Determining predictability of soil water repellency on agricultural lands cultivated with flower bulbs along the Dutch coastal zone

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Determining predictability of soil water repellency on

agricultural lands cultivated with flower bulbs along

the Dutch coastal zone

A Bachelor Thesis

Anne-Lotte Boudeling

Student number: 10799044

2 July 2017, Amsterdam

Supervisor: dr. L.H. Cammeraat

Word count: 6,686 (excl. figures and tables)

University of Amsterdam

Faculty of Science

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Abstract

Objective: Since the late 1980s, important advances have been made in identifying certain causes, consequences and characteristics of soil water repellency (SWR) in different environments and across a variety of climatic conditions and soil types. However, SWR in lands occupied with floriculture, located on sandy soils next to the coastal dune areas has not yet been identified. Therefore, this study aims at

providing the knowledge needed to establish a certain degree of SWR in floricultural lands.

Location: Samples were taken from three flower bulb farms along the Dutch coastal zone in Egmond-Binnen, Callantsoog, and Noordwijkerhout respectively.

Methods: The degree of SWR in these lands has been determined by using the contact angle method. SWR was then correlated to different soil properties to determine whether these can predict the degree of SWR.

Results: After soil classifications of the three sampled locations were made, the soil organic matter (SOM) content, particle size, bulk density and CaCO3 content of the sandy cultivated soils were determined.

Main conclusions: By using the contact angle method, this research was able to determine a difference in SWR between dune soils and bulb cultivation sites. It has also been shown that particle size, bulk density and CaCO3 are not necessarily able to predict SWR in these soils. Finally, there is an observed relation

between SOM and SWR that cannot be explained using the data gathered for this research and it is recommended for future research to also focus on other soil properties and contributing factors to SWR. This will hopefully provide more insights into the level and occurrence of SWR in Dutch bulb field sites. Keywords: water repellency, hydrophobicity, floriculture, contact angle

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List of Figures

Figure 1. Spatial distribution of agricultural practices within The Netherlands in 2015 9

Figure 2. Contact angles 11

Figure 3. Google Earth map indicating the locations of the sample points 13

Figure 4. Soil classifications according to WRB in locations 1, 2, and 3 17

Figure 5. Graphical visualisation (boxplots) of SOM content at location 1, 2, 3, and REF 19 Figure 6. Relationship between contact angle and water drop penetration time (WDPT) 23

Figure A1. Distribution of older beaches intact and levelled older beaches 32

Figure A2. Local geological map of the Dutch coastal area 33

Figure A3. Example of soil cover slips 34

Figure A4. Microscopic set-up for the contact-angle measurement 35

Figure A5. DropSnake contact-angle example 36

Figure A6. Graphical visualisation (boxplots) of the DBD at locations 1, 2 and 3 45 Figure A7. Graphical visualisation (boxplots) of the calcium carbonate content at locations

1, 2 and 3

47

Figure A8. Graphical visualisation of SOM content categorised by depth and location of

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List of Tables

Table 1. Specifying methods of sampling 14

Table 2. Calcium carbonate content values at locations 1, 2, and 3 18

Table 3. SOM values at location 1, 2, 3, and at the REF location 18

Table 4. SOM content values (%) categorised by depth and location for locations 1, 2, 3, and

REF location 19

Table 5. Mean CA of locations 1, 2, 3, and REF location 20

Table 6. Mean CA categorized by location and depth 20

Table 7. SWR classifications per depth and location 21

Table 8. Correlation coefficients and P-levels of SWR with variable per floriculture location

and per depth 22

Table 9. Classifications of WDPT and CA 24

Table A1. DBD values of locations 1, 2, and 3 45

Table A2. Small particle size distribution in percentages 46

Table A3. Large particle size distribution in percentages 46

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List of Abbreviations and Notations

CA Contact angle

CaCO3 Calcium carbonate

CO2 Carbon dioxide

CRM Capillary Rise Method

DBD Dry bulk density

HCL Hydrochloric acid

REF Reference location

TC Total carbon

TIC Total inorganic carbon

SDM Sessile Drop Method

SOC Soil organic carbon

SOM Soil organic matter

SWR Soil water repellency

WDPT Water Drop Penetration Test

WRB World Reference Base

ρt Dry bulk density in equation

Mt Mass of soil solids

Vt Total volume

P Weight loss of sample

Q Weight loss of CaCO3

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1. Introduction

Water repellency, also known as hydrophobicity, of soils has been a topic of interest and a reason for concern of both land managers and scientists for over a century (DeBano, 2000). Since the late 1980s important advances have been made in identifying certain causes and consequences of soil water

repellency (SWR) (Doerr, Shakesby and Walsh, 2000). SWR reduces the affinity of soil particles to water, generating a large resistance of the soils to wetting for either long or short periods of time. This dynamic property of soils is interlinked with physical, chemical and biological soil properties with each its

corresponding hydro- geomorphological impacts on different key ecosystem services that soils provide. In addition to its detrimental implications for plant growth, it often restricts plant fibre production, water retention, facilitation of high infiltration rates as a measure to prevent flooding and clean drinking water through accelerated leaching of agrochemicals (Doerr et al., 2000; Wallis and Horne, 1992).

1.1 Impact analysis

Its characteristics and its hydro-geomorphological impacts on different environments have been identified across a variety of climatic conditions and soil types (Doerr et al., 2000; Müller and Deurer, 2011). In the mid 1980s, it was suspected that SWR only appeared in areas with a semi-arid or Mediterranean climate. However, studies conducted in much wetter regions, such as Great Britain, Sweden, and The Netherlands, have also reported the appearance of SWR, suggesting that it is not only restricted to relatively dry climates (Doerr et al., 2000). In The Netherlands, SWR occurs throughout at varying degrees. Especially the surface layers in sands of the coastal dunes and other nature reserves are particularly susceptible to high degrees of water repellency (Dekker, Ritsema and Oostindie, 2000). For the Dutch coastal dune sands, this high degree of SWR resulted in increased runoff towards low lying areas, such as the fens, as well as sedimentation of organic matter and sand in the fens. SWR also proved to aggravate overland flow by impeding the water infiltration capacity in dry dune soils, resulting in unconcentrated or concentrated slope washes. When water repellency is particularly high, rills and alluvial fans are formed by these slope washes (Dekker, 1998; Jungerius and Dekker, 1990). These consequences are especially of relevance when considering the defence function the coastal dunes have for the human population. SWR also affects the ecologically rich and diverse coastal environment, which are both wet and dry and young and mature (Louisse and van der Meulen, 1991). Subsequently, the Dutch coastal area is used for even more purposes: water catchment, housing, tourism and agricultural practices are quite common in coastal areas (Martinez and Psuty, 2010).

