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Revised Soil Erodibility K-Factor for Soils in the Czech Republic

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Revised Soil Erodibility K-Factor for Soils in the Czech Republic Soil & Water Res., 2, 2007 (1): 1–9 Revised Soil Erodibility K-factor for Soils in the Czech Republic JAN VOPRAVIL, MILOSLAV JANEČEK and MARTIN TIPPL Research Institute for Soil and Water Conservation, Prague, Czech Republic Abstract: In the territory of the Czech Republic there are more than 50% of agricultural soils exposed to water erosion; it is a very urgent problem both at present and for the future. It must be solved now when there is still something to be protected. It is rather complicated to describe the soil properties in terms of soil susceptibility to water erosion because it is a complex relation in which many factors participate. For the complex evaluation of all main factors participating in erosion origination it is possible to apply the Universal Soil Loss Equation (USLE). It consists of six factors interacting with each other and participating in the origination of soil erosion. One of these factors is the soil erodibility factor (K-factor), the revision of which for soil conditions of the CR is the subject of this study. In total ca. 5000 soil pits from the whole territory of the country were processed and evaluated in detail. The main results of this study are K-factor values (means and variances) for the soil types, subtypes and varieties (represented in the database) according to the Taxonomic Classification System of Soils of the Czech Republic. Keywords: water erosion; soil erodibility; soil structure; permeability; soil texture; organic matter In the Czech Republic there is more than 50% so called Universal Soil Loss Equation (hereinaf- of agricultural land exposed to water erosion ter USLE), can be used. It consists of six factors, (JANEČEK et al. 2002). It is a very urgent problem taking part, through their interactions, in the at present and mainly for the future. The problem origination of soil erosion. The soil erodibility must be solved now when there is still something factor (K-factor) is one of them and its determi- to protect. It is rather complicated to describe nation for soil conditions of the CR is the subject soil properties in relation to soil susceptibility to of this paper. water erosion because the relation is a complex one and because of many factors participating METHOD in it. For comprehensive evaluation of all main factors participating in erosion origination, the The procedure for K-factor determination ac- most frequently used and best-known equation, cording to WISCHMEIER and SMITH (1978) was that according to WISCHMEIER and SMITH (1978), used. Supported by the Ministry of Agriculture of the Czech Republic, Projects No. QF 3098, No. QF 3094 and Re- search Plan No. 0002704901. 1 Soil & Water Res., 2, 2007 (1): 1–9 The main background data for K-factor deter- Basic equation for the evaluation of K-factor mination were obtained by the evaluation of the (WISCHMEIER & SMITH 1978) computer database of special soil pits (Sp pits) and a part of selective soil pits (Se pits) from 100K = 2.1M1.1410–4(12–a) + 3.25(b – 2) + 2.5(c – 3) the Comprehensive Survey of Agricultural Soils of Czechoslovakia. This database (NOVÁK et al. where: 2005) currently contains ca. 1200 Sp pits and ca. M – expresses the effect of topsoil texture and is calcu- × 3700 Se pits. The database of Sp pits is complete lated as (% silt + % silty sand) (100% – % clay) and covers the whole territory of the country. The a – % of topsoil organic matter (humus) database of Se pits presently contains soil pits b – class of topsoil structure from the districts Náchod, Pardubice, Rychnov c – class of soil profile permeability nad Kněžnou, Ústí nad Orlicí, Blansko, Brno-Town and Brno-Countryside, Zlín, Hodonín, Jihlava Evaluation of topsoil textural analysis – M and České Budějovice (part). The latter values were used to provide supplementary information To evaluate the soil texture, the percentage of for the statistical processing of K-factor values. clay, silt and silty sand particles were used. In The database consists of two parts. The first textural analyses performed in the past in the CR, part contains general information on the soil pit the percentage of clay was defined as the content and its location, e.g. geographic coordinates, data of grains < 0.001 mm. In the methodology for on soil erosion, data on groundwater table, land K-factor evaluation, however, the content of clay is use – crop, date of sampling, natural conditions delimited by the grain size < 0.002 mm. The limits of of the site (precipitation, temperature, altitude, the grain size of silt and silty sand (0.002–0.1 mm) slope …) and other climatic and agricultural data. are also different from the original limits used in All these items comprise both the original values Czech analyses (0.001–0.01 mm for medium and (ca. 40 years old) and the newly acquired values fine silt, 0.01–0.05 mm for coarse silt, 0.05 to from recent field samplings. The second part 0.25 mm for fine sand, 0.25–2.0 mm for medium of the database