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Separating existing historical precipitation data into solid and liquid precipitation remains a challenge in the study of climate change, extreme precipitation, and hydrological modelling. Based on historical daily air temperature and precipitation data, as well as visual observations of precipitation phase (weather phenomena records) in China mainland, this study proposed a snow‐day direct definition method (SDDM) to determine the threshold air temperature (TAT) of rainfall and snowfall, and analysed the spatial pattern and its influential factors. The main findings include: (1) the TAT based on the SDDM varied from −1.2 to 6.3°C, with a mean value of 2.8°C for the entire study region; (2) TAT was generally higher and more variable in the low‐latitude areas, and the Qinghai‐Tibet Plateau was characterized by an abnormally high average TAT of 5.2°C, almost twice as large as that of the eastern monsoon region; (3) TAT exhibited a significant positive correlation with altitude and negative correlation with precipitation and relative humidity. The results presented in this paper have potential application for studies of large‐scale snowfall climatology and climate change, weather forecasting techniques, and hydrological model parameterization in areas with complex and diverse geographical and climatic conditions. [ABSTRACT FROM AUTHOR]

The hydrological projections provided by the outputs of Global Climate Models (GCMs) combining hydrological models include multi‐source uncertainties, which may challenge the formulation of relevant adaption and mitigation policies. In this paper, the overall uncertainty and the relative contribution of each uncertainty component were investigated for hydrological projections over 408 watersheds in China by using 3 shared socioeconomic pathway emission scenarios (SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5), 21 GCMs, 8 bias correction methods, 4 hydrological models, and 2 sets of optimized hydrological model parameters. The results show that the total uncertainty (T) is mainly contributed by uncertainty related to global climate models (G), with the mean percentage ranging from 60.4 to 64.1%, followed by the interaction uncertainties among all components, with the mean percentage ranging from 22.0 to 26.4%. The uncertainty contribution of hydrological models (H) (6.1–9.4%) ranks third, followed by emission scenarios (S) (2.9–5.9%) and bias correction methods (B) (0.2–1.1%). The uncertainty contribution of the optimized hydrological model parameters (P) (0.2–0.3%) is almost negligible. In terms of spatial variability, the relative contribution of uncertainty related to global climate models (G) is the highest in the near future for northern China (67.5–70.6%) and in the far future for southern China (66.1–66.7%). However, it was found to be lower for the Tibetan Plateau and northwestern China (45.3–57.9%) in the near and far future. The relative contribution of hydrological model uncertainty is higher for southwestern and northwestern China and the Tibetan Plateau (7.2–19.5%) and lower for northern, eastern, and southern China (2.5–6.6%). This study highlights the importance of including multiple GCMs and hydrological models in hydrological impact studies to consider their overall uncertainty. The development of global climate models and hydrological models is still the best way to reduce the uncertainty of climate change impact studies. [ABSTRACT FROM AUTHOR]

Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifthgeneration reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979-2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments. [ABSTRACT FROM AUTHOR]

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]

One of the potential impacts of global warming is likely to be experienced through changes in flood frequency and magnitude, which poses a potential threat to the downstream reservoir flood control system. In this paper, the downscaling results of the multimodel dataset from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5, respectively) were coupled with the Variable Infiltration Capacity (VIC) model to evaluate the impact of climate change on the Feilaixia reservoir flood control in the Beijiang River basin for the first time. Four emissions scenarios [A1B and representative concentration pathway (RCP) scenarios RCP2.6, RCP4.5, and RCP8.5] were chosen. Results indicate that annual distribution and interannual variability of temperature and precipitation are well simulated by the downscaling results of the CMIP3 and CMIP5 multimodel dataset. The VIC model, which performs reasonably well in simulating runoff processes with high model efficiency and low relative error, is suitable for the study area. Overall, annual maximum 1-day precipitation in 2020-50 would increase under all the scenarios (relative to the baseline period 1970-2000). However, the spatial distribution patterns of changes in projected extreme precipitation are uneven under different scenarios. Extreme precipitation is most closely associated with extreme floods in the study area. There is a gradual increase in extreme floods in 2020-50 under any of the different emission scenarios. The increases in 500-yr return period daily discharge of the Feilaixia reservoir have been found to be from 4.35% to 9.18% in 2020-50. The reservoir would be likely to undergo more flooding in 2020-50. [ABSTRACT FROM AUTHOR]

