River Basins In Japan Research Articles

Impacts of High-Concentration Turbid Water on the Groundwater Environment of the Tedori River Alluvial Fan in Japan

The occurrence of high-concentration turbid water due to a large landslide in the upper reaches of the Tedori River Basin in Japan in May 2015 led to a rapid decline in the groundwater levels within the alluvial fan. However, factors other than turbid water, such as changes in precipitation patterns, can have a significant impact on groundwater levels but have not been thoroughly investigated. By analyzing the relationship between river water and groundwater levels, we found that by 2018, conditions had returned to those observed prior to the turbidity events. Regarding seepage, we found that approximately 24% of the Tedori River’s discharge contributed to seepage before the turbidity event. In contrast, during the post-turbidity years, seepage decreased between 2015 and 2017 and returned to the pre-turbidity levels by 2018. Furthermore, by constructing a hydrological model and examining the contributions of turbidity and precipitation, we found that in 2015, turbidity contributed to 76% of the groundwater level changes, whereas precipitation accounted for 24%. In contrast, in 2016, turbidity contributed to 67%, while precipitation contributed to 33%. In essence, the first year was characterized by a significant contribution from turbidity, while precipitation also played a significant role in groundwater level fluctuations in the second year.

Numerical evaluation of mercury concentration by using a distributional multimedia model in the Lake Biwa-Yodo River Basin, Japan

A distributional multimedia model was developed and applied to the Lake Biwa-Yodo River Basin in Japan to reproduce the mercury level in different environmental media. This model was developed based on a Level III steady-state fugacity model, and the space was divided into four environmental media (atmosphere, water, soil, and sediment). The mass transfer of Hg in this model consists of emission, deposition, sedimentation inside one medium, and advection between different media. The dissolution rate and ion exchange equilibrium have also been considered. We estimated Hg emissions in the Lake Biwa-Yodo River Basin from 1957 to 2009 based on the Pollutant Release and Transfer Registry (PRTR) system and the domestic usage of Hg in Japan. The distribution of emission was based on land data, including industrial land area, industrial location, and proportion of the population. The calculated and observed Hg concentrations were compared to evaluate the model. At both large scale and small scale, results showed that the distributional model could predict Hg concentrations in all environmental media. Sediment and soil media showed the accumulation of Hg by showing the higher concentrations than that of other media. In terms of geographical distribution, the urban area and downstream of the river showed high Hg concentrations owing to high Hg emissions. The Hg concentration in the atmosphere was affected by the transboundary pollution. Thus, the distributional multimedia model could reliably calculate the environmental Hg concentration and be utilized in environmental monitoring and management.

A Transfer Learning Approach Based on Radar Rainfall for River Water-Level Prediction

River water-level prediction is crucial for mitigating flood damage caused by torrential rainfall. In this paper, we attempt to predict river water levels using a deep learning model based on radar rainfall data instead of data from upstream hydrological stations. A prediction model incorporating a two-dimensional convolutional neural network (2D-CNN) and long short-term memory (LSTM) is constructed to exploit geographical and temporal features of radar rainfall data, and a transfer learning method using a newly defined flow–distance matrix is presented. The results of our evaluation of the Oyodo River basin in Japan show that the presented transfer learning model using radar rainfall instead of upstream measurements has a good prediction accuracy in the case of torrential rain, with a Nash–Sutcliffe efficiency (NSE) value of 0.86 and a Kling–Gupta efficiency (KGE) of 0.83 for 6-h-ahead forecast for the top-four peak water-level height cases, which is comparable to the conventional model using upstream measurements (NSE = 0.84 and KGE = 0.83). It is also confirmed that the transfer learning model maintains its performance even when the amount of training data for the prediction site is reduced; values of NSE = 0.82 and KGE = 0.82 were achieved when reducing the training torrential-rain-period data from 12 to 3 periods (with 105 periods of data from other rivers for transfer learning). The results demonstrate that radar rainfall data and a few torrential rain measurements at the prediction location potentially enable us to predict river water levels even if hydrological stations have not been installed at the prediction location.

