In recent years, seepage failure near the river confluence has been confirmed in various places. However, safety verification method at river confluences have not been established. In this report, we have summarized the damage cases caused by the infiltration of the foundation ground at the confluence that occurred in recent years, and summarized the points to keep in mind when conducting safety verification and considering countermeasures. we also proposed a flow for setting the study area for safety verification.

 The purpose of this study is to evaluate the function of the historical channels and rivers flood control system in Akizuki, which has been maintained by dry masonry technique and is based on Nature-based Solutions and Natural Flood Management. The flood control function will be evaluated in two scenarios: a simulation of the July 2017 heavy rainfall that reached a maximum hourly rainfall of approximately 100 mm/h, and a scenario with 1.4 times that amount of rainfall. As a result, it was found that the historical flood control system was effective in reducing the peak flow discharge at the downstream end of the basin. Furthermore, it was shown that the high roughness of rock-made rivers and channels ensured the safety of the in-channel structures by keeping the flow velocity below 5 m/s, which is the design flow of dry masonry revetment, even under the 1.4 times rainfall scenario. This study clarified not only the historical flood control characteristics of dry masonry but also the flood control function of the channel network. It was found that the channel network in Akizuki has the function of reducing the peak flow rate of the river from the town to downstream by detouring the rainwater by running parallel to the river.

 The purpose of this study is to quantitatively evaluate the energy dissipation function of a traditional dry masonry bed sill on the Notori River in the Akizuki district of Asakura City, Fukuoka Prefecture, using hydraulic model experiments. The experimental scale was set to 1/30 according to Froude's law of similarity. The experimental discharge was set based on the flow observation results at the time of the heavy rainfall in July 2017.3 types of hydraulic models were prepared: a traditional bed sill model and 2 general concrete bed sill models. The experimental results showed that the traditional bed sill of the Notori River has a high-velocity reduction function, and its roughness coefficient value was determined to be 0.06. The results also suggest that the bed sill can enhance the safety of the in-channel structure because the flow velocity can be kept below the design flow velocity of the dry masonry revetment.

 Multifractal has been widely applied as the tool of quantitative pattern analysis. In this study, multifractal properties of water vapor flux and precipitation particles distribution associated with line-shaped rain bands were analyzed to identify the three-dimensional patterns of self-organization of convection systems. We analyzed water vapor flux obtained by the numerical simulation of the heavy rainfall event over Kameoka City on 15 July 2012. Before heavy rainfall occurred, water vapor flux approached to monofractal corresponding to increasing the convective instability at lower atmosphere. While during heavy rainfall, strong multifractality was shown due to the development of convection systems. Multifractal analysis was also conducted to characterize the multifractality of the mixing ratio distributions of ice-phase precipitation particles obtained by volume scans of X-band MP radars. The time period when the line-shaped rain band area began to expand and the regional averaged rainrate increased coincided with the one when the multifractality of the graupel and snowflake mixing ratio changed significantly.

 This study investigated the vertical mean wind profile within the atmospheric surface layer (ASL). Conventionally, the mean wind profiles within the ASL follow the logarithmic law profile under the conditions of the neutrally stratified, strong wind, and steady mean wind direction. Our Doppler lidar observations over urban and suburban area revealed that there was long time mean wind oscillation above the logarithmic layer. Based on this oscillation, the height, in which the mean wind varies logarithmically, extended until 500 m at least from the ground. The ground-based turbulence monitoring also revealed that the ground level sweep events occurred synchronously with the upper layer oscillation. This indicates that the oscillation could be propagated to the bottom within the surface layer via the sweep events.

 Localized severe heavy rainfalls have frequently occurred in Japan. For reducing the damages by disasters, it is necessary to predict the risk of GHR. Kimand Nakakita(2021) developed the quantitative risk prediction method by considering the relationship between the predicted risk level and the variables based on the stages, which are defined by just time. In time stages, the development of GHR was tracked at 5-minute intervals. However, the length of the whole life of GHR depends on the cases, for example, the second 5-minute interval does not necessarily have the same meaning in the development of GHR for different cases. If we consider the development of GHR based on the statistical and physical aspect, we should make more precise predictions. Therefore, this research aims to show the potentiality of the quantitative risk prediction.

