Spatial heterogeneity of
infiltration in semi-arid areas
Maartje Anna Wadman - 11051248
Institute for Interdisciplinary Studies,
University of Amsterdam
Supervisors: Erik Cammeraat,
Jeroen Zethof
Abstract
Soil erosion and land degradation are common problems in the dryland zones of South-East Spain, because of the sparse vegetation cover. This research has investigated how the soil infiltration rates differ in relation to soil cover in a heterogeneous patchy vegetated semi-arid landscape. Ten plots of Macrochloa tenacissima (= Stipa tenacissima) tussocks and Anthyllus cytisoides were investigated and sampled in the Rambla Honda valley. A distinction was made between canopy, near canopy edge and bare patches. Moreover, a distinction was made between mid-slopes and alluvial fans. The results showed that soil organic matter influences the water repellency and water conductivity. The soil around Macrochloa tenacissima is less water repellent in comparison with soil around Anthyllus cytisoides and the soil moisture content and water repellency are higher on the alluvial fan in comparison on the slope. Furthermore, rainfall infiltrates and evaporates on the spot itself or in the nearby plant tussocks. Lastly, vegetation patches have higher infiltration rates, higher soil moisture contents and higher water repellencies. This is due to the higher organic matter content of vegetation patches and due to the occurring micro-climate under vegetation. The soil moisture content and hydraulic conductivity are in general relatively low and the width of the bare zones will increase even more. With the increase of extreme rainfall events due to climate change, management practices are needed to reduce runoff and erosion problems.
Content
Abstract ... 1
Introduction ... 1
Research aim & questions ... 2
Fieldwork area ... 2
Materials and methods ... 4
Methods fieldwork ... 4
Calculation of the infiltration rate ... 5
Methods laboratory ... 5 Statistical analysis ... 6 Results ... 7 Discussion ... 12 Acknowledgements ... 15 References ... 16 Appendices... 19 Appendix A. Data ... 19
Appendix B. Linear regression analyses ... 22
Appendix C. Kruskal Wallis test (+ post-hoc) ... 23
Introduction
Soil erosion and land degradation are common problems in the dryland zones of South-East Spain, because of the sparse vegetation cover. The importance of identifying and understanding which factors determine degradation and plant-soil-landscape interaction, is an essential component in analyzing these problems (Cammeraat, 2004). This study will zoom in on if water will infiltrate or not, in relation to vegetation.
In semi-arid areas, vegetation is typically spatially distributed in relatively densely vegetated areas and areas with relatively sparse vegetation or bare soil (Contreras, Cantón & Solé-Benet, 2008; Baartman, Temme & Saco, 2018). Consequently, mosaics of vegetated patches and bare areas of different sizes and shapes are formed (Puigdefábregas, Sole, Gutiérrez, Del Barrio & Boer, 1999). Furthermore, semi-arid slopes are often rocky and covered with shallow rocky soils whereas at the base of the slope extensive sediment fills develop (Nicolau, Solé-Benet, Puigdefábregas & Gutiérrez, 1996). Because of this vegetation pattern and differences between mid-slope and base-slope, high spatial heterogeneity, in terms of soil properties, is also a common feature of semi-arid areas (Puigdefábregas et al., 1999; Bautista, Mayor, Bourakhouadar & Bellot, 2007). In general, soils under vegetation are better developed, showing higher organic matter, higher nutrient level and lower pH values than bare patches. All these soil properties improve the infiltrability of a soil (Bochet, Rubio & Poesen, 1999; Maestre & Cortina, 2002). Other differences in soil properties that may influence the infiltrability of a soil are: total porosity of a soil, soil aggregate stability, mineral and biological crusts and surface compaction (Bautista, Mayor, Bourakhouadar & Bellot, 2007; Cantón, Solé-Benet, Asensio, Chamizo & Puigdefábregas, 2009). Lastly, water repellency is another factor that influences the infiltrability of a soil, because water repellency induces preferential flow paths (Bisdom, Dekker & Schoute, 1993; Contreras, Cantón & Solé-Benet, 2008). As a consequence of preferential flow, water infiltrates at some points more rapidly in the soil than in the case of a homogeneous infiltration front (Bisdom, Dekker & Schoute, 1993). Furthermore, crusts influence the impact of water repellency in the topsoil by inhibiting infiltration (Contreras, Cantón & Solé-Benet, 2008).
Over the last years, a range of studies in soil processes, vegetation dynamics and hillslope hydrology have been carried out in the Rambla Honda Basin (Nicolau, Solé-Benet, Puigdefábregas & Gutiérrez, 1996; Puigdefábregas et al., 1996; Puigdefábregas et al., 1999; Cantón et al., 2009; Contreras, Cantón & Solé-Benet, 2008). However, there is still a lack of field data to quantify the underlying key assumptions of the relation between the infiltration rate of a soil, vegetation cover, slope angle, vegetation type and water repellency of the soil (Bautista, Mayor, Bourakhouadar & Bellot, 2007). Most work on these topics has been done on agricultural land in temperate climates, and many studies on vegetation patch dynamics have been conducted in mesic forests and grasslands instead of semiarid environments (Aguiar & Sala, 1999; Cantón et al., 2009). Consequently, studies in semiarid environments on these topics have been comparatively scarce (Aguiar & Sala, 1999). Furthermore, ecological and hydrological processes can interact strongly in landscapes, yet these processes are often studied separately. Therefore, experimental fieldwork is also needed to better quantify these interactions (Ludwig, Wilcox, Breshears, Tongway & Imeson, 2005). This research aims to contribute to this knowledge, by investigating how the soil infiltration rates differ in relation to soil cover in a heterogeneous patchy vegetated semi-arid landscape. This knowledge could also be useful to learn more about the effect of land abandonment on vegetation, hydrology and erosion, since large areas of bare soil are poorly protected against erosion and implies changes in management policies (Cerdà, 1997; Cammeraat, van Beek & Kooijman, 2005).