Unravelling and improving the potential of global discharge reanalysis dataset in streamflow estimation in ungauged basins

Mastery in forecasting the streamflow is of great importance in environmental and sustainability research. Although many global-scale reanalysis products provide a new way to overcome the lack of streamflow records in ungauged basins, streamflow estimation through hydrological models remains a great challenge mostly due to inevitable biases. In this study, we developed a novel bias-correction system equipped with the proposed Piecewise Random Forest (P-RF) model to improve the potential of GloFAS-ERA5 (GloFAS), a global-scale river discharge reanalysis product, as a calibration benchmark for building hydrological models in ungauged basins. Considering three ungauged scenarios, several cases of temporal, spatial, and spatiotemporal bias-corrections were implemented with a total of 13 river gauges located in the Min River Basin in China, and the Fuji River Basin and the Shinano River Basin in Japan. Then, the well-improved GloFAS discharge was applied for the calibration of the Block-wise use of the TOPMODEL (BTOP) model to evaluate its performance in substituting the discharge observations. The results show that: (1) the bias-correction system performs better on the temporal scale, which applies to ungauged basins lacking long-term continuous observations; (2) the integrity and adequacy of the samples used for training the P-RF model have a significant impact on the spatial and spatiotemporal bias-corrections, and they can be reliably estimated by the proposed metric, Ratio of the Valid samples' Proportion; and (3) the statistical metric differences between the simulated discharges obtained by the calibrated BTOP model using observations and GloFAS discharge, are reduced by 25%–50% through the bias-correction.

Assessment of climate change impacts on river flooding due to Typhoon Hagibis in 2019 using nonglobal warming experiments

AbstractIn this study, a series of numerical analyses of meteorology, runoff, river flow, and inundation were performed to quantitatively evaluate the effects of historical warming on precipitation, discharge, water level, and flood inundation. This study was on the flood inundation of the Chikuma River Basin in Japan caused by Typhoon Hagibis in 2019. The historical warming impact on Typhoon Hagibis was analyzed by comparing nonglobal warming experiments (NonWs) and control experiments (CTLs) to reproduce the current situation. Calculated results showed that the ratios of the index of CTLs to that of NonWs (mean CTL to mean NonW) as indicators of the impact of historical warming were 1.08, 1.22, and 1.08–3.08 for total precipitation, peak river discharge, and peak water level (from pre‐flood level and high‐water level), respectively, and 48.1 and 595 for overflow depth and inundation volume for the Chikuma River, respectively. Results of the hydrologic‐sensitivity analysis indicated that the influence of historical warming during the last 40‐year period was already evident on overflow and flooding, whose sensitivities were higher than those of discharge and water level.

Near full-automation of COPMAN using a LabDroid enables high-throughput and sensitive detection of SARS-CoV-2 RNA in wastewater as a leading indicator

Wastewater-based epidemiology (WBE) is a promising tool to efficiently monitor COVID-19 prevalence in a community. For WBE community surveillance, automation of the viral RNA detection process is ideal. In the present study, we achieved near full-automation of a previously established method, COPMAN (COagulation and Proteolysis method using MAgnetic beads for detection of Nucleic acids in wastewater), which was then applied to detect SARS-CoV-2 in wastewater for half a year. The automation line employed the Maholo LabDroid and an automated-pipetting device to achieve a high-throughput sample-processing capability of 576 samples per week. SARS-CoV-2 RNA was quantified with the automated COPMAN using samples collected from two wastewater treatment plants in the Sagami River basin in Japan between 1 November 2021 and 24 May 2022, when the numbers of daily reported COVID-19 cases ranged from 0 to 130.3 per 100,000 inhabitants. The automated COPMAN detected SARS-CoV-2 RNA from 81 out of 132 samples at concentrations of up to 2.8 × 105 copies/L. These concentrations showed direct correlations with subsequently reported clinical cases (5–13 days later), as determined by Pearson's and Spearman's cross-correlation analyses. To compare the results, we also conducted testing with the EPISENS-S (Efficient and Practical virus Identification System with ENhanced Sensitivity for Solids, Ando et al., 2022), a previously reported detection method. SARS-CoV-2 RNA detected with EPISENS-S correlated with clinical cases only when using Spearman's method. Our automated COPMAN was shown to be an efficient method for timely and large-scale monitoring of viral RNA, making WBE more feasible for community surveillance.