 Multi-Parameter Phased Array Weather Radar (For short, MP-PAWR) is the latest weather radar. MP-PAWR can observe stereoscopic rainfall densely in time and space, because MP-PAWR has higher temporal and vertical spatial resolution than conventional weather radars. This study aims to develop a rainfall prediction system that contributes to lead time in the event of localized heavy rainfall evacuation by using highly accurate observation information from the MP-PAWR. The method is based on the calculation of rainfall prediction according to the time variation of Vertically Integrated Liquid Water Content (VIL) in the target basin. The results show that it is possible to provide an accurate rainfall forecast for estimation after about ten minutes. Also, when Kalman Filter is applied to rainfall forecast, the excessive peak rainfall intensity is improved, indicating its applicability to rainfall forecasting by MP-PAWR.

 The development of characteristic patterns of a single-cell to multicell thunderstorms was developed by using a multi-parameter radar analysis. The differential reflectivity (Z_dr) column and specific differential phase (K_dp) column were further investigated, including the analysis of vertical vorticity from a dual-Doppler method. The kinematic mechanism analysis using a dual-Doppler radar was also examined in this study. From the evolution of cells investigation, the convergence was observed before the initiation of the updraft. The peak of updraft and core vorticity intensity were identical in their stage of development, whereby radar reflectivity indicated the increment after the cells merged. During the transition, the characteristic patterns were observed on the increment of positive core vorticity and K_dp at 2 km and 5 km of Constant Altitude Plan Position Indicator (CAPPI) height, respectively, at the same position. The Z_dr column was not observed after the cell merging; however, it was identified 5 min after the cell had merged. In contrast, the K_dp column was always identified after the cell merging, and the column showed an increment of intensity 5 min after the cells had merged. The positions of both Z_dr and K_dp columns were located parallel with the location of the updraft. The results indicated a strong correlation of a maximum K_dp column depth above the melting height with the core positive vorticity, especially in the single-to-multicell case. Analysis of K_dp columns depth revealed the signatures of changing of updraft in the multicell development. The increased updraft intensity was mainly associated with an increase in vertical vorticity. With precipitation, the maximum K_dp column depth is a good indicator for deep convection updrafts, as the life phases of multicell development were controlled by updrafts, and the warm moist inflow from low-level.

 The seeder-feeder mechanism is a phenomenon in which raindrops from the upper layer catch cloud droplets in the lower layer of clouds, thus intensifying rainfall, and was considered the cause of enhanced rainfall over mountainous areas. However, in Typhoon No. 19 in 2019, the seeder-feeder mechanism was confirmed not only over mountainous areas but also over the plains. In this study, we examined the contribution of the Seeder Feeder mechanism to rainfall intensification in the mountainous area around Hakone and the Kanto plain by using an orographic rainfall estimation method based on the Tatehira model for Typhoon No. 19. The results show that rainfall enhancement by the Seeder Feeder mechanism occurred over both mountainous and plain areas. We think that this study will lead to further verification of "heavy rainfall due to stratiform precipitation with shallow convection" that may occur in the future.

 Railway operators enforce train operation control based on actual precipitation observed by rain gauges to ensure safe train operation in heavy rainfall events. Now by utilizing rainfall forecasting information they may make train operation safer. In this study, we study about a prediction method combining the translation model and the orographic rainfall model. About the area around Mt. Hakone when typhoon No. 19 in October 2019, we verified the prediction accuracy and examined the utilization method from comparisons with observation values of rain gauge. As a result, it was found that the estimation accuracy of the rain gauge observation value is improved by considering the orographic rainfall comparing with the case of the translation model only. In addition, we proposed a method to obtain a wide range information of prediction from multiple prediction results obtained by radar data of multiple altitudes.

 Recent years, there is a lot of disasters from line-shaped convective systems. The mechanism of outbreaks has not been clarified, and it is difficult to predict it. Necessity and contingency factors were rarely discussed separate. In this study, numerical experiments were conducted using LES(Large-eddy-simulation), which can exactly calculate turbulence and evaluate necessity and contingency in the presence of contingency, in order to distinguish each factor and to elucidate the detailed mechanism of oubreak. The result indicates that mountain waves caused by the topography of Awaji Island form a low-temperature region in the southern part of Mt. Rokko, contributing to the rise of other warm air masses. In addition, an ensemble experiment with random noise in the initial value of potential temperature suggested the existence of an influence of contingency factors on occurrence.

 The results of the trend analysis of the GPV and AMeDAS data showed that the daily rainfall differed by rainfall rank. The results of the trend analysis of GPV and AMeDAS showed that the trend of daily rainfall was different for each rainfall rank. The results of the trend analysis of GPV and AMeDAS showed that the daily rainfall differed by class, while the hourly rainfall and 10-minutes rainfall did not differ by rainfall rank, indicating that the trend analysis of AMeDAS results as a representative of Thiessen dominated area should be performed with caution. Furthermore, the applicability of radar rain gauges to river planning was examined by comparing summer maximum basin mean rainfall data from GPV and AMeDAS for each year. As a result, it was found that the distributions of GPV and AMeDAS were generally similar, and it was evaluated that the radar rain gauges could be applied to river design planning.