Research aim & questions
The research aims to find a difference in soil infiltration rates between vegetation cover (bare, near canopy edge and canopy patches), geomorphologic units (shoulder and alluvial fan) and vegetation type (Macrochloa tenacissima (= Stipa tenacissima) and Anthyllis cytisoides). To reach the aim of this research, the following research question has been asked: How do the soil hydrological characteristics differ in
relation to soil cover in a heterogeneous patchy vegetated semi-arid landscape? To answer this question,
the following sub questions will be addressed:
1. What is the effect of Macrochloa tenacissima and Anthyllis cytisoides on soil hydrological characteristics?
2. What is the difference in effect of bare, near canopy edge and canopy patches on soil hydrological characteristics?
3. How do soil hydrological characteristics differ in relation to two contrasting geomorphologic units?
Fieldwork area
The research area is located nearby the city of Almeria in South East Spain in the Rambla Honda valley. Figure 1 shows the exact location of the fieldwork area. It is located in the Internal Zone of the Betic Cordillera mountain range, which can be subdivided into different complexes (Galdeano & Garrido, 2016). More specific, the fieldwork area is located in the contact zone between the south versant of the Filabres range, which is part of the Nevado-Filábride Complex, and the Neogene depression of Sorbas-Tabernas (Puigdefábregas et al., 1996). The bedrock is composed of a monotonous series of graphite mica schist’s with garnet and crossed by abundant quartz veins (Instituto Geológico y Minero de España, 1975; Puigdefábregas et al., 1996; Nicolau, Solé-Benet, Puigdefábregas & Gutiérrez, 1996). Its degree of weathering depends on the layering pattern and to the proportions of garnets and quartz (Puigdefábregas et al., 1996). Bedrock hillslopes are transformed by differential erosion and gradate to an alluvial fan system which connects with the Rambla Honda fan system (Puigdefábregas et al., 1996). In the upper part of the slopes, Macrochloa tenacissima tussocks is the dominant vegetation species, whereby Anthyllus cytisoides is the dominant vegetation species on the upper part of the alluvial fans (Puigdefábregas et al., 1996; Cantón et al., 2009). Macrochloa tenacissima is a perennial grass with long and thin leaves. Furthermore, it forms dense tussocks about 70 cm high and has a twofold rooting system. The first 20 cm of the soil consist of a dense matrix of thin roots, which also extends outside the canopy area. More than 20 cm deep, if the soil allows, there is a deep central dense rooting system (Bochet, Rubio & Poesen, 1999). Anthyllus cytisoides is a perennial summer-deciduous shrub about 50 cm high, with a much deeper root system and adjusted to survive extreme drought periods (Bochet, Rubio & Poesen, 1999). Most of the soils have a sandy loam texture, whereby the uppermost layer is composed of a rock fragment cover, the middle layer is a washed-out layer and the bottom layer is a washed-in layer with fine platy particles, mostly parallel to the surface (Puigdefábregas et al., 1996; Cantón et al., 2009; Contreras, Cantón & Solé-Benet, 2008). Coarse fragments larger than 2 mm in diameter range from 12.75% in the alluvial fan to 67% at the slopes (Puigdefábregas et al., 1996). Surface stoniness also increases up the slope (Puigdefábregas et al., 1996). Up to the 1960s, the area was cultivated for grain and there were grazing sheep and goats, thereafter agricultural land has been abandoned (Puigdefábregas et al., 1996; Nicolau, Solé-Benet, Puigdefábregas & Gutiérrez, 1996). The research area has a semi-arid climate with warm dry summers and mild winters and is the driest area of Europe (Cammeraat, 2017; Puigdefábregas et al., 1996). The average annual rainfall measured by the Tabernas weather station, located nearby the fieldwork area, is 250 mm. Furthermore, the average annual temperature in the study area for April is around 17 ˚C, and the daily temperature amplitude is higher in summer than in winter. The occurrence of extreme, intensity rainfall is another important aspect of the local
climate (Cammeraat, 2017). When the water in the Mediterranean Sea is still very warm in September and October, the extremely humid air drifts from the east land inwards where it is pushed upward through the mountains. The air cools down rapidly because of this and creates instability in the atmosphere causing extremely heavy rainfall locally (Cammeraat, 2017).
Figure 1 Fieldwork area, Southeast-Spain (Google Earth, April 9th 2017) with study area Rambla Honda catchment (Wadman,
Materials and methods
Methods fieldwork
Sampling/experimental design
Ten plots of Macrochloa tenacissima tussocks and Anthyllus cytisoides were investigated and sampled in the study area. The plants had to be free standing plants with not that much rabbit droppings around the stem, because rabbits could have influence the crust. Five plots were sampled on mid-slopes and the other five plots were sampled on alluvial fans. A distinction was made between canopy, near canopy edge and bare patches (figure 2). The distance between near canopy edge and bare patches was approximately 0.50 meter. The plots were distributed on three different mid-slopes and fans, covering a wide range of variation in vegetation-patch density and spatial arrangement. Slope angle (20˚ for the shoulder, 9˚ for the alluvial fan), relative position on both slopes, and aspect (East-Southeast) was more-or-less similar between the different plots.