Cadmium body burden and health effects after restoration of cadmium-polluted soils in cadmium-polluted areas in the Jinzu River basin.

Itai-itai disease is caused by environmental cadmium (Cd) pollution in the Jinzu River basin in Japan. To reduce the Cd contamination of rice, soil restoration of paddy fields was carried out. We evaluated the effect of soil restoration on the health status of residents of the former Cd-polluted area. Participants were 1,030 men and 944 women who lived in the area of restoration of Cd-polluted rice paddies. First morning urine was collected and urinary Cd, β2-microglobulin (β2MG), and N-acetyl-β-D-glucosaminidase (NAG) levels were measured. Associations among age, years of residence before and after soil restoration, and urinary Cd, β2MG, and NAG levels were evaluated by multiple regression analysis. The geometric mean (interquartile range) of urinary Cd (µg/g Cr) was 1.00 (0.58-1.68) in men and 1.67 (1.02-2.91) in women. The geometric means of urinary β2MG (µg/g Cr) and NAG (U/g Cr) were 174.6 (92.6-234.2) and 1.47 (0.72-3.14) in men, and 217.6 (115.3-28.7) and 1.48 (0.73-2.96) in women, respectively. Urinary Cd, β2MG, and NAG were significantly positively correlated (p < 0.01 all). Age and duration of residence in the Cd-polluted area before soil restoration were independently associated with urinary Cd, β2MG, and NAG. Among the 916 participants who had resided in the area before the soil restoration, urinary Cd concentrations were significantly higher, thus by 1.03-fold (95% CI, 1.01-1.04) in men and 1.03-fold (95% CI, 1.01-1.05) in women, when the years of residence before soil restoration by each 5-years increment. By contrast, urinary Cd concentrations were significantly lower, thus 0.97-fold (95% CI, 0.96-0.99) lower in men and 0.97-fold (95% CI, 0.95-0.99) lower in women, by each 5-year increment of residence after soil restoration. A similar association was observed for urinary β2MG concentration, and no significant association was observed for urinary NAG levels in men or women. Cd exposure and associated renal tubular dysfunction in residents of a former Cd-polluted area were influenced by Cd exposure from the environment prior to soil restoration. Soil restoration in Cd-polluted areas reduced the Cd exposure of local residents.

Influence of Data Length on the Determination of Data Adjustment Parameters in Conceptual Hydrological Modeling: A Case Study Using the Xinanjiang Model

Minimum data length is vital to guarantee accuracy in hydrological analysis. In practice, it is sometimes determined by the experiences of hydrologists, leading the selection of the acceptable minimum data length to an arguable issue among hydrologists. Therefore, this study aims to investigate the impact of data length on parameter estimation and hydrological model performance, especially for data-scarce regions. Using four primary datasets from river basins in Japan and USA, subsets were generated from a 28-year dataset and used to estimate data adjustment parameters based on the aridity index approach to improve the parameter estimation. The influence of their length on hydrological analysis is evaluated using the Xinanjiang (XAJ) model; also, the effectiveness of outlier removal on the parameter estimation is checked using regression analysis. Here, we present the estimation of the most acceptable minimum data length in parameter estimation for assessing the XAJ model and the effectiveness of parameter adjustment by removing the outliers in observed datasets. The results show that between 10-year to 13-year datasets are generally sufficient for the robust estimate of the most acceptable minimum data length in the XAJ model. Moreover, removing outliers can improve parameter estimation in all study basins.