1.2 Innovative aspects

The spatial distribution of agricultural practices, especially crops and livestock, in The Netherlands changed rapidly after the 17th_{century. Crops and livestock were transferred from the}

excavated coastal dunes to newly constructed polders. Thereupon, these sandy and flat excavated lands, also known as ‘geestgronden’ were used for horticulture and bulb cultivation (Duinbehoud, 2017).

Nowadays, these two types of agricultural practices are still found along the Dutch coast (Fig. 1) (Nature, Landscape and Biodiversity, 2016). According to Doerr et al. (2000), 75% of the crop-and grassland in The Netherlands exhibit SWR, leading to crop losses of up to 80% in agriculture. In many agricultural practices, wetting agents have been introduced as a measure to improve water infiltration and retention in soil. Horticultural practices have been using wetting agents extensively, suggesting that some degree of SWR is present (Hallett, 2007). However, little is known concerning the actual existence of SWR in horticulture specifically and comparisons between SWR associated with different soil management or land uses are problematic. For example, it would not be correct to assume that SWR occurs in horticultural areas because of wetting agents or because of the presence of SWR in adjacent dune sands. Differences in not only organic matter content but also other soil properties, such as surface area will influence SWR (Harper et al., 2000).

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1.3 Research aim and questions

This study aims at providing the knowledge needed to establish a certain degree of SWR in floricultural lands. The degree of SWR in these lands will be correlated to soil organic matter (SOM) content, grain size, dry bulk density (DBD) and CaCO3 content of the same sandy cultivated soils. This

study will investigate whether the above mentioned soil properties affect SWR in these soils and if currently used cultivation techniques for bulb cultivation affect SWR in any aspect. Following from the research introduction and the problem statement described in the previous section, the research question of this study is: ‘’To what extent does soil water repellency occur in agricultural lands used for flower bulb cultivation adjacent to Dutch coastal dunes and to what extent are the indicated soil properties correlated to soil water repellency?’’ In order to answer this question, several sub-questions were formulated and are as follows:

• To what extent is SWR present in both areas cultivated with flower bulbs and in coastal dune sands and how can a difference in SWR between these two be explained by their current land use? • Is SWR related to SOM content and how can a difference in SOM in dune soils and sandy soils

be explained by their current land use?

• Does soil particle size differ in dune soils and soils used for bulb cultivation and does this affect SWR?

• Does CaCO3 influence the extent to which SWR occurs in soils used for flower bulb cultivation?

• Is SWR influenced by soil bulk density and does this differ between the studied locations?

Fig. 1 Spatial distribution of agricultural practices within The Netherlands in 2015 (Nature,

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1.4 Hypothesis and research content

The hypothesis of this research is that SWR will occur to a certain extent in areas cultivated with flower bulbs due to the soil maintaining its original dune characteristics and through the extensive application of SOM under agriculture. This research first provides a concise but detailed literature study containing information on SWR and the study areas. Subsequently, the methodology of the fieldwork and of the work in the laboratory is included, where the contact angle method will be thoroughly explained. The methods chapter is followed by the results chapter and the discussion chapter, in which SWR will be correlated to other soil characteristics. The conclusion will finalize the research with a concise summary of the findings.

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2. Literature review

2.1 Physical-chemical principles of water repellency

A water molecule is composed of two partial positively charged hydrogen atoms and a partial negatively charged oxygen atom. These two atoms are arranged in such a way that the bonds have an angle of 105°, enabling a strong dipolar structure. The positive and negative charges together form hydrogen bonds, enabling the molecules to form aggregates. Natural surfaces are, specifically, easy for water molecules to adhere to, due to its composition of positively and negatively charges ions. However, this attraction to charged surfaces is counteracted by the dipolar structure of the atom resulting in a reduction of the surface area of water. This is due to the net force of a liquid where, on an individual level, the net force is zero, as other molecules and their forces surround the individual molecule. However, beyond the bounds of a liquid, there are no other similar molecules to oppose the attraction, resulting in a net attractive force towards the inside of the molecule, promoting the reduction of the surface area of water. Thus, minimal opposing forces will, presumably, result in the formation of spherical shaped droplets. If adhesive forces between a liquid and solid exceed the cohesive forces within the body of water, the water droplet spreads on a solid. This is due to the surface tension or the surface-free energy of a solid; a solid with a surface-free energy higher than that of a water droplet (72.75 x 10-3 _{N/m) is}

therefore hydrophilic (water spreads on surface) (Doerr et al., 2000) (Fig. 2). However, soft organic solids, such as waxes or organic polymers have a lower surface-free energy than that of a water droplet, reducing the surface area of water. These types of solids are known as hydrophobic (Doerr et al., 2000; Yoshimitsu et al., 2002) (Fig. 2).

The above mentioned water properties are needed to understand the affinity or repellency

between soils and liquids and their forthcoming consequences and repercussions. Hydrophobic soils often deal with reduced infiltration capacity, increased soil erosion and increased aggregate stability. It also affects development of preferential flow paths (such as fingered flow paths), unstable wetting patterns and leaching of agrichemicals (Doerr et al., 2000; de Jonge, Jacobsen and Moldrup, 1999; Shakesby, Doerr and Walsh, 2000).

2.2 Water repellency and SOM

As earlier mentioned, little to no research has yet been done concerning water repellency in floriculture. However, SWR in sandy soils and its relationship with organic material and soil structure has been thoroughly researched in the Southwestern part of The Netherlands. According to this study, the degree of SWR is closely linked to SOM and SOM is often part of soil structures inducing high degrees of SWR. These soil structures, including water repellent organic remains, plant fragments and coatings on sand grains, tend to be, partly or wholly, formed by soil biota. However, a contradictory theory is that

Fig. 2 Contact Angles: the contact angle of surfaces when in contact with water show whether they are hydrophilic (left), hydrophobic (centre) or superhydrophobic (right) (Gundersen, Leinaas and Thaulow, 2014).

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SWR can be reduced by processes in which soil biota are active, for example, decomposition of organic matter, coating of plant fragments with fine wettable soil materials (Bisdom, Dekker and Schoute, 1993). Subsequently, another characteristic of organic matter content is that it is often correlated to soils containing fractions with smaller particle size, which shows a higher degree of water repellency than soils with a larger particle size (de Jonge, Jacobsen and Moldrup, 1999).

Water holding capacity, porosity, infiltration capacity and bulk densities are associated with additions of organic manure in agricultural practices. Large applications of manure can increase production of decomposer fungi, which thus increases water-repellent substances. It has also been

observed that addition of dairy manure to sandy soils can cause a reduction in field capacity due to sudden appearance of waxy, water-repellent substances in the soil profile (Haines and Nadu, 1998). Additionally, a water-repellent plough sole layer consisting of decomposed organic manure can appear when increasing organic manure (Weil and Kroontje, 1979).

