Why lowland riparian trees are difficult to use for streamflow reconstruction

Existing streamflow reconstructions based on tree-ring analysis mostly rely on species from upland,mainly montane areas,while lowland species(generally plain)areas are rarely used.This limits the understanding of streamflow change history in the lowlands,which is an important basis for water resource management.This study focused on Populus euphratica stands located along the main stream,eastern and western tributaries in the lower reaches of the Heihe River basin(HRb),in arid northwestern China.We investigated how streamflow regulation interferes with ripar-ian trees in lowlands when they used for streamflow recon-struction.Tree-ring width chronologies were developed and analyzed in conjunction with meteorological and hydrologic observation data.The results show streamflow regulation leads in sharp fluctuations in the streamflow allocation between the eastern tributaries and western tributaries.This resulted in instability of the correlation between streamflow at the two tributaries and at the Zhengyixia hydrologic station,with corresponding fluctuations in radial growth of poplar trees on the banks of the two tributaries and at the station.Streamflow regulation altered the natural patterns of seasonal streamflow below the station,changing the time window of poplar response.This study provides useful insight into tree-ring width based streamflow reconstruction in the lowlands.

Review of Recent Trends in the Hybridisation of Preprocessing-Based and Parameter Optimisation-Based Hybrid Models to Forecast Univariate Streamflow

Forecasting river flow is crucial for optimal planning,management,and sustainability using freshwater resources.Many machine learning(ML)approaches have been enhanced to improve streamflow prediction.Hybrid techniques have been viewed as a viable method for enhancing the accuracy of univariate streamflow estimation when compared to standalone approaches.Current researchers have also emphasised using hybrid models to improve forecast accuracy.Accordingly,this paper conducts an updated literature review of applications of hybrid models in estimating streamflow over the last five years,summarising data preprocessing,univariate machine learning modelling strategy,advantages and disadvantages of standalone ML techniques,hybrid models,and performance metrics.This study focuses on two types of hybrid models:parameter optimisation-based hybrid models(OBH)and hybridisation of parameter optimisation-based and preprocessing-based hybridmodels(HOPH).Overall,this research supports the idea thatmeta-heuristic approaches precisely improveML techniques.It’s also one of the first efforts to comprehensively examine the efficiency of various meta-heuristic approaches(classified into four primary classes)hybridised with ML techniques.This study revealed that previous research applied swarm,evolutionary,physics,and hybrid metaheuristics with 77%,61%,12%,and 12%,respectively.Finally,there is still room for improving OBH and HOPH models by examining different data pre-processing techniques and metaheuristic algorithms.

Mixed D-vine copula-based conditional quantile model for stochastic monthly streamflow simulation

Copula functions have been widely used in stochastic simulation and prediction of streamflow.However,existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate block for all months.To address this limitation,this study developed a mixed D-vine copula-based conditional quantile model that can capture temporal correlations.This model can generate streamflow by selecting different historical streamflow variables as the conditions for different months and by exploiting the conditional quantile functions of streamflows in different months with mixed D-vine copulas.The up-to-down sequential method,which couples the maximum weight approach with the Akaike information criteria and the maximum likelihood approach,was used to determine the structures of multivariate Dvine copulas.The developed model was used in a case study to synthesize the monthly streamflow at the Tangnaihai hydrological station,the inflow control station of the Longyangxia Reservoir in the Yellow River Basin.The results showed that the developed model outperformed the commonly used bivariate copula model in terms of the performance in simulating the seasonality and interannual variability of streamflow.This model provides useful information for water-related natural hazard risk assessment and integrated water resources management and utilization.

