Water resource vulnerability due to uneven precipitation and water allocations is a significant issue in many regions of the world, including the Mekong Delta. Although numerous studies have already evaluated drought tendencies in many parts of the Mekong Delta, some areas have been excluded. This study targeted these excluded areas, including one inland, one coastal area, and two islands, which are defined as “understudied regions.” The meteorological drought intensity, frequency, and duration in the study areas in the Mekong Delta were evaluated using different time scales of the Standardized Precipitation Index (SPI) between 1994–2020. Unique contrasts in drought features were found between the study areas, indicating that severe drought events occupied the highest percentages inland from 2011 onward, while the most extreme drought events occurred in the coastal areas. Furthermore, trends in drought intensity, tendency, frequency, and duration were identified within the same delta region, demonstrating that combining SPI with other indicators can detect drought patterns in the Mekong Delta. These findings emphasize the importance of comprehensive evaluation of drought tendencies, including in understudied regions, for a better understanding of the features and future of water resources management.

In the renowned Kushiro wetland, Japan, the government has been undertaking a nature restoration project to counter the impact of post-WW2 restoration land development. The recent typhoon landfalls in Hokkaido has triggered concerns about the potential impact of climate change. In response, the government plans to incorporate nature restoration as an adaptation strategy to mitigate climate risks. To support this initiative, which involves an assessment of climate change impacts, we improved the high-resolution climate change projections and hydrological model to predict future impacts on wetlands in terms of river discharge and sediment runoff. The results show that although there is no significant increase in the risk of drought, intense rainfall and flooding are likely. In addition, simulated sediment runoff increased by mean of 2–3 folds due to increased summer flooding, and the frequency of intense sediment runoff events increased by 10 fold. These results show that countermeasures against sediments are important for protecting wetland ecosystems from climate change.

Historical climatological upper percentile rainfall over Japan from the Database for Policy Decision-making for Future climate changes (d4PDF) was compared with that from 121 rain-gauges for the 1952–2010 period. Percentiles calculated excluding or including values below 1 mm, “wet-extremes” and “all-extremes” were compared. The 5 km d4PDF hourly wet (all) extremes matched rain-gauges at 72% (45%) of the locations, but for daily extremes this was 39% (33%). Further comparison with radar-AMeDAS (Automated Meteorological Data Acquisition System) was made for hourly extremes in the 2006–2021 period. Wet (all) extremes matched for 84% (79%) of rain-gauges, and 80% (51%) also matched radar-AMeDAS at the same locations. Exceedance probabilities were calculated for historical and 4 K warmer climates using thresholds based on a non-warming climate. Historically, hourly (daily) extremes were more frequent over most of (eastern) Japan. In a 4 K warmer climate, daily extremes would become more frequent over most of Japan. Rainfall from 5 km d4PDF at hourly and daily resolutions are provided in prefecture and river basin subsets, with compressed sizes of each below 1 Gigabyte.

Localized heavy rainfall events have caused an increasing number of water-related disasters in recent years, particularly in urban areas where drainage capacity is limited. Accurate prediction of such events requires high-resolution, high-frequency three-dimensional (3D) observation data to capture rapidly evolving atmospheric structures. The Multi-Parameter Phased Array Weather Radar (MP-PAWR) provides rapid, high-density observations, offering significant advantages over conventional parabolic radars. However, rainfall prediction methods such as Vertically Integrated Liquid water content (VIL) Nowcast (VIL Nowcast; VILNC), which traditionally rely on limited-resolution radar data, often overestimate rainfall intensities, especially during the dissipating phase of cumulonimbus clouds. In this study, we propose an enhanced VILNC model that incorporates 3D wind field estimations derived from MP-PAWR to better represent the development and decay of rainfall areas. By integrating vertical wind information, the modified VILNC aims to mitigate overestimations associated with downdrafts. Comparative analysis of several localized heavy rainfall events demonstrates that the proposed method improves prediction accuracy, particularly at shorter lead times. These results suggest that the utilization of high-resolution 3D wind fields from MP-PAWR contributes to more reliable short-term rainfall predictions.

Accurate simulation of gross primary productivity (GPP) and evapotranspiration (ET) is essential for understanding global carbon and water cycles. However, land surface models (LSMs), while widely used, still exhibit substantial uncertainties, largely due to poorly calibrated parameters. This study integrated the Morris sensitivity analysis with Differential Evolution calibration (MD framework) to improve GPP and ET simulations in the MATSIRO LSM across twenty FLUXNET sites representing diverse ecosystem types. Results demonstrated that the MD framework led to marked improvements, with ensemble mean Kling-Gupta Efficiency (KGE) for monthly GPP and ET increasing by 43% and 30%, respectively. Among all parameters, GPP and ET were most sensitive to the maximum carboxylation rate of RuBisCO (VMAX0), which was underestimated in the original model. Along with VMAX0, the MD framework identified the top eight sensitive parameters for each site and provided site-specific optimal values, enabling tailored parameterization to improve simulation performance across diverse ecosystems. In addition, our results showed that leaf area index (LAI) is a non-negligible source of uncertainty for GPP simulations in cropland sites. Multiple-cropping systems amplify the importance of accurately capturing the abrupt LAI. These findings offer valuable guidance for improving GPP and ET simulation in LSMs, particularly in managed ecosystems.

