Recent field hydrologic studies revealed that groundwater in weathered bedrock contributes to runoff variabilities. Followed by the findings, distributed runoff models which simulate bedrock groundwater have been also developed. However, efficient modeling of the infiltration processes in unsaturated zone has not been achieved in the distribution runoff models. This study derive an analytical solution of Richards' equation suitable for such modeling. The obtained analytical solution can set arbitrary water content boundary and initial conditions to account for temporal variations of water content on top of the bedrock and groundwater in unsaturated zone. In addition, we applied the derived solution to a one-dimensional vertical simulation, which connects surface soil layer and bedrock, and analyze the infiltration processes with time varying boundary conditions.

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 Prediction / estimation by seepage flow analysis is possible for the moisture content, groundwater level and water pressure distribution in the slope which is the trigger of the slope collapse at the time of heavy rain. However, since it is usually assumed that the ground physical property is spatially uniform, the non-uniformity observed in the actual slope is not taken into consideration. In this study, we investigated the nature of seepage flow in the slope at heavy rainfall considering pore air flow by two phase flow numerical analysis using nonuniform slope models with variations using a spatial distribution model of hydraulic conductivity. As a result, it is shown that there is a risk of underestimating the pore water pressure of the slope in the case of assuming the field is uniform, and that the influence of pore air may be larger in the nonuniform field.

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 While slope failures due to torrential rain occurs frequently in all over the country, it is used two-dimensional saturated-unsaturated flow analysis by finite element method and limit equilibrium method in many of the design practices and various research. In addition, osmosis water pressure of the unsaturated zone obtained by flow analysis is not considered to slope stability evaluation. Therefore, in this study, the coupling was carried out analysis of the seepage and stress by the shear strength reduction method using a simple model of masa soil. In addition, osmotic pressure and torrential rains of the unsaturated zone was carried out the impact study on the stability of the slope. And it was further applicability verification of the design practices of the limit equilibrium method by comparison with the sliding safety factor by comparison with the conventional method. It showed that conventional method is not applicable cases.

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 Numerical evaluation is useful for studying pollution transport in groundwater, and hydraulic parameters play an important role in performing numerical simulation. In this study, multi-level dilution tests were performed to evaluate pore velocity, hydraulic conductivity and dispersion coefficient at a nitrate pollution site. Based on the results obtained from the multi-level dilution test, three-dimensional numerical simulations were conducted, and the attenuation curves of tracer concentration at different soil depths were reproduced. In the numerical simulations, three-dimensional artificial heterogeneous hydraulic conductivity fields generated by the stochastic fractal model were used. Results of the simulations suggest that reproduction of the attenuation curves could be possible by considering field heterogeneity.

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 Dye experiments in a tank having 80 cm height, 200 cm length and 3 cm thickness were conducted to quantify solute transport phenomena in subsurface reservoir with underground dam. Dye solution mixed with NaCl was also employed to elucidate the effect of the specific gravity on the solute spreading. Spatial moment analysis linked with image processing was applied to identify time-series variation of dye distribution. The results revealed that solutes in reservoir flowed over or across the cut-off wall and solutes with larger specific gravity showed a significant spread in the vertical direction. Moreover, solutes approaching the cut-off wall exhibited an increase tendency of transverse spatial moments despite of the release ports.

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 A laboratory-scale experiment measuring the infiltration of Escherichia coli into saturated soils was performed under constant temperatures. Three soil columns were prepared with loamy clay soil using the wet packing method: Column A consisted of a 15-cm soil column with a water head of 5 cm above the soil surface, whereas Columns B and C had a soil column of 10 cm with a water head of 10 cm above the soil surface. Columns A and B were inoculated with autoclaved ultrapure water containing 7.4 × 10⁷ colony-forming units/mL of E. coli K12 for 450 and 180 h respectively. Column C was inoculated only with autoclaved ultrapure water and served as an experimental control. Column A presented a steady decrease in infiltration rate, which showed a strong correlation (correlation coefficient = –0.93) with the amount of E. coli accumulated in the soil (clogging). Column B first presented similar results to Column A; however, after eight pore volumes were flushed, the infiltration rate increased rapidly, doubling the initial infiltration rate prior to E. coli inoculation. It is proposed that heterogeneous accumulation and growth of E. coli in the soil led to increased infiltration rate. In Column C, the infiltration rate decreased from 27.7 to 24.0 mL/h over the duration of the experiment, despite not having any other input than autoclaved ultrapure water. Additionally, the measurements of E. coli at the output of the soil columns were compared using spectrometry, plate counts, and quantitative polymerase chain reaction measurements. The results indicated that spectrometry was the most suitable method for determining breakthrough curves in soil infiltration experiments.