Soil sampling method
Samples were taken from the soil surface (crust layer) and 2-5 cm below soil surface. Except for canopy and stem patches where no crust was available, organic material was removed from the surface and samples were taken. At the end, 100 samples were collected and taken to the soil and environmental chemistry laboratories of the Institute of Biodiversity and Ecosystem Dynamics (IBED) at the University of Amsterdam (UvA) for further analyses, of which the methods will be explained in the third paragraph. Infiltration experiment
The infiltration rate was measured at each sampling point with a Mini Disk Infiltrometer model MI2 from Decagon Devices with a suction of 2.0 cm using Ethanol (96%). Once the Infiltrometer was placed on a soil, ethanol infiltrated at a rate determined by the hydraulic properties of the soil. Every 5 seconds, the volume (shown in mL) was recorded. Furthermore, a ring stand and a thin layer of fine silica sand directly underneath the Infiltrometer was used to make good contact between the soil and the Infiltrometer. Lastly, at least 15 to 20 mL of ethanol needed to be infiltrated into the soil during each measurement (Decagon Devices, 2016).
Figure 2 Illustration of places were different samples were taken. 2a: a distinction was made between slope angle (shoulder &
alluvial fan), vegetation type (Macrochloa tenacissima & Anthyllus cytisoides). 2b: a distinction was made between vegetation cover (bare, near canopy edge & canopy patches) (Wadman, 2018).
Calculation of the infiltration rate
During fieldwork, the volume of the Mini Disk Infiltrometer was recorded every 5 seconds for each sample. This data was plotted using the Microsoft excel spreadsheet, available at www.decagon.com/macro, to calculate the unsaturated hydraulic conductivity. This excel spreadsheet used the method proposed by Zhang (1997), which requires measuring cumulative infiltration versus time and fitting the results with the function:
I = C1t + C2√t
Where 𝐶1(∝ 𝑚𝑠
−1) and 𝐶2(𝑚 ∗ 𝑠−12) are parameters. C1 is related to hydraulic conductivity, and C2 is the soil sorptivity (Decagon Devices, 2016). The hydraulic conductivity for the soil (K) is then computed from:
K = C1 / A
Where C1 is the slope of the curve of the cumulative infiltration versus the square root of time, and A is a value relating the van Genuchten parameters for a given soil type to the suction rate and radius of the Infiltrometer disk (Decagon Devices, 2016). The suction force used during the fieldwork was 2.0 cm and the radius was 2.25 cm. According to Puigdefábregas et al. (1996), Cantón et al. (2009) and Contreras, Cantón & Solé-Benet (2008), the soils in the area were mainly sandy loams. Consequently, A has a constant value of 3.909913417.
However, it has to be taken into account that ethanol was used instead of water to measure the infiltration rate. By using ethanol for the infiltration measurements, the influence of soil water repellency effect on infiltration rates is neglectable.
Methods laboratory
The retrieved samples were analyzed in the laboratory by using different methods for water repellency of the soil and soil moisture content.
Soil moisture content (SMC)
To calculate the soil moisture content, the initial weight of soil (around 5 gram) was measured before the samples were placed inside an oven heated at 105˚C for 24 hours. After the samples were heated, the dry weight of soil was measured. Finally, the difference between wet and dry weight indicated the soil moisture content (Department of Sustainable Natural Resources, n.d.):
𝑆𝑀𝐶% = 𝑊2−𝑊3 𝑊3−𝑊1 𝑥 100 W1 = Weight of container (g)
W2 = Weight of moist soil + container (g) W3 = Weight of dried soil + container (g) Water repellency
Soil samples were air dried at 40˚C and passed through a 200-0.125-sieve to break down larger soil aggregates. After that, the water repellency of a sample was measured with two methods: the water drop penetration time (WDPT) test (Bisdom, Dekker & Schoute, 1993; Contreras, Cantón & Solé-Benet, 2008) and the sessile drop method (SDM) test (Bachmann, Ellies & Hartge, 2000).
Water Drop Penetration (WDPT) Test
The penetration time of each sample is the median value penetration time of five drops of distilled water placed onto each air-dry sample in a Petri dish with a micropipette (50-μL volume) (Bisdom, Dekker & Schoute, 1993; Contreras, Cantón & Solé-Benet, 2008). The classification of water repellency that was used is shown in table 1 (Bisdom, Dekker & Schoute, 1993).
Table 1. Classification of water repellency Water Drop Penetration Time (Bisdom, Dekker & Schoute, 1993)
Sessile Drop Method (SDM) Test
The soil samples that had a penetration time higher than 5 seconds, see WDPT test, were sprinkled on a double-sided adhesive tape which was fixed on a smooth glass slide (Bachmann, Ellies & Hartge, 2000; Leelamanie, Karube & Yoshida, 2008). The glass slides were air dried at 40˚C for an hour and placed on the stage of a digital microscopic camera. Five drops of distilled water were placed onto each sample with a micropipette (50-μL volume) and a digital microphotograph of the horizontal view of the water drop was taken within 5 s (Bachmann, Ellies & Hartge, 2000; Leelamanie, Karube & Yoshida, 2008). The contact angle of each sample was measured with the DropSnake plugin from the program ImageJ
(http://mmrc.caltech.edu/Gniometeer/drop_analysis/drop_analysis.pdf) .