Improving Snow‐Process Modeling by Evaluating Reanalysis Vertical Temperature Profiles Using a Distributed Hydrological Model

AbstractThe use of the Japanese 55‐year Reanalysis (JRA55) vertical temperature profile (VTP) has been suggested in previous studies for estimating gridded air temperatures at high elevations in data‐scarce regions to conduct hydrological simulations. In this study, we investigate and further enhance the applicability of VTP for hydrological simulations through several experimental sets using a distributed hydrological model with improved snow physics (WEB‐DHM‐S) based on water and energy budget to simulate the hydrology of a snowfed river basin in Japan, Kurobe Basin, while simultaneously correcting the snow precipitation estimates through optimization. We examined the simulated discharge, point snow depth, and snow cover, finding that the snow processes were highly sensitive to the individual station used with VTP for extrapolating air temperature to higher elevations, with corrected snowfall estimates differing by as much as 18%. We further compared this with simulations based on linear regression‐based lapse rates derived from station observations (scarce and often distributed at low elevations). It was found that the use of VTP improved discharge simulations but deteriorated point snow depth simulations at low elevations, compared with linear regression‐based lapse rates. A hybrid of the two methods led to better discharge and point snow depth simulations with reasonable snow cover simulations. The study advances the application of snow‐process models in data‐scarce regions by enhancing our understanding about the usage of VTP.

Utilizing environmental DNA for wide-range distributions of reproductive area of an invasive terrestrial toad in Ishikari river basin in Japan

Understanding the distribution of invasive species and their reproductive area is crucial for their managements after invasion. While catch and observation surveys are still embraced, environmental DNA (eDNA) has been increasingly utilized as an efficient tool for identifying these species in the wild. In this study, we developed a Bufo-specific eDNA assay for detecting an invasive, toxic, and terrestrial toad species Bufo japonicus formosus in Hokkaido, Japan, and applied it to their reproductive area at watershed scale. The eDNA assay was field-validated in ponds where B. japonicus were observed, as well as in rivers downstream of the reproductive ponds. Thus, the assay provided us an opportunity to screen watersheds that include their reproductive area by collecting downstream water samples. Applying it to the Ishikari river basin, the largest river basin in Hokkaido (c.a., 14,330 km2), we detected toad eDNA at 32 out of 73 sampling sites. They are composed of eleven sites with species observation records nearby (all the sites with observation records within a 500 m radius) and 21 sites without such records. And those eDNA detections were from twelve out of 31 river systems in the entire river basin. A Bayesian, multiscale occupancy model supported high eDNA detectability among those sites. These results suggest that the eDNA assay can efficiently estimate the presence of reproductive area of the terrestrial toad even from a distant downstream of the watershed, and that it provides a powerful means of detecting new reproductive area and monitoring further spread of invasive species.

Analysis of Changes in Land Use/Land Cover and Hydrological Processes Caused by Earthquakes in the Atsuma River Basin in Japan

The 2018 Hokkaido Eastern Iburi earthquake and its landslides threaten the safety and stability of the Atsuma River basin. This study investigates land use and land cover (LULC) change by analyzing the 2015 and 2020 LULC maps of the basin, and its impact on runoff and sediment transport in the basin by using the soil and water assessment tool (SWAT) model to accurately simulate the runoff and sediment transport process. This study finds that the earthquake and landslide transformed nearly 10% of the forest into bare land in the basin. The simulation results showed that the runoff, which was simulated based on the 2020 LULC data, was slightly higher than that based on the 2015 LULC data, and the sediment transport after the earthquake is significantly higher than before. The rate of sediment transportation after the earthquake, adjusted according to the runoff, was about 3.42 times more than before. This shows that as the forest land decreased, the bare land increased. Conversely, the runoff increased slightly, whereas the sediment transport rate increased significantly in the Atsuma River basin after the earthquake. In future, active governance activities performed by humans can reduce the amount of sediment transport in the basin.

