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This paper presents a detailed analysis of how future climate change may affect water availability in a typical arid endorheic river basin, the Heihe River basin (HRB), in northwest China. The analysis is based on the improved Soil Water Assessment Tool (SWAT), which is calibrated and validated with historical streamflow data from the upper HRB and is used to predict future hydrological responses. Six general circulation models (GCMs), under two emission scenarios (RCP4.5 and RCP8.5), are downscaled to construct future climate change scenarios. The results suggest that the climate of the upper HRB will likely become warmer and wetter in the near future (2021-50), with the largest increase in precipitation occurring in the summer. Correspondingly, the basinwide evapotranspiration, snowmelt, and runoff are projected to increase over the same period. The mean temperature in the near future is projected to rise, relative to the recent 30 years (1981-2010), by 1.2°-1.7°C under scenario RCP4.5 and by 1.4°-2.1°C under scenario RCP8.5. The mean precipitation is projected to increase by 10.0%-16.6% under scenario RCP4.5, and by 10.5%-22.0% under scenario RCP8.5. The mean values of evapotranspiration, snowmelt, and runoff are expected to increase by 14.2%, 4.3%, and 11.4%, respectively, under scenario RCP4.5 and to increase by 18.7%, 5.8%, and 12.8%, respectively, under scenario RCP8.5. Though the model simulations forecast an increase in streamflows in the headwater region of the HRB, future water availability varies significantly over space and time. The findings of this study will help to frame more effective water management strategies for the HRB under changing climatic conditions. [ABSTRACT FROM AUTHOR]

This paper applied a HIMS (hydroinformatic modeling system) model to simulate streamflow in the Luanhe River Basin. This model was compared with SIMHYD and XAJ models for eight sub-basins of the Luanhe River. The results showed HIMS model performed better than SIMHYD and XAJ models, in these areas. We then investigated the streamflow response to climate changes in the different sub-basins. Twenty hypothetical climate change scenarios (perturbed temperatures and precipitation) were used to test the sensitivity of HIMS model simulated annual and mean monthly streamflow. Our results demonstrated that: (i) the annual streamflow was positively related to precipitation, and there was a negative relationship between streamflow and temperature for all the eight sub-basins; (ii) in all sub-basins, the relationship of annual streamflow change to precipitation change was highly non-linear, but the relationship of annual streamflow change with temperature change was approximately linear; (iii) the annual streamflow response to precipitation change was more sensitive when increasing than decreasing; (iv) the annual streamflow response to climate change was more sensitive in the Xingzhouhe River sub-basin, followed by the Wuliehe River sub-basin, and the Sahe River sub-basin was least sensitive; (iv) there were few differences in inner-streamflow response to climate change in the Laoniuhe, Yimatuhe, and Yixunhe Rivers. But for other rivers, when the temperature changed, larger streamflow differences happened in winter and summer; when the precipitation decreased or was unchanged, the larger differences happened in winter months, and when the precipitation increased, larger differences happened in winter and summer. [ABSTRACT FROM AUTHOR]

This study calibrated and downscaled data from four scenarios in the Coupled Model Intercomparison Project Phase 6 (CMIP6) to drive the distributed hydrological model soil and water assessment tool (SWAT). Hereafter, this study systematically quantified the changes in streamflow under future climatic conditions in the middle-upper reaches of the Weihe River Basin. The results show that, compared with the base period (1991–2000), the low-emission SSP1-2.6 scenarios resulted in future streamflow reductions to values less than those recorded in the baseline period. Furthermore, the same is true for medium and high-emission SSP3-7.0 scenarios. Under the SSP1-2.6 emission scenarios, streamflow in the 2030s, 2040s, 2050s and 2060s will be reduced by 40%, 50%, 31%, and 38%, respectively. Under the SSP3-7.0 emission 12 scenarios, streamflow will decrease by 44%, 20%, 34%, and 7% in the 2023s, 2040s, 2050s and 2060s, separately. These results supply support for water resource management and water use in the Kuan-chung Plain in the future climate change. [ABSTRACT FROM AUTHOR]

