In a hilled rural area, it is essential to identify reservoir-water influent from a pond in order to prevent a landslide. However, a usual method to measure only the amounts of surface water inflow and outflow cannot quantify groundwater effluent and reservoir-water influent simultaneously. We applied the analytical method using radon-and water-balance equations to a small-scale pond. The dispersion rate of radon was estimated assuming that there was a stagnant film between water and air. The thickness was calculated to be 820μm from the experimental data. The F Pond, Nagano prefecture, was selected as a study site. A preliminary examination confirmed that reservoir-water was mixed very well. The groundwater effluent and the reservoir-water influent were calculated to be 0.67×10^-3 m³ s^-1 and 0.41×10^-3 m³ s^-1 respectively, by making radon-and water-balance equations and solving them. This analytical method is expected to be useful to not only prevention of a landslide but also effective use of water and prediction of water quality in a pond.

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The snow index S3 (Saito and Yamazaki, 1999) is applied to Landsat-5/TM images, and used for estimating snow water equivalent and snowmelt water. The snow index was developed for ADEOS-II/GLI, but the satellite has not been launched yet. This research is, therefore, the first case to apply the snow index for satellite data. In the Kurobe basin in the spring of 1986, the snow-covered area is extracted from the snow index, and the gross volume of snow water equivalent in the basin is estimated by altitudinal distribution of snow water equivalent in the basin (KEPCO 1960) and the method of Koike et al. (1985) when Landsat-5 passed the study area. Then, the difference of the snow water equivalent estimated by two scenes (14th and 30th, April, 1986) is regarded as the amount of snowmelt during this period.
When the snow index is used for extracting the snow-covered area, the relative error between the estimated amount of snowmelt and the observed water which flows into the Kurobe-daiyon-dam (Kuroyon dam) from 14th to 30th, April is —8.2 percent. While the method which does not consider the disturbance by vegetation is used, the error is as large as —23.8 percent. Since the snow index can capture the ground snow under the plant canopy, the snow index has higher precision. Namely, this guarantees the snow index as the better method for extracting snow-covered area.

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When modelling unsteady groundwater flow in a large area, the estimation of hydraulic parameters and groundwater levels at node points within a finite element or finite difference mesh is particularly important. Unfortunately, the information on these hydraulic parameters and groundwater levels is usually insufficient. To simulate large-scale unsteady groundwater flow without enough data of groundwater level and hydraulic conductivity, a methodology was proposed in this paper basing on geostatistics, snowmelt and unsteady groundwater flow. Firstly, ROKMT (Residual Ordinary Kriging with Modified Trend) was presented to estimate the spatial distribution of groundwater level, where the spatial trend of the observed groundwater level was modified using DEM (Digital Elevation Model) as an auxiliary information.
Secondly, based on the estimated spatial distribution of groundwater level, the spatial distribution of hydraulic conductivity was identified using the optimization algorithm. Furthermore, the snowmelt in space was estimated by a heat balance model, and the unsteady groundwater flow was simulated using TFDM (Triangular Finite Difference Method).
Finally, as a case study, the unsteady groundwater flow of the Sarobetsu wetland was simulated for the period from January 1998 to December 2000. The results indicate that the proposed methodology can simulate the unsteady groundwater flow in satisfactory accuracy.

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This paper examines the relationship between the warm season precipitation and the historical highest hourly and daily precipitations based on AMeDAS data during 20 years (1979 - 1998, 1148 observatories) for simple estimation method of heavy rainfall. The linear regression equation is obtained for the historical highest (20-year highest) precipitation and the warm season precipitation from April to October, which indicates highest correlation. The equation is used for mapping of 20-year precipitation estimates. The equation is also used to define the“heavy rainfall blank areas”, in which some AMeDAS observatories have the historical highest precipitation smaller than one estimated by the equation. Defined“heavy rainfall blank areas”are around border between Akita Pref. and Iwate Pref., east area of Nagano Pref., north area of Nagano Pref., Hokoriku district, Hiroshima Pref., Fukuoka Pref., south area of Kumamoto Pref. and east area of Kagoshima Pref. In addition, this paper tries to estimate probable maximum precipitation (PMP) by using an envelope drawn in the scattergram of the warm season precipitation and historical highest precipitation. Consequently, the envelope could be a tool for estimating PMP, because it covers the highest records at more than 97% among 154 weather stations of JMA.

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Through a series of the studies, targeting high water use efficiency from a viewpoint of effective use of water for crop production, optimum leaf area density obtaining the highest water use efficiency under given meteorological and soil water conditions will be discussed. In this paper, stomatal conductance (gs) model and single leaf photosynthesis (CER_l) model of rice, which could be incorporated to a multilayer model (Oue, 2001), are developed by observed gs, CER_l, crop growth and micrometeorological data within a rice canopy. Analysis of observed data reveal that other than photosynthetically active radiation on the leaf (PAR_l), height of the leaf (z) and VPD at z are very important for parametrizing gs and that PAR_l and gs of the leaf are very important for parametrizing CER_l. Height and VPD are effective parameters for gs because they made a reverse impact on gs each other. The gs model developed is very suitable for incorporating to a multilayer model because it predicts gs of a leaf in every layer in response to micrometeorological condition in the layer. The CER_l model is very suitable to reproduce the photosynthetic processes and water use efficiency in the multilayer model because it predicts CER_l of a leaf in response to gs of the leaf and micrometeorological condition in the layer.