Statistical analysis
All input data was processed in Microsoft Excel2016 and for statistical analysis and visualization of the data, MATLAB R2017b was used. Firstly, multiple linear regression analyses were performed to examine the relations between soil moisture content, water repellency and hydraulic conductivity. Secondly, the Wilcoxon rank sum test, which is a non-parametric statistical hypothesis test, was used to compare two related samples. Thirdly, the Kruskal Wallis test was used as non-parametric method for comparing two or more independent samples and indicating that at least one sample must differ from one other sample. Post-hoc tests were used to test the specific sample pairs for stochastic dominance. Non-parametric tests were used, because when making plots in MATLAB R2017b, the data was not normal distributed. Lastly, an exponential regression analysis was performed to examine the correlation between the WDPT test and SDM test.
WDPT (s)
Classification
<5 Wettable
5-60 Slightly water repellent 60-600 Strongly water repellent 600-3600 Severely water repellent >3600 Extremely water repellent
Results
Results of data are given in this paragraph. All the exact data, full written names and coordinates can be found in Appendix A.
Table 2 gives the outcomes of the linear regression analyses in R-squared and p-values. The graphs of the analyses can be found in Appendix B. The variables soil moisture content and hydraulic conductivity have a significant but very low correlation with a R-squared of 0.15. The variables soil moisture content and WDPT test have a significant but very low correlation with a R-squared of 0.0958. The variables SDM test and hydraulic conductivity have a significant but very low correlation with a R-squared of 0.044243 (table 2).
Table 2 Correlations between soil moisture content, water repellency and hydraulic conductivity. Data is considered significant(*)
if the p-value is <0.05. (SMC = Soil Moisture Content, WDPT = Water Drop Penetration Time, SDM = Sessile Drop Method).
Linear regression Analyses R-squared p-value SMC – Hydraulic Conductivity 0.15 7.47e-05*
SMC – WDPT 0.0958 0.0019225*
SMC – SDM 0.0342 0.36606
WDPT – Hydraulic Conductivity 0.0117 0.28682 SDM – Hydraulic Conductivity 0.158 0.044243*
In table 3, all p-values of the Wilcoxon rank sum tests are shown. P-values lower than 0.05 indicate that there is a significant difference between the variables. These significant differences will be explained with boxplots and bar plots in this paragraph.
Table 3. p-values Wilcoxon rank sum test. Data is considered significant (*) if the p-value is <0.05 (B = Bare, C = Canopy border,
S = Stem, F = Fan, H = Hill, A = Anthyllus cytisoides, M = Macrochloa tenacissima, 1 = soil layer 1 (crust), 2 = soil layer 2 (sub-crust)).
Table 4 gives all significant p-values of a Kruskal Wallis test and indicate a difference in median between the variables. All p-values, included non-significant p-values, can be found in appendix C.
Pair p-value SMC p-value K p-value WDPT
M A 0.9303 0.2034 0.0044* F H 0.0051* 0.9313 0.0886 FM HM 0.0123* 0.1683 0.7125 FA HA 0.1362 0.1073 0.0158* MB AB 0.9676 0.6554 0.1661 MC AC 0.9664 0.0531 0.0603 MS AS 0.9097 0.7337 0.0605 1 2 2.8714e-06* 0.1259 0.0045* B1 B2 0.0193* 0.4570 0.1766 C1 C2 0.0017* 0.7557 0.0583
Table 4: significant p-values Kruskal Wallis test (+ post hoc) (B = Bare, C = Canopy border, S = Stem, F = Fan, H = Hill, A =
Anthyllus cytisoides, M = Macrochloa tenacissima, 1 = soil layer 1 (crust), 2 = soil layer 2 (sub-crust)).
Significant pair p-value SMC p-value K p-value WDPT
B1 C2 0.0008 B1 S 0.0000 0.0035 0.0398 B2 S 0.0467 0.0383 C1 C2 0.0490 C1 S 0.0027 AB1 AS 0.0281 AB1 MS 0.0223 0.0421 AS MB1 0.0229 MB1 MBS 0.0180
Figure 3 displays the hydraulic conductivity (K(cm/s)) grouped per plant and position. There is a significance difference (p = 0.0035) between the hydraulic conductivity of bare soil layer 1 (crust) (B1) and the stem (S). Furthermore, there is a significance difference (p = 0.0383) between the hydraulic conductivity of bare soil layer 2 (sub-crust) (B2) and the stem (S). The hydraulic conductivity of sampling points by the stem have higher K values in comparison with the bare patches. Lastly, there is almost a significant difference (p = 0.0531) between the canopy patches of the Macrochloa tenacissima and the Anthyllus
cytisoides, whereby the canopy patches of the Anthyllus cytisoides have a higher hydraulic conductivity.
Figure 3 Boxplots of Hydraulic Conductivity. a) Boxplot of Slope – Macrochloa tenacissima,. b) Boxplot of Slope Anthyllus
cytisoides. c) Boxplot of Alluvial Fan – Macrochloa tenacissima. d) Boxplot of Alluvial Fan – Anthyllus cytisoides (B = Bare, C = Canopy border, S = Stem, F = Fan, H = Hill, A = Anthyllus cytisoides, M = Macrochloa tenacissima, 1 = soil layer 1 (crust), 2 = soil layer 2 (sub-crust)).
