Suk-Young Hong, Byung-Keun Hyun, Yeon-Kyu Sonn, Sang-Ho Jeon, Myung-Suk Kong, Ye-Jin Lee, Chang-Hoon Lee, Seong-Jin Park, and Goo-Bok Jung
Soil and Fertilizer Division, Department of Agricultural Environment, National Institute of Agricultural Sciences, Rural Development Administration(RDA), Wanju 55365, S. Korea
Soil survey and information is of great importance for the use and conservation of soil resources that are essential for human welfare and ecosystem sustainability. This paper introduces soil survey and soil inventory of Korea focusing on national soil database, soil and environment information system, and use of soil database for natural resources management focusing on agricultural fields. Various scales of soil maps and soil testing data were established through a series of intensive National Soil Survey Projects and Soil Testing Projects conducted by Rural Development Administration (RDA) since early 1960s. An internet-based information system for soil and environment (http://soil.rda.go.kr) was developed on the basis of ‘National Soil Survey Projects’ and ‘Agro-environmental Change Monitoring Project’, which monitors spatial and temporal changes of agricultural environment. Soils data has a great potential of further application in estimation of soil carbon storage, water capacity, depth-wise soil property mapping, and change of soil properties. Digital mapping of soil and environment using state-of-the-art and emerging technologies with a pedometrics concept will lead to future direction.
Detailed knowledge on soil characteristics is of great importance for the use and conservation of soil resources that are essential for human welfare and ecosystem sustainability. The first modern soil survey in Korea was initiated in 1964, when the Korean Government and UNDP/FAO jointly established Korea Soil Survey Organization, Plant Environment Research Institute (recently National Institute of Agricultural Sciences, NAS) which belong to the Office of Rural Development (recently Rural Development Administration, RDA) in Suwon. Since then substantial progress of soil survey has been made to understand spatial soil distribution, to recommend fertilizer prescription and land suitability for crop cultivation in agricultural fields, as well as to manage agricultural soils (RDA, 2005).
All the soil maps surveyed and made in RDA since 1960’s were computerized to make digitized soil maps (NIAST, RDA, 2001). An internet-based soil and environment information system was developed based on the results of all the Soil Survey Projects led by RDA for approximately 40 years for managing soil resources rationally and for providing soil information to the public (NIAST, RDA, 2008).
Many countries established their own soil information system including European Union (http://eusoils.jrc.it/), Canada (http://sis.agr.gc.ca/cansis/), USA (http://soils.usda.gov/technical /nasis/), Australia (http://www.asris.csiro.au/) by user needs for soil resource information.
This paper introduces soil survey and soil inventory of Korea focusing on national soil database, soil and environment information system (http://soil.rda.go.kr), and use of soil database for natural resources management focusing on agricultural fields.
SOIL SURVEY and SOILS DATABASE in KOREA
The soil survey was initiated by RDA, UN, and FAO with a reconnaissance survey, making use of aerial photographs purchased from USA funded by Korea Soil Survey Organization between 1964 and 1967. As a result, 1:250,000 and 1:50,000 scales of soil maps of Korea were published. Thereafter, RDA alone carried out the detailed soil survey by adoption of the Soil Taxonomy of United States Department of Agriculture (USDA) between 1968 and 1990. Now, detailed soil maps (1:25,000) are available for entire country in both hard copies and digital format of soil map. Furthermore, highly detailed digital soil maps (1:5,000) surveyed from 1995 to 1999 for entire country were digitized from 1998 to 2005 and available through the web site (http://soil.rda.go.kr) for the public.
Table 1 summarizes soil survey methods at each scale and its application. All the soil maps were digitized and made in a GIS file format. Based on the National Soil Survey Projects, two different kinds of soil databases were constructed that are the concrete basis of the soil information system of Korea (Table 2). One is spatial database of computerized soil map at a variety of scales (1:250,000, 1:50,000, 1:25,000, and 1:5,000) established between 1998 and 2005. The other is parcel-based soil fertility (chemical properties) database established using an oracle relational database management system through soil testing. It can contribute to make a recommendation for optimum plant growth via amount and type of fertilizer, the timing and location of fertilizer application. Furthermore, it can support proper and effective nutrient management for crops and environment.
Table 1. Soil survey methods at each spatial scale and its applications (NIAST, 2001)
Table 2. Characteristics of soil map and soil fertility database.
RDA is also carrying out the 'Agro-environmental Resources Monitoring Project' since 1999, which collects soil chemical properties and heavy metal concentration in agricultural soils including vulnerable agricultural soils in a regular basis at fixed sampling sites. Soils data from top soil and/or sub soil are collected in paddy fields, dry fields, plastic film houses, and orchards to analyze chemical properties including pH, organic matter, available phosphate, and exchangeable cations as chemical properties and arsenic, cadmium, chromium, copper, nickel, lead, and zinc as heavy metals. Soil samples for each cropland type are designed to collect countrywide every four year in turn in paddy fields, dry fields, plastic film houses, and orchards since 1999. The data collected from the project were accumulated as spatial data to grasp spatial and temporal change of soil properties over the country. And the data are also used for supporting policy decision of sustainable agriculture.