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The multilayer micrometeorological model (Oue, 2001) is improved incorporating the stomatal conductance model and the single leaf photosynthesis model of rice developed in the previous paper (Oue, 2003) . One of the improvements is that energy balance of a plant body is solved for sunlit and shaded side. Simulation by the model can reproduce observed vertical profiles of transmissivity of solar radiation, horizontal wind speed, air temperature, vapor pressure and plant surface temperature successfully. Energy balance in the rice canopy is characterized by negative sensible heat flux from which additional latent heat flux originates in the afternoon. Simulation by the model demonstrates that sensible heat flux on the shaded leaf is negative in almost every case and thus the shaded leaf has an important role in energy balance in the paddy field. Water use efficiency in each canopy layer (WUE_c) is lower in case that incident solar radiation on a leaf surface is large or small enough, which predicts that WUE_c is lower in a canopy of small or large leaf area density and that an optimum leaf area density exists for maximum WUE_c.

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Spectral characteristics and spectrum-based snow and vegetation indices from one visible and two near-infrared bands, on various surface categories were evaluated, using an Airborne Multi-Spectrum Scanner (AMSS) in 2001. The AMSS was improved in sensitivities of near-infrared channels compared with those in 1998. Interrelations between the indices (or visible-to-near-infrared albedo) and vegetation density were also discussed with field observations of forest density in a high spatial resolution.
In addition, differences of atmospheric effects on both the AMSS data and the snow and vegetation indices were estimated with observations at two altitudes and compared with the result of a radiative transfer model. From observation at the higher altitude (13200ft), radiances at bands less than 490 nm in wavelength were strongly affected by the Rayleigh scattering. However, the visible (625nm) and short (865nm) near-infrared channels of the snow and vegetation indices, were not affected so much by the atmospheric effects and long (1650nm) near-infrared also has only a small effect of the water vapor absorption. The indices were little affected by the atmosphere in general.
Moreover, viewing-angle dependencies of detectors on near-ultraviolet (380nm), visible (625nm), and short and long (865nm and 1650nm) near-infrared channels were investigated. As a result, fore-scattering was representative on snow surface in its viewing-angle dependency and forest has a Lambert-like dependency. The dependency at wavelengths of more than 1000nm was approximately half of that in the AMSS of 1998 because the IFOV of those channels was expanded from 2.5 mrad to 5 mrad.

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²²²Rn-and water-balance equations can be used to quantify groundwater effluent and surface-water influent in a small pond. ²²²Rn dispersion from water to air is an important factor in the ²²²Rn-balance equation. The dispersion rate is estimated by assuming that there is a stagnant film between water and air and its thickness is inversely proportional to the dispersion rate. However, few reports on the thickness of a stagnant film of static water such as a pond have been published. The author experimented on the relationship between the thickness of a stagnant film in static water and wind velocity. The thickness was calculated from the rate of decrease of ²²²Rn concentration in water with time. The result showed that the thickness of the film, in this case 750-920μm, was not influenced remarkably by wind velocity when wind velocity was less than 1.5 m s^-1. Above the velocity, the thickness tended to decrease as wind velocity increased.

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The decoupling factor Ω, which expresses relative contribution of the radiative and advective terms in the Penman-Monteith equation to evapotranspiration rate, gives implications for simplifying measurements and modeling of evapotranspiration rate of vegetation canopies. Although Ω=0.1∼0.2 (that is, significant contribution of the advective term) has been regarded as a general rule for forest canopies, it has not been examined whether Ω=0.1∼0.2 is really general for forest canopies. Then, this paper examined whether Ω=0.1∼0.2 is general for forest canopies by surveying Ω values reported in earlier papers. From earlier papers, 35 samples of Ω values were collected. Among them, 15 samples were obtained on broad-leaved forests, and 20 samples were obtained on coniferous forests. 4 samples among the 20 samples (20%) obtained on coniferous forests satisfied Ω > 0.2. On the other hand, 9 samples among the 15 samples (60%) obtained on broad-leaved forests satisfied Ω > 0.2. Moreover, 4 samples among the 15 samples (27%) satisfied 0.4 < Ω ≤ 0.7 which is a typical range of Ω values obtained on crop canopies. Thus, although Ω=0.1∼0.2 is general for coniferous forests, it is not for broad-leaved forests. This suggests that simplifications of measurements and modeling, based on low Ω values, can cause significant error in estimating evapotranspiration rate or surface conductance, when the simplifications are applied to broad-leaved forests.

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