Figure 4 shows the distribution of the soil moisture content (%). There is a significant difference (p = 0.0051) between the alluvial fan (F) and slope (H), whereby the alluvial fan has in general higher soil moisture content frequencies in comparison with the slope. This is also the case for the difference between
Macrochloa tenacissima on a slope (HM) in comparison with Macrochloa tenacissima on an alluvial fan
(FM) (p = 0.0123). However, no significant differences were found between Anthyllus cytisoides on a slope (HA) in comparison with Anthyllus cytisoides on an alluvial fan (FA) (p = 0.1362). Moreover, a significant difference was found between soil layer 1 and soil layer 2 (p = 2.8714e-06), whereby soil layer 2 has a higher soil moisture content. This significant difference is also visible for bare soil layer 1 in comparison with bare soil layer 2 (p = 0.0193) and for canopy layer 1 (C1) in comparison with canopy soil layer 2 (C2) (p = 0.0017). Lastly, there are significant differences between bare soil layer 1 and 2 in comparison with canopy soil layer 2 and stem (table 4), whereby canopy soil layer 2 and the stem have higher soil moisture content frequencies.
Figure 4 Boxplots of Soil Moisture Content. a) Boxplot of Slope – Macrochloa tenacissima. b) Boxplot of Slope Anthyllus
cytisoides. c) Boxplot of Alluvial Fan – Macrochloa tenacissima. d) Boxplot of Alluvial Fan – Anthyllus cytisoides (B = Bare, C = Canopy border, S = Stem, F = Fan, H = Hill, A = Anthyllus cytisoides, M = Macrochloa tenacissima, 1 = soil layer 1 (crust), 2 = soil layer 2 (sub-crust)).
Figure 5 shows the classification of degree of water repellency per vegetation density. Firstly, there is a significant difference (p = 0.0044) between Anthyllus cytisoides and Macrochloa tenacissima, whereby the Anthyllus cytisoides is more water repellent. Secondly, a significant difference is found between
Macrochloa tenacissima on a slope and Macrochloa tenacissima on an alluvial fan (p = 0.0158). Thirdly,
a significant difference is found between soil layer 1 and 2 (p =0.0045). Soil layer 2 is more water repellent in comparison with soil layer 1. Finally, the stem and canopy soil layer 2 have a significant higher water repellency in comparison with bare soil layer 1 (table 4). The difference between the alluvial fan and slope is almost significant (p = 0.0886), whereby the soil of an alluvial fan is more water repellent.
Figure 5 Bar plots of the relative frequency of wettable and water repellent soil samples per vegetation density (B = Bare, C =
Canopy border, S = Stem, F = Fan, H = Hill, A = Anthyllus cytisoides, M = Macrochloa tenacissima, 1 = soil layer 1 (crust), 2 = soil layer 2 (sub-crust)).
Figure 6 shows the distribution of the 26 contact angles for the different sampling points with a higher water repellency than 5 seconds measured with the WDPT test. A slightly upward trend towards the stem is visible, mainly by Anthyllus cytisoides. Figure 7 illustrates the difference between a higher and lower contact angle. The exponential regression analysis that has been done between the SDM test and WDPT test, concludes that the SDM contact angles are well correlated with the water drop penetration time, since the R-squared is 0.9034 (appendix D). Leelamanie, Karube & Yoshida (2008) did a research about the relationship between contact angle and WDPT. They found a correlation between those two tests with a R-squared of 0.92 (Leelamanie, Karube & Yoshida, 2008).
Figure 6 Scatterplot of contact angles for the different sampling points (B = Bare, C = Canopy border, S = Stem, F = Fan, H = Hill,
A = Anthyllus cytisoides, M = Macrochloa tenacissima, 1 = soil layer 1, 2 = soil layer 2).
Figure 7 Microphotographs of (a) sample with a higher contact angle (85˚) and (b) sample with a lower contact angle (45 ˚)
Discussion
Difference in effect of Macrochloa tenacissima and Anthyllus cytisoides on soil hydrological characteristics
Bisdom, Dekker & Schoute (1993) and Contreras, Cantón & Solé-Benet (2008), argue that organic matter induces water repellency in soils, whereby fresh and partly decomposed organic matter have a higher water drop penetration time, than more completely humified fragments. Consequently, the more organic matter, the more water repellent the soil (Bisdom, Dekker & Schoute, 1993; Contreras, Cantón & Solé-Benet, 2008). The results in this research showed that there is a significant difference in effect of Macrochloa tenacissima and Anthyllus cytisoides on the soil water repellency of a soil, whereby the soil around Macrochloa
tenacissima is less water repellent in comparison with soil around Anthyllus cytisoides. Furthermore, the
bachelor thesis of Verweij (2018, in press) showed that organic matter is higher for Anthyllus cytisoides than Macrochloa tenacissima during the same research. Therefore, this relation between organic matter and water repellency is in agreement with the literature described above. The results are also in agreement with a research of Verheijen & Cammeraat (2007), in the Guadalentin area in South-East Spain. They stated that soil water repellency depends on leaf wax contents and on the ectorganic profile of a soil. The ectorganic profile consists of litter, fragmentation and humifaction layers. During their research, the ectorganic profile of an Anthyllus cytisoides was thin and the ectorganic profile of a Macrochloa tenacissima was absent. Furthermore, the estimated relative wax input rate was moderate for Anthyllus cytisoides and low for
Macrochloa tenacissima. Consequently, the soil under Macrochloa tenacissima was less water repellent
than soil under Anthyllus cytisoides. Moreover, they concluded, the less water repellent the soil is, the greater the variation in the WDPT data. An explanation for this may be that a low water repellent soil sample, has fewer soil particles with a water repellent coating and thus a more heterogeneous distribution of water repellent soil particles (Verheijen & Cammeraat, 2007). This could also be an explanation for the relatively great variation in the WDPT data of this research.
