Extrapolation is the essence of extreme value analysis which is applied to the design against the flood risk. In general we face to the obstacle that the finite temporal record length of heavy rainfall is not enough to the reliable estimation, thus as the matter of fact, the applicability of the theories of extreme value statistics to the actual observations of precipitation is uncertain, and we concern there may be discovered another biased story toward the extrapolating region of extreme heavy rainfall. The statistical method is proposed to examine the connection of quantile curves both in our observed record and in the extrapolating region, since the numerous ensembles output by d4PDF are available. The proposed method is demonstrated with an example.

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 The method for estimating detailed flood depth distribution from a rough mesh analysis in a short time was proposed. Pound method and the spline interpolation are applied to the calculated flood depth obtained by 25m mesh model. And, the estimated value near the analytical result of 5m mesh is obtained on the ground altitude model. The following findings were obtained. (1)Analytical time of the proposal method was 1/173 against 5m mesh analysis time. (2)The difference of average flood depth between the proposal method and 5m mesh analysis was 9.1% in an analytical object region. It is thought that produced method is profitable for a real-time flood forecast.

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 In this study, we analyzed the accuracy of 1-km mesh Radar-Raingauge analyzed precipitation transmitted by the Ministry of Land, Infrastructure, Transport and Tourism. This analysis was compared with Radar-Raingauge analyzed precipitation and precipitation data observed by 498 rain gauges installed by East Japan Railway Company in Kanto, Koshin-etsu, and Tohoku regions. As a result, within a 1-hour rainfall, the majority of cases showed close correlation between precipitations provided by Radar-Raingauge analyzed precipitation and by rain gauge, but there were also cases of divergence. Furthermore, precipitations provided by Radar-Raingauge analyzed precipitation tends to average 10 % less than those provided by rain gauges. However, within a 24-hour rainfall, precipitations were closely correlated and on average were practically equal. It should also be mentioned that we found differences in accuracy depending on geographical area; some areas were more closely correlated than others.

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 The aim of this contribution is to investigate the scaling exponent properties of a mountainous river flow fluctuations analyzed by means of detrended fluctuation analysis (DFA). Streamflow data were collected using Fluvial Acoustic Tomography System (FATS) which is a novel approach for continuous streamflow measurements at a high frequency. The crossover times evaluated from discharge data collected by FATS showed a relative delay estimated by 36±6% approximately in contrast to the times detected by the conventional streamflow measurement approaches. Moreover, the detected crossover time seems to be mainly a function of the watershed area and the higher number of intense precipitation events.

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 The experimental equipment was developed to observe the soil temperature and the effect on the infiltration of melting water. One-dimension advection-diffusion model was developed based on the experimental system and was analyzed based on the observed time series variation of soil temperature. Two different conditional methods provided the soil temperature of the steady state for the calculation. Optimization of the model parameter at the top of soil layer results in 0.99 for Nash-Sutcliffe efficiency coefficient in each case, and 2.81×10^-6 and 2.03×10^-6 m/s for the unsaturated hydraulic conductivity. Moreover, the one-dimension model showed the observed soil temperature in the past. The soil heat flux for snow season by the calculation varies from 5 to 15 W/m², which are respectively equivalent to the melting rate from 2 to 3 mm/day. It was shown that the thermal diffusion conductivity was more effective than the hydraulic conductivity.

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 This study presents some investigations on full-scale avalanche-experiments at Niseko and its computational simulation using a refined MPS method. The experiment successfully reproduced a typical flow-type snow-avalance with a real scale. The data of the front-speed, avalanche width throughout the start to the end of avalanche motion are observed and recorded. In addition, numerical calculations were conducted using refined MPS method to reproduce the experimental results. In order to apply this method to snow avalanches, we modified the original erosion-deposition model to more reasonable way and introduced a constitutive equation of Bingham fluid to the bed surface. The model performances are evaluated through the comparison with the real-scale experimental results. It is shown that the present refined model is a powerful tool to predict real scale snow avalanches.

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 In water resource management and disaster prevention, it is very important to estimate snow depth distribution in the mountainous regions as accurately as possible before the snow starts to melt. To estimate snow depth distribution easily with high accuracy, we established a method to estimate it based on similarity of snow depth distribution pattern which measured by airborne laser scanning twice. As a result, the method produced the estimate of snow depth distribution with high accuracy in the dam basin.

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 Porous concreate (POC) pavement has been spreading as one of flood control procedures in an urban area. Though the permeability test for POC is based on linear Darcy's law: q=Ki, it is high possible that POC's permeability law has non-linearity because of its large pores. In this study, through accurate permeability experiments with various glass beads from fine to coarse, relationships between non-linear law: q=K'i^m and particle size dm of media was investigated. In addition, theoretical expressions of seepage flux were formulated by hydraulic consideration on laminar and turbulent flow in pore space of media.