Potential evapotranspiration (PET) is a key input to hydrological models. Its estimation has often been via the Penman--Monteith (P--M) equation, most recently in the form of an estimate of reference evapotranspiration (RET) as recommended by FAO-56. In this paper the Shuttleworth--Wallace (S--W) model is implemented to estimate PET directly in a form that recognizes vegetation diversity and temporal change without reference to experimental measurements and without calibration. The threshold values of vegetation parameters are drawn from the literature based on the International Geosphere--Biosphere Programme land cover classification. The spatial and temporal variation of the LAI of vegetation is derived from the composite NOAA-AVHRR normalized difference vegetation index (NDVI) using a method based on the SiB2 model, and the Climate Research Unit database is used to provide the required meteorological data. All these data inputs are publicly and globally available. Consequently, the implementation of the S--W model developed in this study is applicable at the global scale, an essential requirement if it is to be applied in data-poor or ungauged large basins. A comparison is made between the FAO-56 method and the S--W model when applied to the Yellow River basin for the whole of the last century. The resulting estimates of RET and PET and their association with vegetation types and leaf area index (LAI) are examined over the whole basin both annual and monthly and at six specific points. The effect of NDVI on the PET estimate is further evaluated by replacing the monthly NDVI product with the 10-day product. Multiple regression relationships between monthly PET, RET, LAI, and climatic variables are explored for categories of vegetation types. The estimated RET is a good climatic index that adequately reflects the temporal change and spatial distribution of climate over the basin, but the PET estimated using the S--W model not only reflects the changes in climate, but also the vegetation distribution and the development of vegetation in response to climate. Although good statistical relationships can be established between PET, RET and/or climatic variables, applying these relationships likely will result in large errors because of the strong non-linearity and scatter between the PET and the LAI of vegetation. It is concluded that use of the implementation of the S--W model described in this study results in a physically sound estimate of PET that accounts for changing land surface conditions. [ABSTRACT FROM AUTHOR]

Climate change and human activities significantly impact the hydrological cycle, particularly in regions with numerous large-scale reservoirs. Recognizing the limitations of the reservoir module in the original SWAT model, this study presents an improved reservoir module based on a dispatch function to enhance runoff simulation. Its performance is validated by simulating daily runoff in the Jinsha River Basin, China. The scenario simulation approach is employed to quantitatively analyze the influences of climate change and human activities on runoff. And downscaled Global Climate Models (GCMs) are utilized to predict runoff for the next three decades. The results show that (1) the improved SWAT model outperforms the original model in runoff simulation; (2) during the test period, reservoir regulations caused a reduction of 26 m3/s in basin outlet runoff, while climate change led to an increase of 272 m3/s; and (3) future changes in basin outlet runoff over the next 30 years exhibit a high level of uncertainty, ranging from −5.6% to +11.0% compared to the base period. This study provides valuable insights into the hydrological impacts of climate change and human activities, highlighting the importance of incorporating an improved reservoir module in hydrological modeling for more accurate predictions and assessments. [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]

Summary: In this paper we proposed: (1) an algorithm of glacier melt, sublimation/evaporation, accumulation, mass balance and retreat; (2) a dynamic Hydrological Response Unit approach for incorporating the algorithm into the Soil and Water Assessment Tool (SWAT) model; and (3) simulated the transient glacier retreat and its impacts on streamflow at basin scale. Application of the enhanced SWAT model in the Manas River Basin (MRB) in the Tianshan Mountains in northwest China, shows that the approach is viable as evidenced by a Nash–Sutcliff efficiency of 0.65 and a percent bias of −3.7% for daily streamflow and water balance, respectively. The results indicate that the glacier area decreased by 11% during the simulation period from 1961 to 1999, which is within the range of records from other glaciers. On average, glacier melt contributed 25% to streamflow, although glacier area accounts for only 14% of the catchment drainage area in the MRB. Glacier melt was positively correlated to temperature change (R 2 =0.70, statistical significance P <0.001) and negatively correlated to precipitation (R 2 =0.20, statistical significance P <0.005). The results indicate that glacier melt was more sensitive to temperature change than to precipitation change, implying that modeling the effects of climate change with increasing temperatures and decreasing precipitation should be further studied. [ABSTRACT FROM AUTHOR]