Integrated Hydrological Modeling of the Godavari River Basin in Maharashtra Using the SWAT Model: Streamflow Simulation and Analysis

Hydrological modeling plays a crucial role in efficiently managing water resources and understanding the hydrologic behavior of watersheds. This study aims to simulate daily streamflow in the Godavari River Basin in Maharashtra using the Soil and Water Assessment Tool (SWAT). SWAT is a process-based hydrological model used to predict water balance components, sediment levels, and nutrient contamination. In this research, we used integrated remote sensing and GIS data, including Digital Elevation Models (DEM), land use and land cover (LULC) maps, soil maps, and observed precipitation and temperature data, as input for developing the SWAT model to assess surface runoff in this large river basin. The Godavari River Basin under study was divided into 25 sub-basins, comprising 151 hydrological response units categorized by unique land cover, soil, and slope characteristics using the SWAT model. The model was calibrated and validated against observed runoff data for two time periods: 2003-2006 and 2007-2010 respectively. Model performance was assessed using the Nash-Sutcliffe efficiency (NSE) and the coefficient of determination (R2). The results show the effectiveness of the SWAT2012 model, with R2 value of 0.84 during calibration and 0.86 during validation. NSE values also ranged from 0.84 during calibration to 0.85 during validation. These findings enhance our understanding of surface runoff dynamics in the Godavari River Basin under study and highlight the suit-ability of the SWAT model for this region.

Impacts of degrading permafrost on streamflow in the source area of Yellow River on the Qinghai-Tibet Plateau,China

Many observations in and model simulations for northern basins have confirmed an increased streamflow from degrading permafrost,while the streamflow has declined in the source area of the Yellow River(SAYR,above the Tanag hydrological station)on the northeastern Qinghai-Tibet Plateau,West China.How and to what extent does the degrading permafrost change the flow in the SAYR?According to seasonal regimes of hydrological processes,the SAYR is divided intofour sub-basins with varied permafrost extents to detect impacts of permafrost degradation on the Yellow River streamflow.Results show that permafrost degradation may have released appreciable meltwater for recharging groundwater.The potential release rate of ground-ice melt-water in the Sub-basin 1(the headwater area of the Yellow River(HAYR),above the Huangheyan hydrological station)is the highest(5.6 mm per year),contributing to 14.4%of the annual Yellow River streamflow at Huangheyan.Seasonal/intra-and annual shifts of streamflow,a possible signal for the marked alteration of hydrological processes by permafrost degradation,is observed in the HAYR,but the shifts are minor in other sub-basins in the SAYR.Improved hydraulic connectivity is expected to occur during and after certain degrees of permafrost degradation.Direct impacts of permafrost degradation on the annual Yellow River streamflow in the SAYR at Tanag,i.e.,from the meltwater of ground-ice,is estimated at 4.9%that of the annual Yellow River discharge at Tanag,yet with a high uncertainty,due to neglecting of the improved hydraulic connections from permafrost degradation and the flow generation conditions for the ground-ice meltwater.Enhanced evapotranspiration,substantial weakening of the Southwest China Autumn Rain,and anthropogenic disturbances may largely account for the declined streamflow in the SAYR.

Monthly and seasonal streamflow forecasting of large dryland catchments in Brazil

Streamflow forecasting in drylands is challenging.Data are scarce,catchments are highly humanmodified and streamflow exhibits strong nonlinear responses to rainfall.The goal of this study was to evaluate the monthly and seasonal streamflow forecasting in two large catchments in the Jaguaribe River Basin in the Brazilian semi-arid area.We adopted four different lead times:one month ahead for monthly scale and two,three and four months ahead for seasonal scale.The gaps of the historic streamflow series were filled up by using rainfall-runoff modelling.Then,time series model techniques were applied,i.e.,the locally constant,the locally averaged,the k-nearest-neighbours algorithm(k-NN)and the autoregressive(AR)model.The criterion of reliability of the validation results is that the forecast is more skillful than streamflow climatology.Our approach outperformed the streamflow climatology for all monthly streamflows.On average,the former was 25%better than the latter.The seasonal streamflow forecasting(SSF)was also reliable(on average,20%better than the climatology),failing slightly only for the high flow season of one catchment(6%worse than the climatology).Considering an uncertainty envelope(probabilistic forecasting),which was considerably narrower than the data standard deviation,the streamflow forecasting performance increased by about 50%at both scales.The forecast errors were mainly driven by the streamflow intra-seasonality at monthly scale,while they were by the forecast lead time at seasonal scale.The best-fit and worst-fit time series model were the k-NN approach and the AR model,respectively.The rainfall-runoff modelling outputs played an important role in improving streamflow forecasting for one streamgauge that showed 35%of data gaps.The developed data-driven approach is mathematical and computationally very simple,demands few resources to accomplish its operational implementation and is applicable to other dryland watersheds.Our findings may be part of drought forecasting systems and potentially help allocating water months in advance.Moreover,the developed strategy can serve as a baseline for more complex streamflow forecast systems.