Climatic variability and the quantification of climate change impacts on hydrological parameters are persistently uncertain. Remote sensing aids valuable information to streamflow estimations and hydrological parameter projections. However, few studies have been implemented using remote sensing and CMIP6 data embedded with hydrological modeling. This research studied how changing climate influences the hydro-climatic parameters based on the earth system models that participated in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). GRACE evapotranspiration data were forced into the Soil and Water Assessment Tool (SWAT) to project hydrologic responses to future climatic conditions in the Hongshui River basin (HRB) model. A novel approach based on climate elasticity was utilized to determine the extent to which climate variability affects stream flow. CMIP6 SSPs (shared socio-economic pathways) for the second half of the 20th century (1960–2020) and 21st century (2021–2100) projected precipitation (5–16%) for the whole Hongshui River basin (HRB). The ensemble of GCMs projected an increase of 2 °C in mean temperature. The stream flow is projected to increase by 4.2% under SSP-1.26, 6.2% under SSP-2.45, 8.45% under SSP-3.70, and 9.5% under SSP-5.85, based on the average changes throughout the various long-term future scenarios. We used the climate elasticity method and found that climate change contributes 11% to streamflow variability in the Hongshui River basin (HRB). Despite the uncertainty in projected hydrological variables, most members of the modeling ensemble present encouraging findings for future methods of water resource management. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the uncertainty ranges of high flows under climate change in Jinhua River basin, eastern China. Four representative concentration pathways (RCPs), three global climate models (GCMs), 10 downscaling parameter sets and three hydrologic models are applied to simulate future discharges. Changes of annual maximum discharges are assessed for the baseline period (1961-1990) and future period (2011-2040). The uncertainties of annual maximum discharges are calculated for each uncertainty source and compared with different combinations of them. The minimum temperature will probably increase all year round in the future period and maximum temperature would increase in most cases. The changes of precipitation showed different directions by different models and emission scenarios. The annual maximum discharges would decrease for all RCPs. The order of uncertainty ranges of high flows due to different uncertainty sources from high to low is: hydrologic models, GCMs, parameter sets in the downscaling method and emission scenarios. It must be noted that the small uncertainty contribution from different emission scenarios is due to the study period when the differences in increase of radiative forcing and greenhouse gas concentration are less obvious between different RCPs compared to the second half of the 21st century. [ABSTRACT FROM AUTHOR]

Climate change has a significant impact on water resources. Forecasts and simulations of climate runoff processes are essential for assessing the impact of global climate change on runoff variations. This study focuses on the upper Taohe River Basin, which is an important watershed in the semi-arid regions of northwest China. To assess the runoff in the upper Taohe River Basin and the responses to climate change, the SWAT hydrological model was used to analyze future climate change scenarios and their effects on water resources. The results indicate that the minimum temperature would increase gradually in the 21st century and that the minimum temperature change would be more significant than the maximum temperature change, which indicates that minimum temperature changes would make an obvious contribution to future regional warming. Under RCP2.6, the average precipitation would decrease; at the same time, under RCP4.5 and RCP8.5, the average precipitation would increase. In the future, under different climate scenarios, the runoff will exhibit droughts and flood disasters. These research results provide scientific support for water resource utilization and management in the Taohe River Basin. [ABSTRACT FROM AUTHOR]

A growing number of studies on streamflow projection in the context of global climate change have been widely reported in past years. However, current knowledge on the role of different hydrological models to estimate future climate impact on flood in the Tibet Plateau is still limited so far. In this work, a group of hydrological models in conjunction with statistical downscaling outputs (SDSM and ANN) from the HadCM3 GCM model are used to evaluate the impacts of climate change on floods in the 21st century over the headwater catchment of Yellow River, the Tibet Plateau. The influence of different hydrological models on flood projection and quantile estimation are addressed. The results show that: (1) three hydrological models generate acceptable results of flood magnitude and frequency at Tangnaihai station during the past 50 years; (2) quite similar projections for future floods are obtained by means of different hydrological models, decreasing flood magnitude corresponding to the 2-, 5-, 10- and 50-year return periods is found under most scenarios in the 21st century. Meanwhile, flood frequency is likely to reduce in response to climate change; (3) the uncertainty in projected flood quantile by three different hydrological models increases with recurrence interval in term of relative length of confidence interval (RL). Besides, RL for flood quantile in future climate scenarios is likely to become larger than the baseline period. The results are valuable to improve our current knowledge of climate impact research in the alpine regions. [ABSTRACT FROM AUTHOR]