 To evaluate risk of landslide occurrence based on rainfall, which is a trigger factor, the 1st tank of Soil Rainfall Index tank model as well as the 60-minute cumulative rainfall used by the Landslide Information Delivery System as risk assessment indexes using XRAIN real time precipitation data, were recalculated for 15 years from 2006 to 2021 using the analytical rainfall, and the results were examined. Due to the large variation in the values, the probability of event occurrence per unit of time was calculated using a Poisson distribution. The results show that the probabilities are substantial for almost all of Kyushu, the Pacific coast of Shikoku and the Kii Peninsula, confirming that the probability of landslides occurring in these areas is large due to regular heavy rainfall.

 We investigated an index focusing on K_DP (specific differential phase), to evaluate the vertical gradient of Z_H (radar reflectivity) above the freezing level. We proposed an index (AI; Aggregation Index) that express differences in aggregation degree by taking the ratio of K_DP to Z_H. We confirmed that the index AI at an altitude around -9 °C altitude can evaluate the gradient of Z_H above the freezing level when K_DP > 0. We also confirmed that the index AI at -9 °C altitude decreased as the predominant snowfall particles on the ground changed from larger and slightly rimed to smaller and densely rimed in comparison with snowfall particle observations on the ground.

 Rain gauges play an important role in estimating the spatiotemporal distribution of precipitation and should be installed in effective locations. This study investigates better rain gauge locations using the data-driven sparse sensor placement method (SSP). The SSP can also reconstruct the entire rain fields from a limited number of sparse observations. This study extends to use data assimilation for the reconstruction of the entire rain field (DA-based reconstruction). Using Radar-raingauge analyzed precipitation data from the Japan Meteorological Agency, we investigated the impacts of SSP-based placements of rain gauges in Hokkaido, Japan. We found that DA-based reconstruction yields better estimates on rain fields than the commonly-used nearest neighbor method when the present AMeDAS observation sites are used. The SSP reduced errors in estimated rain fields relative to the AMeDAS placements, suggesting that SSP can be used to place better rain gauge stations in Japan.

 While observations play essential roles in reducing forecast errors in numerical weather forecasts, optimization methods of sensor placements have not been developed yet. Recently, a data-driven sparse sensor placement (SSP) method based on the proper orthogonal decomposition (POD) was proposed for determining efficient sensor placements as well as reconstructing spatial fields of dynamical systems. The SSP method identifies observation placements by maximizing Fisher information matrix F determined by the POD modes. This study aims at improving the SSP methods for large-dimensional dynamical systems such as atmosphere. Through a series of experiments using sea surface temperature (SST) data, reconstruction accuracy was successfully improved using data assimilation approach relative to the original reconstruction method of the SSP. We found that observation placements using singular values is more sensitive to primary modes, and more suitable when more modes are used for the SSP. Minimizing the trace of F⁻¹ yielded smaller errors in reconstructed fields than maximizing the determinant of F, suggesting that the former is more suitable implementation for maximizing Fisher information matrix F for the problem of SST.

 In order to categorize the solutions to the problems that occur when constructing the flood forecasting system for small and medium-sized rivers, we constructed the flood forecasting system for 125 rivers in Japan. During the construction, the following problems arose. (1) The reproducibility of the water level hydrograph in a small basin is low due to the influence of the analysis rainfall specifications. (2) The water budget does not match due to the accuracy of the rainfall product. (3) Low water reproducibility is low due to reduced the accuracy of HQ formula. As solutions to these problems, we proposed (1) use of a rainfall product with finer temporal resolution, (2) use of other rainfall products such as high-resolution precipitation nowcast, and (3) re-creation of the HQ formula by correcting the cross section. In particular, the accuracy of rainfall products is affected by the spatial position of rivers and the rainfall distribution during floods, so it is important from the viewpoint of model building to select an appropriate rainfall product by checking the water budget and comparing it with the ground rainfall.

 To develop a real-time flood forecasting system for small and medium-sized rivers, we investigated the characteristics in the case of applying a particle filter to a rainfall runoff model that expresses runoff processes with different time constants such as surface flow, intermediate flow, and river channel flow. The results found that the forecasted water level decreased due to the time delay of the runoff processes when the particle filter acted to make negative corrections to the slope water depth in the increment period. We also indicated that it is possible to prevent the accuracy of water-level forecasting from decreasing by adding an algorithm that sequentially corrects the correction coefficient of the particle filter and changes the initial distribution of the state value.