Comparison of performance of statistical models in forecasting monthly streamflow of Kizil River,China

This paper presents the application of autoregressive integrated moving average （ARIMA）, seasonal ARIMA （SARIMA）, and Jordan-Elman artificial neural networks （ANN） models in forecasting the monthly streamflow of the Kizil River in Xinjiang, China. Two different types of monthly streamflow data （original and deseasonalized data） were used to develop time series and Jordan-Elman ANN models using previous flow conditions as predictors. The one-month-ahead forecasting performances of all models for the testing period （1998-2005） were compared using the average monthly flow data from the Kalabeili gaging station on the Kizil River. The Jordan-Elman ANN models, using previous flow conditions as inputs, resulted in no significant improvement over time series models in one-month-ahead forecasting. The results suggest that the simple time series models （ARIMA and SARIMA） can be used in one-month-ahead streamflow forecasting at the study site with a simple and explicit model structure and a model performance similar to the Jordan-Elman ANN models.

Streamflow and Soil Moisture of Agroforestry and Grass Watersheds in Hilly Area

A study was conducted in a hilly area of Sichuan Province,Southwestern China, to compare the streamflow and soil moisture in two upland watersheds with different land use patterns. One was an agroforestry watershed, which consisted mainly of trees with alder (Alnus cremastogyne Burkill) and cypress (Cupressus funebris Endl.) planted in belts or strips with a coverage of about 46%, and the other was a grassland primarily composed of lalang grass (Imperata cylindrica var. major (Nees) C. E. Hubb.), filamentary clematis (Clematis filamentosa Dunn) and common eulaliopsis (Eulaliopsis binata (Retz.) C. E. Hubb) with a coverage of about 44%. Streamflow measurement with a hydrograph established at the watershed outlet showed that the average annual streamflow per 100 mm rainfall from 1983 to 1992 was 0.36 and 1.08 L s-1 km-2 for the agroforestry watershed and the grass watershed, respectively. This showed that the streamflow of the agroforestry watershed was reduced by 67% when compared to that of the grass watershed. The peak average monthly streamflow in the agroforestry watershed was over 5 times lower than that of the grass watershed and lagged by one month. In addition, the peak streamflow during a typical rainfall event of 38.3 mm in August 1986 was 37% lower in the agroforestry watershed than in the grass watershed. Results of the moisture contents of the soil samples from 3 slope locations (upper, middle and lower slopes) indicated that the agroforestry watershed maintained generally higher soil moisture contents than the grass watershed within 0-20 and 20-80 cm soil depths for the upper slope, especially for the period from May through July. For the other (middle and lower) slopes, soil moisture contents within 20-80 cm depth in the agroforestry watershed was generally lower than those in the grass watershed, particularly in September, revealing that water consumption by trees took place mainly below the plow layer. Therefore, agroforestry land use types might offer a complimentary model for tree-annual crop water utilization.