2.3 Improved soil physical conditions through fertilizers and manure

Lime, or CaCO3, and other applications of fertilizer are often used combined in agricultural

management to increase clay dispersion and reduce aggregate stability and infiltration rates (Haynes & Naidu, 1998). Moreover, addition of manure to the soil increases biological activity, which increases water-holding capacity and decreases bulk density of the soil. A decreased bulk density influences pore size in the soil, especially the distribution in pore sizes; the relative volume of pores in course soil types will decrease to less than 30 micrometre. This increased number of small pores is the main cause of increased water-holding capacity (Haynes & Naidu, 1998).

The investigated flower bulb soils were mainly fertilized with organic manure and compost. The compost contains structural material, such as straw, branches and wood chips to improve soil structure. The soil structure is especially important in combination with the phosphate content of the soil; with phosphate it is important that the roots grow into the phosphate and do not automatically enter the soil with the soil moisture. Sandy soils (especially those located next to coastal dune areas) are naturally phosphate fixing, which is one of the main reasons why calcium phosphate is added to the soil. Calcium phosphate is not very soluble, but it provides enough phosphate to the plants. Phosphate is also added in the soil through the use of OrgaPlus, which also contains iron, boron, silicon and nitrogen. OrgaPlus is especially used often in bulb cultivation on sandy soils due to the relatively low SOM levels of sandy soils located next to dune areas; the levels are approximately between 1.2% and 1.8% and microbial activity and soil structure will deteriorate when SOM levels are lower than this. A low microbial activity and poor soil structure can cause Pythium, which is a soil fungus that causes rotting of the roots (Apeldoorn, 2017; Bokhorst, Van Leeuwen and Ter Berg, 2008; Duin, 2017; Steijn-Damen, 2017; van Diepen and Braam, 2010).

2.4 Site descriptions

As stated earlier, the three research areas are located next to coastal dune systems in the Western part of The Netherlands (Fig. 3). A short description of the three exact locations and their

geomorphology, lithology and soil type is provided below. For an extended site description, see Appendix I.

Location 1 is based in Egmond-Binnen and is characterized by its combination of old and young dunes. The sandy soil contains less than 2% CaCO3 as it is located south of Bergen, where the so-called

‘lime-jump’ occurs. Other soil constituents, often proportional to the CaCO3 distribution, are iron oxide

and feldspar (Klijn, 1981). Location 2 is based in Callantsoog, where mostly sand and clay are found. Even though location 2 is located north of Bergen, it is not likely that CaCO3 is present (Klijn, 1981). The third

site is located in Noordwijkerhout and also consists of a combination of young and old dunes and of a non-calcareous soil. All three locations have excavated to near groundwater level after the 17th_{century for}

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3. Methodology

3.1 Methods in field

Every sample point has been chosen based on its location next to an area of coastal dunes and on the viability of the site. At every location a soil classification according to the World Reference Base (WRB) was done. Furthermore, a short interview (15 min.) with the producers of the bulbs to learn about used cultivation techniques was held. Table 1 indicates the specific soil characteristics that are sampled, the amount of samples per soil characteristic, materials used for the soil characteristics and depth of soil sample. To compare floriculture soil characteristics with dune soil characteristics, dune soil samples were taken at the first location. In total, 54 samples were collected; see Appendix III for sampling numbers.

3.2 Methods in laboratory

3.2.1 Determination of SWR using the contact angle method

Numerous techniques have been developed to determine water repellency of soils (Hallett, 2008). One of these techniques is the contact angle method, which measures the angle between a liquid and a solid. The contact angle method requires a number of steps, of which a summary is provided below. Appendix II explains the method in greater detail and provides a comprehensive roadmap.

1. Soil samples have been sieved at a recommended sieve fraction of <0.355 and >0.180 mm. 2. The sieved soil samples are adhered to 2/3 of glass coverslips by using strong double-sided tape. 3. Using LEICA IM50 software and cameras associated with the Leica microscope, microscopic

pictures of the soil samples were taken. By using a frame with a 45° mirror, the camera angle was reflected, so that a side-view of the water droplet on the soil was seen. For this research, 5 microscopic pictures of water droplets per soil sample were taken (n = 270).

4. The contact angle of the water droplets has been measured using ImageJ software installation in combination with the DropSnake plugin. This specific software can be used for non-axisymmetric or general drops, which is especially useful if the drop is on a tilted surface or if receding contact angles are present. A polynomial fit will encircle the droplet.

Table 1

Specifying methods of sampling

Locations Location

number Amount of samples per location and depth

Depth of

samples Materials used for samples

Apeldoorn

dune REF 3 3 0 - 15 cm 15 - 25

cm

• Shovel

• Zip lock bags

• Metal rings with a volume of 100 cm3

Apeldoorn

Bloembollen 1 8 8 0 - 15 cm 15 - 25

cm

• Shovel

• Zip lock bags

Duin VOF 2 8

8 0 - 15 cm 15 - 25

cm

• Shovel

• Zip lock bags

Steijn Damen

VOF 3 8 8 0 - 15 cm 15 - 25

cm

• Shovel

• Zip lock bags

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5. In this research, a total of 540 contact angles were retrieved (2 per image). Thereafter, the mean contact angle per image was calculated. The data of these contact angles can be found in Appendix IV.

3.2.2 Determination of DBD

The DBD of the soil has been measured using undisturbed soil cores of 100 cm3_(Dingman,

2015). 5 grams of the soil samples have been taken twice and put in the oven at 105°C for 24 hours. After the drying process, the samples have been weighed again. It was then possible to calculate DBD by using equation 1 (Yu, Kamboy and Cheng, 2015):

𝜌!=

𝑀_!

𝑉! (1)

Where 𝜌t is the DBD, Mt the mass of soil solids, and Vt the total volume.

3.2.3 Determination of soil particle size

Soil particle size is measured using two different methods. For this soil property, the soil samples were bulked related to their depth. Soil particles > 0.25 mm have been measured using a sieve, and soil particles between 1 and 250 𝜇m have been measured using a Sedigraph, a particle sizer that determines the concentration of particles remaining at decreasing sedimentation depths in a cell filled with a liquid. With the sieve analysis, soil particles of 4 fractions were sieved with the powder-sieving machine. The machine was set on 5 min for every sample.