However, according to Bochet, Rubio & Poesen (1999), the soil around Anthyllus cytisoides is poorer in organic matter in comparison with the soil around Macrochloa tenacissima. The first explanation for this is that Macrochloa tenacissima tussocks have much greater canopy densities (Bochet, Rubio & Poesen, 1999). Another explanation is that the Macrochloa tenacissima has a dense matrix of thin roots concentrated in the first 20 cm, which also results in more organic matter, which was already explained in the fieldwork area section (Bochet, Rubio & Poesen, 1999). Finally, the high density of leaves of the
Macrochloa tenacissima forms a transverse barrier on slopes. This increases sedimentation upslope, which
leads to micro terraces and capture of organic matter (Bochet, Rubio & Poesen, 1999). With this last explanation, a significant difference between soil water repellency around a Macrochloa tenacissima on a slope and soil water repellency around a Macrochloa tenacissima on an alluvial fan would be expected. However, only a significant difference between Anthyllus cytisoides on the slope and Anthyllus cytisoides on the alluvial fan was found, whereby the water repellency of the soil around Anthyllus cytisoides on the alluvial fan is higher. An explanation for this could be that an Anthyllus cytisoides shrub consist of one single stem and does not form a transverse barrier on slopes. Consequently, this shape under the combined effect of gravity and water fluxes determine a greater downslope intensity of litter, whereby Anthyllus
cytisoides shrubs on an alluvial fan has a higher water repellent frequency in comparison with Anthyllus cytisoides shrubs on a slope (Bochet, Rubio & Poesen, 1999).
No significant differences in effect of Macrochloa tenacissima and Anthyllus cytisoides on the soil moisture content and hydraulic conductivity were found during this research. An enhancing infiltrability would be expected by an Anthyllus cytisoides in comparison with a Macrochloa tenacissima, because of the higher soil organic matter content in this research (Puigdefábregas et al., 1996). At the same moment, the soil organic matter increases the water repellency of the soil as explained above, which could decrease the infiltrability of a soil for a certain amount. However, the infiltration measurements that have been done during this research were performed with 96% ethanol, which means that the hydrophobicity have neglectable influences on the infiltration rate. There is still a very low correlation between the hydraulic
conductivity and water repellency. This correlation might be caused by an indirect correlation with organic matter, that influences both water repellency and the soil structure.
Soil hydrological characteristics in relation to two contrasting geomorphologic units
The results showed that soil moisture content differ significantly in relation to two contrasting geomorphologic units and that the water repellency almost differ significantly in relation to two contrasting geomorphologic units. The soil moisture content is higher on an alluvial fan in comparison to the slope. Furthermore, the water repellency of an alluvial fan is also higher in comparison with the slope. Many studies indicate that a correlation between them could be expected, whereby water repellency decline as soil moisture increases until a critical moisture content, above which a soil becomes water repellent (Doerr & Thomas, 2000). However, according to Doerr, Shakesby & Walsh (2000), soils can absorb water while being water repellent and an initial increase in water repellency with soil moisture has also been found in different literature. Water repellency was found to be present for soil moisture content of up to 22% in sandy loams (Doerr, Shakesby & Walsh, 2000), while the maximum soil moisture content in this research in sandy loams is about 11%. This absorbing of water, while having a water repellent soil, could occur, because water repellency is discontinuous within the soil vertically (Doerr, Shakesby & Walsh, 2000). When a topsoil crust is broken or have some cracks, the effect of water repellency is less in the sublayer and water can still infiltrate (Contreras, Cantón & Solé-Benet, 2008). Moreover, hydrophobic surface and deep infiltration also reduces evaporation, which causes a higher soil moisture content (Mulligen & Sevink,1992; Granged, Jordán, Zavala & Bárcenas, 2011).
No significant difference was found between the hydraulic conductivity of the slope and of the alluvial fan. However, Abrahams & Parsons (1991), Poesen and Ingelmo-Sánchez (1992) suggest that higher runoff in slopes and higher infiltration in fans could be expected and Puigdefábregas et al. (1996) have confirmed these expectations for the runoff and infiltration in Rambla Honda. Slopes contain larger rock fragments in comparison with alluvial fans (Puigdefábregas et al., 1996). Furthermore, rock fragments larger than 100 mm are mostly embedded in the soil surface, while smaller rock fragments are mostly found on the surface (Puigdefábregas et al., 1996). Rock fragments embedded in the soil causes very low infiltration, whereby rock fragments on the soil surface causes higher infiltration (Poesen & Ingelmo-Sanchez, 1992). Consequently, the surface roughness coefficient is higher over slopes, because of the larger rock fragments that are mostly embedded (Puigdefábregas et al., 1996). However, some other literature state that gravity driven transfer of water from hillslope to alluvial fan only occurs during extreme rainfall events and that most of the time rainfall infiltrates and evaporates on the spot itself or in the nearby plant tussocks (Puigdefabregas et al., 1999).