Increases in water temperature due to climate change have been reported in many parts of the world, raising concerns about potential impacts on ecosystems, human water use, and water quality. In Japan, it is difficult to obtain trends in water temperature changes over a wide area because only a limited number of locations have long-term water temperature observations. Here, we analyzed historical changes in water temperature in Japan using both in situ observation data and satellite-derived surface water temperature (SWT). The annual mean water temperature change in Japan from 1982 to 2022, based on in situ observations, was 0.27 ± 0.19°C decade^–1. This is slightly lower than the estimate for the shorter period from 1982 to 2016 (0.30 ± 0.22°C decade^–1), but the number of sites showing a significant increasing trend was higher (85 sites) compared to the shorter period (66 sites). Similarly, the number of basins with a significant increase in SWT rose from 447 to 520 out of 675 with the inclusion of recent years. The nationwide average satellite-derived annual SWT trend from 1985 to 2022 was 0.47 ± 0.25°C decade^–1, with a particularly strong increasing trend observed in central Japan.

This study investigated the potential impacts of Long Lead-time Flood Forecasting Systems (LFS) on disaster response and societal changes through focus groups involving administrative stakeholders and researchers in Nagano, Japan. LFS has been shown to enhance proactive disaster responses, such as improved evacuation support and shelter environments in flood-prone areas, while fostering long-term societal transformations, including increased resilience and adaptive capacity. However, the study also identified potential negative impacts, such as overreliance on forecasts, psychological biases, and reduced infrastructure investments, underscoring the need for responsible LFS implementation.

Bimodal raindrop size distributions (RDSD) cannot be adequately represented by conventional exponential or gamma distributions. This could affect quantitative precipitation estimation (QPE) using meteorological radars. In this study, we developed a QPE method using a gamma raindrop distribution combined with an exponential (GRACE) distribution, which can represent bimodal RDSDs, and examined its utility. R−K_DP was calculated using the parameters obtained by fitting the GRACE distribution to the RDSD observed using a two-dimensional video disdrometer (2DVD). Estimates based on the GRACE distribution provided results closer to the precipitation intensity observed by rain gauges than estimates based on the gamma distribution or the estimation method used in the extended radar information network (XRAIN), especially during heavy rainfall. The utility of the GRACE distribution for QPE has been clarified; however, it is necessary to investigate the optimal estimation method for various types of rainfall.

Agricultural water infrastructure management by land improvement districts (LIDs) has the primary purpose of irrigation and drainage for agricultural production. However, recent climate change and urbanization have necessitated additional operations for flood control, becoming an additional and significant burden to LIDs. Therefore, this study aimed to evaluate the changes in operational efforts of agricultural water infrastructure resulting from urbanization. The number of gate operations of the main canals was proposed as a quantitative index of the operational efforts. The number of gate operations in the past five years (1994–1998) and the present (2017–2021) were extracted from the management logbooks and classified by operation purpose based on rainfall intensity to analyze the effects of urbanization. The results showed that the number of gate operations can be applied as an indicator of operational effort. The operational efforts for flood control purposes have increased because of urbanization. In contrast, the operation effort for irrigation remained the same as before, even if the number of paddies decreased due to urbanization. These results prove that urbanization is increasing the operational efforts of agricultural water infrastructure by LID.

Hot spring waters are valuable geoscientific samples that provide insights into subsurface water circulation. Among the various geochemical tracers, boron isotopes are particularly effective for identifying deep-seated fluids that mix with hot spring waters, owing to their high mobility and large isotopic fractionation. However, the processes controlling variations in boron isotopic composition remain poorly understood. In this study, we investigate the evolution of boron concentrations and isotope ratios (δ¹¹B) during early burial diagenesis, using fossil seawater-derived hot spring waters from the Niigata region of Japan. The samples have a wide range of δ¹¹B values (+9.4‰ to +41.6‰), with a general trend of decreasing δ¹¹B values with increasing boron concentrations. To explore the controlling mechanisms, we constructed a numerical model incorporating boron release from organic matter and minerals, and isotopic exchange via adsorption and desorption on mineral surfaces. The simulation results successfully reproduced the observed δ¹¹B–1/B trends in hot spring waters and were consistent with published data from subseafloor porewaters and mud volcano fluids. In contrast, simpler Rayleigh-type models without surface exchange failed to reproduce the observed patterns, highlighting the importance of adsorption–desorption processes in shaping boron isotope evolution during early diagenesis.