To prepare the samples for the SediGraph, the smallest fraction (< 0.25 mm) has been collected from the sieve method. 3.5 grams of this fraction was transferred into a beaker, and then 0.5 mL of a peptize solution (Calgon) has been added to prevent flocculation. Afterwards, 70 mL demi-water is added. The samples are then placed into the SediGraph. Using the SediGraph, the high precision x-ray tube was levelled evenly with the cell, where a collision of x-ray beams, originating from the tube, has been transmitted towards the cell. The intensity of transmitted of x-ray beams has been measured at different locations and at different times, allowing for an accurate grain size distribution. The data is provided in a table output as equivalent spherical diameter (ESD) according to different sedimentation depths, assuming Stoke’s law of settling for a particle in a suspension (Syvitski, 2011).

3.2.4 Determination of CaCO3 content using the Van Wesemael method

The calcium carbonate content has been measured using the Van Wesemael method, which is based on weight loss of dissolution. A soil sample approximately of 5 g has been used in combination with 5-10 cm3_{of 1 M HCl (del Campillo, Torrent and Loeppert, 1992). The loss of weight in each sample}

was then attributed to the calcium carbonate content by using equations 2 and 3:

%𝐶𝑂_!=𝑃 × 𝑔𝑟𝑎𝑚 𝐶𝑎𝐶𝑂! × 44

𝑄 × 100 × 𝑅 × 100% (2)

%𝐶𝑎𝐶𝑂_!= %𝐶𝑂_! × 100

44 (3)

Where P is the weight loss of the sample (grams), Q is the weight loss of CaCO3 (grams) and R is the dry

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3.2.5 Determination of SOM

The SOM content has been measured by combining two different techniques to measure organic and inorganic carbon from which the SOM content can be calculated. The total carbon (TC) content has been measured by using an elemental analysis using the modern simultaneous CNS combustion analyser. In this technique, the sample is burned in an excess of oxygen and various traps, from there the

combustion products are collected and calculated. Sulfanillic acid standards are used as a reference (to check whether CNS analysis is correct).

SOM can be hard to calculate in laboratories directly. However, by measuring the total inorganic carbon (TIC) (obtained from the %CO2 by using the van Wesemael method (see method 3.2.4)) the soil

organic carbon (SOC) content has been calculated by subtracting the total inorganic carbon from the total carbon content using equation 4:

%𝑇𝑜𝑡𝑎𝑙 𝑂𝑟𝑔𝑎𝑛𝑖𝑐 𝐶𝑎𝑟𝑏𝑜𝑛 = %𝑇𝑜𝑡𝑎𝑙 𝐶𝑎𝑟𝑏𝑜𝑛 − %𝑇𝑜𝑡𝑎𝑙 𝐼𝑛𝑜𝑟𝑔𝑎𝑛𝑖𝑐 𝐶𝑎𝑟𝑏𝑜𝑛 (4)

Assuming that SOM contains 58% organic carbon, the commonly accepted Van Bemmelen Conversion Factor of 1.724 is used to convert SOC data to SOM data (e.g. Heaton, Fullen and Bhattacharyya, 2016) (equation 5).

%𝑆𝑂𝑀 = %𝑆𝑂𝐶 × 1.724 (5)

3.3 Statistical analysis

To test for significant correlation within the data, the data first needed to be tested on normality for which the Lilliefors test was used. Thereafter, data that comes from a normally distributed dataset has been subjected to a Grubbs test to test for outliers. To test if the data in the different locations is

significantly different, either a one-way-ANOVA or the non-parametric Kruskal-Wallis test has been applied to the datasets.

The last, and most important, statistical test that has been applied is the Spearman correlation test. This test has been applied to datasets of SWR, CaCO3, SOM and bulk density. The Spearman test has

been applied to SWR and the previously mentioned soil characteristics on different locations, different depths, combined locations and combined depths.

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4. Results

This chapter presents the main results of this research, including soil classifications, soil properties, SWR, and statistical results. For additional data on soil properties see Appendix V.

4.1 Soil classifications

The first soil classification was made at location 1 (Apeldoorn bloembollen), in a field cultivated with allium flower bulbs. The upper part of the soil consisted of a relatively deep plough layer, the Ap-horizon, with a depth of approximately 45-50 cm. The next layer is identified as a C/Ap-Ap-horizon, until approximately 80 cm, as a result of deep ploughing in the past. The colour identification on the Munsell colour scale was 10 Y/R 3/3 for the first two layers. The last layer was identified as a C-horizon, as this layer seemed to be little affected by soil forming processes and this layer was not subjected by deep ploughing in the past. The colour identification on the Munsell colour scale was 10 Y/R 6/4. The texture for all of the three layers was loamy sand with rounded grain particles. The structure that was found for all three of the layers was very weak, medium-coarse, blocky and very loose.

The second soil classification was made at location 2 (Duin VOF), where allium flower bulbs were cultivated. Only two soil horizons could be identified in this location. The first soil horizon was identified as an Ap-horizon as a result of a plough layer of approximately 35-50 cm deep. The Munsell colour of this horizon was 10 Y/R 4/2. The second soil horizon was identified as a C-horizon with a 10 Y/R 7/3 Munsell colour. The texture for the two soil horizons is similar to the soil texture in location 1, namely loamy-sand, as the majority of the particle size was larger than 63 𝜇m (Appendix V) (Brown, 2007). The structure of the two soil layers was hardly identifiable; nevertheless the assigned structure is loose, very weak with course- medium sub angular blocky structure.

At location 3 (Steijn Damen VOF), the last soil profile was classified in a field cultivated with daffodils. The first soil layer was identified as an Ap-horizon, in contrast to the other two locations, the Ap-horizon reached relatively deep (approximately 70 cm). The Munsell colour of this horizon was 10 Y/R 3/2. The second soil layer was, similar to that of location 2, classified as a C-horizon and the colour described to this horizon was 10 Y/R 4/3 on the Munsell colour scale. The structure and texture of the soil were identical to that of the second location; namely a loamy sandy texture and a very weak, loose structure.

All three of the soils were classified as an Arenosol, with two suffixes; Eutric and Aric (Fig. 4). The Eutric qualifier was assigned because in the major part of the soil (10-60 cm) there was an effective base saturation and a pH of approximately 5-7 (not reactive to HCl). The supplementary qualifier ‘aric’ was assigned because the soils are being ploughed to a depth > 20 cm from the soil surface (FAO, I., 2014).

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4.2 Soil properties

Soil properties that were determined for this research are bulk density, particle size, CaCO3, and SOM content. For particle size data, see Appendix V. Bulk density samples were taken at all three locations. Unfortunately, there are no bulk density results from the reference location. The results show that the bulk density in location 1 is lower than those of in location 2 and 3 (Appendix V, Fig. A6). Furthermore, location 2 shows an outlier at 1.58 g/cm3_.

Table 2 gives an overview of the CaCO3 of the three different locations. CaCO3 was also

measured in the REF location, however there was 0% CaCO3 present.