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 The physical propertieses of aquifer such as hydraulic conductivity vary spatially even if the aquifer seems to be uniform. This causes spatial varieties of Darcy velocity distribution, and water path flow may exist in the aquifer. However, it is impossible to grasp the spatial distribution of hydraulic properties by field test, and such an inhomogeneity is ignored in the numerical simulation for groundwater flow. In this study, numerical simulations were carried out using the spatial distribution model of hydraulic conductivity for simple rectangular domains. And the influences of the spatial resolution and the aspect ratio of the domains for statistical property of the velocity distribution were investigated. It was shown that local water path can be expressed by numerical simulation using spatial distribution model of hydraulic conductivity.

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 This paper presented a stochastic approach for estimating time-related solute capture zones of a pumping well in spatially correlated heterogeneous flow fields in three dimensions. An estimation algorithm using random walk particle tracking was applied to assess the travel time and subsequent spatial probability distributions of introduced ensemble lattice cells having the probability Ω^W_p that particles located initially within cells reach the pumping wells during a certain duration of the pumping. Proposed methodology demonstrated some proper time-related solute capture zones under the different conditions of the degree of heterogeneity. The results indicated that the volume of solute capture zones having the probability Ω^W_p ≥ 0.5 exhibited the dependency on the pumping rate but on the heterogeneity and the increase of the heterogeneity led to the increase of the volume comprised by the non-zero probability cells.

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 A large variety of volatile organic compounds (VOCs) as chlorinated ethylenes, chlorinated ethanes, chlorinated methanes and benzene were detected in an aquifer at an illegal dumping site. In-situ bioremediation using anaerobic degradation and reductive dechlorination was applied in this site. The aim of this study is to estimate the effect of the in-site bioremediation targeted at VOCs, especially dichloromethane (DCM) and benzene under anaerobic conditions by using numerical simulation. As a result, degradation rates of VOCs were several to several ten times larger than one's of under natural aquifer conditions. Especially the degradation rates of DCM and benzene were also several to several ten times than those of under natural aquifer conditions. This finding provides evidences that it was possible to purify DCM and benzene by anaerobic bioremediation.

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 In order to clarify groundwater environment in the Kurobe River alluvial fan (KRAF), the residence time and recharge area were estimated by environmental isotope, dissolved ions and hydraulic conductivity. As a result of principal component analysis using 10 dissolved ions, it was estimated that lower or middle basin of the Kurobe River basin was recharge area. Tritium concentration of groundwater above 87 m depth in the KRAF was 3.0-4.3 TU, which was estimated 35-39 years as residence time. These results were the same as calculated by hydraulic conductivity. A a result, the recharge area was estimated the middle basin of the KRAF from river mouth to 13.4-26.4 km.

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 Hydrogeochemical processes were investigated based on groundwater chemistry date. The ions composition of groundwater in forest area is influenced by precipitation, and that in upland field and urban area are controlled by water-rock interaction. The both results of CAI and Na⁺ / Cl^- indicated that ion exchange occurred between Ca²⁺, Mg²⁺ in liquid phase and Na⁺, K⁺ on solid phase. The silicate, calcite, and dolomite dissolution are predominant processes compared to alkali feldspar for mineral dissolution. Ion exchange and mineral dissolution are also suggested by Durov diagram.

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 Due to global warming, it is concerned that cooling water for thermoelectric generation would be run short more frequently in many places of the world. We used a Computable General Equilibrium (CGE) model to quantify the socio-economic impact of a hypothetical shock of capital productivity, which represents shortage of cooling water on thermal power generation plants. The result showed that the magnitude of electricity generation change and subsequent economic indicators change due to 1% capital productivity reduction were varied by region. The mean electricity generation loss was largest in Southeast Asia and smallest in North Africa when an identical shock was given to all regions throughout the simulation period. Considerable regional differences in GDP and electricity price were attributed to not only the capital productivity, but also the amount of capital in thermoelectric sector and its contribution for GDP. Additionally, thermoelectric sector shock propagates into the global economy. These finding demonstrate the significance in quantifying the economic consequence of cooling water shortage.