Climate change as a result of the increased greenhouse gas emissions may influence the availability of water resources in many regions on the globe. In the past decades, China has been facing severe shortage of water resources. This study focuses on the assessment of the impact of climate change on both blue and green water resources in ten large river basins in China. The blue and green water resources for these river basins were derived from the terrestrial hydrological fluxes in period 1960-2100, which were simulated with the Max Planck Institute Hydrological Model-MPI-HM. The forcing data for the hydrological model, the precipitation and temperature were obtained from three coupled Atmosphere-Ocean General Circulation Models (GCMs)-ECHAM5, IPSL and CNRM, under A2 and B1 greenhouse gas emission scenarios. The statistical bias correction method was applied on the output from the three GCMs. By using this climate model-hydrology model modeling chain, the impact of climate change on the blue and green water resources was analyzed over the ten Chinese river basins. Here, the projected changes in 2071-2100 are considered relative to 1971-2000. The projected change of monthly mean and annual mean of green water resources show the general increase for all ten river basins; among them, Inland river, Zhemin river and Zhujiang river have larger change signal than other basins. For blue water resources, increases of the annual mean are projected from November to March for Heilongjiang river, Liaohe river and Yellow river, Inland river in Northern China; and decreases are projected for Huaihe river, Zhemin river, Haihe river, Yangzi river, Southwest river, and Zhujiang river basins in Southern China. It is found that climate change has impact on both blue and green water resources over large river basins in China. The sustainable blue water resources management should take into account the different changes in both Northern and Southern China. The results show that a better management of green water resources is of importance for food and ecological securities in the context of global change. [ABSTRACT FROM AUTHOR]

This study investigated land-use and land-cover change (LUCC) and hydrological responses under consistent climate change scenarios (A1B and B1) in the Heihe River Basin (HRB), a typical arid inland river basin in northwest China. LUCC was first projected using the Dynamic Conversion of Land-Use and its Effects (Dyna-CLUE) model. Two cases (Case 1 and Case 2) were then established to quantify the hydrological responses to single climate change and the combined responses to climate change and LUCC with the Soil and Water Assessment Tool (SWAT). The results of LUCC modeling under the A1B and B1 scenarios present distinct regional characteristics and also indicate that the projected future land-use patterns are not appreciably different than the actual map for the year 2000. In Case 1, which only considers the impacts of single climate change, overall, the streamflow at the outlet of the upper HRB is projected to decline, whereas at the outlet of the middle HRB to increase, under both climate change scenarios. Meanwhile, the frequency of occurrence of hydrological extremes is expect to increase under both scenarios. In Case 2, which considers the combined impacts of climate change and LUCC, the changes in streamflow and frequency of hydrological extremes are found to be remarkably consistent with those in Case 1. The results imply that climate change rather than LUCC are primarily responsible for the hydrological variations. The role of LUCC varies with regions in the context of climate change dominated hydrological responses. [ABSTRACT FROM AUTHOR]

Climate change is expected to have large impacts on peak flows. However, there may be bias in the simulation of peak flows by hydrological models. This study aims to improve the simulation of peak flows under climate change in Lanjiang catchment, east China, by comparing two approaches: postprocessing of peak flows and composite objective calibration. Two hydrological models [Soil and Water Assessment Tool (SWAT) and modèle du Génie Rural à 4 paramètres Journalier (GR4J)] are employed to simulate the daily flows, and the peaks-over-threshold method is used to extract peak flows from the simulated daily flows. Three postprocessing methods, namely, the quantile mapping method and two generalized linear models, are set up to correct the biases in the simulated raw peak flows. A composite objective calibration of the GR4J model by taking the peak flows into account in the calibration process is also carried out. The regional climate model Providing Regional Climates for Impacts Studies (PRECIS) with boundary forcing from two GCMs (HadCM3 and ECHAM5) under greenhouse gas emission scenario A1B is applied to produce the climate data for the baseline period and the future period 2011-40. The results show that the postprocessing methods, particularly quantile mapping method, can correct the biases in the raw peak flows effectively. The composite objective calibration also resulted in a good simulation performance of peak flows. The final estimated peak flows in the future period show an obvious increase compared with those in the baseline period, indicating there will probably be more frequent floods in Lanjiang catchment in the future. [ABSTRACT FROM AUTHOR]

