Hiroshi Obara

Spatial prediction of radioactive Cs concentration in agricultural soil in eastern Japan

Abstract As a result of the accident at the Fukushima Dai-ichi Nuclear Power Station (FDNPS) operated by the Tokyo Electric Power Company, radioactive cesium (Cs) was released into the surrounding environment. To determine the extent of decontamination required in agriculture fields and to consider management options, we surveyed and measured soil Cs concentrations in 3461 agricultural fields, and used these data to construct a distribution map of radioactive Cs concentration in agricultural soil in eastern Japan. Soil Cs concentration was positively correlated with radiation dose (r2 = 0.89, n = 2199). This linear correlation was affected to some extent by soil surface condition, soil group and land use type. Linear regression analysis was conducted by land surface condition, soil type and land use type. We constructed a soil Cs concentration map by regression and by a regression-kriging (RK) method that combines regression equations with ordinary kriging of the regression residuals. Prediction accuracy of the RK was higher than that of the regression; we therefore adopted the RK. Total radioactive Cs concentration in soil was highest in the 20-km evacuation zone surrounding FDNPS, and tended to be higher to the northwest of FDNPS than in other directions. About 5900 ha of paddy fields and 3000 ha of upland fields in Fukushima Prefecture were above contamination level 2 (> 5000 Bq kg−1), and were mostly distributed in the evacuation zone.

Factors controlling organic amendment application rate and long-term change in application rate in Japanese paddy field using longitudinal questionnaire survey dataset (the Basic Soil Environment Monitoring Project, Stationary Monitoring, 1979–1998)

Using data from a longitudinal survey (the Basic Soil Environment Monitoring Project, Stationary Monitoring, 1979–1998, launched by the Ministry of Agriculture, Forestry and Fisheries of Japan), it was found that livestock possession, soil type, utilization form of paddy fields and full-/part-time status of farmers were important factors controlling application rates of organic amendments (OA) in Japanese paddy fields. When data points were categorized in terms of these four factors, application rate of livestock waste compost (LWC) on the basis of fresh weight (FW) varied remarkably. Application rates of LWC decreased during the survey period, whereas rice straw residue (RSR) application rates increased. The smallest LWC application rate (average 0.3 ± 0.2 Mg FW ha−1 for the period between 1994 and 1998) was found among rice (Oryza sativa L.) single-cropping, poorly drained lowland paddy soils (PDLPS) including Histosols, with full-time farmers possessing no livestock. Even among rice single-cropping, the application rate was clearly larger (average 10.6 ± 0.5 Mg FW ha−1 for the period between 1979 and 1983) for non-poorly drained lowland paddy soils (non-PDLPS), with full-time farmers possessing livestock. Much greater than this was the LWC application rate for converted paddy fields (average 29.9 ± 4.3 Mg FW ha−1 for the period between 1989–1993), non-PDLPS, with full-time farmers possessing livestock. Accordingly, this study emphasizes the importance of categorizing data points at least in terms of soil type, utilization form of paddy fields, livestock possession and part- or full-time farming status when constructing an inventory, exploring changes in OA application rate, and making policy.

Phosphate adsorption coefficient can improve the validity of RothC model for Andosols

The conventionally-modified RothC model for Andosols required pyrophosphate-extractable aluminum (Alp) for changing humus decomposition rate of the original RothC model. However, any Japanese soil database, which were derived from national soil survey projects, did not have the Alp dataset, and thus the conventionally-modified RothC model required Alp prediction from soil organic carbon (SOC) content. From this reason, there is a risk of Alp prediction error in the run-up to predict the SOC turnover. Objectives of this study were (1) to explore the alternative soil property for re-modifying the conventionally-modified RothC model and (2) to validate the re-modified model against long-term experimental data sets of Japanese Andosols. Phosphate adsorption coefficient (PAC), which is an indicator of the content of amorphous aluminum (Al) and iron (Fe) compounds, was tested to replace Alp using three Andosols database. A stability factor, H(f), was defined as the factor needed to divide the decomposition rate constant of the humus pool so that the modeled SOC level matched the measured level. Phosphate adsorption coefficient showed positive correlation with the H(f). The H(f) was regressed by the exponential equation using PAC as an independent variable, and its R 2 value was higher than in the Alp derived regression. We incorporated the PAC derived regression into the original RothC model as the PAC-modified RothC model. From the comparison of the models validity, the PAC-modified RothC model showed low mean error with low root mean square error in the long-term experimental data sets. These results indicate that PAC can replace Alp for changing the decomposition rate of humus pool in RothC model with accuracy enhancement.

Delineation of Japanese soil temperature regime map

The soil temperature regime map provides for utilitarian classification that can be superimposed on soil classification to permit more precise interpretations and assessments of land use. The objects of this study are (1) to clarify the relationship between soil temperature and meteo-geographical factors, and then (2) to delineate detailed soil temperature regime map (1 km grid) as Japanese land resources inventory. There was a parallel relationship between mean annual soil temperature (MAST) and mean annual air temperature (MAAT), but this relationship was affected to some extent by the mean annual wind speed and mean annual global irradiation in this study. Furthermore, the difference between MAST and MAAT [Diff(MAST–MAAT)] showed the highest correlation with elevation. The map of RK_Diff(MAST–MAAT) was computed using this meteo-geographical relationship with the regression-kriging approach, and then the map of MAST and the soil temperature regime map were delineated using the map of MAAT and the RK_Diff(MAST–MAAT). The root mean square error of this delineation procedure was 0.47°C. It was clear that the majority of the Japanese soils had “mesic” soil temperature regime, and Japanese agricultural land was mainly distributed at “mesic” area and followed by “thermic”, “frigid”, and “hyperthermic” area. For promoting this land resource inventory, the soil temperature regime map will be uploaded on “Soil Information Web Viewer (http://agrimesh.dc.affrc.go.jp/soil_db/)”, which is provided by the National Institute for Agro-Environmental Sciences.