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 Mangla reservoir is reducing its storage capacity due to sedimentation. The sedimentation rate may increase in future due to climate change. This study will provide the changes in sediment yield in Mangla watershed caused by climate and land use changes in future. The areas of watershed under high annual soil loss have identified using Universal Soil Loss Equation (USLE). Adapting proper land use types, it will be possible to reduce the soil loss and hence reduce the sediment load into the reservoir.
 Estimations with CMIP5 rcp 4.5 climate scenario gave 12% increase in average annual sediment yield in late 21^st century. Similarly, the increase in sediment yield due to future land use change arisen by expansion in urban and agricultural lands is 5% of that in present. Future sediment yield can be effectively reduced by 21% by transforming mosaic vegetation above 2000m and bare areas above 3000m elevation to forests. Contour cropping conservation practice for agricultural lands has found effective in reducing 4 to 5 percent of sediment yield in near future. These adaptation measures will help in enhancing the useful life of the reservoir by 31 years.

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 Climate change alters the hydrological cycle in river basins and threaten the future surface water resources under the stress of the rapid urbanization and population growth in many cities. Haji Dam, located upstream of the Gono River in Chugoku region in Japan, is a very important green energy resource for urban water supply, hydropower generation, irrigation and flood controls. Therefore, the assessment of the projected inflow and capacity under present operating rule is very important for the multi-purpose reservoir. As a result, the estimated maximum 100-year probable rainfall will surplus at least 5 % in the whole river basin as well as the approximately 35 -60 mm surcharge in July and +5 to +20 mm extra in September will fall east, west and middle of the basin in near future. Finally, the increasing trend is significant with 50 m³/sec/year in the annual basic and around 100 to 150 m³/sec/month during the wet season. It requires to change the release ratio before and during the flood if the current flood control allocation wants to keep constant and reservoir water level continuously retains under the flood alarm level for reservoir safety. Moreover, the present operating rule assures the enough capacity after flood season or from September for multi-purposes.

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 The tropical cyclones that make landfall in the coastal areas of Vietnam cause increasing economic losses, with an average of six landfalls per year leading to approximately VND 12,500 billion in damages. It is assumed that the losses are mainly due to socio-economic developments, i.e. growing wealth and greater settlement of exposed areas. However, it is also thought that the rise in damages is caused by increasing frequency of severe cyclones resulting from climate change. In this paper, we estimate the impact of socioeconomic and global warming on the tropical cyclones losses. We investigate the historical impact functions of storm damage by using the Ordinary Least Squares estimator and regress damages on tropical cyclone characteristics. Based on simulation results of Typhoon Lekima in 2007 under global warming, socioeconomic development scenarios SSPs (Shared Socioeconomic reference Pathways) and the population density of Vietnam, we estimate the impact of climate and socioeconomic changes on tropical cyclone losses in the end of 21^st century. Economic losses caused by typhoon will change under global warming at landfall. Socioeconomic changes will increase losses by approximately three and sixteen times greater than that due to climate-induced changes corresponding to SSP3 and SSP5 scenarios.

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 Despite increasing utilization and accuracy of models to predict the future climate and hydrology at higher resolutions, urban areas are still underrepresented. A method to determining future distribution of urban parameters in accordance with the global climate and socio-ecoonomic pathways of the future is proposed. An urban growth model was used to project the expansion of urban areas in 2050 of Jakarta. From shared socio-economic pathways (SSP), total population in the future was acquired. Using historical population distribution data, spatial distribution of population was projected until the year 2050. From empirical relationships acquired from population with nighttime lights adjustment, actual urban parameters, and GDP, futuristic urban parameters were calculated. Finally, the calculated future distribution of urban parameters was used in downscaling the future climate of Jakarta using the pseudo-global warming method.

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 Between 2015 and 2016, Vietnamese Mekong Delta (VMD) has undergone the most severe drought event over the last 90 years, causing damages to agriculture, aquaculture, and fresh water suply. Moreover, upstream Mekong River development by constructing hydropower dams will magnify the severity to the region. This research therefore aims at summarizing some damaged information caused by drought event 2015-2016 and analyzing the impacts of eleven proposed mainstream dams in Thailand, Lao PDR, and Cambodia on hydrology of Vietnamese Mekong Delta under the effect of sea level rise. Results show that the flow discharge is reduced by maximum 14.9% whereas the maximum increase in water level exceeds 220%. This leads to more intrusion of saltwater into the delta and reduction of fine sediment and natural nutrients settling in floodplains.

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 In previous studies, reanalysis data has been used instead of observational data for bias correction of GCM outputs in observation data scarce basin. However, reanalysis data does not match the real weather characteristics (e.g. precipitation, temperature) in a local scale since it is targeted at a global scale. Therefore, this study aims to develop a bias correction method for re-analysis data based on observational data. And also, we made an attempt to apply the method for two stations and to validate by splitting data into two periods, to clarify the applicable range. As a result, it is revealed that time-series pattern of precipitation in a reanalysis data can be corrected using three relations of monthly precipitation in reanalysis data and 1) number of precipitation events in each month, 2) average and 3) standard deviation of 3 hourly precipitation in observational data. Furthermore, despite the observational data with and without significance the trend, it is suggested that precipitation pattern of reanalysis data in validation period can be corrected by the developed statistical creation method of pseudo observational data in calibration period.