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 This paper's purpose is revealing that land use change and climate change impacted for water resources quantity in Toyama prefecture basin. We used Land use data during 1977-2014, Meteorological Agency mesh climate value in 2000 and 2010.For evaluation validity of distributed water balance model we chose Kuronagi obs. Station and Hasunuma obs. Station at upper stream basin and compared with observed value of river flow and analysis value. The result we reproduced the observed value of river flow for the most part.
 The result of water balance analysis considered land use change, tendency of underground penetration decrease secular and surface runoff increase. This result was factor that increasing impermeable area as rice field decreased and building site, road and railway progressed. The result of water balance analysis considered climate change, decreasing of water resources availability became clear as decreasing precipitation. If compare with land use change and climate change, it revealed that impact on the water resources by land use change is extremely large.

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 Line-shaped rainbands (LRBs) are severe storm events that cause torrential rainfall and are difficult to accurately predict because of their complex physical processes. Therefore, investigating the detailed characteristcs and physical processes of LRB is of great importance. In this study, we applied a three dimensions wind velocity ground estimate technique MUSCAT (MUltiple-doppler Synthesis and Conitinuity Adjustment Technique) with multi-Doppler radars to analyse the characteristcs of the LRB occurred over central Hokkaido in 11 September 2014. The vertical structures of the rainband suggests that the stronger convection, which is shown by a higher reflectivity from mid- to upper-level, occurs simultaneously with an anomalous in-flow anticyclonic circulation at the height of about 6km. These characteristics are also observed in the Kanto-Tohoku LRB generated over Kinugawa in 9-11 September, 2015.

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 In order to quantitatively evaluate the collection efficiencies of raindrops captured by videosondes at altitudes of 2500m or less, the collection efficiencies were calculated by statistical method with disdrometer as the true value. The synchronized observation using videosondes, disdrometer, and polarimetric radar was conducted during Baiu season in Okinawa Islands. When the change of the raindrop particle size distribution due to differences in time, space and case is small, the influence of variation of collection efficiencies on the relationship between the number of samples captured by videosondes and the slope parameters of particle size distributions was evaluated through random number experiments.
 The 50th percentile of collection efficiencies was approximately 0.2 when the raindrop diameter(D) was 0.5 to 2.4 mm. When D was 1.5 mm or more, the variation of the collection efficiency was large. It was shown that the number of particles of more than 100 for videosonde observation is required to estimate slope parameter(Λ) of particle size distribution. It was found that there is a possibility of estimating the raindrop particle size distributions in the air from the videosonde if the optimum collection efficiencies for the large particle size class are clarified.

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 Nowadays, the frequency of tragic disasters caused by localized torrential rainfall is increasing. This kind of localized rainfall was often triggered by a suddenly-generated and rapidly-developed isolated cumulonimbus cloud. For risk detection of localized rainfall, some researchers found that Ka-band cloud radar can detect cells in 20 minutes before X-band radar can. This study aims to analyze cumulonimbus cloud in the earlier stage using Ka-band cloud radar in some aspects. We discovered the relationship between cloud particle development and first echo height by comparing first echo's height with Lifting condensation level. Also, we revealed Ka-band radar can detect vorticity and vortex tube in the stage earilier than X-band radar can. In conclusion, Ka-band radar is useful for early detection and risk judgement systems.

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 Guerilla heavy rain arises and develops on an extremely small spatial scale and temporal scale, so it is difficult to predict. Precipitation accuracy is improved by C-band and X-band radar. But, because there is a property of getting observation values dependent on precipitation, prediction sometimes delayed in case of developing rapidly. In this research, we conducted an ideal experiment assuming the data assimilation of Himawari-8 and Ka-band radar, which can obtain early cloud information in earlier stage. HImawari-8 is assumed to be the cloud top temperature (CTT), and the Ka-band radar is assumed to be the cloud water mixing ratio qc as the observation value. Assimilation of CTT improves the reproducibility of rainfall start, and Assimilation of qc improves the reproducibility of the peak of ground rain intensity. In the future, we will clarify the mechanism of detailed guerilla heavy rainfall, improve the prediction, and perform data assimilation experiment using actual observation values.

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 Precipitation would be one of the most important inputs for rainfall-runoff (RR) simulations. Therefore, quantifying the Areal Mean Precipitation (AMP) error is important to give the guidance for improving the accuracy and robustness of RR models. Instead of using limited number of rain gauge measurements, satellite based precipitation data would be a surrogate data source. In this study, the capability of remote sensing precipitation including satellite-only GSMaP-MVK and satellite-gauge merged data to evaluate AMP uncertainty is investigated. The adjusted precipitation performances depend upon the number of blended rain gauges, which would not always give superior results than the original data GSMaP-MVK.
 In addition GSMaP-MVK would be one of the choices for precipitation data source to compute AMP error. Therefore, a map of potential AMP uncertainty in major rivers in Vietnam is produced and utilized for improvement of rain gauge network. In order to ensure the fidelity of stream-flow simulation, rain gauge networks in 10 river basins in Vietnam are suggested to be upgraded for a total of 18 rain gauges. The rain gauge network in three river basins in Central of Vietnam Thach Han, Tam Ky and Lai Giang should be given the highest priority, due to their relatively high AMP uncertainty.