Table 2

Calcium carbonate content values of locations 1,2 and 3

Statistics %CaCO3 | 1 %CaCO3 | 2 %CaCO3 | 3

Nbr. of observations 16 16 16 Minimum 1.51 0.00 0.51 Maximum 10.93 6.41 2.02 1st Quartile 1.84 0.27 0.68 Median 2.36 2.58 1.06 3rd Quartile 2.89 3.37 1.36 Mean 3.28 2,29 1.10 Variance (n-1) 7.04 3.81 0.22 Standard deviation (n-1) 2.65 1.95 0.47

The SOM content is calculated for the three flower bulb locations and for the reference location. The SOM categorized by location is visible in Table 3. Several outstanding results can be observed. First, SOM in the REF location is almost four times as high as SOM in the flower bulb fields, despite the fact that a large outlier is visible in the REF location at a maximum of 12.82 (Fig. 5). Another noteworthy result is the large difference in standard deviation between the REF location and the flower bulb fields; it is however likely that removal of the outlier at 12.82 decreases the standard deviation and mean at the REF location.

Table 3

SOM values at location 1, 2, 3 and at the REF location

Statistics 1 2 3 REF Nbr. of observations 16 16 16 6 Minimum 0.00 0.00 1.26 3.05 Maximum 2.33 1.60 2.05 12.82 1st Quartile 1.64 0.48 1.49 3.18 Median 1.78 0.70 1.64 3.66 3rd Quartile 1.98 1.25 1.78 5.40 Mean 1.66 0.84 1.64 5.37 Variance (n-1) 0.39 0.21 0.06 14.44 Standard deviation (n-1) 0.62 0.47 0.24 3.80

The SOM content has also been calculated in categories of depth and location, from which the values are visible in Table 4. The mean of SOM in each location is similar in the two different depths.

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Table 4

SOM content values (%) categorised by depth and location for locations 1,2,3 and REF location

Statistics 1| 0-15 1| 15-25 2| 0-15 2| 15-25 3| 0-15 3| 15-25 REF | 0-15 REF | 15-25

Nbr. of observations 8 8 8 8 8 8 3 3 Minimum 0.35 0.00 0.00 0.34 1.39 1.26 3.39 3.05 Maximum 2.22 2.33 1.33 1.60 1.86 2.05 12.82 3.94 1st Quartile 1.61 1.69 0.54 0.44 1.51 1.42 4.64 3.08 Median 1.69 1.88 0.92 0.70 1.64 1.63 5.89 3.11 3rd Quartile 1.95 1.98 1.25 1.06 1.77 1.82 9.35 3.53 Mean 1.64 1.68 0.85 0.83 1.64 1.64 7.36 3.37 Variance (n-1) 0.32 0.50 0.24 0.24 0.03 0.09 23.87 0.25 Standard deviation (n-1) 0.57 0.71 0.49 0.49 0.17 0.30 4.89 0.50

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4.3 Soil water repellency

Contact Angles (CA) of droplets have been measured in fivefold on 54 soil samples, the descriptive statistics have can be found in Tables 5 and 6. Table 5 contains the mean contact angles per location, the REF location has a considerably higher mean than the three flower bulb locations. Location 1 and 3 show a relatively similar mean contact angle.

Table 5

Mean CA of locations 1,2,3 and REF location

Statistics Mean angle | 1 Mean angle | 2 Mean angle | 3 Mean angle | REF

Nbr. of observations 80 80 80 30 Minimum 65.06 69.24 59.82 59.81 Maximum 93.02 101.76 91.45 118.91 1st Quartile 72.98 82.98 69.35 102.65 Median 78.91 86.84 74.83 111.00 3rd Quartile 84.14 93.20 79.80 114.98 Mean 78.66 87.75 74.78 107.70 Variance (n-1) 48.36 54.85 54.17 132.19 Standard deviation (n-1) 6.95 7.41 7.36 11.50

Table 6 contains the mean contact angles per location and per depth. There are no clear correlations visible from the different depths and the different locations, apart from the obvious higher CA measured in the REF location.

Table 6

Mean CA categorised by location and depth

Statistics 1| 0-15 1| 15-25 2| 0-15 2| 15-25 3| 0-15 3| 15-25 REF| 0-15 REF| 15-25

Nr. of observations 8 8 8 8 8 8 3 3 Minimum 69.68 70.78 80.18 78.92 70.50 65.81 99.25 109.15 Maximum 84.32 83.70 95.06 93.35 79.81 82.37 105.99 114.45 1st Quartile 74.98 74.83 89.26 80.78 71.32 71.19 101.87 111.02 Median 80.55 79.55 90.78 85.56 75.71 73.82 104.49 112.89 3rd Quartile 82.55 83.02 92.70 88.75 77.29 79.00 105.24 113.67 Mean 78.65 78.68 90.04 85.47 75.05 74.52 103.24 112.16 Variance (n-1) 28.16 25.99 22.36 27.59 13.44 31.77 12.49 7.43 Standard deviation (n-1) 5.31 5.10 4.73 5.25 3.67 5.64 3.53 2.73

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SWR classifications per depth and per location can be found in Table 7. The shallow soil sample in location 3 is the only location, except for the REF location, that is categorized as hydrophobic.

Table 7

SWR classifications per depth and location

Depth Location 1 Location 2 Location 3 REF

0 - 15 cm Hydrophilic Hydrophobic Hydrophilic Hydrophobic

15 - 25 cm Hydrophilic Hydrophilic Hydrophilic Hydrophobic

4.4 Statistical results

The Lilliefors test, to test for normality in the samples, was completed for the measured contact angles data from location 1, 2 and 3. The test showed that the computed p-value is greater than the significance level of alpha = 0.05, concluding that one cannot reject the null hypothesis. The risk of rejecting the null hypothesis while it is true was 56.69%. DBD data was also subjected to the Lilliefors test for normality, and the risk to reject the null hypothesis while it was true was 79.69%. The Lilliefors test was also applied to the SOM data, grain size data and the CaCO3 data and it was possible to conclude that

these datasets were not-normally distributed.

For the SWR data a Grubbs test was performed to test for outliers in a normally distributed dataset. The outcome of this test was that the null hypothesis that there is no outlier present in the data should be rejected and that the alternative hypothesis that the minimum of maximum value is an outlier should be accepted. The risk that the null hypothesis was rejected while it was true was lower than 0.01%. The Grubbs test revealed that there was 1 outlier in the soil sample data of the REF location, 1 outlier in the data of location 1 and no outliers in the data of location 2 and 3. However, neither the presence nor absence of the outliers in the data would change the SWR repellency classifications, thus the analysis have been run with the outliers. The outliers are presented in bold in Appendix IV.