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 Quantile mapping method is one of the popular methods to correct the bias of the output of climate models. It has been discussed that there are some issues in this method. One of the issues is related to the robustness of transfer function between climate models and observation. Another problem is about the setting of timeperiod for bias correction. This study assesses the impact of those issues using multiple CMIP5 climate models outputs. We demonstrate the two issues can result in considerable impacts, therefore, the uncertainty of this methods should be carefully considered for the impact assessment studies.

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 In this study, future projection onto regional heavy precipitation in Gifu and Aichi Prefectures is evaluated for the period from 2090 to 2099 by a pseudo global warming experiment using the products of the HadCM3 SRES A1B scenario run. Due to the global warming, the annual maximum daily rainfall becomes 1.5-2.0 times and the annual number of daily rainfall event greater than 100 mm is also increased by about 1.0 days. On the other hand, there are spacial differences that the impacts of the global warming are relatively small around the central part of Gifu Prefecture (corresponding to an inland mountainuous region). It is considered that, in the future climate, low-level moisture advection over the inland mountainous region is inhibited so that the heavy rainfall area shifts to the southern part of Gifu Prefecture (corresponding to an upwind lowland region).

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 In recent years, some flash flood disasters, caused by Guerrilla-heavy rainfall events(GHR events), occurred in urban area in Japan. Although it is pointed out that the number of torrential rainfall events becomes more and more due to global warming, the impact of climate change on such events is not clear yet.
 In this study, we would like to estimate the future tendency of the occurrence frequency of the GHR events in the Kinki region in August, by analyzing simulation outputs of the 5-km-mesh regional climate model(RCM5). We recognized relatively rough rainfall distribution which can be expressed in the RCM5 resolution, by smoothing the rainfall distribution of XRAIN. As the main analysis, we used visual judgement to pick up the possible GHR events, directly from the precipitation output data of present-day and future simulation data of RCM5. As a result, it was indicated that the number of days of such events will significantly increase in August, especially at the end of it, in the future.

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 The damage cost distribution for water-related compound disaster, which flood, storm surge and landslide occurred at the same time, was estimated quantitatively in Japan. Compound disaster was assumed to be caused by rainfall and sea level due to the lowest atmospheric pressure. Firstly, maximum values of rainfall and tide level deviation at the compound disaster were statistically calculated from the relationship between the low atmospheric pressure. The damage cost for compound disaster was estimated using the flood control economy investigation manual. Future damage cost of compound disaster was estimated using future low atmospheric pressure by 4 Global Climate Models and 3 Representative Concentration Pathways scenarios. The potential damage cost of 50-year return period for compound disaster was estimated as 107 trillion JPY in current condition. As a result of future estimation, the damage cost for compound disaster was estimated 1.07 times in near future, 1.08 times in far future compared to the current conditon.

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 Rainfall-runoff phenomenon is more or less stochastic. From its stochastic viewpoint, runoff models are described by stochastic differential equations. In this paper, we propose differential equations whose solutions estimate the first- to fourth-order central moments of discharge under the condition that the rainfall input, the storage coefficient and the initial condition of a storage function runoff model are treated as random variables respectively. The validity of these proposed differential equations was cross-checked by a simulation. Estimation of the probability density function of discharge is possible by using the first- to fourth-order central moments of discharge presented in this paper. The results in this study can be applicable to problems on the river engineering, such as the estimation of the design flood.

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 Time of concentration T_c is defined as the wave travel time from the most hydraulically remote point to the point of study. T_c is an important element in hydrological studies, especially in drainage system designs and the estimations of flood arrival time. The common approach in the estimation of T_c is based on Kinematic Wave (KW) approximation for both overland flow and river routing. This approximation, however, may not be appropriate on a flood plain with inundations. The main objective of this study is to propose the estimation of T_c with Diffusive Wave (DW) approximation considering the effect of flood inundation. The proposed method is demonstrated in the Kelantan River basin, Malaysia, focusing on a severe flood event in December 2014. This study compares the estimated T_c with other estimations based a Rainfall-Runoff-Inundation simulation and with a simple correlation method between rainfall amount in different durations and peak river discharges. In consequence, the proposed method with DW approximation with flood inundation showed closer estimations of T_c by the other two methods.