SOILS IN KOREA
When described using the Soil Taxonomy of the USDA, soils in Korea are classified into 7 Soil Orders which are then further divided into 17 Sub-Orders according to moisture regimes. Among those seven Soil Orders, Inceptisols, Ultisols, Entisols, and Alfisols are dominant. Entisols are the youngest soils, followed by Inceptisols. Alfisols and Ultisols are the older soils. The working unit of soil classification is Soil Series. So far 405 Soil Series have been identified in the country. Table 3 is summary of the areal extent of the different Soil Orders and the number of Soil Series within them. Table 3 clearly shows that the occurrence of younger soils (Entisols and Inceptisols) is overwhelming. This is a result of the influences of both Korea’s unique climate, with concentrated rainfalls in summer, and rugged topography as characterized by the wide occurrence of highly-sloped mountains. This strongly suggests that, if the soil resources are to be adequately conserved, serious attention must be paid to development of measures to minimize the soil erosion in hilly lands. Fig. 1 shows the distribution of soil properties in terms of soil classification, parent materials, soil texture, soil depth, drainage class, and gravel content of Korea.
Table 3. Soil orders, sub-orders, number of soil series and the areal extent of soil orders in Korea.
Fig. 1. Soil properties of Korea based on detailed soil map (1:25,000).
SOIL INFORMATION SYSTEM OF KOREA
RDA established a soil and environment information system (http://soil.rda.go.kr) of Korea based on highly detailed soil maps (1:5,000) and opened 'all about soils' information to the public through the web (Fig. 2). It is an internet-based system to show soil properties mainly about crop suitability and fertilizer recommend. Soil attributes showed graphically in the digital maps are 114 spatial layers which are crop suitability for 64 crops, soil texture (family), gravel content, drainage class, available soil depth, slope, topography, parent material, land use at the time of soil survey, land suitability group for paddy, upland, and orchard, as well as soil classification regimes, etc. as shown in Table 4. Each soil property can be provided in a form of map (Fig. 3), showing its spatial distribution with statistics such as sum and average of the attributes (Hong et al., 2009).
Fig. 2. Main page of ‘Soil and Environment Information System of Korea (http://soil.rda.go.kr)’ (left) and four major parts of the system including web-based GIS map service, fertilizer recommendation, and statistics.
Table 4. Soil attributes provided through the soil and environment information system.
Fig. 3. Morphological, physical, and chemical properties of Korean soils provided through soil information web-site
Soil and environment information system of Korea also provides a web-based fertilizer prescription program for extension people to recommend the amount (rate), type, and the timing of fertilizer application for optimum plant growth by diagnosis of soil nutrition in the crop land as shown in Fig. 4. A person in charge of soil testing and diagnosis at Agricultural Technical Center of each city or county and provincial Agricultural Research Center have his or her own ID and password to access the system to issue fertilizer recommendation for farmers, to manage the data and program functions of the system. Program provides fertilization standards of 133 crops to issue the fertilizer and management prescription, which is used for the certification of agricultural products and soil nutrient management. Soil test data are automatically uploaded to the oracle database located at NAS, RDA when one inputs the soils data and saves them for the program operation.
The statistics of soil attributes queried on the web can be calculated for representative areas in the form of pie charts, bar charts, and tables (Fig. 5). Soil information can be queried for statistics are all 94 attributes including soil morphological, physical, and chemical properties. And the system also provides general information on Korean soils.
Fig. 4. Web-based fertilizer recommendation system based on soil testing and the procedures
Fig. 5. Soil statistics in the form of pie charts and tables for soil texture (left) and soil organic matter (right).
USE OF SOIL INFORMATION
Soil information can be applied to map soil functional properties, soil carbon storage and available water capacity which are important for land management, plant production and ecosystem management. There is a need for accurate, up-to-date and spatially referenced soil information. This need has been asked by the modeling community, land users, and policy and decision makers. This need coincides with an enormous leap in technologies that allow accurate collecting and predicting soil properties (http://www.globalsoilmap.net). Accordingly, there is a global need for making a new digital soil map of the world using state-of-the-art and emerging technologies for soil mapping and predicting soil properties at fine resolution. This new global soil map will be supplemented by interpretation and functional options that aim to assist better decisions in a range of global issues like food production and hunger eradication, climate change, and environmental degradation (http://www.globalsoilmap.net).
Available water capacity
The knowledge on the spatial distribution of soil available water capacity at a regional or national extent is essential, as soil water capacity is a component of the water and energy balances in the terrestrial ecosystem. It controls the evapotranspiration rate, and has a major impact on climate. Hong et al.(2013) demonstrated a protocol for mapping soil available water capacity in South Korea at a fine scale using data available from surveys. The procedures combined digital soil mapping technology with the available soil map of 1:25,000.We used the modal profile data from the Taxonomical Classification of Korean Soils. The data consist of profile description along with physical and chemical analysis for the modal profiles of the 380 soil series. However not all soil samples have measured bulk density and water content at -10 and -1500 kPa. Thus they need to be predicted using pedotransfer functions. Furthermore, water content at -10 kPa was measured using ground samples. Thus a correction factor is derived to take into account the effect of bulk density. Results showed that Andisols has the highest mean water storage capacity, followed by Entisols and Inceptisols which have loamy texture. The lowest water retention is Entisols (mean of 149 mm) which are dominated by sandy materials. Profile available water capacity to a depth of 1mwas calculated and mapped for Korea (Fig. 6). The western part of the country shows higher available water capacity than the eastern part which is mountainous and has shallower soils. The highest water storage capacity soils are the Ultisols and Alfisols (mean of 206 and205 mm, respectively). Validation of the maps showed promising results. The map produced can be used as an indication of soil physical quality of Korean soils.