 Data assimilation can improve forecast accuracy of dynamical models by combining model state variables and real-world observations. This study applied the ensemble Kalman filter (EnKF) for a rainfall-runoff-inundation (RRI) model to adjust model state variables with operational water-level observations. In contrast to atmospheric models, model state errors do not propagate in the non-chaotic RRI model. Therefore, it is important to explore error inflation methods for providing appropriate background error covariance for the EnKF. For that purpose, this study perturbed rainfall intensity for ensemble members as a way of the covariance inflation.

 A series of experiments with and without EnKF were employed in Omono River in Akita Prefecture. Our experiments showed that predicted water level was improved at both observed and unobserved stations compared to the RRI simulations without assimilation. This study also investigated effective localization methods for the RRI model. The application of localization along the river channel was found to perform as well as traditional localization based on Euclid distances commonly used in atmospheric data assimilation.

 In recent years, the flood risk in urban area is increased due to the frequent extreme rainfall. Since underground spaces are vulnerable to flooding, it is necessary to idenify the risk of flooding and prepare for flood damage in underground spaces. In this study, we analyzed inundation of both ground and underground spaces in Sannnomiya combining inundation analysis in Kobe and underground space below Sannnomiya-Station using 1m mesh elevation data. We revealed that it is important to capture subtle changes in inundation depending on availability of elevation data. In addition, evacuation simulation in the underground space was conducted by considering the social distance due to the COVID-19.

 Extreme weather conditions caused by global warming have resulted in frequent floods in recent years. In the highly urbanized area of Tokyo, one of the most vulnerable areas for large-scale flood damage is underground space. Tokyo’s 23 wards have a network of underground tunnels connecting many underground stations, and floodwaters can easily spread through these tunnels. Previous studies have discussed the flooding process in subway tunnels under large-scale external force conditions. In this paper, a new method for estimating the inflow into a subway station entrance was investigated to predict the inundation process in subway tunnels. As a result, the inundation in the tunnel varied depending on the way of estimation used, indicating the importance of proper evaluation of the inundation depth at the entrance to the subway station. It was also confirmed that the installation of watertight panels is effective and that appropriate train deterrent measures are important.

 Heavy rainfall has been occurring frequently in many areas due to climate change in recent years, and Typhoon No. 19 in 2019 caused a lot of damage due to levee failures, river overflows, and internal flooding in many parts of Japan. In this study, inundation forecasting calculations for Chofu City and Mitaka City, which were actually damaged by Typhoon No. 19, as well as the adjacent Musashino City, were conducted using S-uiPS, a sophisticated inundation forecasting method, for the assumed maximum rainfall. This method has been used in the past for the 23 wards of Tokyo and the cities of Kawasaki and Yokohama, and was applied to Chofu, Mitaka, and Musashino in this study. In particular, we focused on depressions and underpasses, where the inundation depths are particularly pronounced, to elucidate the inundation process. The maximum inundation depths of the three cities and the 23 wards of Tokyo were compared and discussed using various quantities related to the sewerage network.

 In recent years, heavy rainfall have caused a number of disasters in Japan. Among them, oil spill accidents in flooded areas have been reported. In this study, numerical predictions using Lagrangian approach methods were investigated with the aim of understanding oil flow in flooded areas. Comparison with Fay's model showed that the temporal variation of radius of oil slick in still water condition can be reasonably calculated by applied models. Next, calculations were performed assuming an oil spill incident in an inland flood area. The computed results showed that the oil flows due to the flood flow and wind, however that the extent of the oil distribution varies depending on the modelling.

 This study aims to generalize a high-resolution distributed rainfall-runoff model to realize discharge predictions in ungauged urban catchments by applying identified general hydrological parameter sets corresponding to land-use categories. The parameter sets were identified and examined at 32 urbanized small catchments located in Osaka Prefecture. To obtain general hydrological parameter sets, parameter values of 1K-DHM, a high-resolution distributed rainfall-runoff model, were obtained for each land-use category so that the simulated discharges could fit with those calculated by the synthetic rational formula method (SRFM). Additionally, the parameter values of the two dominant land-use types were estimated using the Shuffled Complex Evolution optimization method (SCE-UA), and these were replaced with the previously obtained parameters. These two identified parameter sets were validated for 30 catchments with three rainfall events. According to the validation results, we found that the 1K-DHM with the two parameter sets showed better performance than the SRFM in peak discharge estimation and Nash efficiency. Furthermore, the two identification methods showed similar prediction ability in terms of the NSE evaluation, and the latter generated better results regarding stricter NSE value. These findings suggest that a distributed hydrological model with generalized parameter sets based on high-resolution catchment information has the potential to achieve discharge forecasts of flash floods in small ungauged urban catchments.