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 A rainy front brought about the heavy rainfall into watershed of the Sendai River which run through a south part of the Kyushu Island, July 2006. It led to a serious disaster regionally called Hokusatsu heavy rain disaster. A rapid rising of river water level was observed at the Miyanojo observatory station near the Torai district in the heavy rain disaster. In this study, rainfall-runoff analyses were carried out to understand effects of space-time distribution of rainfall on rising rate of river water level in the downstream area of the Tsuruda Dam. As the results, it is implied that not only a high intensity of rain but also rainfall events before/after the high intensity rain affected the rapid rising of river water level at Miyanojo. It is considered that the rising rate of water level as rapid as that at Miyanojo in the heavy rain disaster may occur in other segments of the Sendai River.

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 Since hydrologic drought is a slowly developing phenomenon, it may be possible to forecast low flow conditions, especially in areas with long dry seasons. This study proposes hydrological drought forecasting methods based on two stream flow recession analyses. The first one is based on a recursive digital filters for baseflow separation and recession characterization for the baseflow forecasting. The second one is based on the theory of “simple dynamical systems of catchments”. The applications of the two methods were demonstrated in Lombok Island in Indonesia and showed that the latter method, which reflects more flexible recession characteristics showed better accuracy in the estimations of the low flows. Nevertheless, both of the presented applications showed underestimations in low flow forecastings compared to the observed ones. The underestimations were mainly associated with the ignorance of the rainfall, especially for long lead time cases.

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 Non-point source pollution contribution is one of the major causes of water quality degradation in Chinese rivers and lakes. This research proposes a non-point source pollution modelling based on hydrograph separation by a distributed hydrological model and Time-Space Accounting Scheme. This method simulates spatially exported non-point source pollution nutrient loads by estimating flow discharge contribution rates from different spatial zones and source runoff concentrations of nutrients for each spatial zone. The source runoff concentrations can be estimated by field measurement or an inverse approach based on multiple stream flow samples. The proposed method was applied at the Pingqiao River Basin for a storm event. The inversely estimated source runoff concentrations showed satisfactory agreement with field measurement in the upstream area. The analysis suggested that this area (22.3 km²) exported about 2,630 kg of total nitrogen during an investigated storm event, and the urban area (5.3% of total area) contributed 18.5% of total nitrogen and 80.1% of ammonia nitrogen. The estimated source runoff concentrations were further applied for one-year simulation (2014/12/1 ～ 2015/11/30), which estimated 102,600 kg of total nitrogen export. The result was compared with the estimation based on measured source runoff concentrations (79,000 kg of total nitrogen) and revealed that the inverse method showed about 30% overestimation.

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 We carried out a virtual experiment of data assimilation, which assimilates virtual SWOT satellite observation data into global river model CaMa-Flood with LETKF, at the Amazon basin. Assimilating virtual SWOT observed water surface height improved reproducibility of land surface water dynamics such as river discharge, even for simulations using bias corrupted runoff as external forcing. Unlike previous researches which set relatively small scale rivers as target, we set the whole basin of large scale river as target, allowing correction effect to flow down rivers in this research. This caused reproducibility improvement of river discharge, especially at the downstream where catchment area is large. For locations where correction is difficult because of large river discharge comparing with local runoff, discharge was improved by correction effect propagated from river upstream. This research showed that data assimilation method is valid to improve estimation of spatio-temporal land surface water dynamics variability even for large scale rivers.

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 Under the future global warming conditions, increasing frequency of heavy rainfall and intensification of typhoons are assumed. To consider non-structural flood countermeasure, estimation of the maximum flood is important. In this study, a combined technique of ensemble numerical weather simulation and pseudo global warming (PGW) method was applied to a heavy rainfall event in the Tsurumi-gawa river basin, and future variations of the rainfall were examined. Future projections by multiple global climate models were used to prepare PGW conditions. Then, runoff-analyses were made by a distributed hydrological model with results of the weather simulations. Total and the maximum hourly rainfall in the Tsurumi-gawa basin showed significant increase in future climate conditions. Results of the hydrological simulations showed that river discharges were smaller than the design flood discharge in reproductive simulations. On the other hand, simulated river discharges exceeded the design-flood in most of simulations with future rainfall. Probability density of the maximum discharge of ensemble simulation were quite different between present and fucure climate conditions. And the results showed that probability of flood exceeding the design-flood or more is higher in future, and most of future simulation results exceed the maximum discharge in present simulation.