To test for significant differences in SOM, CaCO3, grain size and DBD per location, the

Kruskal-Wallis test was applied for non-normally distributed datasets. The results of these tests were that the grain size distribution was not significantly different for the three different locations. On the contrary, SOM and CaCO3 were significantly different for location 1 and location 3. DBD was significantly different for

location 1 and 2. To test for significant difference between locations of SWR (excluding the REF location), a one-way ANOVA test was used, as this data was normally distributed. The result of the ANOVA test is that CA angles are not significantly different for location 1, 2 and 3.

To test for a significant correlation between SWR and SOM, DBD, CaCO3 and DBD, the

Spearman correlation coefficient was calculated per depth, per location and per location and depth for location 1, 2 and 3. It was not possible to include the REF location due to its small sample size. The results of these tests can be found in the Table 8. The spearman correlation coefficient (𝜌) shows either a positive or negative correlation among variables and a P-value of <0,05 indicated whether a correlation is significant. Table 8 shows that there are only three significant correlations between SWR and the

measured variables. SOM is negatively correlated to SWR all locations combined at depths of 0-15 cm and 0-25 cm, the latter likely due to the strong correlation at a depth of 0-15 where the P-value is extremely low (<0.0002). Additionally, there is a significant negative correlation in DBD and SWR in location three in a combined depth.

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Table 8

Correlation coefficients and p-levels of SWR with variable per floriculture location and per depth. Significant at P<0.05 (bold).

Variable Depth Location 1 Location 2 Location 3 Locations 1, 2, 3

𝜌 P-value 𝜌 P-value 𝜌 P-value 𝜌 P-value

SOM 0 - 15 cm -0.6190 0.1150 -0.4286 0.3536 -0.5357 0.2357 -0.7078 < 0.0002 15 - 25 cm 0.4524 0.2675 0.0000 1.0000 0.6786 0.1095 -0.1270 0.5529 0 - 25 cm -0,0765 0,7797 0.1464 0.6024 0.2321 0.4039 -0.3896 0.0065 CaCO3 0 - 15 cm 0.3810 0.3599 0.0714 0.9063 -0.2857 0.5560 0.0391 0.8563 15 - 25 cm 0.0000 1.0000 -0.0357 0.9063 -0.3214 0.4976 0.2809 0.1832 0 - 25 cm 0,1824 0,4979 -0.3199 0.2447 -0.2357 0.3966 0.1414 0.3366 DBD 0 - 15 cm -0.4000 0.7500 -0.5000 1.000 -1.0000 0.3333 0.1399 0.6672 15 - 25 cm -0.2000 0.9167 -1.0000 0.3333 -1.0000 0.3333 -0.1049 0.7495 0 - 25 cm -0.3333 0.4279 -0.4286 0.3536 -0.7748 0.0480 -0.0413 0.8483

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5. Discussion

This study expands on previous work conducted with the contact surface angle method for measuring SWR in soils and on the degrees of occurrence of SWR along the Dutch coastal zone. Earlier studies have established that water repellency in the coastal dune area is not dependent on calcium carbonate content of dune sand, although organic matter content of soils appears to play an important role (Dekker and Jungerius, 1990). However, limited research has been done concerning the existence of SWR in agricultural lands cultivated with flower bulbs.

5.1 Evaluation of research errors

This study required an intensive research design due to the limited data available on this subject. The research design, made in the beginning stages of the research, contained several flaws, which were only detected in a later stage. An example of such a flaw is that several samples of straw and soil crusts were included in the sample taking process. However, these samples were not included in the research design, which has led them to be left out in the laboratory analyses. Another research error occurred when using the CNS combustion analyser; the soil samples were put in shortly after soil samples of another research were not put in correctly, causing possible errors in total C contents. To adjust for these possible errors, several samples were put in in triplex. The total C content was then calculated by taking the mean of the two samples that were the closest to each other. However, there is a possibility that the C contents were still disturbed by the error.

5.2 The presence of SWR in soils cultivated with flower bulbs

The results show that only the reference soil samples, retrieved from the coastal dune area adjacent to location 1, show high degrees of water repellency, with a mean contact angle of 107.70 (Table 5). These soils can therefore be classified as hydrophobic. Previous research from Bisdom et al. (1993) also retrieved dune samples from the Southwestern part of The Netherlands. According to their research with the water drop penetration test (WDPT), the dune samples exerted high levels of water repellency and were classified as either severely or extremely water repellent. It is difficult to compare classifications of the WDPT and the contact angle method used in this research. The WDPT test is often categorized into five categories and its associated classifications of repellency. The contact angle method is a quantitative measure used to define the wettability of the surface and is often only categorized in either hydrophobic of hydrophilic. Nonetheless, the relationship between the contact angle and the WDPT is defined by Leelamanie, Karube and Yoshida (2008) in Fig. 6 and will be further used to compare

outcomes of this research with previous studies. Using this relationship, it is possible to conclude that the

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levels of water repellency are similar in the dune soils retrieved from location 1 and research of Bisdom et al. (1993) (Table 9).

Table 9

Classifications of WDPT and CA (Leelamanie et al., 2008; Gundersen et al., 2014)

WDPT Classification of WR Contact Angle Classification of solid

< 1 Wettable < 10° _Hydrophilic

1 - 60 Slightly water repellent 10°- 90°

60 - 600 Strongly water repellent 90° - 100° _Hydrophobic

600 - 3600 Severely water repellent 95° - 100°

> 3600 Extremely water repellent > 100° Extremely hydrophobic

Table 7 shows that for location 2, the soil samples taken in a depth between 0-15 are also

classified as hydrophobic. However, the mean contact angles of these samples are 90.04° (Table 5), which means that they are classified as hydrophobic by only 0.04°. If the samples from location 2 are combined (Table 5), the mean contact angle is 87.75°, which would not be classified as hydrophobic, but would be classified as slightly water repellent. Furthermore, location 1 and location 3 (with samples of combined depths) show comparable degrees of contact angles (79° and 75°, Table 5), both these contact angles lean more towards strongly water repellent than to slightly water repellent. This is comparable to degree of SWR in location 2 (with samples of combined depths) as this contact angle is tending more towards strongly water repellent than to slightly water repellent. This degree of water repellency in floriculture is opposing to the hypothesis, based on reports of water repellent sandy soils in agriculture (DeBano, 2000), that the samples will be severely or extremely water repellent. The hypothesis was based upon the

assumption that the retrieved samples from flower bulb fields have similar soil characteristics to those of dune soils.

5.3 Relationship between SWR and CaCO3

There are no direct relations found between SWR and CaCO3 content in previous research.

