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Escalating climate extreme events disrupt hydrological processes by affecting both water availability and sediment dynamics. However, the interconnection between hydrological variability and climatic extremes remains underexplored, particularly in cold regions under a changing climate. Here, we develop a yield-based dichotomy framework to examine the impact of shifted climatic extreme patterns on hydrological regimes in the Ishikari River Basin (IRB), Hokkaido, Japan, which is a crucial area for local agriculture and urban development. Utilizing a modified Soil and Water Assessment Tool (SWAT) integrated with downscaled CMIP6-GCM climate projections under Shared Socioeconomic Pathways (SSPs) scenarios, we identified significant annual variability in water and sediment yields associated with extreme climate events. Hot-dry conditions correlate with lower water and sediment yields, whereas increased cold extremes may result in higher sediment yields across the IRB. Our findings also indicate that hotter and drier patterns interact with hydrological processes, potentially establishing new hydrologic regimes and shifting climatic extremes-induced thresholds for yield classification within the IRB. Notably, under SSP585, both water availability and sediment transport are projected to intensify, increasing flood risks and exacerbating sedimentation challenges. Our study highlights the urgent need for adaptive water management strategies to address these anticipated changes in hydrological regimes in response to global climate change.

RESUMEN

Simulation of future climate changes, especially temperature and rainfall, is critical for water resource management, disaster mitigation, and agricultural development. Based on the category-wise indicator method, two preferred Global Climate Models (GCMs) for the Ishikari River basin (IRB), the socio-economic center of Hokkaido, Japan, were examined from the newly released Coupled Model Intercomparison Project Phase 6 (CMIP6). Climatic variables (maximum/minimum temperature and precipitation) were projected by the Statistical DownScaling Model (SDSM) under all shared socioeconomic pathway-representative concentration pathway (SSP-RCP) scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, SSP5-3.4OS, and SSP5-8.5) in two phases: 2040-2069 (2040s) and 2070-2099 (2070s), with the period of 1985-2014 as the baseline. Predictors of SDSM were derived from CMIP6 GCMs and the reanalysis dataset NOAA-CIRES-DOE 20th Century Reanalysis V3 (20CRv3). Results showed that CMIP6 GCMs had a significant correlation with temperature measurements, but could not represent precipitation features in the IRB. The constructed SDSM could capture the characteristics of temperature and precipitation during the calibration (1985-1999) and validation (2000-2014) phases, respectively. The selected GCMs (MIROC6 and MRI-ESM-2.0) generated higher temperature and less rainfall in the forthcoming phases. The SSP-RCP scenarios had an apparent influence on temperature and precipitation. High-emission scenarios (i.e., SSP5-8.5) would project a higher temperature and lower rainfall than the low-emission scenarios (e.g., SSP1-1.9). Spatial-temporal analysis indicated that the northern part of the IRB is more likely to become warmer with heavier precipitation than the southern part in the future. Higher temperature and lower rainfall were projected throughout the late twenty-first century (2070s) than the mid-century (2040s) in the IRB. The findings of this study could be further used to predict the hydrological cycle and assess the ecosystem's sustainability.

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It is difficult to investigate the factors that control the riverine nitrate-nitrogen (NO3--N) export in a watershed which gains or losses groundwater. To control the NO3--N contamination in these watersheds, it is necessary to investigate the factors that are related to the export of NO3--N that is only produced by the watershed itself. This study was conducted in the Shibetsu watershed located in eastern Hokkaido, Japan, which gains external groundwater contribution (EXT) and 34% of the annual NO3--N loading occurs through EXT. The riverine NO3--N exports from 1980 to 2009 were simulated by the SWAT model, and the factors controlling the temporal and spatial patterns of NO3--N exports were investigated without considering the EXT. The results show that hydrological events control NO3--N export at the seasonal scale, while the hydrological and biogeochemical processes are likely to control NO3--N export at the annual scale. There was an integrated effect among the land use, topography, and soil type related to denitrification process, that regulated the spatial patterns of NO3--N export. The spatial distribution of NO3--N export from hydrologic response units (HRUs) identified the agricultural areas with surplus N that are vulnerable to nitrate contamination. A new standard for the N fertilizer application rate including manure application should be given to control riverine NO3--N export. This study demonstrates that applying the SWAT model is an appropriate method to determine the temporal and spatial patterns of NO3--N export from the watershed which includes EXT and to identify the crucial pollution areas within a watershed in which the management practices can be improved to more effectively control NO3--N export to water bodies.