 We applied the bivariate extreme value theory to d4PDF 4-degree rise experiment in the Kanto and Kyushu regions and the metropolitan areas and analyzed the future change of cooccurrence probability of floods over the design level (extreme floods). Its return period in the 4-degree rise scenario was estimated as 800 years in Kanto and 473 years in Kyushu which is similar to the past experiment, indicating that future changes in extreme floods will be caused by enhanced frequency of extreme floods in each river system. That between the Ara and Shonai Rivers was obtained as 4,000 years by non-parametric estimation while parametric estimation was unstable; therefore, further ensemble enrichment or meteorological analysis is crusial for more robust estimation.

 For comprehensive disaster prevention and mitigation measures, multi-stage inundation estimation is needed nationwide, including for small rivers. d4PDF is useful for this purpose because it provides various rainfalls with small extensions, including in areas with little observed rainfall. However, it is too large a workload to define a rainfall return period for each individual river in a large d4PDF ensemble, and to perform runoff and inundation analysis. To reduce this workload, this study investigated a method to represent the flow rate of a specific watershed using rainfall data that can be shared by multiple rivers in a limited number of d4PDF events. As a result, it was found that by using a maximum of about 30 rainfall data and taking the median or upper value of the obtained flow rates, it is possible to represent the flow rates at multiple locations and at multiple scales with an error of about 10%.

 Taiwan has been devastated by water-related disasters during the wet season and will face more challenges under climate change. The uncertainty of future projections of extreme rainfall events is primarily derived from the internal climate variability. The d4PDF, especially at a 20-km resolution, has the potential to assess the impact of climate change on catchment-scale hydrologic extremes in Japan. The present study first compared the probability plots of annual maximum basin-averaged rainfall derived from rain gauge observations and d4PDF in four major river basins in Taiwan. In three out of the four catchments, d4PDF was in good agreement with observations, showing its overall applicability in Taiwan. For the other basin with large bias, we applied three bias correction methods to explore robust bias adjustment. Based on raw or corrected d4PDF, we reevaluated the return period of basin-averaged rainfall in Kaoping river basins during record-breaking events that caused severe water-related disasters in Taiwan and estimated it to be 120–125 years. This evaluation has not yet been achieved with limited and sparse observational data. Finally, the d4PDF 4-degree increase experiment data were analyzed, which showed a clear and common rate of increase in the rainfall amount of 10–40% at all the four river basins in Taiwan.

 Areal Reduction Factors, which have been used as one method of analyzing regional extreme precipitation events, estimate the ratio of extreme precipitation between a location and a region, but cannot express the relationship between the timing of extreme precipitation events. This study proposes a method to express the likelihood of extreme precipitation events occurring at the same period for a location and a region by applying spatial extreme modeling that can express the spatial autocorrelation of extreme values between locations. Using the database for Policy Decision making for Future climate change for 1,200 years, which is a long-term climate simulation data around Japan, the correlation of extreme precipitation events at a point and a region is expressed by the proposed method. It was confirmed that the proposed method can express how the possibility of extreme precipitation events occurring at the same period is affected by climatic and geographical conditions.

 Scale law is an important concept to comprehend the physical phenomena of nature, whose applicability has also examined to the depth-duration-frequency relationship in the hydrological research. In the frequency analysis of extreme precipitation, the large amount of estimation error is inevitable by extrapolation against the return period to be employed for the design of flood disaster prevention. We propose a new system of the embedded frequency analysis with scale law, and demonstarate the effectiveness of estimation error reduction and the validity of application of the scale law through the model-selections by a rainfall dataset of Daru island, Papua New Guinea.

 Hydrological frequency analysis generally deals with annual maximum series of flood peak discharges or catchment average rainfalls during rainfall duration of the flood control plan. The shape parameter of the generalized extreme value distribution is closely related with the thickness of the upper tail of the probability density function. Because the peak flood discharge at a flood control reference point is closely connected with basin averaged rainfall in the basin upper than the reference point during adequate duration, it is expected to get similar results between peak discharge direct frequency analysis and runoff analysis after rainfall depth frequency analysis, however, they are often different. This paper shows the reasons of the difference and matters to be attended to flood control planning.