According to Korenková et al. (2015), certain soils exhibit higher degrees of water repellency when higher degrees of CaCO3 were found, but all soils that were developed on loose sediments, contained CaCO3 and

were wettable. CaCO3 content in location 1, 2, 3 and in the REF were significantly different from one

another. No CaCO3 content was found in de dune soil samples, but there was more than 4% CaCO3

found in the flower bulb cultivated field adjacent to the coastal dunes, which can be explained by the addition of Ca3(PO4)2 in these fields to act as a phosphate-fixing agent. CaCO3 contents in the other

locations were slightly less evident (Table 2), especially CaCO3 contents in location 3 were lower. Location

1 and 3 were, therefore, significantly different from one another. From the statistical analyses it is possible to conclude that there is no significant positive or negative correlation between CaCO3 and SWR, which is

in line with the abovementioned research of Korenková et al. (2015).

5.4 The role of SOM and particle size

The appearance and degree of water repellency is, according to Bisdom et al. (1993), interlinked with organic matter in sandy soils. With increasing degrees of water repellency, more soil fractions are occupied with soil structures that contain water-repellent organic remains (Bisdom et al., 1993). Similar results have been found in this study when comparing SOM contents and degrees of SWR.

SOM in the REF location is almost 4 times as high as in the other locations (Table 3) and is, statistically speaking, significantly different. An explanation for the relatively low SOM content in the three bulb cultivation fields in comparison with the dune samples could be that soil life on bulb

cultivation fields consume more organic material and at a higher rate than at dune sites, since the organic matter is used by the plants as food throughout the growing season to ensure high quality flower bulbs (Bokhorst et al., 2008). Additionally, decomposition of organic matter on calcareous soils is significantly faster than decomposition on non-calcareous soils (Bokhorst et al., 2008).

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soils. On the contrary, while the SOM content in location 2 is much lower than in location 1 and 3, only in the latter two locations does the SOM content differ significantly. In addition, the relatively low SOM content of location 2 does not match its higher average contact angle.

Furthermore, we find a significant negative correlation between SOM content and SWR when using all samples from all three locations at 0-15 m and at 0-25 m. However, this is contrary to the findings of the above mentioned research by Bisdom et al. (1993), who found a statistically significant positive correlation between SOM content and SWR. Since correlation does not equal causality, it may be that there are other factors, not taken into account into this research, that influence the level of SWR on the locations researched. As a result, while the negative correlation between SWR and SOM content in this case is statistically significant, it may be circumstantial and additional research is needed to see whether factors such as fertilizer use may be able to explain this contradictory finding.

According to de Jonge et al. (1999) and Doerr, Shakesby and Walsh (1996) soil samples exhibit a higher degree of water repellency in fine (< 0.125 mm) than in the coarse (> 0.5 mm) soil fractions. Tables A2 and A3 in Appendix V show that AD1 and AD2, which contain the dune samples, contain higher fractions of fine material than the other locations. This can partly be explained by the higher SOM content in these soil samples, as soils with a high SOM content have significantly greater levels of microbes than soils with a low SOM, often resulting in smaller particle sizes (Six et al., 2004).

5.5 Relationship between SWR and DBD

DBD was significantly different for location 1 and 2, however this difference in DBD was only 0.15 g/cm3_{and this was not enough to influence SWR, as there was no significant difference in SWR}

between location 1 and 2. Furthermore, only 8 bulk density samples per location were calculated, which, most likely, highly influences the significant difference in bulk density in the bulb cultivated fields. It would be expected that DBD would be similar for all three of the locations because bulb cultivation requires good air supply, which depend upon specific soil structure and soil density (Bokhorst et al., 2008). A larger sample size would reduce these types of uncertainties.

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6. Conclusions

The aim of this research was to determine the extent to which SWR occurs in agricultural lands used for flower bulb cultivation, adjacent to Dutch coastal dunes, and the extent to which associated soil properties correlate to SWR. Resulting from the soil analysis conducted to answer this question, several key conclusions can be made.

First, it has been shown that dune soils and soils for floriculture in the Netherlands are not comparable to each other in terms of their soil properties including SWR. Instead, dune soils appear to be extremely water repellent whereas floriculture soils are only slightly water repellent. Reasons for this observation vary, but are likely to be most strongly related to SOM content, which is consistent with available literature. It could therefore be possible to determine SWR by looking at the SOM content in dune soils, but the findings in this research do not necessarily support a similar correlation in floriculture soils. Second, a difference in SOM content found in the three sampled locations, which is contrary to what was expected, is likely due to the fact that organic matter in some soils is used as crop food. Third, soil particle size, which is not significantly different for the three locations, and which is related to SOM content, does not directly influence SWR. Fourth, while CaCO3 does also not directly influence SWR in

the sampled locations, it has been shown that this soil property correlates to SOM content and might therefore indirectly influence SWR. Finally, the soil bulk density is significantly different among the three sampled locations, but this might be due to the small sample size.

In sum, this research has been able to determine a difference in SWR between dune soils and flower bulb cultivation sites and it has been shown that important soil properties are not necessarily able to predict SWR in these soils. However, more research is needed to determine whether other soil properties, not taken into account in this research, might be able to predict SWR, and to be able to fully explain the observed discrepancy between the SOM content-SWR relationship in the sampled locations and what is found in the literature. It is recommended for future research to use a larger sample size for bulk density while also focusing on other soil properties and contributing factors to SWR. This will hopefully provide more insights into the level and occurrence of SWR in Dutch bulb field sites.

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Acknowledgements

I would like to thank my supervisor, Erik, for his guidance during the research process and for providing valuable feedback. I would also like to thank the Laboratory of the UvA at Science Park for allowing me to use their equipment and machines for data analysis. Finally, I would like to thank Thomas for his continued support.

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Appendix I: Extended site descriptions

I.1 Location 1 – Apeldoorn Bloembollen, Egmond-Binnen

The first site description is of the area surrounding Apeldoorn Bloembollen, located in Egmond-Binnen, relatively close to Alkmaar. The site is characterized by its proximity to a coastal dune system that is part of the Noordhollands Duinreservaat (maintained by PWN). The coastal dune system consists of two types of dune deposits; these deposits are distinguished as ‘old dunes’ and ‘young dunes’ as is shown in Fig X. This distinction is mainly based upon its time of origin, the associated disparities in soil

development and often the geomorphological differences. Differences in lithology are hardly apparent because the material of the young dunes either originates from the old dunes and beaches or has a substantially different origin (Klijn, 1981). According to Jelgersma et al. (1970), absolute dates of young dune deposits between Monster and Egmond revealed that formation began only in the 12th_{century and}

that the formation of the young dunes largely was determined over the next four centuries.

The beach and dune sand along the Dutch coast has a variable composition in both chemical and physical properties. The most striking phenomenon is the so-called ‘lime-jump’ at Bergen. The sand usually contains more than 2% CaCO3 south of Bergen, and it contains less than 2% north of Bergen.