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River water quality was evaluated with respect to eutrophication and land use during spring snowmelt and summer base flow periods in Abashiri (mixed cropland-livestock farming) and Okoppe (grassland-based dairy cattle farming), eastern Hokkaido, Japan. Water from rivers and tributaries was sampled during snowmelt and summer base flow periods in 2005, and river flow was measured. Total N (TN), NO(3)-N, and Si concentrations were determined using standard methods. Total catchment and upland areas for each sampling site were determined with ArcGIS hydrology modeling software and 1:25,000-scale digital topographic maps. Specific discharge was significantly higher during snowmelt than during base flow. In both areas, TN concentrations increased, whereas Si concentrations decreased, with increased specific discharge, and were significantly higher during snowmelt. The Si:TN mole ratio decreased to below or close to the threshold value for eutrophication (2.7) in one-third of sites during snowmelt. River NO(3)-N concentrations during base flow were significantly and positively correlated with the proportion of upland fields in the catchment in both the Abashiri (r = 0.88, P < 0.001) and Okoppe (r = 0.43, P < 0.01) areas. However, the regression slope, defined as the impact factor (IF) of water quality, was much higher in Abashiri (0.025) than in Okoppe (0.0094). The correlations were also significantly positive during snowmelt in both areas, but IF was four to eight times higher during snowmelt than during base flow. Higher discharge of N from upland fields and grasslands during snowmelt and the resulting eutrophication in estuaries suggest that nutrient discharge during snowmelt should be taken into account when assessing and monitoring the annual loss of nutrients from agricultural fields.

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This study was carried out to evaluate the quality of river water by analysis of land use in drainage basins and by estimating the N budgets. The drainage basins of Shibetsu River (Shibetsu area) and Bekkanbeushi River (Akkeshi area) in eastern Hokkaido, Japan were selected for a case study, and the evaluation of water quality was up-scaled to the regional level in Hokkaido by using the Arcview/GIS and statistical information. Water sampling was carried out in August 2001 and May 2002 in the Shibetsu and Akkeshi areas, respectively. The proportions of major land uses in drainage basins such as upland field, forest, urban area, wetland and wasteland for each sampling site were estimated by using topographic maps scaled at 1:25,000. The linear regression results showed that the correlation between NO3-N concentration and the proportion of upland in the drainage basins was highly and positively significant for both the Shibetsu area (r = 0.84, n = 57) and the Akkeshi area (r = 0.71, n = 73) at < 0.001 significance level. The regression coefficients or impact factors of river water quality were 0.015 and 0.0052 for the Shibetsu and Akkeshi areas, respectively. A comparison of these results with that of the previous study results in Hokkaido indicated that the impact factors were highest for intensive livestock farming areas (0.040), medium for mixed agriculture and livestock farming (0.020-0.030), and the lowest for grassland-based dairy cattle and horse farming areas (0.0052-0.015). The results of a simple regression analysis showed that the impact factors had a significant positive correlation with the cropland surplus N (r = 0.93, P < 0.01), chemical fertilizer N (r = 0.82, P < 0.05), and manure fertilizer N (r = 0.76, P < 0.05), which were estimated by using the N budget approach. Using the best-correlated regression model, impact factors for all cities, towns and villages of the Hokkaido region were estimated. The NO3-N concentrations for all major rivers in Hokkaido were predicted by multiplying the estimated impact factors by the proportion of uplands. The regression analysis indicated that the predicted NO3-N concentrations were significantly correlated (r = 0.62, P < 0.001, n = 203) with the measured NO3-N concentrations, reported previously. It can be concluded that estimating the proportions of upland fields in drainage basins, and calculating cropland surplus N enables us to predict river water quality with respect to NO3-N concentration.

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