Implications of Climate Change on Streamflow of a Snow-Fed River System of the Northwest Himalaya

Air temperature and snow cover variability are sensitive indicators of climate change. This study was undertaken to forecast and quantify the potential streamflow response to climate change in the Jhelum River basin. The implications of air temperature trends （＋0.11℃decade） reported for the entire north-west Himalaya for past century and the regional warming （＋0.7℃/decade） trends of three observatories analyzed between last two decades were used for future projection of snow cover depletion and stream flow. The streamflow was simulated and validated for the year 2007-2008 using snowmelt runoff model （SRM） based on in-situ temperature and precipitation with remotely sensed snow cover area. The simulation was repeated using higher values of temperature and modified snow cover depletion curves according to the assumed future climate. Early snow cover depletion was observed in the basin in response to warmer climate. The results show that with the increase in air temperature, streamfiow pattern of Jhelum will be severely affected. Significant redistribution of streamflow was observed in both the scenarios. Higher discharge was observed during spring-summer months due to early snowmelt contribution with water deficit during monsoon months. Discharge increased by 5%-40% during the months of March to May in 2030 and 2050. The magnitude of impact of air temperature is higher in the scenario-2 based on regional warming. The inferences pertaining to change in future streamflow pattern can facilitate long term decisions and planning concerning hydro-power potential, waterresource management and flood hazard mapping in the region.

A Modified Groundwater Module in SWAT for Improved Streamflow Simulation in a Large, Arid Endorheic River Watershed in Northwest China

Interactions between surface water and groundwater are dynamic and complex in large endorheic river watersheds in Northwest China due to the influence of both irrigation practices and the local terrain. These interactions interchange numerous times throughout the middle reaches, making streamflow simulation a challenge in endorheic river watersheds. In this study, we modified the linear-reservoir groundwater module in SWAT(Soil and Water Assessment Tools, a widely used hydrological model) with a new nonlinear relationship to better represent groundwater processes; we then applied the original SWAT and modified SWAT to the Heihe River Watershed, the second largest endorheic river watershed in Northwest China, to simulate streamflow. After calibrating both the original SWAT model and the modified SWAT model, we analyzed model performance during two periods: an irrigation period and a non-irrigation period. Our results show that the modified SWAT model with the nonlinear groundwater module performed significantly better during both the irrigation and non-irrigation periods. Moreover, after comparing different runoff components simulated by the two models, the results show that, after the implementation of the new nonlinear groundwater module in SWAT, proportions of runoff components changed-and the groundwater flow had significantly increased, dominating the discharge season. Therefore, SWAT coupled with the non-linear groundwater module represents the complex hydrological process in the study area more realistically. Moreover, the results for various runoff components simulated by the modified SWAT models can be used to describe the hydrological characteristics of lowland areas. This indicates that the modified SWAT model is applicable to simulate complex hydrological process of arid endorheic rivers.

Capability of TMPA products to simulate streamflow in upper Yellow and Yangtze River basins on Tibetan Plateau

Due to the high elevation, complex terrain, severe weather, and inaccessibility, direct meteorological observations do not exist over large portions of the Tibetan Plateau, especially the western part of it. Satellite rainfall estimates have been very important sources for precipitation information, particularly in rain gauge-sparse regions. In this study, Tropical Rainfall Measuring Mission （TRMM） Multi-satellite Precipitation Analysis （TMPA） products 3B42, RTV5V6, and RTV7 were evaluated for their applicability to the upper Yellow and Yangtze River basins on the Tibetan Plateau. Moreover, the capability of the TMPA products to simulate streamflow was also investigated using the Variable Infiltration Capacity （VIC） semi-distributed hydrological model. Results show that 3B42 performs better than RTVSV6 and RTV7, based on verification of the China Meteorological Administration （CMA） observational precipitation data. RTVSV6 can roughly capture the spatial precipitation pattern but overestimation exists throughout the entire study region. The anticipated improvements of RTV7 relative to RTVSV6 have not been realized in this study. Our results suggest that RTV7 significantly overestimates the precipitation over the two river basins, though it can capture the seasonal cycle features of precipitation. 3B42 shows the best performance in streamflow simulation of the abovementioned satellite products. Although involved in gauge adjustment at a monthly scale, 3B42 is capable of daily streamflow simulation. RTV5V6 and RTV7 have no capability to simulate streamflow in the upper Yellow and Yangtze River basins.

