Effects of mulching on soil physical properties and runoff under semi-arid conditions in southern Spain

Catena 81 (2010) 77–85

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Catena j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / c a t e n a

Effects of mulching on soil physical properties and runoff under semi-arid conditions in southern Spain Antonio Jordán a,b,⁎, Lorena M. Zavala a,b, Juan Gil a,c a b c

MED_Soil Research Group, Spain Departamento de Cristalografía, Mineralogía y Química Agrícola, Facultad de Química, Universidad de Sevilla, C/Profesor García González #1, 41012, Sevilla, Spain Departamento de Química Agrícola y Edafología, Facultad de Ciencias, Universidad de Córdoba, Edificio Marie Curie, Campus de Rabanales, 14014, Córdoba, Spain

a r t i c l e

i n f o

Article history: Received 31 July 2009 Received in revised form 17 November 2009 Accepted 14 January 2010 Keywords: Aggregate stability Bulk density Mulching No till Simulated rainfall Soil loss Soil structure Southern Spain

a b s t r a c t Application of crop residues to soil and reduced or no tillage are current management practices in order to achieve better water management, increase soil fertility, crop production and soil erosion control. This study was carried out to quantify the effect of wheat straw mulching in a no tilled Fluvisol under semi-arid conditions in SW Spain and to determine the optimum rate in terms of cost and soil protection. After a 3-years experiment, mulching application significantly improved physical and chemical properties of the studied soil with respect to control, and the intensity of changes was related to mulching rate. The organic matter content was generally increased, although no benefit was found beyond 10 Mg ha−1 year−1. Bulk density, porosity and aggregate stability were also improved with increasing mulching rates, which confirmed the interactions of these properties. Low mulching rates did not have a significant effect on water properties with respect to control, although the available water capacity increased greatly under high mulching rates. After simulated rainfall experiments (65 mm h−1 intensity), it was found that the mulch layer contributed to increase the roughness and the interception of raindrops, delaying runoff generation and enhancing the infiltration of rain water during storms. Mulching contributed to a reduction in runoff generation and soil losses compared to bare soil, and negligible runoff flow or sediment yield were determined under just 5 Mg ha−1 year−1 mulching rate. It was observed that during simulations, the erosive response quickly decreases with time after prolonged storms (30 min) due to the exhaustion of available erodible particles. These results suggest that the erosive consequences of intermediate intensity 5-years-recurrent storms in the studied area could be strongly diminished by using just 5 Mg ha−1 year−1 mulching rates. © 2010 Elsevier B.V. All rights reserved.

1. Introduction Soil organic matter is known to be a key factor in soil quality of semiarid soils. Differently to other land uses, cultivated soils show low organic matter contents (Masciandaro et al., 1998). Intensive use of soil throughout history has led to depletion in soil quality, leading in turn to low yields because of the consequent reduced organic matter (Reicosky et al., 1995). Reductions in organic matter following cultivation of grassland soils are reasonably well documented (Anderson and Coleman, 1985). Celiki (1987) observed that Mediterranean cultivated soils present lower saturated hydraulic conductivities than forest soils. He found that cultivation degrades soil physical properties, and makes soils more susceptible to erosion processes. Addition of crop residues to cultivated soils helps to improve soil quality and productivity through its

⁎ Corresponding author. Departamento de Cristalografía, Mineralogía y Química Agrícola, Facultad de Química, Universidad de Sevilla, C/Profesor García González #1, 41012, Sevilla, Spain. Tel.: + 34 954556950; fax: + 34 954557140. E-mail address: [email protected] (A. Jordán). URLs: http://grupo.us.es/medsoil (A. Jordán), http://grupo.us.es/medsoil (L.M. Zavala). 0341-8162/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.catena.2010.01.007

favorable effects on soil properties (Lal and Stewart, 1995; Mulumba and Lal, 2008). Application of crop residue mulches to cultivated soils increases the organic matter content (Havlin et al., 1990; Duiker and Lal, 1999; Saroa and Lal, 2003). Favorable effects of residue mulching on soil organic matter, water retention and stability of aggregates have been reported for the surface layer (Havlin et al., 1990; Duiker and Lal, 1999). No till management is generally associated with high levels of crop residues left on the soil surface, and it has positive effects on soil erosion control, organic matter content, physical and chemical fertility, and soil biology (Crovetto, 1999; Mulumba and Lal, 2008). Generally, the effect of crop residue on soil organic matter content is highly related to the amount and only weakly to the type of residue applied (Mulumba and Lal, 2008), although contradictory results have been reported. Ouédraogo et al. (2007), for example, observed negative effects of maize straw mulch application to semi-arid soil, and this effect was reduced when maize straw was combined with urea. Conservation of soil moisture is one of the major advantages of mulch farming system (Mulumba and Lal, 2008). Sharma et al. (1990) found that, independently from tillage, residual soil moisture was increased after application of maize stalk mulch in sandy loam soils.

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Also, Zhang et al. (2009) found positive effects respect to conventional tillage systems. These effects are especially important under arid or semi-arid conditions. High soil water capacity under semi-arid conditions in Spain has been attributed to the mulching effect of crop residues under conservation tillage systems, as consequence of greater soil organic matter content and changes in pore-size distribution (Bescansa et al., 2006). Soil erosion is a major problem in the Mediterranean region due to the arid conditions, intensity of storms and concentration of rainfall, which are factors that contribute largely to degradation of agricultural land (López-Bermúdez and Albadalejo, 1990; Lal, 1999). Soil loss is enhanced in cultivated soils by the high susceptibility of soil particles and aggregates to become detached and transported by erosive agents (Boardman et al., 1990; Gómez et al., 1999). Research conducted in Spain since the 1980s has reported that soil loss is an especially important problem in agricultural land in comparison to other land uses (Boix-Fayos et al., 2005). Mulching protects soil from rainfallinduced erosion by reducing the rain drop impact. A partial covering of mulch residue on the soil can strongly affect runoff dynamics, and reduce runoff amount (Rees et al., 2002; Findeling et al., 2003). Blavet et al. (2009) have reported a significant reduction of soil loss when plant residues were left on the soil. They found that vineyards mulched with straw or with rock fragment cover were protected against runoff, and soil erosion. Addition of organic plant residues to crop soils also helps to improve soil structure. Mulumba and Lal (2008) reported positive effects on soil porosity, available water content, soil aggregation, and bulk density after application of wheat straw mulch. Several authors (Gerzabek et al., 1995; Le Bissonnais and Arrouays, 1997; Wright and Hons, 2005) have found that soil aggregation and related structure properties are influenced by soil organic matter content for different tillage and crop regimes. For a wide variety of soils, it has been found that roots and hyphae contribute to stabilization of macro-aggregates (Tisdall and Oades, 1982). Thus, macroaggregation is controlled by soil management, since it influences the growth of plant roots, and the oxidation of organic carbon, while stability of micro-aggregates depends on the persistent organic binding agents and appears to be a characteristic of the soil, independent of management (Tisdall and Oades, 1982). Traffic and heavy machinery causes mechanical compaction, increasing bulk density and decreasing porosity in most soils. However, this compaction may be compensated by progressive creation of macropores from roots and faunal activity under no-till (Kay and VandenBygaart, 2002). Reported results of mulching effects on soil bulk density and porosity are ambiguous. The effects of mulching on bulk density may vary due to soil type, type of management, type of mulch, climate and land use. Martens and Frankenberger (1992) and Unger and Jones (1998) showed that addition of organic matter decreased soil bulk density. In contrast, other researchers have observed that mulching increased significantly (Bottenberg et al., 1999) or had no effects on bulk density (Blevin et al., 1983; Acosta et al., 1999; Duiker and Lal, 1999). During the last decades, conventional tillage systems have been displaced by conservation tillage systems, and especially no till practices, in many areas of the world. Benefits of no till practices have been reviewed by Lal (1989) and Unger (1990), but despite those well-recognized benefits, no till practices have not been implemented in large areas (Álvaro-Fuentes et al., 2008). In large Mediterranean arid and semi-arid areas under soil degradation risk, where intensive tillage is commonly used, it is necessary to substitute conventional tillage with more conservative practices. Availability, costs and application efforts of crop residues are factors that local farmers must take into account. It is thus necessary to find an optimum rate for mulch application without an excessive cost for farmers. Mulumba and Lal (2008) stated that this critical level of mulch rate needs to be established for site-specific soil and environmental conditions.

Therefore, the objectives of this work are [1] to study the effects of different mulch rates on soil bulk density, soil porosity, soil aggregate stability, organic matter content and soil moisture retention characteristics, [2] to investigate the runoff generation and erosional response of soils under different mulch rates, and [3] to determine the optimum rate of mulch application under semi-arid conditions in the studied area.

2. Materials and methods 2.1. Study site and experimental design The experimental site is located in Jerez de la Frontera, in the province of Cádiz (SW Spain), approximately on the coordinates 36°38′ N–6°00′W and 30 m above sea level. The climate is Mediterranean, with hot dry summers and moderately wet cool winters. According to nearby weather station in Jerez de la Frontera Airport, annual average temperature is 17.6 °C, with mean maximum air temperature is 25.6 °C in August and mean minimum air temperature is 10.8 °C (January). Annual average precipitation is 645.7 mm, and monthly rainfall ranges from 1.7 (August) to 108.7 mm (November). The main soils are Fluvisols (classified according to IUSS-ISRICFAO, 2006) and soil texture is loam. Wheat straw residues (C/N ratio 79.2 ± 3.1, on average) were applied at 0, 1, 5, 10, and 15 Mg ha−1 year−1 (hereinafter, mulching rates MR0, MR1, MR5, MR10, and MR15) on untilled soil during 2005, 2006 and 2007. The plot size was 3 m × 3 m, replicated five times for each treatment, and distributed according to a randomized Latin square design. Since crop type can influence largely the water-stability of soil aggregates and other soil properties (dos Reis Martins et al., 2009), no crop was cultivated during the study period and no fertilizer was applied. Only herbicides (glyphosphate) were eventually applied in order to control weeds. This also allowed eliminating crop interferences during rainfall simulations.

2.2. Soil analysis Soil samples (0–10 cm) were collected at randomly distributed points prior to the experiments in 2005 (N = 5) and at each plot after the experiments in 2008 (N = 5 samples × 5 treatments = 25) for physical and chemical analysis. Each sample was dried at laboratory room temperature (25 °C) to a constant weight and sieved (2 mm) to eliminate coarse soil particles. Soil acidity (pH) was measured in aqueous soil extract in de-ionized water (1:2.5 soil:water). Soil salinity was measured as the electrical conductivity of the aqueous soil extract in de-ionised water (1:5 soil:water). Soil organic matter was determined by the Walkley–Black method (Walkley and Black, 1934). Carbonates were determined by the method of the Bernard calcimeter. Prior to determinate the particle size distribution, samples were treated with H2O2 (6%) to remove organic matter and HOAc-NaOAc buffer solution (pH 5.0) to remove carbonates. The proportion of particles of diameter above 2 mm was determined by wet sieving and particles b2 mm were classified according to USDA (2004). Water content at 1500 kPa (wilting point), 33 kPa (field capacity), and 0 kPa (saturation water) was determined using a pressure-membrane extraction apparatus (Richards, 1941). The available water capacity was calculated as the difference in moisture retention between 33 and 1500 kPa suctions, expressed on a volumetric basis. Bulk density was measured by the core method (Blake and Hartge, 1986), using cores 3 cm in diameter, 10 cm in length, and 70.65 cm3 in volume. Particle density (PD) was determined by the picnometer method (Blake and Hartge, 1986). Total porosity (TP) was calculated from the bulk density (BD) values and the measured particle density as TP = 1−BD/PD.

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2.3. Measurement of aggregate stability Undisturbed soil samples (0–10 cm depth) were collected at each plot for aggregate stability determinations. Soil aggregation parameters were determined by two methods: 1) Water-drop test (CND) and 2) Ultrasonic disruption (UD). 1) The water-drop test used here was the ‘counting the number of water drop impacts’ (CND) test (Imeson and Vis, 1984). Distilled water drops (approx. 0.05 mL) were allowed to fall from a constant-feed buret 1 m through a polyethylene pipe (Ø 10 cm) onto aggregates 4–4.8 mm in diameter separated by dry sieving and pre-wetted during 24 h with distilled water to standard moisture conditions (pF 1) to avoid slacking (Imeson and Vis, 1984). Individual aggregates were placed on a 2.8 mm mesh sieve (Imeson and Vis, 1984). The number of drops necessary to destroy each aggregate was recorded and used as an index of the stability of that aggregate. Several authors have used the same aggregate sizes for studying the aggregate stability of Mediterranean soils (Imeson and Verstraten, 1985; Lavee et al., 1991; Boix et al., 1995; Cerdá, 1996; Cantón et al., 2009). Twenty individual aggregates from each sample were analyzed and mean number of drop impacts was chosen as representative for that sample. 2) Ten aggregates 4–4.8 mm in diameter separated by dry sieving and pre-wetted during 24 h with distilled water to standard moisture conditions (pF 1) were immersed in distilled water (40 mL), and then subjected to an ultrasound probe for 5–10 s with the probe tip placed 10 mm under the water surface. The energy applied varied between 30 and 115 W. After the treatment, the amount of surviving aggregates (N2.8 mm) was weighed (Imeson and Vis, 1984), and used as an index of aggregate stability. 2.4. Saturated hydraulic conductivity Undisturbed soil cores (10 cm in diameter and 10 cm deep) were collected at each plot for determination of saturated hydraulic conductivity and soil porosity. Cores were collected on the soil surface, after gently removing the residues. Cores were saturated from underneath for 24 h prior to saturated hydraulic conductivity measurements using the constant head method (Klute and Dirksen, 1986). 2.5. Rainfall simulation Rainfall simulation was performed using a rainfall simulator similar to that described by Lasanta et al. (2000). The structure, in the shape of a truncated pyramid, is supported on metal legs. The simulator was covered with a wind protector. The legs are telescopic so that the simulator can be levelled when placed on a sloping surface. At the top of the structure (3.5 m high) there is a single nozzle which is connected through a rubber pipe to a mobile automatic pump. The water from the nozzle falls onto a circular area of 1963.5 cm2 that is delineated by a steel ring (50 cm in diameter). The ring was carefully tapped into the soil following the slope to prevent leakage and direct the runoff flow to the outlet of the plot. Before the experiments, rainfall intensity was measured by five rain gauges (10 cm in diameter) distributed uniformly over the plot. The mean rainfall intensity for the experiments was 65 ± 1.35 mm h−1 and the duration of the simulations was 30 min. Average kinetic energy of rainfall was 13.3 J m−2 mm−1 (calculated as in Navas et al., 1990). The return period for 66.1 mm h−1 rainfall intensity storms in the study area is 5 years (Jerez de la Frontera — Airport Weather Station), what supports the chosen rainfall intensity for the simulation tests. Deionized water was used because the chemical composition of the water may influence the soil response (Agassi et al., 1994). A gutter installed on the downstream side of the plot conducted the runoff to a sample collection box. Runoff was

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recorded at regular intervals (2 min) for volumetric determinations and measuring sediment concentrations, after coarse organic residues were removed. Finally, soil loss rates were calculated from sediment concentrations in collected runoff. 2.6. Data analysis Data analysis included correlations, regression, and ANOVA tests. Assumptions of normality and homogeneity of variances were tested using the Shapiro-Wilk and Brown-Forsyth tests, respectively. Since most of the variables did not satisfy these assumptions, alternative nonparametric tests were used for comparing multiple independent groups of samples (Kruskall–Wallis ANOVA). When ANOVA null hypothesis was rejected, pos-hoc pair wise comparisons were performed to investigate differences between means (Bonferroni test). All computations were made using STATISTICA version 6 (StatSoft, 2001). 3. Results 3.1. Changes on soil properties under different mulching rates The main characteristics of the experimental plots are shown in Table 1. No significant differences were observed for plots under different mulching rates. Slope varied between 3.6 and 5.3% (4.4 ± 0.6, on average). Soil texture at the studied plots was loam (32.9% sand, 44.5% silt, and 22.6% clay, on average). The proportion of coarse fragments varied between 0 and 3% (1.5 ± 1%, on average). Salinity was moderate-high (electric conductivity 1.1 ± 0.2 dS m−1). Average percentage of carbonates was 12.6 ± 1.5%, and pH ranged between 7.2 and 8.1 (7.6 ± 0.3, on average). The soil organic matter content varied significantly for the different mulching rates (p = 0.0001, Table 1). The organic matter content at the initial stage was 0.4 ± 0.2%, and no significant differences were observed between this value and the organic matter content from MR0 (control) and MR1 plots, with values ranging between 0.1 and 2.0%. The organic matter content ranged between 3.1 and 4.4% at MR5 plots. Higher organic matter contents were measured at MR10 and MR15 plots, ranging between 6.3 and 11.7%. The relationship between soil bulk density and mulching rate was best described by a second-order polynomial function (R2 0.90; Fig. 1). The Bonferroni test separated bulk density values in five groups (Kruskall–Wallis p = 0.0001; Table 1). Bulk density at the initial stage was significantly lower than bulk density measured after MR0 control treatment (1.41 ± 0.01 and 1.45 ± 0.01%, respectively), what can be due to previous management practices. Average bulk density was 1.45 ± 0.02 g cm−3 for mulching rates MR0 and MR1, and decreased to 1.39 ± 0.02 g cm−3 for mulching rates MR5 and MR10. Finally, the lowest bulk density was observed for mulching rate MR15 (1.32 ± 0.02 g cm−3). Total porosity increased with mulch rate (Fig. 2) and did not show significant differences for mulching rates MR0-MR5 (Table 1). Mean porosity was 0.3 ± 0.1% under mulching rates MR0-MR5. It increased by 173% for mulching rates MR10-MR15 (0.6 ± 0.1%, on average). 3.2. Aggregate stability under different mulching rates Aggregate stability (measured as CND under wet conditions, pF 1) varied between 2 and 176 (44.3 ± 49.8 drops, on average). The linear relationship between CND and mulching rate is shown in Fig. 3. CND under MR0 was 7.8 ± 4.0 drops, and no significant benefit was observed under MR1 (6.8 ± 6.2 drops) or MR5 (16.6 ± 11.9 drops). CND increased significantly (Kruskal–Wallis p 0.0009) under higher mulching rates as MR10 (90.0 ± 50.2 drops) and MR15 (100.2 ± 35.7 drops), although not significant differences were observed between these groups. Most stable aggregates (CND values approximately above 50 drops) showed a dense proportion of fine roots and organic

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Table 1 Soil physical and chemical properties (0–10 cm) at the initial stage before the experiments and under different mulching rates. MR0 = control; MR1 = 1 Mg ha−1 year−1, MR5 = 5 Mg ha−1 year−1; MR10 = 10 Mg ha−1 year−1; MR15 = 15 Mg ha−1 year−1.

Initial state (2005) MR0 MR1 MR5 MR10 MR15 Kruskall–Wallis, p

Slope (%)

Sand (%)

Silt (%)

Clay (%)

Gravels (%)

Salinity (dS m−1)

CO3Ca (%)

pH

Organic matter (%)

Bulk density (g cm−3)

Total porosity (%)

4.3 ± 0.6 4.2 ± 0.7 4.7 ± 0.7 4.1 ± 0.5 4.8 ± 0.7 4.4 ± 0.4 NS

33.2 ± 1.9 32.8 ± 1.5 32.4 ± 1.7 33.8 ± 0.8 33.4 ± 1.7 32.0 ± 1.2 NS

44.0 ± 4.1 43.8 ± 3.4 45.0 ± 2 44.6 ± 1.5 45.0 ± 2.3 44.2 ± 3 NS

22.8 ± 2.6 23.4 ± 2.4 22.6 ± 1.5 21.6 ± 0.9 21.6 ± 1.5 23.8 ± 2.3 NS

1.2 ± 0.4 1.2 ± 0.8 1.6 ± 0.9 1.4 ± 1.1 2.0 ± 1 1.2 ± 1.3 NS

1.3 ± 0.1 1.3 ± 0.1 1.0 ± 0.2 1.2 ± 0.4 1.1 ± 0.3 1.1 ± 0.2 NS

13.3 ± 1.1 12.9 ± 1.2 12.4 ± 2.0 11.6 ± 1.6 13.3 ± 1.2 12.9 ± 1.5 NS

7.8 ± 0.3 7.7 ± 0.3 7.6 ± 0.2 7.5 ± 0.2 7.8 ± 0.3 7.6 ± 0.4 NS

0.4 ± 0.2 0.4 ± 0.2 1.6 ± 0.3 3.4 ± 0.6 7.8 ± 2.2 8.5 ± 2.2 0.0001

1.41 ± 0.01 cd 1.45 ± 0.01 e 1.44 ± 0.02 de 1.40 ± 0.01 bc 1.38 ± 0.01 b 1.32 ± 0.02 a 0.0001

0.3 ± 0.0 a 0.3 ± 0.1 a 0.3 ± 0.0 a 0.4 ± 0.0 a 0.5 ± 0.1 b 0.6 ± 0.1 b 0.0003

matter that included inorganic materials and contributed to aggregation. CND and organic matter content were related by a second order polynomial function. Fig. 4 shows that when organic matter content increases above approximately 6%, CND is triggered up. The UD test confirmed that stability of aggregates increased with mulching rate. Fig. 5 shows the stability curves determined under different ultrasonic intensities for soil aggregates under different mulching rates. The stable aggregate percentage reached 0% at 70 W (MR0), 80 W (MR1), 90 W (MR5), 100 W (MR10) and 110 W (MR15). A 30 W power supply was enough to get less than 50% stable aggregates under MR0, while 50 and 60 W were needed for soil aggregates under MR10 and MR15, respectively. 3.3. Soil water properties under different mulching rates Soil water retention under different mulching rates is shown in Table 2. Significant differences were observed for water content at 1500, 33 and 0 kPa between low and high mulching rates. In general, no differences were observed between control plots (MR0) and low or moderate mulching rates (MR1 and MR5). Although soil water content increased in MR10 and MR15 plots for all suction intensities, MR15 did not show any effect respect to MR10. The wilting point (1500 kPa) varied between 12.7 and 15.9% for MR0, MR1 and MR5 (14.7 ± 0.9%, on average), but it increased for MR10 and MR15, where it varied between 16.6 and 19.2% (18.2 ± 1.1%, on average). Soil moisture content at field capacity increased with mulching rate. Field capacity and mulching rate were related by a polynomial function (Fig. 6). The Kruskall–Wallis test found significant differences between field capacity at mulching rates MR0, MR1 and MR5, respect to those at MR10 and MR15 (Table 2). Field capacity ranged between 27.7 and 31.4% (29.7 ± 1.1%, on average) for low mulching rates (MR0, MR1, and MR5), while it ranged between 33.7 and 40.1% (36.3 ± 2.3%, on average) for high mulching rates (MR10 and MR15). As no significant differences were observed for field capacity at MR10 and MR15, no benefit was

Fig. 1. Relationship between bulk density and mulching rate.

a a ab b c c

obtained beyond MR10. Mean saturation water (0 kPa) varied in a similar way, and increased from 45.0 ± 3.4% (MR0, MR1, and MR5) to 62.5± 6.3% (MR10 and MR15). The available water was related with mulching rates by a polynomial function (Fig. 7). Although mean available water content increased progressively with mulching rate, the Kruskal–Wallis test did not show significant differences for mulching rates under 5 Mg ha−1. Available water was significantly higher under MR10 and MR15. The application of mulching rates MR10 and MR15 increased the available water content to approximately 18%, but MR15 had no effects respect to MR10 (Table 2). Soil hydraulic conductivities varied between low and high mulching rates. Significant differences were found for high mulching rates (MR10 and MR15) respect to control and low mulching rates (Table 2). Average saturated conductivity under MR10 and MR15 was 7.6 times higher than observed in control experiments (MR0), although no benefit was found for rates higher than 10 Mg ha−1 year−1.

3.4. Runoff rates and soil losses under different mulching rates Surface runoff and runoff at the plot outlet was delayed as mulching rate increased (Fig. 8). Organic residues in the soil surface not only contribute to aggregation, but also increase the hydraulic roughness and interception, which favours a higher infiltration of rain water. The runoff rate increased during the first 15–20 min for soil plots under different mulching rates, and the steady state was reached after 25 min in all cases (Fig. 8).Runoff rates decreased with increasing mulching rates, between MR0-MR1 and MR5-MR15. Although runoff rate under MR5 was almost 9 times that under MR15, both rates were relatively low and no significant differences were observed (Table 3). The steady state runoff rate was 25.54 ± 0.97 mm h−1 for control plots under no mulch (MR0), and it decreased progressively to 24.37 ± 0.90 mm h−1 (MR1), 10.16 ± 1.45 mm h−1 (MR5), and 2.49 ± 0.26 mm h−1 (MR10)

Fig. 2. Relationship between soil porosity and mulching rate.

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Fig. 3. Relationship between aggregate stability (CND) and mulching rate.

and 1.09± 0.41 mm h−1 (MR15), although not significant differences were observed between mulching rates MR10 and MR15 (Table 3). Runoff coefficients varied in the same manner. Mean runoff coefficients varied between 27.34 ± 17.61 (MR0) and 0.97 ± 0.78% (MR15), although no significant differences were observed under higher mulching rates, MR5-MR15 (Table 3). The steady state runoff coefficient did not show significant variations between control treatment, MR0, and MR1, although it increased significantly with increasing mulching rates (Table 3). The interrill soil detachment is also highly determined by the mulching rate because of aggregate stability and the protection of the soil surface against the impact of rain drops. The sediment concentration in interrill runoff increased linearly during the first 10 min of simulated rainfall. After approximately 8–10 min from the beginning of the experiments, there was a steady decrease of sediment concentration, which became stable after approximately 25 min for all experiments (Fig. 9). Average interrill soil detachment rate (Table 3) was 4.4 ± 2.3 g L−1 for soil control soil plots, and it decreased to 3.4 ± 1.8 g L−1 (MR1), 1.0 ± 0.4 g L−1 (MR5), 0.3 ± 0.1 g L−1 (MR10) and 0.1 ± 0.1 g L−1 (MR15). 4. Discussion 4.1. Changes on soil properties under different mulching rates Application of wheat straw mulch to soil produced a significant increase in soil organic matter content between 0 and 10 cm after 3 years of treatment with respect to control, which confirms the interaction of the studied properties. The higher organic matter content was reached under mulching rates MR10 and MR15 during a period of

Fig. 4. Relationship between aggregate stability (CND) and soil organic matter content.

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Fig. 5. Aggregate stability curves for soils under different mulching rates. MR0 = control; MR1 = 1 Mg ha−1 year−1, MR5 = 5 Mg ha−1 year−1; MR10 = 10 Mg ha−1 year−1; MR15= 15 Mg ha−1 year−1.

three years, although no benefit was found for 15 Mg ha−1 year−1 respect to 10 Mg ha−1 year−1. The high average organic matter content under MR10 and MR15 can be explained by slow mineralization rates. Ceccanti et al. (2007) reported the presence of condensed and less mineralized organic substances in soil organic matter under straw mulching and no-till. The increased C/N ratio after MR10 and MR15 treatments and no fertilisation might have led to an increase in stable soil organic matter under local conditions, while mineralization rate was higher under low mulching rates. Bulk density, porosity and aggregate stability were also improved with increasing mulching rates, which confirmed the interaction of these properties. This is in agreement with other studies. GarcíaOrenes et al. (2009) found that straw mulch was able to significantly improve soil properties after a 16 months study period in a Mediterranean farming area. Mulumba and Lal (2008) found that mulch application increased total porosity and soil aggregation with increasing mulching rates (0, 2, 4, 8 and 16 Mg ha−1 year−1). In this last work, mulch rate effects on soil bulk density and aggregate stability were not linear, which is in agreement with our results. Spearman correlation coefficients demonstrate the narrow relationship between mulching rate and the studied soil chemical and physical properties (organic matter, bulk density, porosity, and aggregate stability; Table 4). Similar positive relationships between organic matter and aggregate stability indices were found in other Mediterranean type-ecosystems (García-Orenes et al., 2005; Zornoza et al., 2007). Marinari et al. (2006) found significant increases of microbial biomass carbon content with organic management in farming systems in Italy, but did not find significant differences in soil organic carbon content after 14 months. In contrast, Blanco-Canqui and Lal (2008) demonstrated that organic carbon content varies with soil depth, and in many cases, till or no till systems do not induce significant differences through the soil profile. Soil bulk density decreased with increasing mulching rates, fitting a second order polynomial function. This is in agreement with Mulumba and Lal (2008), who found a similar relationship. Mulumba and Lal (2008) found low variations in bulk density for mulching rates between 0 and 8 Mg ha−1, while it decreased almost linearly between 8 and 16 Mg ha−1. In our experiments, no significant differences were observed between bulk density after control or low intensity mulching treatments (MR0 and MR1). But bulk density decreased deeply when mulching rate increased (MR5-MR15), showing an almost linear relationship. This is in agreement with Oliveira and Merwin (2001), who found that bulk density was lower and soil porosity greater under mulch than under other groundcover management practices, and Ghuman and Sur (2001), who studied the effect of mulching on soil properties and yields of rainfed maize and wheat in a subhumid subtropical climate and demonstrated that mulching decreased bulk density in compacted soils particularly in no

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Table 2 Soil water characteristics and saturated conductivity (0–10 cm) under different mulching rates. MR0 = control; MR1 = 1 Mg ha−1 year−1, MR5 = 5 Mg ha−1 year−1; MR10 = 10 Mg ha−1 year−1; MR15 = 15 Mg ha−1 year−1. Mulching rate (Mg ha−1)

Wilting point, 1500 kPa (%)

Field capacity, 33 kPa (%)

Saturation, 0 kPa (%)

Available water (%)

Saturated conductivity (mm h−1)

All 0 1 5 10 15 Kruskall–Wallis, p

16.1 ± 2.0 14.5 ± 1.3 14.6 ± 0.9 15.1 ± 0.2 17.5 ± 1.1 18.9 ± 0.6 0.0013

32.4 ± 3.7 28.8 ± 0.8 a 29.6 ± 0.9 a 30.8 ± 0.4 a 35.6 ± 2.6 b 37.0 ± 2.0 b 0.0003

52.0 ± 9.9 41.6 ± 0.3 44.3 ± 0.8 49.1 ± 1.7 62.3 ± 6.3 62.6 ± 7.0 0.0002

16.3 ± 1.9 14.4 ± 0.5 a 15.0 ± 0.3 a 15.7 ± 0.5 a 18.1 ± 1.7 b 18.1 ± 1.8 b 0.0004

24.2 ± 22.6 5.9 ± 1.4 a 8.9 ± 1.2 a 16.4 ± 3.8 ab 45.0 ± 23.5 b 44.7 ± 25.1 b 0.0002

a a a b b

tillage system what can be ascribed to higher soil carbon content and biotic activity. In contrast, increased bulk density has been observed after mulching respect to conventional tilling by Bottenberg et al. (1999), showing even negative consequences in plant growth. Reduced or no tillage usually increases soil density what has been widely reported by many authors (Van Ouwerkerk and Boone, 1970; Pidgeon and Soane, 1977; Singh and Malhi, 2006). Głąb and Kulig (2008) found that bulk density increased in the 10–20 cm soil layer after reduced tillage, although bulk density from the upper soil layer (0–10 cm) decreased and reached the similar value as those obtained at conventional tillage. Other researchers have not found linear relationship between mulching rate and bulk density (Blevin et al, 1983; Acosta et al., 1999), although some of them have demonstrated that no till practices contribute to a decrement in bulk density in Mediterranean (Murillo et al., 2006) and other climatic areas of the world. Many authors have found comparable or increased bulk densities in the first centimeters of soil after reduced tillage short-term studies in eastern Canada (Angers et al., 1997), and USA (Yang and Wander, 1999; Puget and Lal, 2005; Al-Kaisi et al., 2005). Long term studies, anyway, have shown that bulk density under reduced tillage long-term experiments was comparable or lower than under conventional tilling. Tebrügge and Düring (1999) reported that bulk density generally increased under no tillage, but it decreased at the surface (0–3 cm). They explained it as a direct consequence of the mulch layer on top of nontilled soils that provides organic matter and food for soil fauna, which loosens surface soil by burrowing activities. Other authors have reported no significant differences between different tillage practices. Deen and Kataki (2003) compared the results from long term conventional tilling and conservation tillage practices, and reported that different management practices had no significant influence on soil bulk density at different soil layers between 0 and 60 cm. Also, Dolan et al. (2006) found that soil bulk density did not vary among tillage treatments in the 0–5 cm soil layer. Besides the duration of experiments, the diversity of results may be due to differences in

Fig. 6. Relationship between field capacity moisture and mulching rate.

a a a b b

management practices, soil type and the type of mulch material used (Mulumba and Lal, 2008). Aggregate porosity increased with mulching rate according to a second order polynomial function. Soil porosity is especially important to crop development since it helps to renew soil atmosphere and to enhance root growth. The improved root growth makes it possible for the plant to absorb soil water and nutrients from the subsoil. Hoffmann and Jungk (1995) found that soil compaction inhibits root growth after oxygen deficiency and mechanical soil resistance. Increased porosity due to mulch application was also reported by many other authors. Głąb and Kulig (2008) observed that fodder radish mulching increased soil porosity in compacted soil under reduced tillage and temperate climate in Poland; Oliveira and Merwin (2001) studied the effect of a 15 cm shredded hardwood bark and found that soil porosity increased more under mulch than other management systems.

4.2. Soil water properties under different mulching rates Low mulching rates (MR1 or MR5) did not have an appreciable effect on water properties, since significant differences were not observed respect to control (MR0). On the other hand, available water capacity increased respect to control in 25.7% under high mulching rates (MR10 and MR15). After MR10 and MR15, the wilting point increased to 20.6 and 30.3%, respectively; field capacity increased to 23.6 and 28.5% respectively; and saturation water increased to 49.8 and 50.5%. Generally, no benefit was observed beyond 10 Mg ha−1 year−1 (MR10). The improvement of available water capacity with mulching rate is in agreement with most of published literature, although different results have been reported. Mulumba and Lal (2008) found that applying mulch even at low rates can have a strong impact on the available water content, although the effects of mulching rates higher than 2 Mg ha−1 year−1 were not significantly different from those under higher rates. High available water capacities have been reported under high mulching rates and no till by Duiker and Lal (1999)

Fig. 7. Relationship between available water content and mulching rate.

A. Jordán et al. / Catena 81 (2010) 77–85

Fig. 8. Variation of mean runoff rates under different mulching rates. MR0 = control; MR1 = 1 Mg ha−1 year−1, MR5 = 5 Mg ha−1 year−1; MR10 = 10 Mg ha−1 year−1; MR15 = 15 Mg ha−1 year−1. N = 5 for each mulching rate treatment. Vertical bars indicate ± standard deviation.

and Mahboubi et al. (1993). Anyway, contradictory data have been reported by Głąb and Kulig (2008), who found no effect in available water content after applying mulch and different tillage systems. 4.3. Runoff and erosional response under different mulching rates The runoff and erosional response of soils depends largely on the mulching rates applied during the experiments. The mulch layer contributed to increase the roughness and the interception of raindrops, what delayed runoff generation. The delay of runoff flow enhanced the infiltration of rain water during storms. Our results showed that, under an intensity of 65 mm h−1, mulching contributes to a decrease in runoff generation and soil losses compared to bare soil. This is in agreement with other findings reported by several authors. Puustinen et al. (2005) found that mulching contributes to decrease runoff flow and enhance infiltration. Lal et al. (1980) reported that saturated conductivity was significantly increased after mulch application in a tropical Alfisol. Prasad and Power (1991) observed that mulching can increase saturated conductivity because of higher activity of soil fauna. Other authors have found that runoff flow and infiltration may be affected by mulching rate in a different way (Jin et al., 2009). They suggested that the relation between mulching rate and interill soil detachment is not unique and can vary from negative to positive depending on the rainfall intensity, showing that soil mulching at the soil surface is not always negatively related to interill soil loss. They explained it by a reduction in infiltration rate with increasing cover rate that leads to an increasingly net flux which becomes deeper and/or faster in its concentrated flow part. So, concentrated flow increases detachment and transport of soil particles resulting in high soil losses, as it has been demonstrated for stony soils (Cerdà, 2001; Martínez-Zavala and Jordán, 2008). Ponding is

83

Fig. 9. Variation of mean soil losses under different mulching rates. MR0 = control; MR1 = 1 Mg ha−1 year−1, MR5 = 5 Mg ha−1 year−1; MR10 = 10 Mg ha−1 year−1; MR15 = 15 Mg ha−1 year−1. N = 5 for each mulching rate treatment. Vertical bars indicate ± standard deviation.