River discharge prediction for ungauged mountainous river basins during heavy rain events based on seismic noise data

Several mountainous river basins in Japan do not have a consistent hydrological record due to their complex environment and remoteness, as discharge measurements are not economically feasible. However, understanding the flow rate of rivers during extreme events is essential for preventing flood disasters around river basins. In this study, we used the high-sensitivity seismograph network (Hi-net) of Japan to identify the time and peak discharge of heavy rain events. Hi-net seismograph stations are distributed almost uniformly at distance intervals of approximately 20 km, while being available even in mountainous regions. The Mogami River Basin in Northeastern Japan was selected as a target area to compare the seismic noise data of two Hi-net stations with the hydrological response of a nearby river. These stations are not located near hydrological stations; therefore, direct comparison of seismic noise and observed discharge was not possible. Therefore, discharge data simulated using a hydrological model were first validated with gauging station data for two previous rain events (10–23 July 2004 and 7–16 September 2015). Then, the simulated river discharge was compared with Hi-net seismic noise data for three recent events (10–23 July 2004, 7–16 September 2015, and 10–15 October 2019). The seismic noise data exhibited a similar trend to the time series of simulated discharge in a frequency range of 1–2 Hz for the selected events. Discharge values predicted from the noise data effectively replicate the simulated discharge values in many cases, especially the timing and amount of peak discharge.Simulated and predicted discharge near NIED Hi-net seismic stations in the Mogami River Basin for the event of October 2019 (Typhoon Hagibis).

How did the characteristics of the growing season change during the past 100 years at a steep river basin in Japan?

The effects of climate change on plant phenological events such as flowering, leaf flush, and leaf fall may be greater in steep river basins than at the horizontal scale of countries and continents. This possibility is due to the effect of temperature on plant phenology and the difference between vertical and horizontal gradients in temperature sensitivities. We calculated the dates of the start (SGS) and end of the growing season (EGS) in a steep river basin located in a mountainous region of central Japan over a century timescale by using a degree-day phenological model based on long-term, continuous, in situ observations. We assessed the generality and representativeness of the modelled SGS and EGS dates by using phenological events, live camera images taken at multiple points in the basin, and satellite observations made at a fine spatial resolution. The sensitivity of the modelled SGS and EGS dates to elevation changed from 3.29 days (100 m)-1 (-5.48 days °C-1) and -2.89 days (100 m)-1 (4.81 days °C-1), respectively, in 1900 to 2.85 days (100 m)-1 (-4.75 days °C-1) and -2.84 day (100 m)-1 (4.73 day °C-1) in 2019. The long-term trend of the sensitivity of the modelled SGS date to elevation was -0.0037 day year-1 per 100 m, but the analogous trend in the case of the modelled EGS date was not significant. Despite the need for further studies to improve the generality and representativeness of the model, the development of degree-day phenology models in multiple, steep river basins will deepen our ecological understanding of the sensitivity of plant phenology to climate change.

Simultaneous flood risk analysis and its future change among all the 109 class-A river basins in Japan using a large ensemble climate simulation database d4PDF

This study investigated simultaneous flood risk among all the 109 class-A river basins over Japan using the big data of (over 1000 years) annual maximum hourly flow simulated from a large ensemble climate simulation database for policy decision making for future climate change, and proposed a novel approach in its geospatial analysis by applying two informatics techniques: the association rule analysis and graph theory. Frequency analysis of the number of rivers with the annual maximum flow over the flow capacity in the same year (defined as simultaneous flooding here) indicated that simultaneous flood risk will increase in the future climate under 4-degree rise scenarios in Japan, whose increment is larger than the variation of sea surface temperature projections. As the result, the return period of simultaneous flooding in eight river basins (the same number as in a severe storm in western Japan, 2018, causing the second worst economic damage since 1962) is estimated at 400 years in the historical experiment, 25 years in the 4-degree rise experiment. The association rule and graph theory analyses for the big data of annual maximum flows in the future climate scenarios indicated that simultaneous flood occurrence is dominated by spatial distance at a national scale as well as by the spatial relation between mountainous ridges and typhoon courses at a regional scale. Large ensemble climate simulation data combined with the informatics technology is a powerful approach to simultaneous flood risk analysis.

Lifetime Cadmium Exposure and Mortality for Renal Diseases in Residents of the Cadmium-Polluted Kakehashi River Basin in Japan.