Vegetation and land-surface hydrology are intrinsically linked under long-term climate change. This paper aims to evaluate the dynamics of potential natural vegetation arising from 21st century climate change and its possible impact on the water budget of the Hanjiang River basin in China. Based on predictions of the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC-SRES) A1 scenario from the PRECIS (Providing Regional Climates for Impact Studies) regional climate model, changes in plant functional types (PFTs) and leaf area index (LAI) were simulated via the Lund-Potsdam-Jena dynamic global vegetation model. Subsequently, predicted PFTs and LAIs were employed in the Xinanjiang vegetation-hydrology model for rainfall-runoff simulations. Results reveal that future long-term changes in precipitation, air temperature and atmospheric CO2 concentration would remarkably affect the spatiotemporal distribution of PFTS and LAIS. These climate-driven vegetation changes would further influence regional water balance. With the decrease in forest cover in the 21st century, plant transpiration and evaporative loss of intercepted canopy water will tend to fall while soil evaporation may rise considerably. As a result, total evapotranspiration may increase moderately with a slight increase in annual runoff depth. This indicates that, for long-term hydrological prediction, climate-induced changes in terrestrial vegetation cannot be neglected as the terrestrial biosphere plays an important role in land-surface hydrological responses. [ABSTRACT FROM AUTHOR]

Summary: Miyun Reservoir is the main raw water source for Beijing’s domestic water supply. Flow discharge to Miyun Reservoir decreased drastically over a 50-year period, from 1956 to 2005, and had seriously affected Beijing’s water supply. Climate variability and human activity had been identified as the two main reasons for the decrease in flow. Here, climate variability refers to changes in precipitation and temperature. Impact of human activity includes direct withdrawal of water (referred to as “direct abstraction” in this paper) from the river (primary) or groundwater and indirect impact due to man-made changes in land use and vegetation in the upstream of the reservoir. According to the historical record, “direct abstraction” from the upstream of the reservoir has increased significantly since 1984. The study period was split into two sub-periods, from 1956 to 1983 and from 1984 to 2005. Based on the historical record, annual runoff in the upstream catchment of Miyun Reservoir (i.e., inflow into the reservoir) had decreased from 90.3mm to 41.8mm for the two sub-periods, a decrease of 48.5mm. Over the same period, average annual “direct abstraction” increased from 2.2mm to 13.4mm, an increase of 11.2mm. The latter accounted for 23% (11.2mm/48.5mm) of the decrease in inflow into the reservoir. This study utilised: (1) a distributed hydrological model (geomorphology-based hydrological model, or GBHM) and (2) a climate elasticity model to conduct a quantitative assessment of the impact of climate variability and the indirect impact of human activity on the inflow into the reservoir. Simulation results of GBHM and the climate elasticity model showed that climate impact was accountable for about 55% and 51% of the decrease in reservoir inflow, respectively. The indirect impact of human activity (mainly man-made land use and vegetation changes) accounted for 18% of the decrease in reservoir inflow. [Copyright &y& Elsevier]

The sediment yield of the Yellow River Basin has obviously decreased since the 1980s, and the impacts of precipitation on sediment yield changes have become increasingly important with the global climate change. The spatial and temporal variations in annual precipitation and different classes of precipitation in the Hekouzhen-Longmen region (HLR) in the middle reaches of the Yellow River Basin were investigated using data collected from 301 rainfall stations from 1966 to 2016. The impacts of precipitation variation on sediment yield were evaluated, and the hydrological modeling method was used to quantitatively assess the attribution of precipitation and other factors to sediment yield changes in the HLR. The results show that the annual precipitation and P10 increased from the northwest to the southeast of the HLR, suggesting it was drier in the northwest region of the HLR. P25 and P50 were mainly concentrated in the northwestern and southwestern parts of the HLR, reflecting that heavy rain was more likely to occur in these regions of the HLR. All of the annual precipitation and different classes of precipitation had no significant changing trends from 1966 to 2016, and the relationship between rainfall and sediment yield obviously changed in 2006. Compared with the average annual mean values from 1966 to 2016, both the annual precipitation and the different classes of precipitation were higher in the HLR during 2007–2016. The sediment yield decrease during 1990–1999 was mainly influenced by precipitation, while other factors were the main driving factor for the sediment yield decrease in the periods of 1980–1989, 2000–2009, and 2010–2016, and other factors have become the dominant driving factors of the sediment yield change in the HLR since 2000. [ABSTRACT FROM AUTHOR]