contains complete information sand). Therefore, it was necessary to convert old on individual genetic horizons of each profile textural categories into the new ones. The contents (in fact, it is an ancillary database to the first of the new categories were evaluated graphically part), mainly the results of chemical and physi- by the computer program MS EXCEL from the cal analyses and other, mainly quantitative data grain size curve to the nearest 0.5%. (soil structure, living organisms, root systems, new formations, compaction, profile gleyization, Percentage of topsoil organic matter colours of horizons and their depths, horizon (humus content) – a classification according to several classification systems such as FAO, etc.). Like the first part, The percentage of humus content computed the second part of the database contains both the by multiplication with a constant from the total original values and the newly acquired ones. The oxidisable carbon content (Cox) is a good enough whole database is administered by the database to estimate the parameter a for Czech soils. Cox program MS Access and its statistical outputs are was multiplied by the value 1.724, which is Welte’s processed by the UNISTAT program. coefficient based on the assumption of 58% carbon content in humus (VALLA et al. 2000). Method of evaluation The percentage of humus content is a standard part of the database of Sp pits. For Se pits, the For the adequate determination of K-factor val- percentage of humus content was computed from ues from the basic equation according to WIS- Cox, using the Welte’s coefficient. CHMEIER and SMITH (1978), it was necessary to define for each soil pit the limits of topsoil texture Class of topsoil structure – b categories, the percentage of organic matter in topsoil (percentage of humus content), the class The stability of soil structure is currently an of topsoil structure and the class of soil profile urgent problem mainly due to the intensive agricul- permeability. ture, its disturbance being directly connected with 2 Soil & Water Res., 2, 2007 (1): 1–9 Table 1. Classes of topsoil structure Table 3. Parent rocks classified as light Class of topsoil structure Topsoil structure granites (mainly coarse-grained) 1 granular Igneous rocks quartz porphyries 2 crumb rhyolites Metamorphic rocks gneisses (mainly orthogneisses) 3 lumpy (terrace, lake, sea, aeolian) sands 4 laminar, compact sandstones Sediments arkoses soil compaction. Heavy-duty machines, producing breccias high specific pressures, destroy the soil structure conglomerates after repeated wheel traffic, increase the bulk den- sity of soil, decrease its porosity and permeability, and reduce the life in the soil. Heavier-textured For the other types of soil structure, not ap- soils are more susceptible to compaction. The pearing in Table 1, or for soils without recog- consequences are reduced groundwater recharge, nisable structure (structureless horizons), the acceleration of surface runoff and water erosion, soil type and geology base were also considered deterioration of conditions for plant rooting and (Table 2 and 3). Light soils (p – sandy, hp – loam- reduction of soil productivity (NOVÁK 2000). sandy) were placed into class 1, medium soils (ph For the calculation of K-factor according to WIS- – sandy-loam, h – loamy) into class 3, medium CHMEIER and SMITH (1978), four classes of topsoil soils on light substrates into class 1 and heavy structure are used (Table 1). soils (jh – clay-loamy, jv, j – clay) into class 4. This The type of soil structure is described by means classification was done on the basis of common of a code in the database of Sp pits. If the struc- knowledge of the formation of various types of ture type in the database was identical to that soil structure in relation to soil type and soil- in Table 1, the corresponding class number was forming substrate. attributed to it for the purpose of the K-factor calculation formula. Class of soil profile permeability – c Table 2. Classification of the other types of soil structure To estimate the infiltration capacity and per- in topsoil meability of soils, the following information was Class of topsoil used: Topsoil texture Note structure – The categorisation of Main Soil Units (MSU) into Light soils: p/hp 1 Hydrological Groups (KURÁŽ & VÁŠKA 1998). All agricultural soils of the Czech Republic are 3 grouped into 78 MSU, according to soil clas- Medium soils: ph/h on light parent 1 sification unit (soil type, subtype, variety...), rocks (Table 3) texture composition, water and air regime, parent Heavy soils: jh/jv/j 4 material, skeleton content and the depth of soil Table 4. The categories of infiltration capacity and soil profile permeability used for K-factor determination Class Main soil units 1 04, 05, 17, 21, 31, 32, 37, 40, 55 2 13, 16, 18, 22, 27, 30, 34, 38, 41 3 01, 02, 08, 09, 10, 12, 14, 15, 23, 26, 28, 29, 35, 36, 51, 56 4 03, 06, 11, 19, 24, 25, 33, 42, 43, 44, 45, 46, 48, 50, 52, 58, 60 5 07, 20, 39, 47, 49, 57, 59, 62, 64, 65, 75, 77, 78 6 53, 54, 61, 63, 66, 67, 68, 69, 70, 71, 72, 73, 74, 76 3 Soil & Water Res., 2, 2007 (1): 1–9 profile.
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