Fig. 6. Map of Korean soil profile available water capacity to 1 m (in mm).
Depth-wise soil carbon mapping
Hong et al.(2012) produced digital soil maps of soil organic carbon and clay content at different depths for Korean soils based on the GlobalSoilMap.net specification. A Korean soil database of 380 soil series was compiled, which includes chemical and physical properties such as organic carbon and clay content. We applied the equal-area spline depth functions for soil organic carbon and clay content. Derived mean values of organic carbon and clay content from the fitted spline at standard depths were mapped by corresponding soil series to produce raterized spatial and depth-wise soil property maps (Table 5 and Fig. 7). We also compared the results to recently collected soil samples to estimate the accuracy of the maps. Clay content showed better agreement compared to soil organic carbon content.
Table 5. Soil organic carbon and clay content distribution at different soil depths.
Fig. 7. Predicted soil profile of soil organic carbon (g/kg) and clay content in 5 profile layers.
Soil carbon storage
Soil carbon storage is an important property for land management, plant production and environment and ecosystem management. This paper applied the digital soil mapping concept for mapping soil carbon storage property using legacy soil data such as soil profile description and monitoring data in South Korea. A Korean soil database was compiled, which includes chemical and physical properties such as particle size, moisture retention, organic matter, cation exchange capacity, and a limited number of bulk density data based on 380 soil series. The first step is to estimate bulk density for estimation of C storage. Bulk density at different depths of soils was predicted by deriving a pedotransfer function model with sand, depth, and organic matter, based on Adams’ model (1973). Organic C distribution with depth was first derived by converting from mass basis C (kg/kg) to volume basis C (kg/m3). C storage (kg/m2) was first calculated by multiplying C on the volume basis to the thickness of each soil layer (m). The carbon storage from surface to a depth of 0.3 m and 1 m based on soil profile data collected in the 1970s for the south part of whole Korean peninsula was mapped at 100 m x 100 m using the estimated parameters in a 1:25,000 soil series map unit (Fig. 8, Table 6).
Fig. 8. Soil carbon storage map (100 m x 100 m) to a depth of 0.3 m (left) and 1 m (right) in Korea.
Table 6. Summary of soil organic carbon distribution at a depth to 0.3 m and 1 m in Korea.
Soil pH increase
There is a growing body of knowledge on the spatial distribution of soil properties. Fewer studies have investigated temporal trends in soil properties whereas such information is essential for understanding soil productivity and long-term sustainability of agro-ecosystems. Minasny et al.(2016) have investigated temporal trends of soil chemical properties in paddy soils of South Korea using data from over two million topsoil samples(0–15 cm) from soil test laboratories collected between 2000 and 2012. The soil pH increased from5.6 prior to 2000, to 5.9 after 2009, and the rate of increases was about 0.3 pH units per decade. Based on the confidence interval of spatial prediction, 35% of the paddy area (4180 km2) likely has a pH increase (likelihood >66%), and 20% (2350 km2) was very likely to have an increased soil pH (likelihood >90%). The rate of soil pH increase was higher in more acid soils. In addition to the soil pH increase, soil silicate (SiO2) content increased from a mean of 81 mg kg1 prior 2000 to 153 mg kg1 after 2009. This is the result of programs that recommend and subsidize the application of silicate fertilizers that has also caused higher levels of soil exchangeable Ca. The soil test data quantified soil changes over time and demonstrated the long-term effects of soil management on soil chemical properties, which is crucial to develop sustainable soil management systems.
Table 7. Soil pH prediction from block kriging for the paddy of S. Korea.
Soil inventory based on Korean soils database and soil monitoring database was explained in terms of survey history, data types collected and established, spatial and temporal scope for sampling. Internet-based soil and environment information system of Korea was developed in 2006 that consists of five main parts; Soil and Environment, Web-GIS Soil Map Service, Fertilizer Recommendation, Statistics, and Love Soil. One hundred fourteen soil property layers are available through the web-GIS map service of soil information and web-based fertilizer recommendation is available for 133 crops. Soil monitoring data for internal users can be browed to understand spatial and temporal changes of soil properties of interest. Soils database is used for further applications to estimate soil carbon storage, water capacity, change of soil properties, and soil loss. Digital mapping of soil and environment using state-of-the-art and emerging technologies with soil mapping pedometrics concept and predicting soil and environment properties will lead to future direction. Also, remote sensing plays an important role for the estimation of soil properties as one of emerging technologies to contribute to multi-scale analysis and modeling.
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