 We have published several reports explaining that the “Guide for River Plan Design for Small and Medium-sized Rivers” has some shortcomings. Although comparison of the goodness-of-fit of some probability distributions using SLSC is inappropriate, many analysts apparently do not understand our insistence and do not agree with our theory or our explanation of it. Therefore, we shall attempt a simpler explanation of our insistence using the mean of SLSC, for which we have succeeded with theoretical derivation. In the process of obtaining the mean, we use the joint probability density function of order statistics.

 We have insisted that the method for evaluating the goodness-of-fit of the probability distribution in the “Guide for River Plan Design for Small and Medium-sized Rivers” must be modified because of several important shortcomings. Although we regard our insistence as valid from an academic perspective, we can understand the difficulty of analysts in government agencies in changing their methods quickly from the perspective of policy continuity. Therefore, we show some issues related to the conventional method, which they seem to prefer. Especially, this report describes some considerations related to evaluating the SLSC of the three-parameter probability distribution and Etoh’s distribution. Finally, we present guidelines for analysts, in which our reports are aggregated.

 Since WBGT is an index to evaluate the risk of the thermal environment for human health, they have been measured at several points in Japan. We proposed a formula to estimate WBGT from the thermal infrared measured in Himawari-8, Band 7, 13, 15 and Band 8, 10, which are sensitive to the cloud water and water vapor, respectively. The equation considered the height correction too. The estimated WBGTs were accurate as the root mean square errors averaged among 75 monitoring locations around Tokyo were within 2.0 degree. The improvement of the estimation was confirmed regarding the different altitude and the cases of the cloud cover.

 The urban heat island becomes severer. One of the countermeasures is "cool roof", which enhances the roof albedo and reduce the solar energy absorption to the city. There are many studies investigating the effect of cool roof. However, due to the lack of roof albedo data in city scale, there are uncertainties about temperature reduction by cool roofs in the previous works. We constructed a super-resolution model “ExEEGAN” using deep learning and attempted to estimate the individual roof albedo by increasing the spatial resolution of open satellite data. Training was done with a commercial satellite data of World View-3 which resolution is 1.24 m and fine enough to caputure individual buildings and houses. ExEEGAN successfully created finer images of open satellite data of both Landsat-8 and Sentinel-2, and identified roof albedos more accurately than the ordinary image interpolation methods, or bicubic and nearest neighbor interporation methods. RMSE of estimated roof albedos of individual buildings estimated from Sentinel-2 0.0279 in ExEEGAN, 0.0451 in bicubic interporation, and 0.0458 in nearest neighbor interporation.

 Observation of the water surface area of lakes is essential for understanding the amount of water stored in them. This study analyzed the long-term and seasonal changes in the area of natural lakes and reservoirs using a global dataset of monthly area estimates. The global area of natural lakes has been decreasing while the seasonal amplitude is increasing. Those trends are not significant in reservoirs. Seasonal variations and their interannual trends were different depending on the size of reservoirs. The results were consistent with the results of the change in the terrestrial water storage by gravity observation, but some areas showed different trends. Thus, satellite observation of lake surface area provides helpful information for water resource management. In combination with water surface elevation observation, it is expected to enable a more comprehensive estimation of water storage volume.

 Small satellite constellation (SSC) technology has been evolving rapidly and a project of SSC which carries passive microwave (PM) sensors for earth observation is now being planned. Toward application of such new technology to hydrometeorology in near future, this study proposes a new validation method of local- and river-basin-scale rainfall prediction performance assimilating virtual but realistic SSC-PM measurements by combining virtual observation simulation and observing system simulation experiment (OSSE). Results of application of the proposed method showed that frequent assimilation of SSC-PM observations has a potential to remarkably improve short-term rainfall prediction. Also, changes in frequency and time step of observations depending on SSC structure have a large impact on rainfall prediction accuracy.

 The effect of the change of the wet-soil dielectric model in the microwave soil moisture retrieval algorithm was examined by comparing among Dobson, Mironov, and our proposing dielectric models at 1.4, 10, and 36 GHz. The result showed that Mironov and proposing models tend to estimate larger soil water amount, but with different effects depending on observation frequencies, seasons, and soil types.

 In the global satellite precipitation product GSMaP (Global Satellite Mapping of Precipitation), Greenland is being masked due to the difficulty in snowfall estimation over the region. In southern Greenland, the GSMaP’s radiometer retrieval algorithm for the Global Precipitation Measurement (GPM) Microwave Imager (GMI) tends to estimate significantly larger snowfall rates compared to other global precipitation products, which suggests an overestimation bias of the GSMaP snowfall. This study investigates the causes of the bias focusing on the microwave characteristics of the snow-covered surfaces in southern Greenland.