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 The Integrated Flood Analysis Model (IFAS), a distributed hydrological model, developed by the International Center for Water Hazard and Risk Management (ICHARM) was utilized to assess runoff from a flood event using two satellite-based rainfall products: Global Satellite of Mapping Precipitation (GSMaP): Near Real Time (NRT) and Tropical Rainfall Measuring Mission (TRMM):3B42RT V7. The devastating Thailand flood of 2011 in the Upper Nan river basin (13,000 km²) was selected as a case study. The temporal and spatial distribution of the satellite rainfall products were statistically evaluated using volume bias, peak bias, root mean square error (RMSE), correlation coefficients (CCs), and the coefficient of determination (R²). The statistical performance of simulated flood runoff using the GSMaP NRT and 3B42RT rainfall products were also analyzed by the Nash–Sutcliffe efficiency index (NSE), CCs, and the RMSE. This study found that both satellite-based rainfall products demonstrated weak CCs and R² values at most ground-based rain gauges with respect to daily rainfall intensity. Runoff simulation results from the IFAS model demonstrated better performance from the 3B42RT than the GSMaP NRT product (NSE: 0.79, CCs: 0.90, and RMSE: 18.03 mcm), despite the smaller pixel resolution of 3B42RT.

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 To calculate the return period of previous heavy rainfall events and to simulate rainfall data under a future climate, high-accuracy and high-resolution spatial rainfall data are required. While Precipitation Analysis (Radar-AMeDAS) by Japan Meteorological Agency is used in previous studies, X-band Multi-Parameter radar network (XRAIN) is used in this study to take the advantage of its higher-resolution. XRAIN has been pointed out to overestimate rainfall over mountainous area and around radar sites, we corrected these overestimation using Dual-frequency Precipitation Radar (DPR) data on the core satellite of the Global Precipitation Measurement (GPM) mission. We generate the extreme rainfall events using correction XRAIN data, and calculate 100-year probable rainfall and return period in Kanto region and Northern Kyushu region.

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 In recent years, high-precision rainfall observation using operational polarimetric radar data has been realized. On the other hand, there are various problems in the case of classifying solid precipitation particles, and observation accuracy is not high enough. Therefore, we have developed a winter precipitation estimation method using hydrometeor classification method. As a result of comparison with the ground observation results, it was confirmed that the estimation accuracy of the particle type on the ground is about 70%. In addition, it was possible to identify the radar constant(B, β) for each particle in the Z-R relationship.

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 Focusing on the rainfall phenomenon in the snowy season in the snowy cold district, we investigated the rainfall estimation accuracy of the X-band multi-parameter radar operating in Hokkaido and Niigata district.
 It was confirmed that estimation of radar rainfall based on AMeDAS rainfall was overestimated. In terms of rain intensity, the tendency to be estimated more excessively was observed at the time of weak rain such as observed as rainfall during the snowy season. On the other hand, during heavy rain leading to summer flooding, the total rainfall by the radar rain gauge was about the same as that by the AMeDAS rain gauge, and it was confirmed that the estimation error was smaller than at the time of weak rain. In addition, when comparing the rainfall estimation accuracy between the snowy season and the summer season, there was a point that was about the same at both weak rain and heavy rain, but there was a tendency for the snowy season to be estimated excessively depending on the location.

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 This paper presents the reproducibility analysis of the urban runoff model using several rainfall data, such as XRAIN and ground observation rainfall data, in the upper basin of Kanda river in Tokyo. XRAIN is known for its spacial high resolution, simulation with the original XRAIN data revealed a probability of lowering reproducibility for runoff analysis. On the other side, Urban runoff simulation using high density deployed ground observation rainfall data showed the hydrograph with the highest reproducibility among the simulation using other rainfall data. Instead, the corrected XRAIN, which considers the spatiotemporal characteristics of correlation with the ground observation rainfall data, indicated a possibility of improving the simulation hydrograph with high reproducibility.

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 We developed a regional ensemble prediction system to support advanced dam operation including predischarge of dam water for the purpose of reducing flood risk and effective water resource management, simultaneously. The targets were Ooigawa and upper Saigawa Basin. The prediction experiment was performed during July to September in 2015 to 2017. Their prediction accuracy was evaluated, and the effective use of probabilistic predictions were discussed. Higher percentile prediction could capture flood risk well, on the other hand, lower percentile prediction could escape from false alarms. For the dam operation with hydro power generation in the target basin, 25 to 50 percentile predictions would be useful to control false alarm ratio under 10%, with reasonable amount of missing ratio with 35%, simultaneously.

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 To assess climate change impacts and study adaptation measures in the water sector, development of macro scale hydrological model covering an entire nation or a vast regios is effective. By using the H08 global water resources model, one may efficiently proceed model development in data scarce regions. In this study, we applied H08 to the Kyusyu Island, Japan, and found the past observed hydrology was well reproduced with a standard simulation protocol which was originally designed for major continental rivers in the world. Then we extended our knowledge on the relationship between the observation density of input meteorological data and the simulation performance utilizing the benefits of good availability of accurate input and validation data.

