We numerically simulated wind conditions in a mountainous region during Typhoon 0423 using LAWEPS (Local Area Wind Energy Prediction System), and estimated wind speed at the locations of the AMeDAS and pipe-houses. As a result, the maximum estimated wind speed at the AMeDAS location agreed with the maximum wind speed observed by AMeDAS, and the maximum estimated wind speed at the pipe-house locations corresponded well to the damage rate (ratio of numbers of pipe-houses with damage to numbers of all pipe-houses) calculated for each wind speed scale. We concluded that maximum wind speed at the pipe-house locations could be estimated using LAWEPS. Estimated wind speed can be used to analyze damage factors such as pipe structures, covering films, and site conditions, etc. in investigations of pipe-house damage by strong wind.
This study presents a crop production model improvement: the previously adopted Michaelis-Menten (MM) type photosynthesis response function (frad_MM) was replaced with a Prioul-Chartier (PC) type function (frad_PC). The authors' analysis reflects concerns regarding the background effect of global warming, under simultaneous conditions of high air temperature and strong solar radiation. The MM type function frad_MM can give excessive values leading to an overestimate of photosynthesis rate (PSN) and grain yield for paddy-rice. The MM model is applicable to many plants whose (PSN) increases concomitant with increased insolation: wheat, maize, soybean, etc. For paddy rice, the PSN apparently shows a maximum PSN. This paper proves that the MM model overestimated the PSN for paddy rice for sufficient solar radiation: the PSN using the PC model yields 10% lower values. However, the unit crop production index (CPIU) is almost independent of the MM and PC models because of respective standardization of both PSN and crop production index using average PSN0 and CPI0. The authors improved the estimation method using a photosynthesis-and-sterility based crop situation index (CSIE) to produce a crop yield index (CYIE), which is used to estimate rice yields in place of the crop situation index (CSI); the CSI gives a percentage of rice yields compared to normal annual production. The model calculates PSN including biomass effects, low-temperature sterility, and high-temperature injury by incorporating insolation, effective air temperature, the normalized difference vegetation index (NDVI), and effects of temperature on photosynthesis. Based on routine observation data, the method enables automated crop-production monitoring in remote regions without special observations. This method can quantify grain production early to raise an alarm in Southeast Asian countries, which must confront climate fluctuation through this era of global warming.
We developed a statistical model to evaluate the influences of climate conditions and farm household characteristics on the degree of yield loss in paddy rice production. In the model, actual yield loss is divided into potential yield loss and resistance to yield loss. The potential yield loss is assumed to be dominated mainly by the climate conditions, whereas the resistance to yield loss is determined by the level of cultivation practices, indirectly represented by farm household characteristics. The model was applied to two adjacent towns in Tochigi, with a focus on the yield loss from the cool summer of 1993. The results indicated that the yield loss of 1.264 t/ha was prevented through cultivation practices, and the value corresponded to 44.2% of the potential yield loss. The resistance to yield loss was low among farm households with a high percentage of elderly population, without regular workers, and with abandoned arable fields. The negative influence of the percentage of elderly population on the resistance to yield loss was slightly greater than those of other farm household characteristics, raising concerns that the yield loss in paddy rice production may increase with the aging population of the rural area.
In many global scale research such as vegetation changes and carbon dynamics concerning with earth warming, precise validation was not enough applied to ascertain if the results of satellite analysis representing correct information at ground surface. In order to resolve such problems, “Creating Satellite Ecology Project” is aiming at satellite data analysis combined with biometric study at ground and model evaluation in Gifu University. We are collecting precise ground data for validation at the main site on the Daihachiga river basin in Takayama city. In this paper, we reported about ground phenology observations (1) in agriculture fields, (2) using indicator tree species, and (3) using digital images at the basin scale. In the case of (1), it was shown that there were differences in the biomass and LAI (Leaf Area Index) by the difference of the cropping type, and the seasonal changing pattern is also different. Moreover, in the case of (2), it was proposed the technique for detecting the phenology change using indicator trees (Juglans ailanthifolia), and we could observe the difference of the phenology change according with the altitude. In addition, in the case of (3), the events of green-up, yellowing and defoliation were able to be detected by analyzing the digital images simply acquired by commercialized cameras. It was expected that such methods provide useful ground information of agriculture and forest lands.
It is necessary to comprehend the both of spatial and temporal variation of ecosystem function to understand the ecosystems in basin scale. Remote sensing data with one-meter to several tens-meter spatial resolutions and daily to weekly temporal resolutions are suitable for basin scale ecosystem analysis. However, there is no such satellite sensor that meets requirements for both of spatial and temporal resolutions. It is getting important to develop the production methods of the high spatial / temporal data set for basin scale ecological science with remote sensing data, such as 1) pixel merge method with high spatial / low temporal resolution data and high temporal / low spatial resolution data, 2) improvement of temporal resolution with many scenes acquired by several high spatial resolution sensors, such as SPOT, ALOS/AVNIR-2, QuickBird, IKONOS. This paper describes the investigation of spatial evaluation of ecosystem function / structure and summary of investigation of appropriate spatial / temporal resolution of remote sensing data for basin-scale satellite ecology.
The 21st century COE program at the River basin research center, Gifu University, “Satellite ecology for basin ecosystem studies” was started from 2004. The main target of the program is to evaluate the distribution of the basin ecosystem functions, such as the amount of carbon absorption, in Daihachiga river basin in Gifu, Japan. Two intensive observation sites are located on the representative two surface types: deciduous broadleaf forest and evergreen coniferous forest. The ecological process study data obtained by field observations mainly in two intensive observation sites are used to improve land surface numerical model. The distributions of the parameters, such as surface type in the basin, are from satellite remote sensing. The land surface model with the distributed parameters is connected with the meso-scale numerical weather model and calculates the ecosystem functions, such as the distribution of the amount of carbon absorption in the basin. The researchers in ecosystem, satellite remote sensing and numerical simulation collaborate with each other to accomplish the work above and also they deepen mutual understandings. The evaluation of ecosystem function is now reaching to final stage.
In this decade, improvements of resolution of satellite sensors, along with the spatio-temporal scales of satellite remote sensing have been overlapped with field measurements in ecological environment study. River Basin Research Center of Gifu University organized “Satellite Ecology Project” in the 21st Century COE Program to construct a new paradigm of ecological process measurement, remote sensing analysis and climatic modeling evaluation. Experiments started in 2004 at the Daihachiga River Basin area in central Japan of Takayama. The current object of this study is to clarify carbon dynamics at river basin scale. Here, previous researches at Takayama super site have been presented with general description of the study area, background and objects of the research, and relation between agricultural system researches.