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 Shingu river basin has been damaged with inundation and landslide disasters by frequently occuring rainfalls due to typhoons near Kii peninsula. These damages may become stronger owing to a climate change, thus we need counter-measures to control the damage for the future.
 In this paper, we first try to reproduce the cumulative rainfall distribution of T1204 by WRF focusing on Shingu river basin. Then, we carried out the pseudo global warming experiment. Finally, the potential area of the landslide disaster was investigated using soil water index based on tank model concept and simulated rainfalls. As the result, it was demonstrated that the proposed method can identify the potential landslide area on some level. The paper briefly summarizes these analysis.

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 Recent advances of regional ensemble weather predictions could improve the prediction of torrential rainfall and resulted severe floods with a longer lead time. To realize this goal, we have developed an ensemble flood forecasting system, composed of an ensemble Kalman filter and a regional numerical weather prediction model in atmospheric part, and Rainfall-Runoff-Inundation (RRI) model in hydrological part. We applied this system to the Kinugawa flood event in Sep. 2015 and studied the forecast feasibility. Ensemble flood forecasts with lead time of 21-15 h were successful in quantitative prediction of a flood discharge peak, while forecasts with lead time of 33-27 h showed a possibility of flood occurrence though its probability was low. The flood forecasting system was superior to deterministic forecasts based on the JMA operational MSM in predictability of flow peak. This study revealed the high potential and limits in predicting flood peaks of the ensemble flood forecasting system.

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 When tropical cyclone (TC) 201610, namely Lionrock, was moving over the western North Pacific from southeast of Honshu to cut across the Tohoku region during 29-30 August 2016, continuous and intense rainfall occurred in mid- to southeastern Hokkaido, far from the TC center. The Weather Research and Forecast (WRF) model is used to investigate the possible remote effect of TC Lionrock on this heavy rain in Hokkaido. The National Center for Environmental Prediction (NCEP) global final (FNL) analysis is used to provide both the initial and lateral boundary conditions for the model. Three numerical experiments are performed. In the control experiment (CTL), the original FNL is used. In the no-TC experiment (NoTC), the vortex associated with TC Lionrock in the FNL is removed such that the TC signal does not appear at the initial time. In the no-topography experiment (noTopo), the terrain height over Hokkaido set to 1 m if it is higher than 1 m. As verified against observations, the CTL and noTopo experiments capture reasonably well the TC track. The CTL experiment also reproduces relatively well the spatial distribution and temporal evolution of rainfall, whereas the remote rainfall in Hokkaido is largely suppressed in the noTC experiment, suggesting a significant far-reaching effect of TC Lionrock. The combined effect of Lionrock and the stationary low-pressure system located over the Sea of Japan enhances the moisture transport towards Hokkaido through their outer circulation. Particularly, only very small amount of rainfall is observed in Hokkaido in the noTopo experiment, indicating that the orographic forcing of the southeastern mountains in Hokkaido plays the most critical role in this extreme rainfall event.

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 While short-time forecasting using X-band MP radar has been developed in recet years, the assimilation of X-band MP radar with mesoscale weather prediction has been limited. This study aims to quantify the effects of the data assimilation with WRF (Weather and Research Forecasting) model coupled with 3-D variational method for the torrential rainfall in Hiroshima City in August 2014. The prediction results of hourly rainfall with data assimilation show improvement in its spatial distribution, resulting in better prediction of total precipitation. Threat Score with data assimilation shows high performance at the initial stage of the lead time. The assimilation using radial velocity and reflectivity is found to change the wind velocity and moisuture fields which are closely related to the evolution of convective rain cells.

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 The short lead time rainfall prediction by Numerical Weather Prediction model has some difficulties in the spin-up problem. Therefore, data assimilation (DA) is expected to improve the initial condition in the model. In this study, our developed ensemble DA system, CReSS-LETKF, and the method of estimation of ice-water mixing ratios are employed. DA of rain, graupel, ice crystal, snowflake and Doppler velocity estimated by polarimetric Doppler radar are carried out after the first convective cloud in mesoscale convective systems is generated. As a result, the first convective clouds formed in initial condition have effective influence on the short lead time rainfall prediction. As the next challenging step, DA is carried out before the first convective cloud. As a result, convective clouds are not generated although the atmosphere conditions, such as potential temperature change.

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 This paper presents the analyses of the spatiotemporal characteristics, by comparison of X-band MP radar data with 1-minute ground observation rainfall data, and of the movement of rainfall area by means of advection model analysis, in the upper basin of Kanda river in Tokyo. These analyses established a relationship between the movement of the rainfall area and the spatiotemporal characteristics. In cases like a rainfall caused by a typhoon, where the rainfall area moved with a clear direction, the meshed area of X-band MP radar data containing higher correlation with the ground observation rainfall data described spatiotemporal movement associated with the movement of the rainfall area. In contrast, in cases of atmospheric instability, the meshed area of X-band MP radar did not show a specific spaciotemporal trend and the meshes surrounding the observation station showed a higher correlation instead of the overlapping mesh.