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 A fundamental study on impact assessment of climate change on operation of reservoir systems and river discharges in Japanese river basins were conducted as a fundamental study in order to develop a method to operate reservoirs more effectively under the expected future climate condition. Current climate data (1979-2003) and future climate data (2075-2099) projected by MRI-AGCM3.2S, a high resolution AGCM developed by Meteorological Research Institute, were used as meteorological input. River discharges in both climates were respectively estimated from climate data by use of Hydro-BEAM, a cell concentrate type hydrological model, integrating operation of reservoirs for water supply and water intake in the target river basins. The assessment was conducted in the Yoshino River basin where droughts often occur, and the Mogami River basin where snow melting water contributes to river discharge significantly. The results suggested that the potential changes in river discharge that may increase a risk of drought in the future. The assessment also showed that the a shift in the snow melting period may not impact water use operation of multi-purpose reservoirs such as the Shirakawa Reservoir that has a seasonal regulation to lower the water use capacity in order to enlarge flood control capacity after the drawdown period.

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 In this study, we investigated daily reservoir inflows and water volumes of Wonogiri dam and dry and wet seasons irrigated areas in the Solo River Basin, Indonesia, by applying the BTOP model with the Japanese Meteorological Research Institute (MRI)-Atmospheric General Circulation Model (AGCM)3.2S precipitation outputs of the Representative Concentration Pathways (RCPs) 8.5 emission scenario for the present (1/1979-12/2003) and future (01/2075-12/2099) climates. Wonogiri Dam is located in the headwaters of the Solo River basin and is a multi-purpose dam with the effective water storage capacity of 0.615 cubic km. From BTOP model results, Wonogiri Dam inflows increase during rainy seasons from November to March due increased future RCP8.5 precipitation of the MRI-AGCM3.2S outputs. In the future climates, the downstream irrigated area is expected to increase, especially in dry seasons, due to available water for irrigation in the reservoir and the period of fully occupied storage also increases indicating the ineffective dam discharge. As a result, there is a potential for new water resources development in the Solo River basin while the revision of Wonogiri dam operation rule is necessary for adjusting for the future climatic patterns.

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 It is pointed out that initial soil moisture affects peak river discharge. Using a distributed hydrologic model, soil moisture impact on river discharge can be considered explicitly.
 It was assumed that monthly rainfall amount in rainy season on Bhumibol dam catchment in Thailand doesn't show autocorrelation based on statistical correlation test except the relationship between monthly rainfall in July and that in August. Therefore, recombining atmospheric data between August and September, and then, a long-term river discharge data was generated by a distributed hydrologic model and recombination atmospheric data. A histogram of annual maximum daily river discharge from generated long-term river discharge data was similar with that of original data. Moreover, it is suggested that annual maximum daily river discharge is determined not only by rainfall but initial soil moisture.

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 Prototype model to quantify transport of land derived dissolved organic carbon was proposed as a simple future projection method in Kushiro River basin where various land usage, such as forest, pasture, wetland, farmland, etc., were distributed like a mosaic. By field observation in a part of upstream reach and a river mouth of Kushiro River, non-point source load of dissolved organic carbon from Kushiro River basin with huge carbon potential were determined throughout the year including snowmelt season. By incorporating the output of general circulation models of CMIP5 to simple hydrological model in DOC transport, the increase trend of DOC discharge to the marginal sea were estimated with partially-seasonal decrease.

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 This research aims to estimate the future change of Baiu-heavy rainfall system in all Japan from the meso-β and macro scales. The high-resolution regional climate model, NHRCM05, is used for meso-β scale analysis of heavy rainfall events. A huge ensemble data, d4PDF_NHRCM20, is then used for macro scale analysis of atmospheric features prone to cause heavy rainfall.
 As a result, the meso-β analysis shows 5% of statistically significant increase in the frequency of heavy rainfall in the area of Japan Sea side and Northern Japan and in early July, early and middle Augsut in future climate. On the other hand, from the results of macro scale analysis, we successfully picked up some atmospheric patterns as well as their significant increase of occurrence frequency. Also, the results indicate that some of new atmospheric patterns will appear in future change.

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 In this study, the change in frequency of extreme precipitation between previous and recent period in Japan was compared with Clausius-Clapeyron (CC) rate:7%°C^-1, in order to check if the change in frequency of extreme precipitation is similar to the CC rate as suggested based on dataset in Europe. In many results, the change in frequency of extreme precipitation was similar to the CC rate:7%°C^-1, but also some results showed the change in frequency more than twice as much as the CC rate:14%°C^-1.

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 The downscaling method for hydrometeorological field is developed, using deep learning. The models are 4 layer feed-forward artificial neural networks which predict RCM's surface 2m temperature and precipitation fields from GCM's field. They are trained by stochastic gradient descent method, using the back propagation method. For initialization, stacked autoencoder was used. The developed models are applied to an area around Japan. The downscaling result represents the spatio-temporal variation of RCM's surface 2m temperature and precipitation well. This implies the effectiveness of our method for the emulation of RCM's dynamical downscaling with low calculation cost.