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Quantification of the impacts of climate change on streamflow and other hydrological parameters is of high importance and remains a challenge in arid areas. This study applied a modified distributed hydrological model (HEC-HMS) to the Yarkant River basin, China to assess hydrological changes under future climate change scenarios. Climate change was assessed based on six CMIP6 general circulation models (GCMs), three shared socio-economic pathways (SSP126, SSP245, SSP370), and several bias correction methods, whereas hydrological regime changes were assessed over two timeframes, referred to as the near future (2021–2049) and the far future (2071–2099). Results demonstrate that the DM (distribution mapping) and LOCI (local intensity scaling) bias correction methods most closely fit the projections of temperature and precipitation, respectively. The climate projections predicted a rise in temperature of 1.72–1.79 °C under the three SSP scenarios for the near future, and 3.76–6.22 °C under the three SSPs for the far future. Precipitation increased by 10.79–12% in the near future, and by 14.82–29.07% during the far future. It is very likely that streamflow will increase during both the near future (10.62–19.2%) and far future (36.69–70.4%) under all three scenarios. The increase in direct flow will be greater than baseflow. Summer and winter streamflow will increase the most, while the increase in streamflow was projected to reach a maximum during June and July over the near future. Over the far future, runoff reached a peak in May and June. The timing of peak streamflow will change from August to July in comparison to historical records. Both high- and low-flow magnitudes during March, April, and May (MAM) as well as June, July, and August (JJA) will increase by varying degrees, whereas the frequency of low flows will decrease during both MAM and JJA. High flow frequency in JJA was projected to decrease. Overall, our results reveal that the hydrological regime of the Yarkant River is likely to change and will be characterized by larger seasonal uncertainty and more frequent extreme events due to significant warming over the two periods. These changes should be seriously considered during policy development. [ABSTRACT FROM AUTHOR]

The soil and water assessment tool (SWAT) model was applied for the first time in Cuba to assess the potential impacts of climate change on water availability in the Cauto River basin. The model was calibrated (and validated) for the 2001–2006 (2007–2010) period at a monthly timescale in two subbasins La Fuente and Las Coloradas, representative of middle and upper sections of the Cauto basin; the calibrated models showed good performance. The output available for the regional climate Model RegCM4.3 was used to force the calibrated SWAT models to simulate a baseline (1970–2000) period and near-future (2015–2039) hydrologic regimes under the representative concentration pathway (RCP) 8.5 emission scenario. The future projections suggest regional increases of 1.5 °C in mean annual temperature and a 38% decrease in mean annual precipitation in the subbasins. These changes translate to possible reductions in the annual streamflow of up to 61% with respect to the baseline period, whereas the aquifer recharge in the basin is expected to decrease up to 58%, with a consequent reduction of groundwater flow, especially during the boreal summer wet season. These projection scenarios should be of interest to water resources managers in tropical regions. [ABSTRACT FROM AUTHOR]

Investigating the impact of climate change at regional scales is of importance for adaption purposes. In this study, a regional climate model PRECIS is for the first time run for East China on a spatial resolution of 25 km using two global climate models (GCMs) ECHAM5 and HadCM3 as boundary data under A1B emission scenario. The baseline period is 1961-1990. An upgraded quantile mapping method is used to correct the bias of PRECIS outputs for providing reliable future climate change projections (2011-2040). The regional climate model is then coupled with a mesoscale distributed hydrology soil vegetation model (DHSVM), to investigate the impact of climate change on future water resources in the Jinhua River Basin, East China. The hydrological model is calibrated and validated on a daily basis and show reasonable performance. The results show that under both GCMs, statistically, no significant changes in future annual runoff are projected. However, large changes in seasonal and monthly runoff are projected. ECHAM5 projects large decreases in summer () and autumn () and slight increases in spring and winter whereas HadCM3 projects large decreases in autumn () and large increases in spring (28.7%) and winter (60%). The seasonal changes in precipitation in this region are the main driving force for the changes in future runoff. [ABSTRACT FROM AUTHOR]