Very few studies have investigated the dose–response relationship between external cadmium (Cd) exposure and mortality. We aim to investigate the relationship between lifetime Cd intake (LCd) and mortality in the Cd-polluted Kakehashi River basin in Japan. Mortality risk ratios for a unit of increase of LCd and urinary Cd were analyzed using Cox’s proportional model. LCd was estimated based on residency and Cd in rice produced in their living areas. In men, mortality for all causes was significantly increased for a 10-μg/g Cr increase in urinary Cd, but not for a 1-g increase in LCd. In women, mortality risks for all causes and renal diseases, particularly renal failure, were significantly increased for a 10-μg/g Cr increase in urinary Cd. Similarly, mortality risks for renal diseases and renal failure were significantly increased for a 1-g increase of LCd in women. Comparing the contribution of two exposure markers to increased mortality in women, LCd was more effective for increasing mortality risks for renal diseases and renal failure, while urinary Cd contributed more to increased mortality risk for all causes. LCd may show a better dose–response relationship with mortality risk for renal diseases in women.

Relationship between urinary β2 -microglobulin concentration and mortality in a cadmium-polluted area in Japan: A 35-year follow-up study.

The relationship between urinary β2 -microglobulin (β2 -MG) and the risk of all-cause mortality and cause-specific mortality in a cadmium (Cd)-polluted area was investigated in 3139 inhabitants (1404 men and 1735 women) of the Kakehashi River basin in Japan at 35-year follow-up. The subjects had been participants in the 1981-1982 health impact survey that assessed Cd-induced renal dysfunction, as measured by the urinary β2 -MG concentration. Hazard ratios were calculated to assess the risk of all-cause and cause-specific mortality according to the urinary β2 -MG concentrations. Risk ratios (RRs) were assessed using the Fine and Gray regression model to account for competing risks of cause-specific mortality. The mortality rate was significantly higher in participants with urinary β2 -MG concentrations >1000 μg/g creatinine (Cr) for men and >300 μg/g Cr for women. In the proportional hazard model, higher urinary β2 -MG concentrations were associated with higher risks of circulatory disease, digestive system diseases, and kidney and urinary tract diseases in men and women, and with senility for women. However, when competing risk was accounted for, the RRs were significantly higher only for kidney and urinary tract diseases in men and women (RR for each increment of 1000 μg/g Cr [95% confidence interval]: 1.02 [1.00-1.04] for men, and 1.01 [1.00-1.02] for women). The long-term prognosis of participants with renal tubular dysfunction was poor, most likely due to kidney and renal tract diseases.

Inundation Analysis of the Oda River Basin in Japan during the Flood Event of 6–7 July 2018 Utilizing Local and Global Hydrographic Data

During the first week of July 2018, widespread flooding caused extensive damage across several river basins in western Japan. Among the affected basins were the Mabicho district of Kurashiki city in the lower part of the Oda river basin of the Okayama prefecture. An analysis of such a historical flood event can provide useful input for proper water resources management. Therefore, to improve our understanding of the flood inundation profile over the Oda river basin during the period of intense rainfall from 5–8 July 2018, the Rainfall-Runoff-Inundation (RRI) model was used, with radar rainfall data from the Japan Meteorological Agency (JMA) as the input. River geometries—width, depth, and embankments—of the Oda river were generated and applied in the simulation. Our results show that the Mabicho district flooding was due to a backwater effect and bursting embankments along the Oda River. The model setup was then redesigned, taking into account these factors. The simulated maximum flood-affected areas were then compared with data from the Japanese Geospatial Information Authority (GSI), which showed that the maximum flood inundation areas estimated by the RRI model and the GSI flood-affected area matched closely. River geometries were extracted from a high-resolution digital elevation model (DEM), combined with coarser resolution DEM data (global data), and then utilized to perform a hydrological simulation of the Oda river basin under the scenarios of backwater effect and embankment failure. While this approach produced a successful outcome in this study, this is a case study for a single river basin in Japan. However, the fact that these results yielded valid information on the extent of flood inundation over the flood-affected area suggests that such an approach could be applicable to any river basin.