In recent decades, remarkable hydrological variations resulting from climate change and human activities have significantly affected rivers globally. Thus, it is important for local water resource planning and management to examine hydrologic regime variations. The aim of this study was to determine the changes in the mean annual runoff series and hydrological characteristic parameter of the Wenyu River. In addition, climate change and human activity were discussed for looking for the most causative factors of hydrological variations of the Wenyu River. The results indicated that annual runoff series exhibited an overall decreasing trend with two significant change points in 1972 and 1984. Over time, the number of hydrological variation index increased significantly and different changes of hydrological regime were exhibited during various periods. The comparative analysis indicated that the variations in runoff were likely driven by human activity rather than climate change. Reservoir operations and changes in water consumption resulting from regional economic development in human activities markedly affected the hydrological features of the Wenyu River. To be specific, the variations in annual runoff and low flow were attributed to regional fluctuations in water demand, but the inter-annual changes and maximal and minimal flow variations after 1972 were likely due to the joint influence of reservoir regulations and variations in water consumption. [ABSTRACT FROM PUBLISHER]

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]

Five General Circulation Model (GCM) climate projections under the RCP8.5 emission scenario were used to drive the Variable Infiltration Capacity (VIC) hydrologic model to investigate the impacts of climate change on hydrologic cycle over continental China in the 21st century. The bias-corrected climatic variables were generated for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). Results showed much larger fractional changes of annual mean Evapotranspiration (ET) per unit warming than the corresponding fractional changes of Precipitation (P) per unit warming across the country, especially for South China, which led to a notable decrease of surface water variability (P-E). Specifically, negative trends for annual mean runoff up to −0.33%/year and soil moisture trends varying between −0.02% to −0.13%/year were found for most river basins across China. Coincidentally, interannual variability for both runoff and soil moisture exhibited significant positive trends for almost all river basins across China, implying an increase in extremes relative to the mean conditions. Noticeably, the largest positive trends for runoff variability and soil moisture variability, which were up to 0.41%/year and 0.90%/year, both occurred in Southwest China. In addition to the regional contrast, intra-seasonal variation was also large for the runoff mean and runoff variability changes, but small for the soil moisture mean and variability changes. Our results suggest that future climate change could further exacerbate existing water-related risks (e.g., floods and droughts) across China as indicated by the marked decrease of surface water amounts combined with a steady increase of interannual variability throughout the 21st century. This study highlights the regional contrast and intra-seasonal variations for the projected hydrologic changes and could provide a multi-scale guidance for assessing effective adaptation strategies for China on a river basin, regional, or as a whole. [ABSTRACT FROM AUTHOR]

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A comparison study of meteorological, hydrological and agricultural drought responses to climate change resulting from different General Circulation Models (GCMs), emission scenarios and hydrological models is presented. Drought variations from 1961-2000 to 2061-2100 in Huai River basin above Bengbu station in China are investigated. Meteorological drought is recognized by the Standardized Precipitation Index (SPI) while hydrological drought and agricultural drought are indexed with a similar standardized procedure by the Standardized Runoff Index (SRI) and Standardized Soil Water Index (SSWI). The results generally approve that hydrological and agricultural drought could still pose greater threats to local water resources management in the future, even with a more steady background to meteorological drought. However, the various drought responses to climate change indicate that uncertainty arises in the propagation of drought from meteorological to hydrological and agricultural systems with respect to alternative climates. The uncertainty in hydrological model structure, as well as the uncertainties in GCM and emission scenario, are aggregated to the results and lead to much wider variations in hydrological and agricultural drought characteristics. Our results also reveal that the selection of hydrological models can induce fundamental differences in drought simulations, and the role of hydrological model uncertainty may become dominating among the three uncertainty sources while recognizing frequency of extreme drought and maximum drought duration. [ABSTRACT FROM AUTHOR]

