTs by each season. The ends of the box are the upper and lower quartiles, so the box spans the interquartile range, the median is marked by a vertical line inside the box, and the whiskers are the two lines outside the box that extend to the highest and lowest observations.
Figure 3. Seasonal distribution of the percentage of rainfall, runoff and sediment yield for the different WTs by each season. The ends of the box are the upper and lower quartiles, so the box spans the interquartile range, the median is marked by a vertical line inside the box, and the whiskers are the two lines outside the box that extend to the highest and lowest observations.
Atmosphere 11 00609 g003
Figure 4. Spatial distribution of the percentage of rainfall, runoff and sediment yield in the west (W) and east (E) weather types for each season. The 2.5% value represents the uniform distribution of 10 WTs and 4 seasons.
Figure 4. Spatial distribution of the percentage of rainfall, runoff and sediment yield in the west (W) and east (E) weather types for each season. The 2.5% value represents the uniform distribution of 10 WTs and 4 seasons.
Atmosphere 11 00609 g004
Figure 5. Frequency of the reference climate period (1981–2010) and in the study events (1985–2015) in the WTs in each season.
Figure 5. Frequency of the reference climate period (1981–2010) and in the study events (1985–2015) in the WTs in each season.
Atmosphere 11 00609 g005
Figure 6. Frequency of the weather types with the major contribution (more than 5%) of the percentage of rainfall, runoff, and sediment yield in each season.
Figure 6. Frequency of the weather types with the major contribution (more than 5%) of the percentage of rainfall, runoff, and sediment yield in each season.
Atmosphere 11 00609 g006
Figure 7. Efficiency index calculated by the product of magnitude (%) and frequency of the seasonal rainfall, runoff, and sediment yield for the different weather types.
Figure 7. Efficiency index calculated by the product of magnitude (%) and frequency of the seasonal rainfall, runoff, and sediment yield for the different weather types.
Atmosphere 11 00609 g007
Table 1. Location of study sites (catchments and plots), data collection period (start and end), number of records, and reference of the study sites included in the database
Table 1. Location of study sites (catchments and plots), data collection period (start and end), number of records, and reference of the study sites included in the database
IDNameLat.Long.ScaleStartEndRecordsReference
1Aisa42.6744−0.6119Plots19952010637Nadal-Romero et al. [34]
2Aixola43.1529−2.5014Catch.20032008222Zabaleta et al. [35]
3Albaladejito40.0762−2.1957Plots1994199728Bienes et al. [36,37]
4Araguás42.5958−0.6208Catch.20052015360Nadal-Romero and Regüés [38]
5Aranjuez40.0798−3.5250Plots1994199738Bienes et al. [36,37]
6Abanilla38.1994−1.0917Plots1988199240Díaz et al. [39]
7Ardal38.0741−1.5383Plots19892000146Romero-Díaz et al. [40]
8Arnas42.6430−0.5847Catch.1999200996Lana-Renault et al. [41]
9Bardenas Norte42.1677−1.4547Plots19932004118Desir and Marín [42]
10Bardenas Sur42.1550−1.4191Plots1993200489Desir and Marín [42]
11Burete38.0500−1.7667Plots20062011142Martínez-Mena et al. [43]
12Can Revull39.55003.1011Catch.2004200719Estrany et al. [44]
13Corbeira43.2181−8.2285Catch.20052014651Rodríguez-Blanco et al. [45]
14El Cautivo37.0027−2.4404Catch.19922014134Cantón et al. [46]
15Idanha39.8467−7.1667Catch.2010201527Canatario-Duarte [47]
16La Conchuela37.8178−4.8958Catch.20062011185Gómez et al. [48]
17La Concordia39.7500−0.7167Plots19952012203Gimeno-García et al. [49]
18La Parrilla37.7333−5.1500Catch.2010201374Cid et al. [50]
19La Puebla41.6645−0.7239Plots19912003187Desir et al. [51]
20La Tejeria42.7363−1.9492Catch.20002014177Casali et al. [52]
21Lanaja41.7797−0.2889Plots19912004163Sirvent et al. [53]
22Latxaga42.7854−1.4364Catch.20032014189Casali et al. [52]
23Laval44.14065.6392Catch.19852014465Cambon et al. [54]
24Marchamalo40.6822−3.2147Plots1994199748Bienes et al. [36,37]
25Mediana41.4534−0.7158Plots19912004137Desir et al. [51]
26Morille40.8315−5.7053Catch.2002201088Hernández-Santana and Martínez [55]
27Moulin44.14065.6392Catch.19882003149Cambon et al. [54]
28Munilla42.1912−2.2908Catch.2012201517Lana-Renault et al. [56]
29Oskotz42.9584−1.7792Catch.20032014416Casali et al. [57]
30Porta Coeli39.6590−0.4890Plots19882012240Andreu et al. [58]
31Puente Genil37.4128−4.8383Catch.2005201193Taguas et al. [59]
32Rinconada40.6003−6.0367Catch.20002010331Hernández-Santana and Martínez [55]
33Roujan43.49173.3213Catch.19922015410Molénat et al. [60]
34Santomera38.2700−1.1167Plots19892002283Martínez-Mena et al. [61]
35Sa Vall39.63863.1766Catch.2004200677Estrany et al. [62]
36Setenil36.8736−5.1269Catch.20052011121Taguas et al. [63]
37Venta Olivo38.3544−1.5194Catch.19972011108Castillo et al. [64]
38Venta Olivo plot38.3833−1.1667Plots20012008161Boix-Fayos et al. [65]
39Vernega Bosc41.87722.9325Catch.1993201144Outeiro et al. [66]
40Vernega Campas41.87382.9213Catch.1993201144Outeiro et al. [66]
41Villamor41.2457−5.5839Catch.2002201087Martínez Fernádez et al. [67]
42Navalón38.9166−0.8333Plots20042014470Cerdà et al. [68]
43Ca L’Isard42.19341.8232Catch.2005201255Latron et al. [69]
44Can Vila42.19811.8234Catch.2005201293Latron et al. [70]
45Parapuños39.6105−6.1333Catch.20012015161Schnabel and Gómez Gutiérrez [71]
46Montnegre41.70002.5666Catch.1998200277Bernal and Sabater [72]