 Normally, snow-cover land surfaces are accompanied by a scattering signature of microwaves, where the brightness temperature (TB) at the high-frequency channel is lower than that of the low-frequency (i.e., TB19 – TB89 > 0). However, in southern Greenland, the scattering signature of snow-cover suface is absent (i.e., TB19 – TB89 < 0). The geographical pattern of such scatter-free snow-cover surfaces in southern Greenland shows a close similarity to that of the GSMaP snowfall overestimation, impling the unique microwave characteristics are related to the GSMaP’s snowfall overestimation. Because the lookup tables used for GSMaP snowfall estimation are developed based on global observations, it is geared toward general relationships between microwave TBs and surface snowfall. The result of this study suggests that a separate lookup tabel is reauired for the snowfall estimation over snow-cover scatter-free surfaces.

 Estimating the amount of glacier melt and assessing its impact on disasters and water resources are important issues. Debris, rocks covering the glacier surface, is a non-negligible factor that affects the melting speed of glaciers. In this study, we applied methods using satellite remote sensing data to estimate debriscover distribution and calculate thermal resistance over a wide area. The estimation of debris-cover distribution showed that 4.8% of global glaciers were covered with debris and the debris-covered rate varied by regions. According to the thermal resistance estimation in Central and South Asia, there were many thick debris which prevent glaciers to melt. These results suggested the importance of considering the effects of debris when estimating glacier melting, and provided basic data for broadening the analysis.

 The purpose of this study was to analyze the runoff in small river basins and to predict the impact of depopulation. Depopulation is expected to promote land-use change and channel change and alter the hydrological processes in the basins. A distributed runoff model evaluated the changes in inflow with forested land use and vegetation cover after no population. The annual maximum flows decreased in the Sukawa and Ohtani Rivers, indicating a decrease in flood risk. In the lack of river management, the risk of inundation increases in the vicinity of the river channel. In addition to land-use change, the inundation processes were evaluated by the flow change. The annual maximum flow was further reduced in the Sukawa and Ohtani Rivers, and runoff was delayed by one hour. The results indicate that the inundation in uninhabited basins may reduce flood risk in the downstream areas.

 In this study, a flood simulation was conducted and hearings were held with local residents to clarify the flooding situation in the city of Hitoyoshi and determine the factors that caused human damage, with a focus on the Omizo River basin, during the Kuma River heavy rainfall in July, 2020. Consequently, a maximum depth of 2.7 m and the maximum velocity of 2.4 m/s was obtained in certain areas around the Omizo River. In the Omizo River basin, it was confirmed that flooding from rivers flowing down the mountain valley and the roads constructed in the rice paddy field areas acted as cross levees against flooding, which has not been reported before. In addition, the results of the estimation of the flooding conditions during heavy rainfall in the affected areas of the five victims around the Omizo River indicated that flooding occurred from three direction: "Kuma River in the south, Omizo River in the north, and Fuku River in the west". It was also observed that there is a risk of flood-related death even at a flood depth and velocity limit where underwater walking is possible.

 We quantified the disaster mitigation effect when the agricultural land was converted into a rice field dam over a wide area in the basin on the left bank of the middle course of the Kuma River using a flood analysis model. We also calculated the difference in effect between the case where the rice field dam is placed in the flooded plain and the case where it is placed in the tributary alluvial fan area.

 The peak time of the tributaries became slower due to the wide-area rice field damming, while the water level rose before the peak. Although the rice field dam in the alluvial fan area contributed to the reduction of inundation near the confluence of the main tributary, the conversion of the rice field dam in the inundation plain area increased the inundation depth in the surrounding area and tended to raise the tributary peak slightly. As a result, it was suggested that when positioning the rice field dam in the flood control plan, the difference in function depending on the arrangement should be strategically considered.

 The Weakly Compressible Smoothed Particle Hydrodynamics (WCSPH) has been reformulated to simulate overland flow on natural terrain due to rainfalls. The rainfall is lumped into discrete particles falling over the terrain and the overland flow is simulated as three dimensional free surface flows over topography following the WCSPH method. The terrain and objects on it such as buildings and other strictures are represented by boundary particles that are distributed over the combined surfaces having the normal directions and the roughness height used for setting the dynamic boundary conditions and the actual and the potential moisture contens used to set the infiltration conditions. The basic method is verified with the experimental data of rainfall runoff from a model plot and comparing with existing runoff models based on two-dimensional shallow water approximation. Then it is applied to a simulation of rainfall runoff over a real catchment in Malaysia.