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 Localized torrential rainfall called as “Guerrilla-heavy rainfall” is widely considered to be important phenomena related to severe disaster. Look-ahead information related to preventing natural disaster risk is necessary for urban traffic management. On the other hand, multicell cluster storm which is causing terrible damage has received much attention in the last few years. However, there has been no little discussion on early warning of that phenomena using advanced radar. This paper is an overview of a fundamental study to detecting multicell cluster storm using X-band polarimetric radar information network (XRAIN). The new theory for detecting multicell is based on early detection method of Disaster Prevention Research Institute at Kyoto University. Our results indicated the possibility that three dimentional data of XRAIN is contributed for forecasting flood risk caused by multicell cluster storm.

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 The present study investigates the relationship between the accuracy of predicted rainfall intensity by using the advection model and the patterns of parameters as well as the number of preceding data. The advection model uses nine parameters, and they are assigned by the regression method using several preceding data. Each set of nine parameters has kinematic meaning and it is defined as a pattern of prediction. By using the patterns of parameters, uncertainty of prediction decreases, and the accuracy of the rainfall prediction improves. In order to improve the short-term rainfall prediction, this study investigated the method to select appropriate pattern using the data from high resolution radar and the advection model. The present study found out that movement and time development of rainfall predicted by the advection model are characterized by Eigen values of the matrix whose elements are a subset of the parameters. Moreover, it shows that the Eigen values provide information on which pattern should be used.

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 The purpose of this study is to clarify the charactaristics of areal rainfall of rain-gauge data, C-band radar data and X-band Multi-Parameter radar data in the Tedori River basin by several analyses.
 As result of analysis using 4-patterns of rain-gauge station combination and 16 rainfall events, the biggest difference value of areal rainfall of hourly and daily rainfall were about 2 mm/h and 13 mm/day. Areal rainfall of X-band MP radar underestimated against that of rain-gauge station and C-band radar, that data weren't depend on the missing data ratio of X-band MP radar in this study.

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 Extreme rainfall by typhoons can cause floods and landslide disasters, and bring down serious damage to the society. However, typhoon track data is multivariate data which consists of genesis position, route, termination position and so on, so it is difficult to understand the relationship between extreme rainfall and characteristics of typhoon tracks. In this study, the typhoons which were observed in the Northwest Pacific from 1951 to 2014 were classified into 20 track patterns (nodes) by using self-organizing maps which is suitable for pattern extraction. Then, in the 10 observation points which were selected from each region in Japan, the rate of precipitation caused by typhoons of each node was calculated. In addition, top 3 events of daily precipitation were extracted, and the factors of extreme rainfall such as nodes of typhoons and fronts were examined. As a result, it is found that the relationship between extreme rainfall and typhoon track patterns are different depending on the observation point like the combination of the particular node and front or only front.

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 The present study discusses the setting half-life of effective rainfall as a standard of debris flow occurrence. Three debris flow disasters in Osumi district, Nagiso-town and Hiroshima-city are chosen for investigation, and the rainfall index R', which expresses rainfall history by one value that combines long-term and short-term effective rainfalls, is calculated. According to the results, around 20% of R' increase and decrease by considering a geologic difference for setting of the half-life, but we need attention when the long-term half-life is less than 12 hours (e.g., volcanic ashes). Geology greatly influences the effective rainfall and R' through the half-life. Precise of the prediction of debris flow occurrences is expected by adding geological feature information to rain indexes.

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 GPM Core Observatory satellite was launched in February 2014. GPM is equipped with the Dual-frequency Precipitation Radar (DPR). The observation made with the spaceborne radar DPR is the first trial, and the evaluation is needed for the observation results. Therefore, we focus on matchup cases with the XRAIN ground radar, and compare the rain rate estimates by DPR and XRAIN. In addition, we consider the factor on the DPR algorithms for the differences of the rain rate estimates.

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 This study conducted experimental simulations of cloud seeding on torrential rains with the forced-cooling technique in order to examine the mitigation effect and acceleration risk on precipitation. Some severe rainfall events including linear convective systems were simulated using a mesoscale meteorological model. Results of this study clarified that relatively small-scale cloud seeding as the discrete or dynamic seeding can produce some mitigation effects on precipitation. The mitigation and acceleration ratios calculated in all nine events and in four linear convective systems showed that precipitation from the latter events can be more readily decreased with the lower acceleration risk than other events by cloud seeding in the early stage of cloud development.