Better governance for integrated management of the Lake Biwa—Yodo River Basin

AbstractThe present study discusses the efforts of the Union of Kansai Governments to resolve serious issues in the Lake Biwa—Yodo River Basin in Japan. It identifies many of the issues related to the basin on a ‘no man's land’ mindset of today's governmental framework, which has constrained both the will and the approach to remedy the associated problems. It also highlights better governance that not only encourages individual efforts, but also promotes collaboration and cooperation among the major stakeholders in the area, as important to developing acceptable solutions to relevant issues. The present study also recognizes objective scientific evidence as an effective driver for improving governance, being the basis for making informed decisions and highlighting the use of appropriate indicators to evaluate the conditions characterizing a specific location or the basin as a whole. The present study also describes the Union of Kansai Governments as a behind‐the‐scenes coordinator that gathers knowledge and intelligence on the basin, and works to integrate policies by getting basin stakeholders to gradually improve governance by repeating a cycle of: (a) recognizing the current situation; (b) identifying relevant issues to be addressed; (c) establishing a framework and policy for collaboration and corporation; and (d) taking necessary actions. To this end, the present study discusses the studies and efforts of the Union of Kansai Governments to develop and implement integrated management of this important interlinked lake–river water system in Japan.

The Role of the Spatial Distribution of Radar Rainfall on Hydrological Modeling for an Urbanized River Basin in Japan

Recently, the use of gridded rainfall data with high spatial resolutions in hydrological applications has greatly increased. Various types of radar rainfall data with varying spatial resolutions are available in different countries worldwide. As a result of the variety in spatial resolutions of available radar rainfall data, the hydrological community faces the challenge of selecting radar rainfall data with an appropriate spatial resolution for hydrological applications. In this study, we consider the impact of the spatial resolution of radar rainfall on simulated river runoff to better understand the impact of radar resolution on hydrological applications. Very high-resolution polarimetric radar rainfall (XRAIN) data are used as input for the Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) to simulate runoff from the Tsurumi River Basin, Japan. A total of 20 independent rainfall events from 2012–2015 were selected and categorized into isolated/convective and widespread/stratiform events based on their distribution patterns. First, the hydrological model was established with basin and model parameters that were optimized for each individual rainfall event; then, the XRAIN data were rescaled at various spatial resolutions to be used as input for the model. Finally, we conducted a statistical analysis of the simulated results to determine the optimum spatial resolution for radar rainfall data used in hydrological modeling. Our results suggest that the hydrological response was more sensitive to isolated or convective rainfall data than it was to widespread rain events, which are best simulated at ≤1 km and ≤5 km, respectively; these results are applicable in all sub-basins of the Tsurumi River Basin, except at the river outlet.

How Inter-Basin Transfer of Water Alters Basin Water Stress Used for Water Footprint Characterization

Water footprint assessments contribute to a better understanding of potential environmental impacts related to water and have become essential in water management. The methodologies for characterizing such assessments, however, usually fail to reflect temporal and spatial variations at local scales. In this paper, we employ four widely-used characterization factors, which were originally developed with global estimates of water demand and availability, to evaluate the impact that inter-basin transfer (IBT) of water has on water risk assessments and, consequently, on the evaluation of the soundness of water cycle. The study was conducted for two major river basins in Japan, where diversion channels were built to move water from the Tone river basin to the Arakawa river basin. Considering IBT, the available water in the Arakawa river basin increases a 45%, reducing the characterization factors a 44% on average and denoting their tendency to overestimate the risk in this basin, while the Tone river basin increased the characterization factors a 28% on average by IBT. Moreover, with a simple example we show how ambiguity in the definition of some characterization factors may cause significant changes in the result of the assessments. Finally, we concluded that local water footprint characterization can be more helpful in local assessment of water resources if the results are unanimous, Targetable, Replicable, Ameliorable, Comparable, and Engageable (uTRACE).