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 We conducted dynamical downscaling simulations for 20 years over the Asian CORDEX domain to validate uncertainty of RSM-ROMS, a regional atmosphere and ocean coupled climate model. We compared some surface quantities simulated by RSM-ROMS with observation data sets or simulated result by RSM, a regional atmosphere climate model. The results are summarized as follows.
 1) The coupled model had some systematic negative bias for observed sea surface temperature (SST), but the correlation coefficient was over 0.99 and the model reasonably captured the interannual and seasonal variations. In addition, power spectrum suggested a detailed SST structure.
 2) The ocean coupling increased a tendency to overestimate precipitation over the mountainous area. On the other hand, the coupled model more accurately reproduced precipitation over the oceans.
 3) Although there was cool bias of sea water temperature (SWT) more than 4 degrees Celsius at 100m depth, the coupled model captured interannual validations of SWT as similar as those of SST. This SWT bias is larger than seasonal variations, and it indicates there is uncertainty in the coupled model.
 4) Net heat flux was improved in the coupled model, especially in subtropical and tropical areas but got worse in middle latitude areas.

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 Summer monsoon brings over 70% of total annual precipitation to Vietnam northern mountainous region. The large amount of rainfall concentrated in a short time resulted in various flood-related disasters in many regions, especially in Cau-Thuong-Luc Nam (CTLN) watershed. Under the global warming, frequency and intensity of flood occurrence in CTLN watershed have been gradually increasing. There is an urgent need to establish the countermeasures for this key economic region based on the deep understanding of the hydro-meteorological characteristics of the watershed. In this study, we investigated the rainfall-runoff and inundation characteristics of the CTLN watershed in connection with the correspondence climate condition of the present (2000-2009) and future (2060-2069). The Rainfall-Runoff and Inundation (RRI) model was used for the simulation of watershed hydrological characteristics. The essential future precipitation inputs for RRI were achieved by using the Weather Research and Forecasting (WRF) model nested inside GFDL-CM3, and MIROC-5 models. Results of this study suggest the severe flood and inundation condition of the CTLN watershed in the mid-21^st century. We have found the increasing trend in total rainfall during the rainy season throughout the watershed. Compared to the present climate, both GFDL-CM3 and MIROC-5 models show the significantly stronger flood intensity with extended inundation radius.

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 The rapid increase of the information about future climate projection needs conciderations for methods to classify those projection data. This study investigated the characteristic of precipitation in database for Policy Decision making for Future climate change (d4PDF), and found that the clustering approach works well in north reagions. This result indicates that the classification of projection can contribute to conduct an effective impact assessment study.

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 In this study, we evaluated the impact of climate change on explosive cyclone using the large ensemble climate prediction data (d4PDF) of present climate experiment 3,000 years (60 years × 50 members) and future climate experiment 5,400 years (60 years × 90 members). Explosive cyclones were extracted from sea level pressure and examined. Although the trend of increasing explosive cyclone didn't have statistical significance from the difference between present- and future-climate around Japan, the strongest explosive cyclone intensified in future-climate, and future change was estimated about -12 hPa. In addition, as a result of analyzing the explosive cyclone going through the coastal area of Japan, the proportion of strong explosive cyclone like the typhoon had increasing trend.

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 This research proposes a procedure to conduct climate change impact assessment on flood risks aiming smooth risk communication. The large ensemble database “d4PDF” was applied to flood runoff analysis used by the river manager. The hydrological observation data was utilized for verification of the model calculation results. The proposed method was verified in the Nagara River basin. The results of the flood runoff analysis by the annual maximum rainfall event extracted from d4PDF NHRCM 20 well represented the distribution of annual maximum flood observations. Although the influence of the spatial resolution of the climate model is still unclear, the assessment procedure presented by this research has versatility applicable to other domestic river basins.

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 In this study, we analyzed annual maximum area averaged precipitation over first-class river domains in Japan (109 domains) from a large-ensemble dataset (d4PDF), which enable us to have better estimation of return period of heavy precipitation, in order to reveal the statistical dispersion of annual maximum precipitation and changing rate of heavy precipitation amount associated with climate change. The results showed that the statistical dispersion among 50 ensemble members of annual maximum precipitation during 60 years was different in region and the heavy precipitation amount in future climate simulation is higher in all first-class river domains. This result suggested that the countermeasures against floods will become even more important in the future associated with climate change.