Share and Cite

MDPI and ACS Style

Peña-Angulo, D.; Nadal-Romero, E.; González-Hidalgo, J.C.; Albaladejo, J.; Andreu, V.; Bahri, H.; Bernal, S.; Biddoccu, M.; Bienes, R.; Campo, J.; et al. Relationship of Weather Types on the Seasonal and Spatial Variability of Rainfall, Runoff, and Sediment Yield in the Western Mediterranean Basin. Atmosphere 2020, 11, 609. https://doi.org/10.3390/atmos11060609

AMA Style

Peña-Angulo D, Nadal-Romero E, González-Hidalgo JC, Albaladejo J, Andreu V, Bahri H, Bernal S, Biddoccu M, Bienes R, Campo J, et al. Relationship of Weather Types on the Seasonal and Spatial Variability of Rainfall, Runoff, and Sediment Yield in the Western Mediterranean Basin. Atmosphere. 2020; 11(6):609. https://doi.org/10.3390/atmos11060609

Chicago/Turabian Style

Peña-Angulo, D., E. Nadal-Romero, J.C. González-Hidalgo, J. Albaladejo, V. Andreu, H. Bahri, S. Bernal, M. Biddoccu, R. Bienes, J. Campo, and et al. 2020. "Relationship of Weather Types on the Seasonal and Spatial Variability of Rainfall, Runoff, and Sediment Yield in the Western Mediterranean Basin" Atmosphere 11, no. 6: 609. https://doi.org/10.3390/atmos11060609

APA Style

Peña-Angulo, D., Nadal-Romero, E., González-Hidalgo, J. C., Albaladejo, J., Andreu, V., Bahri, H., Bernal, S., Biddoccu, M., Bienes, R., Campo, J., Campo-Bescós, M. A., Canatário-Duarte, A., Cantón, Y., Casali, J., Castillo, V., Cavallo, E., Cerdà, A., Cid, P., Cortesi, N., ... Zorn, M. (2020). Relationship of Weather Types on the Seasonal and Spatial Variability of Rainfall, Runoff, and Sediment Yield in the Western Mediterranean Basin. Atmosphere, 11(6), 609. https://doi.org/10.3390/atmos11060609

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop