Use of barley straw residues to avoid high erosion and runoff rates on persimmon plantations in Eastern Spain under low frequency-high magnitude simulated rainfall events

Document downloaded from: This paper must be cited as: The final publication is available at Copyright Additional Information http://dx.doi.org/10.1071/SR15092 http://hdl.handle.net/10251/77484 CSIRO Publishing Cerdà, A.; González-Pelayo, Ó.; Giménez Morera, A.; Jordán, A.; Pereira, P.; Novara, A.; Brevik, EC.... (2016). Use of barley straw residues to avoid high erosion and runoff rates on persimmon plantations in Eastern Spain under low frequency-high magnitude simulated rainfall events. Soil Research. 54(2):154-165. doi:10.1071/SR15092. The use of barley straw residues to avoid high erosion and 1 runoff rates on persimmon plantations in Eastern Spain under low frequency – high magnitude simulated rainfall events Artemi Cerdà (1) Óscar González-Pelayo (1), Antonio Giménez-Morera (2), Antonio Jordán (3), Paulo Pereira (4), Agata Novara (5), Eric C. Brevik (6), Massimo Prosdocimi (7), Majid Mahmoodabadi (8), Saskia Keesstra (9), Fuensanta García Orenes (10), Coen Ritsema (9) (1) Soil Erosion and Degradation Research Group, Department of Geography, University of Valencia, Valencia, Spain. oscar.gonzalez-pelay[email protected] and [email protected] / www.soilerosion.eu (2) Departamento de Economía y Ciencias Sociales, Escuela politécnica superior de Alcoy, Universidad Politécnica de Valencia, Paseo del Viaducto, 1 03801 Alcoy, Alicante, Spain. [email protected] (3) MED_Soil Research Group. Dep. of Crystallography, Mineralogy and Agricultural Chemistry, University of Seville, Spain. [email protected] (4) Department of Environmental Policy, Mykolas Romeris University, Ateities g. 20, LT-08303 Vilnius, Lithuania.pau[email protected] (5) Dipartimento dei Sistemi Agro-ambientali, University of Palermo, viale delle scienze –Italy, [email protected] (6) Department of Natural Sciences, Dickinson State University, Dickinson, ND, USA [email protected] (7) Department of Land, Environment, Agriculture and Forestry, University of Padova, Agripolis, Viale dell'Università 16, 35020 Legnaro (PD), Italy. [email protected] Cerd, Artemi, Óscar González-Pelayo, Antonio Gimnez-Morera, Antonio Jordán, Paulo Pereira, Agata Novara, Eric C. Brevik, Massimo Prosdocimi, Majid Mahmoodabadi, Saskia Keesstra, Fuensanta García Orenes, and Coen Ritsema. The use of barley straw residues to avoid high erosion and runoff rates on persimmon plantations in Eastern Spain under low frequency – high magnitude simulated rainfall events. Soil Research. in press. (8) Dep. of Soil Sci. Agriculture Faculty, Shahid Bahonar University of Kerman, P. O. Box. 76169133, Kerman, Iran. mahmo[email protected] (9) Soil Physics and Land Management Group, Wageningen University, 27 Droevendaalsesteeg 4, 6708PB Wageningen, The Netherlands [email protected] and coen.ritse[email protected] (10) Environmental Soil Science Group. Department of Agrochemistry and Environment. Miguel Hernández University, Avda. de la Universidad s/n, Elche, Alicante, Spain, fuensanta.g[email protected] Abstract Soil and water losses due to agricultural mismanagement are high and non-sustainable in many orchards. An experiment was setup using rainfall simulation experiments at 78 mm h-1 over one hour on 20 paired plots of 2 m2 (bare and straw covered) in new persimmon plantations in Eastern Spain. The effects of a straw cover on the control of soil and water losses was assessed. An addition of 60% straw cover (75 g m-2) resulted in delayed ponding and runoff generation and as a consequence reduced water losses from 60 to 13% of the total rainfall. The straw cover reduced raindrop impact and as a consequence sediment detachment from 1,014 to 47 g per plot in one hour. The erosion rate was reduced from 5.1 to 0.2 Mg ha-1 h-1. The straw mulch was found to be extremely efficient in reducing soil erosion rates. Keywords: persimmon plantations, management, erosion, hydrology, rainfall simulation. Introduction Soil erosion is widely known to be one of the triggering factors of land degradation and desertification worldwide (Bai et al., 2013; Izzo et al., 2013; Wang et al., 2013; Jafari and Bakhshandehmehr, 2013; Zhao et al., 2013; Ola et al., 2015; Yan et al., 2015). High and non-sustainable erosion rates are due to human mismanagement of soils and their vegetation cover due to grazing (Cerdà and Lavee, 1999; Mekuria and Aynekulu, 2013; Angassa, 2014), forest fires (González-Pelayo et al., 2010), mining (Martín-Moreno et al., 2015) and agriculture (Brevik, 2009; Cerdà et al., 2009a; 2009c; Leh et al., 2013; Lieskovský and Kenderessy, 2014; Yuan et al., 2015). Agriculture causes higher sediment yields from the continents than any other single source due to ploughing, removal of the original vegetation, soil disturbance and the use of pesticides and herbicides that reduce biological activity in soils, lower overall vegetation cover, the lack of terraces in sloping terrain, depletion of organic matter, and soil compaction and sealing (Cerdà et al., 2009c; Novara et al., 2011; Laudicina et al., 2012). This relationship is now well known. Civilizations have failed throughout human history due to erosion (Brevik and Hartemink, 2010), and erosion continues to negatively affect civilizations in all regions of the world (Costa, 1975; Pimentel et al., 1987; O’hara et al., 1993; Shi and Shao, 2000; Cerdà et al., 2007). Orchards, more than cereal and vegetable production, are sources of sediments from agricultural land due to the lack of vegetation cover over large areas of the field (Dabasish-Saha et al., 2014). The compaction of soils as a consequence of heavy machinery passes, soil degradation due to the weakening of soil structure, and related organic matter depletion also affects sediment production (Fialho and Zinn, 2014; Parras-Alcántara et al., 2014). Soil erosion has been found to be high in olive (Olea europaea) orchards (Gómez et al., 2003; VanWalleghem et al., 2010), new citrus plantations (Cerdà et al., 2009b; Li et al., 2015), avocado (Persea Americana) orchards (Atucha et al., 2013) and vineyards (Novara et al., 2013; Costantini et al., 2015; Tarolli et al., 2015). Other types of orchards such as almonds (Prunus dulcis) (Faulkner et al., 1995) and apricots (Prunus armeniaca) (Abrisqueta et al., 2007) have also shown high erosion rates, but there is little information on soil erosion rates in orchards compared to other agricultural settings, and no research has been reported for pears (Pyrus sp.), apples (Malus pumila), cherries (Prunus sp.) or persimmons (Dyospirus sp.), even though fruit production is growing and the land area covered by various fruit and citrus orchards and vineyards is heavily managed with machinery and pesticides leading to soil damage and degradation. Annual world persimmon production in 2013 was 4.6 million tonnes with China producing about 78% of the total world yield (FAO, 2015). Korea and Japan are the second and the third leading producers respectively with 0.35 and 0.21 million tonnes produced in 2013, and combined the three Asian countries represented more than 90% of 2013 world production (FAO, 2015). Spain produces 0.1 million tonnes annually but there has been a sudden increase in the production of and land used for persimmon production, making Spain an emerging producer and exporter of persimmons as a new product for the European markets. There has been a quick land use change from citrus orchards to persimmon orchards in Eastern Spain, which means much less vegetation cover as the latter is a deciduous tree that leaves the soil bare for 4 months of the year (Figure 1). The persimmon expansion in Eastern Spain is due to the high prices and the new markets that have developed in Europe, Brazil and the Arabic countries. The new chemically managed and highly mechanized plantations in Eastern Spain are using high doses of herbicides and the lack of vegetation is triggering high erosion rates due to the bare soils. Previous studies, in citrus orchards, have discussed how mulching reduced runoff and erosion by buffering the raindrop impact and improving soil physical conditions (Liu et al., 2014). Others such as Wakindiki and Danga (2011) described its effects on nutrient accumulation in soils, but few studies have addressed effects of extreme rainfall events on soil erosion on new persimmon plantations in semiarid conditions. This paper aims to assess soil erosion rates on these new persimmon plantations and to test the efficiency of straw cover to reduce soil losses. Forty rainfall simulation experiments were carried out in 20 paired plots to determine the effect of a 60% straw cover on soil erosion and runoff generation on agricultural soils that were originally bare. Materials and methods The research was run in the western Mediterranean basin, within the Canyoles River watershed in the La Costera district of the Valencia region (Eastern Spain), where new persimmon plantations are widely replacing citrus production in drip-irrigation and flood-irrigated crop systems. Parent materials in the area belong to Cretaceous limestones and Tertiary deposits that develop Typic Xerothent (Soil Survey Staff, 2014) soils. Low levels of soil organic matter (SOM) are found (< 2%) in agricultural land in Eastern Spain and the Canyoles River watershed due to the millennia old agricultural use and soil disturbance by fire, grazing and ploughing, basic pH (8) and loamy soil textures that characterize the soils of the area. The climate is typically Mediterranean with 3-5 months of summer drought (June-September). Mean annual rainfall at the study site is 590 mm and there are 41 mean annual days of rain. Rainfall is distributed amongst autumn, winter and spring, with maximum peak rain intensities during the autumn season. The mean annual temperature is 14.2ºC while the hottest month (August) has average temperatures of 23ºC. Extreme storm events with return periods of 50 years are found in this area, which is 60 Km from the Mediterranean Sea. Examples of extreme events include more than 600 mm of rainfall in two days in 1982 in the Màssis del Caroig and 800 mm in slightly more than 24 hours in Gandia in 1987. Recurrent rainfall events of more than 100 mm day-1 make extreme rainfall events a key factor in local soil erosion. A 15 year old plantation of persimmon (Dyospirus lotus var. Rojo brillante) was selected in Eastern Spain (Canals Municipality, La Costera District) to measure soil losses on no-till bare management (herbicide treatments, called Bare) and on barley straw covered plots (called Straw) (Figure 2). Persimmon trees were positioned in parallel rows with a slope angle and length of 2% and 40 meters, respectively. The straw cover was applied 3 days before the rainfall experiments at doses that covered on average 60% of the soil surface using 75 g of straw per m2. Cover in the no-till bare treatments averaged 3%. Forty rainfall simulations (RS) conducted at 78 mm h-1 rainfall intensity for one hour were carried out on paired rectangular plots that were 2 m2 (1 m wide x 2 m long); the paired plots were bare (20 RS) and covered with straw (20 RS). The measurements were carried out during July 2014 under very dry soil moisture contents ranging from 4.6 to 7.9% for the whole month. These measurements are representative of interill or pedon scale soil erosion processes since RS were placed in the row spaces between trees. Detailed information about the rainfall simulator set and on the distribution of rainfall parameters can be found in Cerdà and Doerr (2010) and Cerdà and Jurgensen (2011); the rainfall simulator is placed at 2 meters height. It uses three nozzles (Hardi-1553-12) with a constant rainfall intensity using deionized water. Overland flow from the plot area was measured at 1-min intervals at the plot outlet. Every tenth 1-min runoff sample was collected for laboratory analysis in order to determine sediment concentration. Runoff rates and sediment concentration were used to calculate the sediment yield, total runoff, runoff coefficient, and erosion rates. Parameters such as time to ponding (Tp, determines when the soil is saturated), time to runoff (Tr, is the time when runoff is initiated), time to runoff - time to ponding (Tp-Tr), time to runoff outlet (Tro, is the time of runoff initiation at the plot collector), and time to runoff outlet - time to runoff (Tro-Tr) were also analysed through statistical tests as described below. Vegetation cover was determined with 100 pins measurement in each 2 m2 plot, and soil moisture was measured by means of the desiccation of soil samples collected before the simulated rainfall experiment drying at 105ºC for 24 hours. Sediment concentration in the runoff was calculated after the desiccation of the samples in the laboratory. Normality of the data was tested through the Shapiro-Wilk test. The statistical differences between the mean values of some parameters for the Bare and Straw treatments was tested with the T-test (Tp, Tr, Tp-Tr, Tro, Tro-Tr, runoff coefficient, total runoff, sediment concentration, sediment yield, and soil erosion). Some other parameters did not meet the assumption for normality (Tp bare, Tr bare, sediment concentration bare, sediment yield bare and erosion bare), and data square-root and logarithmic transformations were carried out to achieve normality before carrying out the T-test. Linear correlation coefficients (R2) with polynomial, exponential and linear fitting were also calculated to assess the relationship between RS (Tp, Tr, Tp-Tr) and erosion parameters (total runoff (l), sediment concentration (g l-1), sediment yield (g) and soil erosion (Mg ha-1 h-1). Statistical analyses were computed with the SPSS 22.0 software package (IBM Corporation, Armonk, NY, USA). Results The soil moisture in the 0-2 cm depth interval previous to RS experiments was very low (< 5% in all plots) and very homogeneous as the experiments were carried out in an area that is not irrigated and during the Mediterranean summer drought. There was no rain in the 45 days prior to the experiments. Measurements of the vegetation and litter (straw) cover (Table 1) showed that plants covered 2.5% of the bare plots, while the straw plots had 61.6% cover on average (Table 1; p-value<0.05). The bare (control) plots had a vegetation cover ranging from 0 to 6% and the straw plots ranged from 48 to 90% cover. The increase in cover reduced the raindrop impact and as a consequence the Tp increased from 64 (ranging from 33 to 96 s) to 309 seconds (from 201 to 495 s) in bare and straw plots, respectively (Table 1). Microtopography and soil roughness delayed runoff generation (Tr), which was reached after 262 seconds on the bare soils but took 815 seconds on the straw covered soils (Table 1; p-value<0.05). The minimum and maximum Tr values were 234 and 342 s for bare plots and 702 and 1,005 s for straw covered plots (Table 1; p value<0.05). The differences between Tp and Tr show the time that is needed for runoff to be initiated and is much more delayed in the straw covered soils (506 seconds) than on the bare soils (198 s) (Table 1; p-value<0.05). The time to runoff outlet (Tro) was 1,222 s in the straw mulch covered plots and 419 s in the bare ones (Table 1; p-value<0.05). Tro-Tr shows the velocity of the runoff, and this is delayed in the soil covered with straw (406 s) and much faster in the bare soils (156 s) (Table 1; p-value<0.05). Table 2 shows the runoff rates, sediment yield and soil erosion. The runoff coefficient decreased from 60% in the bare control plots to 29% in the straw plots. Runoff in the bare plots ranged from 50 to 72%, meanwhile in the straw plots Rc ranged from 15 to 45% of the total rainfall. The bare plots also contributed runoff with much higher sediment concentration (10.9 g l-1) in comparison to the straw covered plots (1 g l-1). The amount of runoff generated in the bare plots had an average value of 93 litres (ranging from 79 to 113 l), while the amount of runoff was much less in the straw plots (46 l, ranging from 24 to 71 l). Regression analyses between hydrological parameters (Figure 3) shows how Tr is dependent on the Tp, with the relationship being stronger in the straw plots than in the bare ones (R2 of 0.34 vs 0.06, respectively). In fact, the relationship of the delay time between ponding and runoff (Tp-Tr) and Tr is stronger in the bare plots than in the straw ones (R2 of 0.63 vs 0.20, respectively) and weaker between Tp-Tr and Tp (R2 of 0.24 vs 0.36, respectively). In the bare soil plots the total sediment yield was more than 1 Kg while it was only 47 g in the straw covered plots. The values ranged from 546 to 1,971 g in the bare plots and 21 to 80 g in the straw plots. This resulted in high erosion rates on the bare plots (5.1 Mg ha-1 h-1) in comparison to the straw plots events as a consequence of raindrop impact and surface wash. These high erosion rates exceed soil formation rates and are due to the lack of vegetation cover as a consequence of the use of herbicides in the soils. Straw mulch cover reduced soil losses from 5.1 to 0.2 Mg ha-1 h-1 immediately after straw application. The use of straw mulches is very efficient at reducing soil and water losses in Mediterranean orchards as they suffer from a low vegetation cover and climatic conditions that induce very intense rainfall events, and as a consequence high erosion rates, which must be controlled in agricultural land to achieve sustainable production. 