This study was performed to clarify the soil characteristics of 40 damaged and 45 undamaged small embankment dams for irrigation (tame-ike in Japanese) in Northern Awaji Island, due to the 1995 Hyogo-ken Nanbu earthquake. With reference to the results of multivariate statistical analyses, pairs of damaged and undamaged dams were selected so that the conditions such as distance to epicenter, embankment volume (=dam height)×(crest length)(m2) and distance to Nojima Fault might become almost the same. Soil properties of damaged dams such as D50 (0.514mm), moisture content (9.4%) and the cone penetration resistance (223kPa) are smaller than those of undamaged dams by 45 point, 30 point and more 30 point, respectively. But both specific gravities are the same. The damage rate (DR) of sandy soil is almost twice of that of gravelly soil. DR decreases as the moisture content or the cone penetration resistance increases.
Surface roughness plays a considerable role on radar backscatter models designed for soil moisture estimation. Some parameters such as the root mean square height (s) and the correlation length (l) are used for evaluating surface roughness. Since each study uses a unique profile length, the relationships between radar signal and surface roughness parameters are not clear. So, the correlation coefficients between the parameters (s and l) and gamma naught collected from frozen ground were calculated and the relationship among gamma naught and surface roughness parameters was revealed. Using the relationship and the linear relationship between soil moisture and backscattering coefficient, a soil moisture estimation model was developed. The model developed in this study has a Root Mean Square (RMS) error of 3.6%.
In this paper, application of a model for planning transportation and spread of digested slurry to farmlands is presented, which was developed by the authors. The model estimated a plan without intermediate storage tanks for transportation and spread of annual volumes of 10,000 m3 digested slurry, based on existing statistical data. Three cases were given for the estimation. Case 1-S modeled relatively short-distance transportation of digested slurry, and the farm area consisted of 220 ha of paddy fields and 30 ha of upland fields. By contrast, Case 2-S and 2-M modeled relatively long-distance transportation, and the farm area consisted of 100 ha of paddy fields and 150 ha of upland fields. Numbers of vacuum trucks in all units were equal in the application term for Case 1-S and 2-S whereas specific numbers of vacuum trucks were set for each field to reduce labor for Case 2-M. Case 1-S showed the lowest annual labor and the shortest annual travel distance for vacuum trucks of the three cases. However, Case 1-S demanded the most spreaders and trucks because most transportation and spreading were concentrated in the term before rice planting in Case 1-S. According to the comparison of Case 2-S and 2-M, variable settings for vacuum truck numbers reduced the initial expenditures for machinery and operations.
In Hachirogata Reclaimed Land, the community is becoming a mixture of farmers and non-farmers. We investigated the histories of the residents and opportunities of forming relationships. Based on the results of an oral survey of residents and social network analysis, we revealed characteristics of their personal networks. The main findings were as follows: 1) opportunities of formation of relationships were classified as “work”, “children”, “theme-based organization”, “community-based organization” and “same class”. 2) A farmer-based community is sustained. On the other hand, there is insufficient formation of relationships between farmers and non-farmers. 3) The differences in dwelling place and lifestyle between farmers and non-farmers impede relationships between them. 4) The formation of relationships through children and theme-based organizations contributes to improvement of the relationship between farmers and non-farmers.
A multiple regression model was used to predict the averaged soil water content in root zone instead of solving a Richards' equation numerically, which of applicability was examined. (1) The soil water content of the depth of 5cm (model I) or (2) the effective rainfall and evapotranspiration (model II) were used as the explanatory variables of the multiple regression model. As a result, it became clear that both models could predict the averaged soil water content in the root zone. In addition, it was necessary to convert the original data to its difference and to apply them to the multiple regression model because it was judged that the decrease of the autocorrelation coefficient for the time series data of soil water contents was slow, and therefore, the explanatory variables were correlated each other.