Other soil constituents evident in beach sand are iron oxide and feldspar, and are often proportional to the CaCO3 distribution. These soil constituents do not only affect vegetation, which is reflected, for

example, in the floristic distinction between the (calcareous) Duin district and the (limestone) Wadden district, but also reflects floristic distinction between different geomorphological states. Thus, the material differences are related to the origin of the sand, but also to the nature and intensity of secondary

processes, such as shell propagation or leaching (Klijn, 1981). Moreover, human activities have also affected the beaches and the old dunes. After the Middle Ages, the human activities at the Western coast increased. The agricultural exploits then focused on the beach plains, large-scale excavations for the purpose of sand extraction for the expansion of major cities particularly affected higher parts of the dunes. The parts that were excavated to near groundwater level were cultivated and these calcareous sandy soils have mainly served bulb cultivation after the 17th_century.

I.2 Location 2 – Duin VOF, Callantsoog

The second site description is of the area surrounding floriculture company Duin VOF, located in Callantsoog, relatively close to Den Helder. The area of dunes between Den Helder and Callantsoog consists of three main dune systems; ‘De Grafelijkheidsduinen’, ‘De Donkere duinen’ en ‘De

Noordduinen’, which consist of a combination of Dunkirk deposits (where peat is possibly present) and young dunes with older deposits (Fig X) (Synbiosis, n.d.; Klijn, 1981). The northern parts of the dune system are remains of former islands, which were part of the contiguous dune row of Holland ended at Camperduin. To the North was a series of sand dunes, including the islands of Callantsoog and

Huisduinen. Increased siltation started in the lee of the dunes, where underlying salt marshes and mudflats were covered in sludge. These areas were gradually reclaimed through a process of ‘inpolderen’. This process sped up when Callantsoog and Huisduinen were connected with a dike (Synbiosis, n.d.). Similar to location 1, large-scale excavation for agricultural purposes in this area has increased since the Middle Ages as well (Klijn, 1981). Deposits of sand and clay sand alternating with clay layers now characterize the area between Callantsoog and Julianadorp. The soil has a humid-bearing top layer of approximately 0.45 cm thickness and CaCO3 is not present in the soil (Natura, 2000).

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I.3 Location 3 – Steijn Damen VOF, Noordwijkerhout

The third site is located in Noordwijkerhout, which is located relatively close to Leiden. This floriculture company was located slightly more inlands than the other two. Similar to the first two

locations, this area consists of a combination of young dunes and old dunes (Fig. 4). As it is located under the Bergen where levels of CaCO3 are below 2%, the soil is not calcareous (Klijn, 1981). The Southern

part of The Netherlands has corresponding human activities to those in locations 1 and 2; especially excavating activities have been properly visualized for this area 60 years ago (Fig. 3) (Klijn, 1981).

Fig. A1 Distribution of older beaches intact and levelled older beaches

(Klijn, 1981).

Old beach ridges and excavated dunes Old beach ridges and old dunes

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Appendix II: Extended description of contact angle method

1. Soil samples need to be sieved to retrieve an even surface to prevent water droplets from falling in between multiple soil particles. A recommended sieve fraction is <0.355 and >0.180 mm. 2. The sieved soil samples need to be adhered to 2/3 of glass coverslips by using strong

double-sided tape (Fig. A3).

3. For the microscopic pictures a microscope needs to be attached to camera that is connected to a computer. This research used LEICA IM50 software and cameras associated with the Leica microscope. By using a frame with a 45° mirror, the camera angle was reflected, so that a side-view of the water droplet on the soil was seen (Fig. A4). The following steps need to be followed:

a. Before making the picture, ensure that the zoom of the microscope is perfectly set. b. Ensure that every water droplet has a fixed volume.

c. Establish a certain routine while capturing the photos. For example, place a water droplet with a pipette and ‘acquire’ the picture within 90 seconds (recommended time frame, as water droplets spread easily on hydrophilic soils).

d. It is not recommended to place a droplet on the same area on the coverslip twice. e. For this research, 5 microscopic pictures of water droplets per soil sample were taken

(total = 270).

4. After acquiring the photos, they need to be converted to grayscale JPEG images.

5. The contact angle of the water droplets will be measured by using ImageJ software installation in combination with the DropSnake plugin. This specific software can be used for non-axisymmetric or general drops, which is especially useful if the drop is on a tilted surface or if receding contact angles are present. A polynomial fit will encircle the droplet.

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6. After opening an image in ImageJ, the DropSnake plugin can be launched (the image should first be opened). The snake can be initialized by pressing ‘’place knots automatically’’. The user can then start placing ‘knots’, beginning at the lower-left triphase point and contouring the droplet clockwise until the lower- right triphase contact point is reached (ensure that the minimum number of 7 knots is reached). Finalize the snake by double clicking after the last knot is placed. A blue snake curve will appear around the drop edge with a symmetric reflection of the snake below the drop. The knots placed around the drop can be adjusted using the mouse, to ensure that the blue curve follows the drop edge closely. The final snake is computed and the angle measurements for both angles are displayed in the final curves dialog box in the upper left side of the image (Fig. A5).

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7. In this research, a total of 540 contact angles were retrieved (2 per image). Thereafter, the mean contact angle per image was calculated. The data of these contact angles can be found in Appendix III.

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Appendix III: Sample numbering

Sample number Original numbering

1 A.D.1.1 2 A.D.1.2 3 A.D.1.3 4 A.D.2.1 5 A.D.2.2 6 A.D.2.3 7 A.F1.1 8 A.F1.2 9 A.F2.1 10 A.F2.2 11 A.F3.1 12 A.F3.2 13 A.F4.1 14 A.F4.2 15 A.F1.B1 16 A.F1.B2 17 A.F2.B1 18 A.F2.B2 19 A.F3.B1 20 A.F3.B2 21 A.F4.B1 22 A.F4.B2 23 D.F1.1 24 D.F1.2 25 D.F2.1 26 D.F2.2 27 D.K1.1 28 D.K1.2 29 D.K2.1 30 D.K2.2 31 D.F1.B1 32 D.F1.B2 33 D.F2.B1 34 D.F2.B2 35 D.K1.B1 36 D.K1.B2 37 D.K2.B1 38 D.K2.B2 39

S.F1.1

40

S.F1.2

41

S.F2.1

42

S.F2.2

43

S.F3.1

44

S.F3.2

45

S.F4.1

46

S.F4.2

47 S.F1.B1 48 S.F1.B2 49 S.F2.B1 50 S.F2.B2 51 S.F3.B1 52 S.F3.B2 53 S.F4.B1 54 S.F4.B2

Determining predictability of soil water repellency on agricultural lands cultivated with flower bulbs along the Dutch coastal zone