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 Projections of river discharge at the Indochinese Peninsula under climate change were analyzed by comparing the empirical distributions of annual maximum daily river discharge for the present and future climate experiments. The river discharge was simulated by a kinematic-wave flow routing model, 1K-FRM using the runoff generation data stored in the database for Policy Decision Making for Future climate change, d4PDF. To fully utilize the multi-initial and boundary condition datasets, the differences between each couple of the empirical distributions of the future annual maximum river discharge produced by different groups of SST patterns were investigated firstly using the non-parametric two-sample KS-test and AD-tests. The analysis results indicated that the differences in the distributions were significant for much of the study area except parts of the Mekong Delta and southern Indochina Region. Thus, the total number of samples was limited within the same SST pattern, which is equivalent to 900-year period data. Then, the changes of river discharge in the future period for each SST pattern and its statistical significance were assessed using the Mann-Whitney U-test. The outcome demonstrated that despite the various degrees of changes according to locations, the detected changes at the Mekong Delta, southern Indochinese Peninsula and at the mouth of the Red River were statistically meaningful with the 95% confidence level.

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 The purpose of this study is to appropriately assess the amount of water resource in a dam catchment basin in Hokkaido, where the amount of water resource is dependent on the amount of snowfall, and to assess the influence of climate change on the water resource. The hydrologic cycle of cold, snowy areas depends strongly on snow; therefore, accurate estimation of the snow cover consolidation process is necessary for accurately estimating the water resource. In this study, the authors clarified the consolidation process of a snow cover in a catchment basin of a dam in Sapporo City by using the values obtained in a long-term observation of snow cover in detail. The authors also attempted to improve the process of calculating the density of the total depth of the snow cover by using the Long-term Hydrologic Assessment model considering Snow process (LoHAS). By using the improved technique and the MRI-NHRCM20 regional climate model, which was created based on the Future Climate Scenario RCP8.5, the authors quantified and compared the water resource under the current climate and under the future climate. The technique of this study, which was based on the values obtained from observations of snow cover in detail, allows us to quantitatively and appropriately assess the water resource. This study demonstrates that hydrological variables indispensable in planning measures against future climate changes can be estimated by using the proposed technique.

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 As a basic study for formulating adaptation plans to climate change, meteorological and hydrological characteristics at the regional level in snowy cold regions were estimated by spatial interpolation method, using climate change data (MRI-NHRCM20) based on RCP emission scenario adopted by the IPCC's Fifth Assessment Re-port. We quantitatively evaluated the future change of water quality in brackish lake, bias correcting and downscaling of climate change data, using the heat/water-balance model (LoHAS), the tank model and the water quality analysis model. The results of water quality simulation indicated that climate change is expected to raise brackish lake surface temperature by approximately 4°C and increase salinity of surface of the lake by approximately 1psu, also the concentration and the deflection of daily value of COD, T-N and T-P in the surface of the lake might decrease.

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 Climate forging is one of the most significant source of uncertainties to project glacier melt by using glacier models. We applied a calibration method for a glacier model “HYOGA2” to evaluate uncertainty from climate forcing. Two additional meteorological parameters have been applied to calibrate HYOGA2. Three precipitation products were used for calibration of the glacier model and bias correction for GCM outputs (daily temperature and precipitation). After calibrating HYOGA2, we projected glacier melt forced by (1) combinations using three precipitation products and three GCM outputs and (2) GCM shuffling forcing data. One GCM showed almost same spread of glacier melt projections among precipitation products as a difference between some GCMs. Some simulations showed larger difference of projected glacier melt caused by GCM temperature output than difference caused by GCM precipitation output.

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 In this study, we investigated the impact of black carbon, BC, as one of Short-Lived Climate Pollutants or SLCP on terrestrial water circulation, in addition to that of sulfur dioxide, SO₂, with the terrestrial offline simulation framework. Results are shown as follows: 1) Both BC and SO₂ decrease the global precipitation whereas decrease in runoff is relatively large with BC. 2) However, spatial distributions of the change in precipitation and runoff are quite patchy and different in BC and SO₂. 3) Decrease in BC emission would relax the global water stress. 4) No matter decrease or increase, change in BC or SO₂ emission would cuase increase the risk of severe flood exposure.

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 A systematic method to project the future distribution of population in megacities is introduced. Two general steps were discussed: (1) estimation of urban sprawl by an urban growth model, SLEUTH; (2) estimation of population distribution by a logistic model with variable empirical coefficients. Predicting the annual change from 2014 to 2050, Jakarta megacity was used as a benchmark urban agglomeration. The key inputs are historical land cover and geographic information, transportation networks, high-spatial resolution population density, and country-level projection of population as defined by various shared socio-economic pathways (SSP). Coefficients were modified in SLEUTH to predict urban sprawling (and auxiliary probability map) compatible with a suitable SSP faced by the encompassing country. Utilizing the predicted annual probability of urbanization and the key inputs into a discrete logistic model with empirical coefficients fitted to minimize the difference of total predicted population with that provided by SSP, population distribution of the target urban agglomeration, Jakarta, was obtained.