 In this study, we developed a unit cost model of structural river management, reflecting differences in economic development and construction cost factors in different regions. Specifically, by performing multivariate analysis of multiple construction cost factors such as worker wages and location and the cost of structural river management projects around the world, we developed a model that represents the unit cost of structural river management using two factors: the hourly wage of skilled workers and the difference in construction costs among regions (location factors). The developed model explained approximately 82% of the reported unit cost of river management. The model reduced the cost estimation error by 51% on average compared to the simple methods using GDP. Especially in high-income countries, the estimated unit cost of structural river management was close to the actual value. The model and the SSP scenario were used to project the unit cost of structural river management in each country, and the results showed that the unit cost of structural river management in Japan in 2100 was estimated to be more than eight times higher than in 2020, depending on the scenario.

 This study uses the Rainfall-Runoff-Inundation (RRI) model applied to the entire Japan with 150-m resolution to conduct large-scale flood simulations for the Kumagawa flood in 2020 and Typhoon Hagibis in 2019. By reflecting actual river cross sections and elevation data corrections, the river water level and inundation simulations were improved for the 2020 Kumagawa flood. It was important to remove the effects of river channels reflected in the topographic data and adjust the elevation corresponding to the surrounding floodplain levels before explicitly embedding actual cross section data into the model. In the case of Typhoon Hagibis, the simple modeling of floodgates and additional parameter setting in the floodplain were important.

 This paper examined the influence of machine learning detection accuracy of riverine land covers using satellite images on their application of flood flow simulation. A planar 2D flow model was employed for the accuracy examination with riverbed roughness detected from the riverine land cover classification by random forests. Examined here were two cases with different machine learning training for a 2 km channel section in the Kurobe River. The result indicated that the flood flow model in this study could simulate both the velocity field and water surface profile with an accuracy high enough for practical flood flow analysis when the F-measure of the riverine land cover detection exceeded 0.8. It could suggest the practical applicability of F-measure for riverine land covers as an accuracy index necessary for the flood flow simulation.

 The hydraulics of an open channel is summarized in the energy gradient I_e, which can be determined when a pair of v and h is known. Although I_e has conventionally been calculated theoretically based on the coupled equation of motion and continuity, there is no guarantee that such a theoretically calculated I_e based on v and h will match the actual hydraulic I_e. If v can be calculated with the measured depth of flow h known, I_e that matches the actual hydraulic conductivity can be obtained. In this study, we proposed a method of estimating two-dimensional velocities on sandbars by feeding the measured flow depths to a Mass-Consistent model. As a result, it was confirmed that the Mass-Consistent model can calculate the appropriate corrected velocity, and that it agrees with the measured velocity using a laser Doppler velocimeter.

 The driftwood accumulation tests at a single pier bridge were conducted. We evaluated the critical condituion for driftwood blocking by changing the woody debris length. We measured the backwater rise during the driftwood accumulation tests and evaluated the blocking ratio of the woody debris jam. The inclination angle of trapped log relative to the flow direction was measured using a camera placed above the flume and examined the effect of the wood debris length on the driftwood carper shape. During the experimets, the force exerted on the bridge increases due to the driftwood accumulation. We also measured the force exterted on the bridge using a force gage.

 There are few observational data on the production mechanism of submerged wood and its transport process in rivers, and many unclear points still remain. In this study, we focused on the long-term capturre by the backflow circulation behind a weir as one of the causes, and verified it by model experiments. It was quantitatively shown that the scale of the backflow circulation changes depending on the water level difference between the downstream and upstream of the weir, which affects the capture rate. Further, the critical tractive force is considered for the submerged wood partially buried to the flume bed. For the case of being buried horizontally, empirical formulae for the normalized critical tractive force were proposed. We also dealt with cases of being buried diagonally to the bed, and considered the effect of pitch and yaw angles on the critical tractive force.

 This study investigated some influences of vegetation flexibility on flow structure and suspended load transport process around vegetation through laboratory experiments. For four cases with different vegetation heights, flow velocity distributions were measured by vertical and horizontal plane PIV, and sediment deposition was observed around a vegetation patch. Results of the velocity measurement indicate that for more deflected vegetation case, transverse momentum transport by horizontal vortex is more dominant than wall-normal transport by vertical vortex. This difference in vortex structure seems to determine adjustment process of mean flow and areas of fine sediment deposition.