Impact of Meteorological Drought on Streamflow Drought in Jinghe River Basin of China

Under global climate change, drought has become one of the most serious natural hazards, affecting the ecological environment and human life. Drought can be categorized as meteorological, agricultural, hydrological or socio-economic drought. Among the different categories of drought, hydrological drought, especially streamflow drought, has been given more attention by local governments, researchers and the public in recent years. Identifying the occurrence of streamflow drought and issuing early warning can provide timely information for effective water resources management. In this study, streamflow drought is detected by using the Standardized Runoff Index, whereas meteorological drought is detected by the Standardized Precipitation Index. Comparative analyses of frequency, magnitude, onset and duration are conducted to identify the impact of meteorological drought on streamflow drought. This study focuses on the Jinghe River Basin in Northwest China, mainly providing the following findings. 1) Eleven meteorological droughts and six streamflow droughts were indicated during 1970 and 1990 after pooling using Inter-event time and volume Criterion method. 2) Streamflow drought in the Jinghe River Basin lagged meteorological drought for about 127 days. 3) The frequency of streamflow drought in Jinghe River Basin was less than meteorological drought. However, the average duration of streamflow drought is longer. 4) The magnitude of streamflow drought is greater than meteorological drought. These results not only play an important theoretical role in understanding relationships between different drought categories, but also have practical implications for streamflow drought mitigation and regional water resources management.

Streamflow Simulation for the Yellow River Basin Using RIEMS and LRM

The streamflow over the Yellow River basin is simulated by using the high-resolution Regional Integrated Environmental Model System (RIEMS), and an off-line Large-scale Routing Model (LRM). The RIEMS was designed and has been developed by the Global Change System for Analysis, Research and Training Regional Center for Temperate East Asia (START/TEA) since 1991 and has a good capability to simulate the regional climate of East Asia. The LRM is based on the assumption of linearity and time invariance and can calculate the horizontal travel of water. The RIEMS-LRM allows the direct comparison of predicted and observed streamflow data for large-scale rivers. The application of the RIEMS-LRM to the upper reaches of the Yellow River verifies that the coupled model system has the capability to simulate the streamflow over a large-scale river. Furthermore, the paper discusses the reasons leading to simulation errors.

Streamflow response to shrinking glaciers under changing climate in the Lidder Valley,Kashmir Himalayas

The study investigated the streamflow response to the shrinking cryosphere under changing climate in the Lidder valley, Upper Indus Basin(UIB), Kashmir Himalayas. We used a combination of multitemporal satellite data and topographic maps to evaluate the changes in area, length and volume of the glaciers from 1962 to 2013. A total of 37 glaciers from the Lidder valley, with an area of 39.76 km^2 in 1962 were selected for research in this study. It was observed that the glaciers in the valley have lost ~28.89 ±0.1% of the area and ~19.65 ±0.069% of the volume during the last 51 years, with variable interdecadal recession rates. Geomorphic and climatic influences on the shrinking glacier resources were studied. 30-years temperature records(1980-2010) in the study area showed a significant increasing trend in all the seasons. However, the total annual precipitation during the same period showed a nonsignificant decreasing trend except during the late summer months(July, August and September), when the increasing trend is significant. The depletion of glaciers has led to the significant depletion of the streamflows under the changing climate in the valley. Summer streamflows(1971-2012) have increased significantly till mid-nineties but decreased significantly thereafter, suggesting that the tipping point of streamflow peak, due to the enhanced glacier-melt contribution under increasing global temperatures, may have been already reached in the basin. The observed glacier recession and climate change patterns, if continued in future, would further deplete the streamflows with serious implications on water supplies for different uses in the region.