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 Since wind flow is a nonlinear phenomenon, it is generally difficult to predict how the wind at a certain point will change at the next moment. However, since the wind speed fluctuation near the ground surface appears as a part of the turbulence phenomenon in the atmospheric boundary layer, it is not a completely random but has "some feature" accompanying the passage of the turbulent structure. In this study, we tried to predict wind speed fluctuation up to 10 seconds ahead by learning the "feature" of wind speed fluctuation using LSTM (Long Short-Term Memory) which is one of Deep Learning. In addition, considering the nature of the turbulent flow in the ground surface layer, we examined the change in accuracy of prediction which depends on input conditions of LSTM. Although the accuracy of prediction decreases as the lead-time is longer, it has been confirmed that appropriate setting of learning time length and adding the vertical wind speed to the input condition contributes to improving prediction accuracy of the wind speed.

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 In this research, we aimed to evaluate the influence of the thermal load of citizens going back and forth in urban area in summer. We conducted micro-meteorological observations along the subjects' movement as well as their physiological (Skin temperature, core body temperature) thermal psychological responses (thermal and comfort sensation) around the Tokyo station. SET^* in the urban district changed ranging from 25 °C to 45 °C, reflecting the urban molophology, such as the height of the building and its density, and the distribution of street trees. The skin temperature showed a high correlation with SET^*. Core body temperature was not greatly influenced by heat stress. The thermal sensation correlated with SET^* reasonably.

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 Mean Radiant Temperature (MRT) is an important indicator for assessing the thermal environment. Cities have complicated heat and radiation environment, reflecting sunlight/shadow distribution. Thus, for the detailed understanding of the urban heat environment mobile observation of MRT is necessary. Various MRT measurement methods have been proposed: integral radiation measurements (MRT_true), upward/downward radiation measurement with direct solar radiation (MRT_dir), gray globe thermometer with air temperature and wind speed (MRT_gray), and globe anemo-radiometer (MRT_GAR). We carried out the accuracy validation of different methods of MRT measurement in stationary observation and mobile observation. In stationary observation in an open space, accuracy MRT_dir, MRT_gray, and MRT_GAR were 1.32 K, 1.94 K and 5.43 K, in root mean square of error, respectiviry. MRT on globe thermometers had larger fluctuation than other 2 methods. MRT_dir, MRT_gray, and MRT_GAR had a maximum error of 4.1 K, 13.1K and 9.9K, respectiviry. In mobile observation within urban canyon, MRT_gray and MRT_GAR had a maximum error of 13.2 K and 11.5 K, average eroor of 1.2 K and 0.6 K for each point. MRT_GAR can replace MRT_gray because of better accuracy lower cost.

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 This study investigated the Wet-bulb Globe Temperature (WBGT) within a urban residential district based on a mobile observation. The difference in clearsky and cloudy conditions are examined. The observation pathway extends about 3 km. In this observation, WBGT changed about 5 degrees along the whole observation route even though the street surface was monotonically asphaltic paving. Although WBGT in different cloudiness conditions were almost same, it was mainly attributed to the globe temperature under clearsky, but to the wet-bulb temperature under cloudy condition. In addition, it was also observed that a street within a residential area is more humid than in a borad street.

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 This study investigated a ensemble mean characteristics of urban environment within a pedestrian level based on a mobile observation. The mobile observation was conducted using globe anemometer thermometer, developed by Nakayoshi et al. (2015), which measure three type of globe temperature and air temperature to obtain the net shortwave radiation and longwave radiation, and wind speed. The observation was taken place for 20 days, and three times per day. The route is set to be in a residential area of Tokyo, exnteded to 3.4 km along the way.
 The ensemble average revealed that the wind speed is enhanced due to the topography effect if the obstraction of the surface obstactles are less effective, i.e. in a street parallel to the synoptic wind direction. Air temperature distribution within a urban canopy also depend on the topography as the temperature becomes high in a slope directed to the solar angle in addition to the sky view factor.

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 Recently, temperature in urban areas continue to rise as an effect of climate change and urbanization. Asian megacities are projected to expand rapidly resulting to serious in the future atmospheric environment. Thus, detailed analysis of urban meteorology for Asian megacities is needed to prescribe optimum countermeasure for these warming. A building-resolving large eddy simulation (LES) offline coupled with an energy balance model is conducted for a highly urbanized district in central Jakarta on typical daytime hours. Six cases were considered; two cases which utilized present urban scenario and four cases represent different urban configurations in 2050. The present case was used for validation by comparison with a moving observation of wet bulb temperature (WBGT). Meteorological inputs of the other present case and four future cases were acquired from a downscaling model. The future configurations were based on representative concentration pathways (RCP) and shared socio-economic pathways (SSP). Using the standard new effective temperature (SET^*), thermal comfort in urban area in Jakarta was calculated and analyzed. Construction of dense high-rise buildings can reduce SET^* (thermal comfort) due to increased shading throughout the district during daytime. Near-surface winds and temperatures were affected by the projected changes in morphology. For example, homogeneous high-rise buildings (case 3 and 4) prevented cooler downdrafts thereby maintaining high potential temperature within the street canyons.

