The objective of this paper is to evaluate effects of stratified porous formation on solute dispersion using two-dimensional laboratory tracer tests. An image analysis technique was used to analyze the solute dispersion processes and quantify the dispersivity and behaviors of forward and backward tails of solute plumes. Longitudinal dispersivity estimates for the stratified porous media increased with travel distance and are in reasonable agreement with previous work. Moreover, in all of the stratified cases the transverse dispersivity exhibited a similar trend which decayed with travel distance. The summary of dispersivities estimated from this study and previous studies suggests that if both degree of heterogeneity and scale for stratified and randomly heterogeneous porous media are similar, the longitudinal dispersivity is larger in stratified media than in randomly heterogeneous media. In order to quantify behaviors of forward and backward tails, we defined the travel distances x₀₅ and x₉₅ corresponding to the 5th and 95th percentiles, respectively, of the cumulative concentrations in the longitudinal direction, and found that the distance between x₀₅ and x₉₅ spread out linearly in the stratified cases.

Information on future climate change considering regional characteristics is necessary to establish adaptation strategies for global warming. We investigated the seasonal characteristics of future climate projections over Japan and surroundings (JPN) in the late 21st century, focusing especially on the source of uncertainty, based on two ensembles of the Coupled Model Intercomparison Project Phase 5 (CMIP5) and the Meteorological Research Institute atmospheric general circulation model (MRI-AGCM) global warming simulations. The ensemble mean surface air temperature increase over JPN is lower than that over the East Asian land region (EAS), reflecting the continent–ocean contrast, whereas quantitative changes in future precipitation depend on the ensembles. The CMIP5 mean atmospheric circulation around JPN weakens in winter and summer, while the future seasonal march tends to be delayed in the northern part of JPN during spring and autumn. Significant CMIP5 inter-model correlations are detected between the JPN climate projections and future circulation anomalies − e.g. the ensemble members simulating the westerly/southeasterly wind anomaly tend to project hotter/wetter future summers. The high-resolution MRI-AGCM projection is consistent with the CMIP5 inter-model correlations when the future change in typhoon–associated precipitation is removed, indicating typhoon simulations can substantially influence future projections.

Using high-resolution elevation data (2 m × 2 m), obtained during a 2012 aerial Lidar survey as part of the Chao Phraya River basin flood management project in Thailand, we assessed the impact of sea level rise due to climate change on the Bangkok metropolitan area. The area below the current median tide of 1.11 m was estimated to be 2,520 km², with a vulnerable population of 3.9 million, equivalent to 23% of the total population of the Bangkok metropolitan area. In the worst-case scenario of Representative Concentration Pathway (RCP) 8.5 (sea level rise of +1.10 m), the affected area would extend to 6,140 km², increasing the estimated vulnerable population by 86% to 7.2 million. With a sea level rise of less than +1.10 m, the affected area would extend from the Chao Phraya River mouth to Suphan Buri, which is about 80 km inland; however, the density of the vulnerable population would increase. The results of this study suggest that sea level rise adaptation measures, such as migration and settlement, must be developed as soon as possible.

External nutrient loadings to Lake Biwa were estimated using a combined tank model and loading-discharge curve approach. The model was applied to collective drainage basins of the lake’s Imazu (northwest), Hikone (northeast), and Otsu (south) areas. The hourly model was conducted using particular discharges from Kita (Ado) river, Takatoki (Ane) river, and Yasu River to obtain loading curves for phosphate (PO₄) and silica (SiO₂) by assimilating measured concentrations (2002–2003). The tank model was updated by adding an evapotranspiration routine and direct paths of groundwater discharges to the lake floor. The daily model was calibrated through analysis of water budget among the basin, inflow, lake and outflow, and then validated. The model was established and combined into a loading-discharge curve to determine the long-term external nutrient loadings entering the lake (1980–2017). Seasonal variation in nutrient loadings increased during spring and summer and decreased during winter. Annual phosphate-phosphorus (PO₄-P) loading ranged from 217 to 296 tons yr^–1 in the North Basin and 45 to 76 tons yr^–1 in the South Basin, while SiO₂ loading fluctuated from 16,027 to 32,655 tons yr^–1 and 2,518 to 5,490 tons yr^–1 in the North and South Basins, respectively.

This study examined the effect of three organic amendments − compost (CP), sugarcane bagasse (SB), and rice husk ash (RA) − on soil moisture and maize growth in rain-fed farmland under agricultural drought conditions in Central Java, Indonesia. The wet organic amendments were applied at a rate of 20 t ha^–1 and mixed into the root zone 3 days before seeding. Chemical fertilizers were not included in any treatment during the experiment. CP and RA kept the soil moisture above the soil suction of pF 1.0 between initial planting and harvesting. By contrast, SB treatment exacerbated the impact of the agricultural drought compared with the control (CO) or no organic material. The maize yields of CP (690 kg ha^–1) and RA (538 kg ha^–1) were higher than those of CO (456 kg ha^–1) and SB (382 kg ha^–1); all yields were lower than the regional average in Central Java (698 kg ha^–1). Maize yield was correlated with the lowest soil moisture value (R² = 0.80). Overall, CP and RA substantially reduced the damage to rain-fed farmland caused by agricultural drought. The lowest soil moisture value was a major explanatory factor with respect to the yield gap of maize under agricultural drought conditions.

This study investigates the change in extreme rainfall and river flooding for a large river basin due to climate change during the summer monsoon using a large ensemble dataset (d4PDF) coupled with the Integrated Flood Analysis System (IFAS). Frequent severe flooding causes significant damage in Japan. Therefore, we aim to provide useful information to mitigate flood damage. The study area is the Ishikari River basin (IRB) in Hokkaido, Japan. We used the d4PDF 5-km downscaled rainfall data as input for the IFAS model. The results showed that, for a given increase in extreme rainfall, the discharges from the IRB and its main sub-basins increase to a greater extent. The differences between the time of peak discharge at the reference stations in each tributary and the time of peak water level at the confluence points in the main river are evaluated. Climate change effects are significant in the southern sub-basins, wherein the amount of extreme rainfall increases by 29%–35%, whereas the river discharge increases drastically (37%–56%). Additionally, the time difference decreases by 1.02–2.14 h. These findings will help policymakers develop future flood control measures in flood-prone areas.