Abstract:The impacts of temperature and precipitation changes on regional evaporation and runoff characteristics have been investigated for the Biliu River basin, which is located in Liaoning Province, northeast China. Multiple climate change scenarios from phase 3 and phase 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) (21 scenarios in total) were utilized. A calibrated hydrologic model-SWAT model-was used to simulate future discharges based on downscaled climate data through a validated morphing method. Results show that both annual temperature and precipitation increase under most of the CMIP3 and CMIP5 scenarios, and increase more in the far future (2041-2065) than in the near future . These changes in precipitation and temperature lead to an increase in evaporation under 19 scenarios and a decrease in runoff under two-thirds of the selected scenarios. Compared to CMIP3, CMIP5 scenarios show higher temperature and wider ranges of changes in precipitation and runoff. The results provide important information on the impacts of global climate change on water resources availability in the Biliu River basin, which is beneficial for the planning and management of water resources in this region.

The decomposition and quantification of uncertainty sources in ensembles of climate-hydrological simulation chains is a key issue in climate impact researches. The mainly objectives of this study partitioning climate internal variability (CIV) and uncertainty sources in the climate-hydrological projections simulation process, the climate simulation process formed by six downscaled GCMs under two emission scenarios called GCMs-ES simulation chain, the hydrological simulation process add one calibrate Soil and Water Assessment Tool (SWAT) model called GCMs-ES-HM simulation chain. The CIV and external forcing of climate projections are investigated in each GCMs-ES simulation chain. The CIV of precipitation and ET are large in rainy season, and the single-to-noise ratio (SNR) are also relatively high in rainy season. Furthermore, the uncertainty decomposed frameworks based on analysis of variance (ANOVA) are established. The CIV and GCMs are the dominate contributors of runoff in rainy season. It worth noting the CIV can propagate from precipitation and ET to runoff projections. In additional, the hydrological model parameters are the third uncertainty contributor of runoff, which embody the hydrological model simulate process play important role in hydrological projections in future. The findings of this study advised that the uncertainty is complex in hydrological, hence, it is meaning and necessary to estimate the uncertainty in climate simulation process, the uncertainty analysis results can provide effectively efforts to reduce uncertainty and then give some positive suggestions to stakeholders for adaption countermeasure under climate change.

Investigating and understanding the responses of runoff and nitrogen loading to climate and land use change is particularly important for future water resources management. In this article, the Soil and Water Assessment Tool (SWAT) was used to simulate runoff and nitrogen loading in the middle reaches of the Fenhe River. The model was calibrated by the SWAT calibration and uncertainty procedure (SWAT-CUP) to achieve the accuracy of simulating runoff and nitrogen loadings. Furthermore, 20 climate change scenarios and 7 extreme land use change scenarios were set up and run on the calibrated model. The results showed that runoff and nitrogen loading decreased when temperature increased and increased with increasing precipitation. Runoff was more sensitive to changes in precipitation (±10%) than temperature (±2 °C), while nitrogen loading showed the opposite pattern. When the two climatic factors changed in the same direction, the combined effect was larger than either factor alone, whereas the change in the opposite direction produced a weaker effect. The changes produced by different extreme land use scenarios on runoff and nitrogen loading were significantly different and were more obvious during the flood season than in the non-flood season. The results of this study provide a useful guide for water resource managers.

The Double-Excess (DE) model is a flood forecasting model which was developed to reflect the characteristics of runoff generation in semi-arid and semi-humid areas. However, the empirical unit hydrograph used in the subbasin confluence module often has low precision because of the difficulty associated with parameter quantification. This study improves the subbasin confluence module of the DE model by coupling the geomorphologic instantaneous unit hydrograph (GIUH) to establish the improved DE model (DE-GIUH) to calculate the subbasin confluence based on topographic physical characteristics. The improved model is applied to the Wangjiahui Hydrological Station Basin in Northern China. Compared with the conventional DE model and the widely used hydrologic modelling system (HEC-HMS) model, the results show that DE-GIUH improved flood forecasting, including the component peak discharge, flood peak appearance time and flood progress. The qualified rate (QR) of all three models reached grade A(QR ≥ 85.0%). However, the proportion of the deterministic coefficient (DC) reaching grade B or above (DC ≥ 0.70) improved from 50% (HEC-HMS) and 30% (DE) to 90% (DE-GIUH) in the calibration period, and from 62.5% and 25% to 75% in the validation period. In particular, for large and medium floods, the proportion of DC reaching grade B and above is 100% for DE-GIUH, which is much higher than that of the other two models. The proposed improved model provides an alternative method for flood prediction in ungauged areas.double-excess model, flood forecasting, geomorphic instantaneous unit hydrograph, HEC-HMS, semi-arid and semi-humid areas | INTRODUCTIONHydrological models that can reflect the characteristics of runoff generation and confluence from physical mechanisms together with good data, including complete and abundant hydrometeorological data are important bases for flood forecasting simulation. However, it is difficult to study flood forecasting in semi-arid and semi-

Hydrological climate-impact projections in the future are limited by large uncertainties from various sources. Therefore, this study aimed to explore and estimate the sources of uncertainties involved in climate change-impacted assessment, in a representative watershed of Northeastern China. Moreover, recent studies have indicated that the climate internal variability (CIV) plays an important role in various hydrological climate-impact projections. Six downscaled global climate models (GCMs) under two emission scenarios, and a calibrated Soil and Water Assessment Tool (SWAT) model were used to obtain hydrological projections in future periods. The CIV and signal-to-noise ratio (SNR) are investigated to analyze the role of internal variability in hydrological projections. The results shows that the internal variability shows a considerable influence on hydrological projections, which need to be particularly partitioned and quantified. Moreover, it is worth noting the CIV can propagate from precipitation and ET to runoff projections through the hydrological simulation process. In order to partition the CIV and the sources of uncertainties, the uncertainty decomposed frameworks based on analysis of variance (ANOVA) are established. The results demonstrate that the CIV and GCMs are the dominant contributors of runoff in the rainy season. In contrast, the CIV and SWAT model parameter sets provided obvious uncertainty to the runoff in January to May, and October to December. The findings of this study advised that the uncertainty is complex in the hydrological simulation process; hence, it is meaningful and necessary to estimate the uncertainty in the climate simulation process. The uncertainty analysis results can effectively provide efforts for reducing uncertainty, and then give some positive suggestions to stakeholders for adaption countermeasures under climate change.