faster and deeper in the exposed soil surface, thus the water column pressure is greater and thereafter infiltration takes place more quickly and penetrates more deeply. However, this response can be overridden under moderate rainfall intensity by a dense soil cover or thick mulch layers. García-Orenes et al. (2009) observed that time to ponding was delayed after straw mulching treatment respect to other types of management, as systemic herbicide or ploughing. They found that no runoff was initiated after 55 mm h−1 simulated rainfall after treatment under just 2.5 Mg ha−1 year−1. In our experiments, infiltration rates almost reached 100% after 10–15 Mg ha−1 year−1 treatments, and it was more than 90% under 5 Mg ha−1 year−1. Moore and Singer (1990) and Roth and Helming (1992) divided the evolution in time of runoff in three stages. In stage I (pre-runoff) rainfall may cause ponding, but no runoff or soil loss. The extent of this stage depends on factors as soil properties and cover. In stage II, rates of runoff and soil loss increase sharply, until a maximum is reached. This peak is followed after some time by a sharp decline of splash towards the end of stage II. Finally, in stage III (steady state) rates of runoff and soil loss achieve equilibrium. Jordán and MartínezZavala (2008) approached logarithmic functions to the evolution of runoff rates with time on unpaved forest roads. This behaviour may be due to changes in the cohesion of aggregates at the soil surface. The peaks of sediment yield appear when aggregates are sheared under raindrop impacts and the soil shear strength is decreased as the soil moisture goes up to saturation. As runoff increases in the first few minutes, loose sediments on the surface are flushed off. The mulch layer preserves the soil from erosion by protecting the soil immediately below the residues against rain drop impact. Soil erosion is markedly reduced under high mulching rates because runoff and rainfall detachment are diminished and soil infiltration rates are increased. The curves of sediment yield under different mulching

Table 3 Mean runoff rate, steady state runoff rate, runoff coefficient, steady state runoff coefficient, sediment yield and standard deviations (SD) under each mulching rate. Within-a-row values followed by the same letter are not significantly different.

Runoff rate (mm h−1) Steady state runoff rate (mm h−1) Runoff coefficient (%) Steady state runoff coefficient (%) −1

Sediment concentration (g L

)

Mean SD Mean SD Mean SD Mean SD Mean SD

MR0

MR1

MR5

MR10

MR15

Kruskal–Wallis. p

17.77b 11.45 25.54d 0.97 27.34b 17.61 43.01d 1.49 4.35b 2.27

13.65b 9.99 24.37c 0.90 20.99b 15.36 37.49d 1.38 3.46b 1.9

5.56a 4.18 10.16b 1.45 8.55a 6.43 15.63c 2.22 0.94a 0.53

0.94a 1.08 2.49a 0.26 1.45a 1.66 3.83b 0.40 0.31a 0.16

0.63a 0.51 1.09a 0.41 0.97a 0.78 1.68a 0.64 0.1a 0.09

0.0000 0.0001 0.0000 0.0002 0.0000

84

A. Jordán et al. / Catena 81 (2010) 77–85

Table 4 R-Spearman rank correlation coefficients for mulching rate and different studied soil properties.

Organic matter content Bulk density Porosity CND Wilting point Field capacity Saturation Saturated conductivity

R-Spearman

p-level

0.94 − 0.90 0.88 0.81 0.79 0.92 0.93 0.91

0.000000 0.000000 0.000000 0.000001 0.000003 0.000000 0.000000 0.000000

rates show that relatively high sediment concentration is recorded at the beginning of each experiment during the first 10 min of simulated rainfall, especially for control (MR0) and low mulching rates (MR1). Thereafter, the erosive response quickly decreases with time after prolonged storms. Of course this behaviour is related to the changes in sediment availability along the duration of experiments. As the simulations progress, the soil detachment diminishes due to the exhaustion of available erodible particles and to the protective effect against the rain splash of the thin laminar flow of runoff. These results suggest that the erosive consequences of intermediate intensity 5-years-recurrent storms in the studied area could be strongly reduced by using just 5 Mg ha−1 year−1 mulching rates.

5. Conclusions A 3-year experiment with five different mulching rates demonstrated that application of straw mulching to cultivated soils under semi-arid conditions contributed to a general improvement of soil physical and chemical characteristics and reduced runoff and erosional response to rainfall. This is especially important under semi-arid conditions, where soil organic matter content in farm areas may be rather low. • Increasing mulch application rates contributed to increase soil porosity, stability of aggregates, and organic matter content, and decrease bulk density. • Wilting point, field capacity and saturation water were increased after 10 Mg ha−1 year−1 straw mulch application. As a consequence, available water capacity was slightly increased after 10 Mg ha−1 year−1 treatments, and no benefit was observed beyond this rate. • Runoff rates at a simulated rainfall intensity of 65 mm h−1 were greatly reduced with just 5 Mg ha−1 year−1 straw mulch; rainfall simulation under higher mulching rates produced a negligible runoff flow. • Soil loss was also reduced after mulch application. Mulching rates above 5 Mg ha−1 year−1 decreased soil losses to values below g L−1 after simulated rainfall.

Acknowledgements The authors are grateful to V. Espárrago, farm owner, for his assistance during the field work and management of the experimental farm in Jerez, and students A. Roldán and M.J. Blanco, for their field work support. J.L. Lozano and E. Pérez (technical staff, Dep. of Crystallography, Mineralogy and Agricultural Chemistry, University of Sevilla), for collaboration in processing soil samples and helping with some of the laboratory analysis. Dr. C. Bing and two anonymous reviewers contributed to improve the original manuscript with their valuable comments and suggestions. Dr. B. Diekkrüger (University of Bonn) also made interesting suggestions to the original manuscript.

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