Hydrological processes change from the impacts of climate variability and human activities. Runoff in the upper reaches of the Hun-Taizi River basin, which is mainly covered by forests in northeast China, decreased from 1960 to 2006. The data used in this study were based on runoff records from six hydrological stations in the upper reaches of the Hun-Taizi River basin. Nonparametric Mann-Kendall statistic was used to identify change trends and abrupt change points and consequently analyze the change characteristics in hydrological processes. The abrupt change in the annual runoff in most subcatchments appeared after 1975. Finally, the effects of climate change and land cover change on water resources were identified using regression analysis and a hydrology model. Results of the regression analysis suggest that the correlation coefficients between precipitation and runoff prior to the abrupt change were higher compared with those after the abrupt change. Moreover, using hydrology model analysis, the water yield was found to increase because of the decrease in forest land. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Runoff in major rivers in China has been decreasing in recent decades. The attribution of hydrologic variability to human activity or climate change is a challenging problem and an active research area. In this study, a sequential cluster analysis method was used to detect undisturbed parts of the record for the Kuyehe River catchment in China. The variable infiltration capacity (VIC) land-surface model was calibrated and verified using observed hydrometeorological data from a period with relatively little human-induced disturbance. The calibrated VIC model was then used to simulate natural runoff during the human-regulated period. Results indicate that the recorded runoff at Wenjiachuan station had significant decline trend of . Time series of runoff was detected and divided into three epochs at two critical years of 1980 and 1998. The VIC model performed well in simulating monthly discharges in the catchment, both Nash and Sutcliffe efficiency (NSE) critera in calibration (1955 to 1969) and verification (1970 to 1979) were above 70% while relative errors (REs) were less than 5%. Human activity was the main driver behind 68% of the runoff reduction that occurred for the period of 1980 to 2008. [ABSTRACT FROM AUTHOR]

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]

Model calibration is essential for hydrologic modeling of large watersheds in a heterogeneous mountain environment. Little guidance is available for model calibration protocols for distributed models that aim at capturing the spatial variability of hydrologic processes. This study used the physically-based distributed hydrologic model, MIKE SHE, to contrast a lumped calibration protocol that used stream- flow measured at one single watershed outlet to a multi-site calibration method which employed streamflow measurements at three stations within the large Chaohe River basin in northern China. Simulation results showed that the singlesite calibrated model was able to sufficiently simulate the hydrographs for two of the three stations (Nash-Sutcliffe coefficient of 0.65-0.75, and correlation coefficient 0.81-0.87 during the testing period), but the model performed poorly for the third station (Nash-Sutcliffe coefficient only 0.44). Sensitivity analysis suggested that streamflow of upstream area of the watershed was dominated by slow groundwater, whilst streamflow of middle- and down- stream areas by relatively quick interflow. Therefore, a multi-site calibration protocol was deemed necessary. Due to the potential errors and uncertainties with respect to the representation of spatial variability, performance measures from the multi-site calibration protocol slightly decreased for two of the three stations, whereas it was improved greatly for the third station. We concluded that multi-site calibration protocol reached a compromise in term of model performance for the three stations, reasonably representing the hydrographs of all three stations with Nash-Sutcliffe coefficient ranging from 0.59- 072. The multi-site calibration protocol applied in the analysis generally has advantages to the single site calibration protocol. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau and the adjacent high mountain regions of the Himalayas play an important role in the global climate dynamic through its impact on the Asian monsoon system, which in turn is impacting the water resources of this extremely vulnerable region. To provide further knowledge about the changing impact of rainfall patterns, spatial and temporal variability of snow cover contribution, amount of snow and ice melt runoff, evapotranspiration as well as dynamics of wetlands and permafrost water balance studies are required. This is of particular importance in terms of global climate change because of a severe gap in the knowledge of the short, mid and long term implications on the hydrological system. This study concentrates on the macroscale catchment of the lake Nam Co, located at 4718ma.s.l. at the foot of the Nyainqentanglha Mountains in central Tibet (30° N, 90° E). The water balance of the Nam Co basin is dominated by semi-arid climate, snow and ice melt runoff and high evaporation rates due to the high radiation input and the low air humidity. The observed temperature rise, glacier retreat, permafrost decay and lake level increase indicate significant system changes and the high sensitivity of the Tibetan Plateau on global warming. The development of a suitable water balance model and its preliminary application was the main objective of this study. The development was done with the Jena Adaptable Modelling System JAMS along with existing scientific process components of the J2000 module library which were partly further developed to reflect the specific conditions of the high elevation Nam Co basin. The preliminary modelling exercise based on gridded data from a downscaled ECHAM5 data set provided reasonable estimates about the important hydrological water balance components of the Nam Co basin. With the modelling results the observed lake level rise could be reproduced and it could be shown that the runoff from the glaciered areas seems to be the most important component to explain the increasing amount of lake water. [ABSTRACT FROM AUTHOR]