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 The hydroelectric power dams, which don't have the function of the flood control, become more important for the flood control in Japan, because many abnormal floods occurred recently. In order to reduce the flood discharge of the hydroelectric power dams at Kumano river basin, GSM(Japan Meteorological Agency's Global Spectral Model) is applied to the dam operation, but the precipitation of GSM at the basin is underestimated frequently. So, in order to improve the underestimation of GSM at the basin, a new method of correcting the underestimation by using two indexes is proposed and evaluated for the dam operation in this study. The one index is the spatial variation of GSM, another is the variation of the ensemble rain forecast of JMA.

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 To estimate daily sectoral urban water consumption considering the changes in characteristics of water consumption such as popularization of water saving appliances is important for reservoir operation during drought period or designing long-term water resources management planning. Univariate temporal disaggregation method previously suggested estimates daily sectoral water consumption from monthly or bimonthly metered water consumption. This method cannot take account of rainfall or weekly cycle. In this paper, multivariate temporal disaggregation method is applied to utilize not only monthly metered water consumption but also daily urban water consumption. Estimated daily sectoral water consumption by this method can consider daily fluctuation. This method was effectively applied to the estimation of daily sectoral water consumption in Matsuyama City in Japan.

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 To understand future inundation patterns due to climate change, temporal-spatial flood inundation in the Pampanga River basin was analyzed. Dynamic downscaling by the WRF model and bias correction using ground rainfall were applied to the results from MRI-AGCM3.2S with the RCP 8.5 scenario to prepare rainfall data in future climate. Inundation analysis with the RRI model shows that the area of inundation may increase by 20% in the future while the duration may shorten by 10%. The finding that wider inundation and a shorter duration of inundation are concurrently recognized suggests that the mean duration of the maximum inundation may be shorter in future climate due to the spatial-temporal trend of annual maximum rainfall. As further researches, a clarification of the interaction between wider inundation and a shorter duration of inundation by considering a temporal aspect such as the hazard evaluation value defined in this study, can contribute to more reliable assessment of future flood damage risk.

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 Reclamation areas were extracted using MNDWI, NDVI and NDSI in the lower Mekong River Basin. The 49 reclamation areas, which covers 95%, were extracted out of all 52 reclamation areas decided by visual extraction. However, in terms of some reclamation areas, only about 10% of total area were extracted because of overestimation by visual extraction. Moreover, to grasp the tendency of land reclamation, multiple regression analysis has been done. By setting the existence of reclamation area in each commune as response variable and setting the maximum water depth and the distance from the center of Phnom Penh as explanatory variable, multiple correlation coefficient was 0.34. Also field observation of water quality(T-P, COD, Heavy metal) has been done. In the floodplain affected by reclamation of waste, the value of T-P was 25 times of the value of floodplain unaffected by reclamation and the value of COD was about 4 times of the criteria for polluted water. In the floodplain affected by construction of factories, the value of iron was higher than others and it was about 21 times of the criteria of WHO at one point.

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 Nowadays, the arsenic pollutant in groundwater is a serious problem in the world. In Cambodia, the ratio of the water-supply system coverage is 14 % and the sewage system coverage is 11 %, and due to this conditions, it is estimated that people utilize untreated well-water as their domestic water and directly drain the raw sewage to the surrounding of their houses. In addition, Mekong river inundates in Cambodia every year. Therefore, the surface water is possibly polluted by arsenic and arsenic is diffused in the surface water. In this study, in order to estimate the arsenic concentration in the surface water in Cambodia, we propose a new simulation model. This model is composed from a flood-inundation model, a transport of suspended sediment model and a transport arsenic model. We chose the parameters in this model from the data acquired by the field survey in Cambodia.
 The result of the arsenic concentration in the surface water obtained from the numerical simulation model was close to the almost digit of the result of the field survey in the rainy season. The simulation results suggested that during the rainy season, arsenic in the surface water is widely spreaded in the inundate area. On the other hands, in the dry season, the arsenic concentration in the surface water increases before the dry season. In Camnodia, the inundation of Mekong river happens every year. Therefore, we estimate that the arsenic concentration in the surface water may increase furthermore in the future.

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 Weeding of levee is one of the important river management to maintain safety against flood. In Japan, many citizen-based river groups are engaged in weeding, however, their actual states have not been thoroughly investigated. In order for an effective collaboration with river managers and citizen groups, it is necessary to investigate quantitatively how many times and staffs of the citizen-based river groups related to weeding of embankment. We extracted 207 groups through questionnaires and interviews. The result shows that the total active mass of river groups are accounted for about 210,000. With this active mass, river groups are able to weed 3% of river section managed by the government. Also economic value for activities of river groups was estimated to be 1.6 % (0.013 million yen) of official cost for weeding.

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