Difference in effect of distance to the plant on soil hydrological characteristics
The results showed that there is a significant difference in effect of distance to the plant on all three soil hydrological characteristics. According to Puigdefábregas et al. (1996) and Aguiar & Sala (1999), bare patches have lower infiltration rates than vegetation patches. In other words, bare patches represent areas of overland flow, whereby vegetation patches are sinks for the transported water (Aguiar & Sala, 1999; Ludwig et al., 2005; Belnap, Welter, Grimm, Barger & Ludwig, 2005). The input of water to vegetation patches stimulate plant growth, which increases the capacity of the patch to obstruct overland flows (Ludwig et al., 2005). Furthermore, the higher water availability in the vegetation patches combined with the input of (fresh) organic matter, promotes soil aggregate and macropore formation, resulting in an enhance infiltrability (Ludwig et al., 2005). Researches of Roth et al. (2003), Dunkerley (2002) and Wilcox et al. (2003) also support that vegetation patches have higher infiltration rates compared to bare patches (Ludwig et al., 2005).
Although, a significant but very low correlation was found during this research between the hydraulic conductivity and soil moisture content, the difference of infiltration rates between bare patches
comparison with bare patches. Furthermore, Bochet, Rubio & Poesen (1999) pointed out that under vegetation a micro-climate occurs, where inputs of wind speed, solar radiation and soil temperature are reduced. This results in lower evaporation rates under vegetation cover in comparison with bare patches (Bochet, Rubio & Poesen, 1999).
As already explained in this paragraph, organic matter induces water repellency in soils. Vegetation patches have a higher supply of organic matter than bare soil, causing a higher water repellency (Bisdom, Dekker & Schoute, 1993; Contreras, Cantón & Solé-Benet, 2008). Two factors that might reduce this water repellency are biodegradation of biomass and deactivation of soil organic matter (Bisdom, Dekker & Schoute, 1993). During biodegradation of biomass, organic macromolecules are broken down, which reduces water repellency. Deactivation of soil organic matter takes place when water-repellent plant fragments are partly or wholly coated with clay, quartz or amorphous substances (Bisdom, Dekker & Schoute, 1993). Furthermore, the effects of broken topsoil crusts or cracks on the water repellency and soil moisture content are also already explained in this paragraph. These effects could explain why the soil moisture content is much lower on the mid-slope for bare soil layer 1 and bare soil layer 2 in comparison with the alluvial fan, while the soil moisture content for bare soil layer 2, canopy soil layer 2 and stem stays relatively high on the mid-slopes. On a slope, there are more cracks due to the larger rock fragments. Consequently, the effect of water repellency is less in soil layer 2 on a slope in comparison with soil layer 2 in an alluvial fan, because the water has a higher frequency of preferential flow pathways (Doerr, Shakesby & Walsh, 2000).
Further research
Currently, with an average of 250 mm annual rainfall measured by the Tabernas weather station, rainfall events do not cause that much runoff and erosion problems on the hill slopes and alluvial fans. Only rare events are able to produce broad scale changes. However, fine scale processes of soil hydrological characteristics in relation to vegetation cover, geomorphologic units and vegetation types modify runoff and erosion little by little further over time (Cammeraat, 2004). Especially with the increase of extreme rainfall events due to climate change, runoff and erosion will become a problem (Puigdefabregas et al., 1999). This research looked at the interaction between these fine scale processes. It has to be taken into account that a total of 16 mm rainfall was measured by the Tabernas weather station on 25 April and 26 April 2018 during fieldwork. No samples were taken during these days, however it could have led to small changes in the measured results. In general, the soil moisture content and hydraulic conductivity are already relatively low in comparison with the humid northern areas of the Mediterranean region (Poesen and Hooke, 1997). Furthermore, the slopes and alluvial fans are already bare due to human influence on the soils (Puigdefábregas et al., 1996). The width of the bare zones will increase even more due to climate change and providing more runoff C9erdà, 1997).
Therefore, it is important to undertake management practices whereby high infiltration rates will be enhanced, which is related to soil moisture content and water repellency of a soil, and whereby land degradation will be avoided (Cerdà, 1997). Vegetation patterns in direction perpendicular to the slope could increase the resistance to downhill flows and could increase the infiltration of water on hillslopes (Puigdefabregas et al., 1999). Furthermore, gullies could be effective for transferring runoff from slope to alluvial fan (Poesen et al., 2003). Further research is needed to determine if these management practices could be effective in this research area. It is difficult to extrapolate this research to larger areas, because the small-scale location of the measurements strongly influences the results (Cammeraat, 2004; Doerr, Shakesby & Walsh, 2000). Therefore, the same research has to be done in many more different areas. Moreover, more extreme water repellent samples should be taken, to could justify that there is actually an exponential regression between the WDPT test and SDM test. In this research, it was assumed that the significant differences according to the WDPT test could also be applied for the SDM test, while the end of the fitted curve was determined by just two sampling variables. Lastly, a correction factor for measuring the hydraulic conductivity with ethanol 96% instead of water in the Microsoft excel spreadsheet from Decagon would also be a good improvement for calculating the hydraulic conductivity.