A distributed biosphere hydrological (DBH) model system was used to explore the internal relations among the climate system, human society, and the hydrological system in the Yellow River basin, and to interpret possible mechanisms for observed changes in Yellow River streamflow from 1960 to 2000. Several scenarios were evaluated to elucidate the hydrological response to climate system, land cover, and irrigation. The results show that climate change is the dominant cause of annual streamflow changes in the upper and middle reaches, but human activities dominate annual streamflow changes in the lower reaches of the Yellow River basin. The annual river discharge at the mouth is affected by climate change and by human activities in nearly equal proportion. The linear component of climate change contributes to the observed annual streamflow decrease, but changes in the climate temporal pattern have a larger impact on annual river discharge than does the linear component of climate change. Low flow is more significantly affected by irrigation withdrawals than by climate change. Reservoirs induce more diversions for irrigation, while at the same time the results demonstrate that the reservoirs may help to maintain environmental flows and counter what otherwise would be more serious reductions in low flows. [ABSTRACT FROM AUTHOR]

Hydrological models at a monthly time-scale are important tools for hydrological analysis, such as in impact assessment of climate change and regional water resources planning. Traditionally, monthly models adopt a conceptual, lumped-parameter approach and cannot account for spatial variations of basin characteristics and climatic inputs. A large requirement for data often severely limits the utility of physically based, distributed-parameter models. Based on the variable-source-area concept, we considered basin topography and rainfall to be two major factors whose spatial variations play a dominant role in runoff generation and developed a monthly model that is able to account for their influences in the spatial and temporal dynamics of water balance. As a hybrid of the Xinanjiang model and TOPMODEL, the new model is constructed by innovatively making use of the highly acclaimed simulation techniques in the two existing models. A major contribution of this model development study is to adopt the technique of implicit representation of soil moisture characteristics in the Xinanjiang model and use the TOPMODEL concept to integrate terrain variations into runoff simulation. Specifically, the TOPMODEL topographic index In(a/tan β) is converted into an index of relative difficulty in runoff generation (IRDG) and then the cumulative frequency distribution of IRDG is used to substitute the parabolic curve, which represents the spatial variation of soil storage capacity in the Xinanjiang model. Digital elevation model data play a key role in the modelling procedures on a geographical information system platform, including basin segmentation, estimation of rainfall for each sub-basin and computation of terrain characteristics. Other monthly data for model calibration and validation are rainfall, pan evaporation and runoff. The new model has only three parameters to be estimated, i.e. watershed-average field capacity WM, pan coefficient η and runoff generation coefficient α. Sensitivity analysis demonstrates that runoff is least sensitive to WM and, therefore, it can be determined by a prior estimation based on the climate and soil properties of the study basin. The other two parameters can be determined using optimization methods. Model testing was carried out in a number of nested sub-basins of two watersheds (Yuanjiang River and Dongjiang River) in the humid region in central and southern China. Simulation results show that the model is capable of describing spatial and temporal variations of water balance components, including soil moisture content, evapotranspiration and runoff, over the watershed. With a minimal requirement for input data and parameterization, this terrain-based distributed model is a valuable contribution to the ever-advancing technology of hydrological modelling. [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]