The Guelph Permeameter (GP) method is a widely used in-situ test for estimating field-saturated hydraulic conductivity (K_fs). However, its applicability to forested hillslopes, where large macropores such as soil pipes are often present, remains insufficiently examined. This study investigated the effects of pipes on GP measurements using three-dimensional infiltration simulations. Two pipe representations were assessed, namely, a seepage face boundary and a highly permeable porous medium. Simulation results indicated that pipes contribute to a significant increase in the infiltration rates only when they are directly connected to a well. Sensitivity to pipes was found to be influenced by the size of saturated bulbs (SBs), which differs according to soil texture. When pipes are located at a distance of more than 2.0 cm from a well, the increase in infiltration remains within 6%, regardless of soil texture. These findings indicate that GP measurements primarily reflect the properties of the soil matrix, rather than structures such as pipes and macropores.

In recent years, the scale and frequency of torrential rains and floods have increased globally due to climate change. Under this situation, Japan’s flood control policy was shifted to the basin-wide flood control named “River basin disaster resilience and sustainability by all,” and many counter and adaptation measures have been proposed to be implemented in several basins. This study presents a cost-benefit analysis of various adaptation measures for reducing flood damage in the Oyabe, Jinzu, Joganji, and Shogawa Rivers in Toyama Prefecture, utilizing a flood inundation model with future climate data (d4PDF). This study focuses on paddy field dams (PFDs) and river vegetation cutting and removal (VCR) because of their green infrastructure benefits and climate change mitigation effects. PFDs were effective in the Oyabe River, where the cost-benefit ratio reached 2.98 at a 50% implementation rate and 3.48 when fully implemented in the target area. Additionally, the VCR in rivers proved to be a useful countermeasure based on the cost-benefit analysis, especially for Shogawa River. However, the overall cost of VCR should be minimized by prioritizing specific areas within rivers.

Climate change is intensifying drought conditions globally, posing significant threats to agricultural production, food security, and rural livelihoods, especially in developing countries like Indonesia. This study provides a high-resolution assessment of agricultural drought vulnerability across Indonesia by integrating drought hazard and crop-yield risk indicators at a 1-km spatial resolution. For hazard assessment, the Standardized Precipitation and Evapotranspiration Index (SPEI) was calculated using ERA5-Land precipitation and evapotranspiration data from 2001 to 2021. Agricultural risk was assessed by developing a spatially detailed crop yield dataset on dry cropping season derived from MODIS-based vegetation indices (NDVI) and shortwave radiation data to estimate Net Primary Productivity (NPP). Yield anomalies, calculated by detrending the historical yield time series, served as indicators of drought-induced agricultural risk. By combining hazard and risk indicators, this research identified spatially explicit drought vulnerability hotspots across Indonesia, particularly highlighting intensified drought conditions in regions with major agricultural activities such as Java, South Sumatra, and South Sulawesi. The findings emphasize the importance of utilizing high-resolution satellite data for accurately identifying vulnerability hotspots, providing critical insights for targeted agricultural planning and drought adaptation strategies to support sustainable food production under increasing climatic uncertainty.

This study assesses long-term hydroclimatic variability in Japan using the Standardized Precipitation Index (SPI) derived from the JRA-3Q (Japanese Reanalysis for Three-quarter Century) dataset. Among various accumulation periods (SPI-3, SPI-6, SPI-12), the 12-month SPI (SPI-12) exhibited the strongest spatial correlation with observations from AMeDAS, Japan’s dense meteorological observation network, confirming its ability to capture interannual precipitation variability. A long-term trend analysis from 1949 to 2023 revealed a widespread wetting tendency across Japan. Composite analysis between the early (1949–1978) and recent (1994–2023) 30-year periods suggested potential dynamical and thermodynamical drivers, including enhanced water vapor flux at 850 hPa near Japan and the Philippines, and subtropical jet changes at 200 hPa – stronger winter flow and reduced northward migration in summer. These circulation shifts appear to contribute to the observed persistent wetting trend. Overall, the findings demonstrate that integrating SPI with JRA-3Q, a moderately resolved reanalysis dataset, enables effective detection of regional hydroclimatic trends. This approach offers a valuable framework for drought monitoring and climate risk assessment, even in regions with dense observation networks like Japan. Future studies should incorporate more advanced diagnostic or modeling approaches to better understand the underlying physical mechanisms.

River water temperature patterns show diurnal and annual oscillatory behavior mainly due to the energy exchange between atmosphere and river water. In addition to this, rainfall runoff events can also contribute river temperature patterns. As a result of superposition of these factors, river water thermal regime shows complex patterns. In this study, we attempted to characterize the thermal regime of 16 tributaries of the Nagara River Basin by classifying them into atmospheric-dominated, groundwater-dominated, and intermediate. This classification was based on seasonal oscillatory behavior extracted from river and air temperature data during the period from 2017 to 2019, specifically using annual air–water temperature metrics, including the amplitude ratio and phase lag. Diurnal temperature variations standardized against air temperature, as well as seasonal responses to rainfall events, were then examined to validate and support the robustness of this classification, which revealed consistent thermal behavior across the identified classification types. A preliminary hydrogeographic interpretation indicates that land-use patterns and bedrock composition have a possible influence on the hydro-thermal regimes. The relative importance of groundwater inflow as a stable heat source and atmospheric heat exchange might be important in determining the thermal regime.