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Persimmon orchards in December (left) and February (right). Winter is when the soil is bare of vegetation and leaves and when the soil erosion risk is higher. Figure 2. Plots. To the left the control (bare) plot, to the right the straw-covered plot. Figure 3. Relationship between time to runoff (Tr) and time to ponding (Tp), and delay time between ponding and runoff (Tr-Tp) and time to ponding (Tp), and with time to runoff (Tr), for all the datasets. N=40. Bare means no-till bare (herbicide treatments), and Straw means barley straw covered plots. Figure 4. Relationship between sediment concentration (g l-1) and sediment yield (g), soil erosion (Mg ha-1 h-1) and runoff coefficient (%), and sediment concentration (g l-1) and runoff coefficient (%) for all the rainfall simulation datasets. N=40. Bare means no-till bare (herbicide treatments), and Straw means barley straw covered plots. Table 1. Values by plot, average, maximum and minimum values, and standard deviation of the cover (plants and straw, %), Time to ponding (Tp), Time to runoff (Tr), Tp-Tr, Time to runoff outlet (Tro) and TrTro in seconds. Bare means no-till bare (herbicide treatments), and Straw means barley straw covered plots. Different letter for each parameter in paired rows (bare and straw) means statistical significant differences according to T-test. P. value <0.05 level. Plots Cover (%) Tp (s) Tr (s) Tp-Tr Tro TroTr N=20 Bare Straw Bare Straw Bare Straw Bare Straw Bare Straw Bare Straw 1 1 65 85 375 234 972 149 597 343 1235 109 263 2 2 58 94 485 342 869 248 384 502 1258 160 389 3 3 78 85 485 234 845 149 360 356 1269 122 424 4 0 56 96 495 238 1005 142 510 365 1325 127 320 5 2 54 75 358 256 865 181 507 365 1145 109 280 6 1 52 82 205 245 849 163 644 345 1203 100 354 7 5 53 74 236 296 789 222 553 409 1421 113 632 8 2 59 65 245 258 745 193 500 402 1025 144 280 9 2 57 45 259 245 856 200 597 436 1254 191 398 10 0 52 48 268 275 851 227 583 495 1325 220 474 11 2 59 49 245 265 725 216 480 456 1259 191 534 12 2 65 45 275 245 854 200 579 425 1268 180 414 13 4 75 60 245 265 789 205 544 401 1302 136 513 14 2 48 90 265 284 702 194 437 436 1020 152 318 15 1 66 75 294 295 768 220 474 441 1143 146 375 16 2 45 33 201 247 828 214 627 501 1074 254 246 17 5 59 39 261 256 702 217 441 410 1194 154 492 18 6 55 48 336 235 735 187 399 434 1239 199 504 19 2 85 45 327 285 795 240 468 434 1305 149 510 20 5 90 47 321 245 762 198 441 415 1167 170 405 Average 2.5 61.6 64.0 309.1 262.3 815.3 198.3 506.3 418.6 1221.6 156.3 406.3 Max 6 90 96 495 342 1005 248 644 502 1421 254 632 Min 0 45 33 201 234 702 142 360 343 1020 100 246 Std 1.7 12.0 20.3 90.1 27.3 81.0 29.7 82.5 48.2 102.7 40.3 104.8 Table 2. Values by plot, average, maximum and minimum values, and standard deviation of the runoff coefficient (Rc, %), sediment concentration (Sc, g l-1), total runoff (Total R, l), sediment yield (Sy, g), soil erosion (Se, g m2 h-1) and soil erosion (Se, Mg ha-1). Bare means no-till bare (herbicide treatments), and Straw means barley straw covered plots. Different letter for each parameter in paired rows (bare and straw) means statistical significant differences according to Ttest. P. value <0.05 level. Table 3. Statistical analyses. Mean (standard deviation) and range of datasets for the time to ponding (Tp), time to runoff (Tr), time to runoff - time to ponding (Tp-Tr), time to runoff outlet (Tro), and time to runoff - time to runoff outlet (Tr-Tro), total runoff (l), sediment concentration (g l-1), sediment yield (g), and erosion (Mg ha-1 h-1) for the rainfall simulation plots (n=40) over Bare (no-till bare) and Straw (straw mulch). Values for all water loss parameters are in seconds. For the normality assumption, the Shapiro-Wilk (S-W, p) tests were applied at the 0.05 significance level and non-normal parameters were transformed to meet normality. The parametric T-test was applied to check for differences between treatments (in bold). Treatment N Mean (SD) Range K-S S-W T-test Tp (s) Bare 20 64 (12) 63 0.012 0.063 0.001 Straw 20 309 (20) 294 0.04 0.007 Tr (s) Bare 20 262 (27) 108 0.18 0.009 0.001 Straw 20 815 (81) 303 0.2 0.168 Tp-Tr (s) Bare 20 198 (30) 106 0.2 0.387 0.001 Straw 20 506 (82) 284 0.2 0.744 Tro (s) Bare 20 419 (48) 159 0.2 0.247 0.001 Straw 20 1222 (103) 401 0.2 0.415 Tr-Tro (s) Bare 20 156 (40) 154 0.2 0.407 0.001 Straw 20 406 (105) 386 0.2 0.629 Runoff coef (%) Bare 20 60 (6) 22 0.085 0.199 0.001 Straw 20 29 (6) 30 0.088 0.105 Total runoff (l) Bare 20 93 (8) 34 0.084 0.198 0.001 Straw 20 45 (10) 47 0.087 0.105 Sed concentration (g l-1) Bare 20 11 (4) 14 0 0.001 0.001 Straw 20 1 (0,2) 0,6 0.003 0.011 Sed yield (g) Bare 20 1015 (345) 1425 0.001 0.001 0.001 Straw 20 47 (13) 59 0.2 0.315 Erosion (Mg ha-1 h-1) Bare 20 5 (1.7) 7 0.001 0.001 0.001 Straw 20 0.24 (0.06) 0.3 0.2 0.275 All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.