Conclusion
The results of this study showed that soil organic matter influences the water repellency and water conductivity. Due to a difference in soil organic matter, the soil around Macrochloa tenacissima is less water repellent in comparison with soil around Anthyllus cytisoides. No enhancing infiltrability was found by an Anthyllus cytisoides in comparison with a Macrochloa tenacissima. This is normally caused by a higher organic matter content, which indicates better development of the soil.
Furthermore, the soil moisture content and water repellency are higher on the alluvial fan in comparison to the slope. A correlation was expected whereby water repellency decline as soil moisture increases until a critical moisture content, above which a soil becomes water repellent. However, water can still infiltrate via cracks and a hydrophobic surface and deep infiltration also reduces evaporation. The surface roughness of the slope, because of the larger embedded rock fragments, did not make a difference between the hydraulic conductivity of the slope and the alluvial fan. Most of the time, rainfall will infiltrates and evaporates on the spot itself or in the nearby plant tussocks.
Moreover, vegetation patches have higher infiltration rates than bare patches. Higher water availability increases the input of organic matter, promotes soil aggregate and macropore formation, which all results in an enhancing infiltrability. Under vegetation a micro-climate also occurs, where inputs of wind speed, solar radiation and soil temperature are reduced. This results in a higher soil moisture content by the stem in comparison with bare patches. Lastly, vegetation patches have a higher supply of organic matter than bare soil, causing a higher water repellency.
Currently, rainfall events do not cause that much runoff and erosion problems. However, the soil moisture content and hydraulic conductivity are relatively low and the width of the bare zones will increase even more. With no management practices, runoff and erosion will become problems, especially with the increase of extreme rainfall events due to climate change.
Acknowledgements
Thanks are due to Erik Cammeraat and Jeroen Zethof as being interested in general, helping me during my research and fieldwork and for their useful comments on my bachelor thesis. Rutger van Hall is thanked for guidance in the laboratory. Niels Verweij, Annabel Isarin, Adriaan Dekkers & Etienne de Jong are kindly thanked for their help during fieldwork and their mental support .
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Appendices
Appendix C. Kruskal Wallis test (+ post-hoc)
Pair p-value SMC p-value K p-value WDPT
B1 B2 0.2308 0.9495 0.6963 B1 C1 0.7828 0.2848 0.9186 B1 C2 0.0008* 0.4783 0.0549 B1 S 0.0000* 0.0035* 0.0398* B2 C1 0.8955 0.7328 0.9925 B2 C2 0.3419 0.8973 0.6264 B2 S 0.0467* 0.0383* 0.5507 C1 C2 0.0490* 0.9974 0.3618 C1 S 0.0027* 0.5029 0.2988 C2 S 0.8980 0.3045 1.0000 AB1 AB2 0.9539 0.9996 0.9768 AB1 AC1 0.9997 0.6236 0.9972 AB1 AC2 0.1227 0.7806 0.4324 AB1 AS 0.0281* 0.3909 0.2749 AB1 MB1 1.0000 1.0000 0.9993 AB1 MB2 0.8616 1.0000 1.0000 AB1 MC1 0.9969 0.9996 1.0000 AB1 MC2 0.1925 1.0000 0.9979 AB1 MS 0.0223* 0.2186 0.9991 AB2 AC1 0.9999 0.9567 1.0000 AB2 AC2 0.8755 0.9892 0.9879 AB2 AS 0.5651 0.8395 0.9499 AB2 MB1 0.9385 0.9985 0.6674 AB2 MB2 1.0000 1.0000 0.9649 AB2 MC1 1.0000 1.0000 0.8795 AB2 MC2 0.9406 1.0000 1.0000 AB2 MS 0.5149 0.6559 1.0000 AC1 A2 0.5240 1.0000 0.9535 AC1 AS 0.2186 1.0000 0.8727 AC1 MB1 0.9994 0.5300 0.8551 AC1 MB2 0.9973 0.7714 0.9949 AC1 MC1 1.0000 0.9567 0.9684 AC1 MC2 0.6533 0.8852 1.0000 AC1 MS 0.1878 0.9998 1.0000 AC2 AS 1.0000 0.9999 1.0000 AC2 MB1 0.1044 0.6979 0.0879 AC2 MB2 0.9605 0.8915 0.3817 AC2 MC1 0.6316 0.9892 0.2187 AC2 MC2 1.0000 0.9584 0.9297 AC2 MS 0.9999 0.9973 0.8997 AS MB1 0.0229* 0.3090 0.0421* AS MB2 0.7512 0.5465 0.2351 AS MC1 0.2904 0.8395 0.1202
MB1 MB2 0.8312 1.0000 0.9997 MB1 MC1 0.9948 0.9985 1.0000 MB1 MC2 0.1667 0.9999 0.8608 MB1 MS 0.0180* 0.1622 0.8981 MB2 MC1 0.9996 1.0000 1.0000 MB2 MC2 0.9865 1.0000 0.9960 MB2 MS 0.7062 0.3416 0.9981 MC1 MC2 0.7561 1.0000 0.9720 MC1 MS 0.2522 0.6559 0.9833 MC2 MS 0.9990 0.4915 1.0000
p-values Kruskal Wallis test (+ post hoc). Data is considered significant (*) is the p-value is <0.05. B: Bare, C: Canopy border, S: Stem, F: Fan, H: Hill, A: Anthyllus cytisoides, M: Macrochloa tenacissima, 1: soil layer 1, 2: soil layer 2.