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 Momentum exchange is always carried out between atmosphere and sea surface. In the previous studies, the drag coefficient is a significant value to indicate how much momentum is conveyed. The drag coefficient has been treated as monotonically increasing with wind speed. This drag coefficient takes account of only the atmospheric shear stress, however it does not consider the effects of large amounts of sea spray and raindrop under a rainstorm event. It has also been studied that when the wind speed exceeds 25 ～ 30 m/s, the sea surface is covered with sea spray and it develops into two-phase environment. When the wind speed becomes 30 ～ 40 m/s, the drag coefficient reaches the maximum value. Under the severe storm conditions, raindrop probably effects on the momentum exchange because there is amount of sea spray and raindrop. However, the effects are not classified into each effect. This study proposes an equation that additionally includes the effect of raindrop on the drag coefficient that takes into account of sea spray proposed by Andreas(2004). Under wind speed at 23 ～ 38 m/s, the drag coefficient decreases with heavier rainfall intensity. At stronger winds greater than 38 m/s, the drag coefficient decreases due to the effect of sea spray than the effect of raindrop.

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 Soil moisture is one of the most important hydrological values for a long-term water cycle variation as well as a rain-fed agriculture in developing countries. This research uses the data from AMSR2 boarded GCOM-W satellite, and examined an estimation approach to eliminate the effect of brightness temperature from water and irrigation areas, to avoid the heterogeneity in the footprint area of 6.9GHz. The targeted area is in the Pursat observation site in the west side of Tonlesap lake in Cambodia. Its target period is one year from August 2013 to July 2014. Firstly we calculated the brightness temperature after removing the effect from water and irrigation area, then input this brightness temperature into the LDAS-UT, and finally estimated the soil moisture. Validation was made by the 10cm depth soil moisture observation data in the Pursat site, and the results showed that the estimation accuracy was much improved.

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 In mid-latitude regions, atmospheric blocking leads a strongly meandering jet pattern that remains in same place for several weeks, causing meteorological and hydrological extremes. Rossby (1950) and Armi (1989) proposed a theoretical approach for atmospheric blocking utilizing analogies between open channel flow and jet stream. Kitano and Yamada (2017) extended this theory to realistic atmosphere and showed a relationship between typical blocking flow and specific energy in jet stream. In this study, we analyzed several blocking episodes in 1989 winter using specific energy theory and found energetic signals over Japan and its surroundings before Pacific blocking occurances. This signals may contribute to prediction on blocking.

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 This research aims to investigate the growth stage of cumulus cloud before the occurrence of Guerilla-heavy rainfall (GHR) using the rapid scan observation of Himawari-8, which has fine temporal and spatial resolutions. For our goal, we utilized Rapid Development Cumulus Area (RDCA) index for earlier detection of first echo aloft (baby-rain cell). As our research focuses on the development of small-scale cloud, we eliminated parallax problem in Himawari-8 observation. We overlaid 16 cases of brightness temperature (T_B; Band 13) of Himawari-8 and composite radar observational data. Based on the distance between cloud and rain cell centers in two images, we retrieved the linear equation to solve the parallax effect. The correctness of relocated cloud was confirmed by comparing the estimated top heights of cloud and precipitation. The displacement vector of T_B was applied to solve parallax effect for Band 03 visible channel and RDCA index. In this research, we modified the usage of RDCA index from lightning prediction to the baby-rain cell prediction of GHR. The original RDCA index, ranging from 0.1 to 0.9 was used to detect the early signal in cloud development process to predict the occurrence of baby-rain cell. By analyzing some case studies we confirmed that detailed RDCA index can predict the occurrence of baby-rain cell of GHR.

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 In the predawn on July 5, 2017, the emergency warning on heavy rainfall was issued in the west of Shimane prefecture prior to so-called the severe rainfall in north Kyushu. However, the rainfall in west Chigoku area brought little damages as compared to destructive damages in north Kyushu. It is necessary to investigate the mechanism of the precipitation over the west-Chugoku in order to understand the reason of little damage in the region under the condition of heavy rainfall. Hence, we conducted the data analysis on various weather records and the numerical simulations. As the result, the precipitation system become stationary along the wind convergence. The convective available potential energy (CAPE) was as high as 1000 J/kg in west Chugoku, however, the convective motion was much more active in the north Kyushu.

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 Floods and droughts are a fundamental driver of riverine ecosystems. The occurrence timings of such hydrologic events are associated with organismal phenology and can affect riverine biodiversity. We aimed to evaluate a relationship between basin-scale fish species richness and the occurrence timing of high/low flow pulses at 59 rivers worldwide using circular statistics. As a result, the periodicity of large and medium floods had second-order polynomial relationship with native species richness per area, which supported the intermediate disturbance hypothesis. The periodicity of small floods was negatively correlated to native species richness per area. We conclude that the high periodicity in the occurrence of small high flow pulses may increase competition within a fish community for benefitting from floodplain at a restricted timing, while the high stochasticity in those occurrence can alleviate the competition by offering more opportunities for the benefit across a wider variety of timing.

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