Hydrological Impacts of Climate Change on Streamflow of Dongliao River Watershed in Jilin Province,China

The impacts of future climate change on streamflow of the Dongliao River Watershed located in Jilin Prov-ince, China have been evaluated quantitatively by using a general circulation model （HadCM3） coupled with the Soil and Water Assessment Tool （SWAT） hydrological model. The model was calibrated and validated against the historical monitored data from 2005 to 2009. The streamflow was estimated by downscaling HadCM3 outputs to the daily mean temperature and precipitation series, derived for three 30-year time slices, 2020s, 2050s and 2080s. Results suggest that daily mean temperature increases with a changing rate of 0.435~C per decade, and precipitation decreases with a changing rate of 0.761 mm per decade. Compared with other seasons, the precipitation in summer shows significant downward trend, while a significant upward trend in autumn. The annual streamflow demonstrates a general down-ward trend with a decreasing rate of 0.405 m^3/s per decade. The streamflow shows significant downward and upward trends in summer and in autumn, respectively. The decreasing rate of streamflow in summer reaches 1.97 m^3/s per decade, which contributes primarily to the decrease of streamflow. The results of this work would be of great benifit to the design of economic and social development planning in the study area.

Snow Cover Variation and Streamflow Simulation in a Snow-fed River Basin of the Northwest Himalaya

Snowmelt is an important component of any snow-fed river system.The Jhelum River is one such transnational mountain river flowing through India and Pakistan.The basin is minimally glacierized and its discharge is largely governed by seasonal snow cover and snowmelt.Therefore,accurate estimation of seasonal snow cover dynamics and snowmeltinduced runoff is important for sustainable water resource management in the region.The present study looks into spatio-temporal variations of snow cover for past decade and stream flow simulation in the Jhelum River basin.Snow cover extent(SCE) was estimated using MODIS(Moderate Resolution Imaging Spectrometer) sensor imageries.Normalized Difference Snow Index(NDSI) algorithm was used to generate multi-temporal time series snow cover maps.The results indicate large variation in snow cover distribution pattern and decreasing trend in different sub-basins of the Jhelum River.The relationship between SCE-temperature,SCE-discharge and discharge-precipitation was analyzed for different seasons and shows strong correlation.For streamflow simulation of the entire Jhelum basin Snow melt Runoff Model(SRM) used.A good correlation was observed between simulated stream flow and in-situ discharge.The monthly discharge contribution from different sub-basins to the total discharge of the Jhelum River was estimated using a modified version of runoff model based on temperature-index approach developed for small watersheds.Stream power - an indicator of the erosive capability of streams was also calculated for different sub-basins.

Streamflow responses to climate change and LUCC in a semi-arid watershed of Chinese Loess Plateau

Climate change and Land Use/Cover Change（LUCC） have been identified as two primary factors affecting watershed hydrological regime. This study analyzed the trends of streamflow, precipitation, air temperature and potential evapotranspiration（PET） from 1962 to 2008 in the Jihe watershed in northwestern Loess Plateau of China using the Mann-Kendall test. The streamflow responses to climate change and LUCC were quantified independently by the elasticity method. The results show that the streamflow presented a dramatic decline with a turning point occurred in 1971, while the precipitation and PET did not change significantly. The results also show that the temperature rose markedly especially since 1990 s with an approximate increase of 1.74°C over the entire research period（1962–2008）. Using land use transition matrix, we found that slope cropland was significantly converted to terrace between 1970 s and 1990 s and that forest cover increased relatively significantly because of the Grain for Green Project after 2000. The streamflow reduction was predominantly caused by LUCC and its contribution reached up to 90.2%, while the contribution of climate change to streamflow decline was only 9.8%. Although the analytical results between the elasticity method and linear regression model were not satisfactorily consistent, they both indicated that LUCC（human activity） was the major factor causing streamflow decline in the Jihe watershed from 1962 to 2008.

Identification of Suitable Hydrologic Response Unit Thresholds for Soil and Water Assessment Tool Streamflow Modelling

Use of a non-zero hydrologic response unit(HRU) threshold is an effective way of reducing unmanageable HRU numbers and simplifying computational cost in the Soil and Water Assessment Tool(SWAT) hydrologic modelling. However, being less representative of watershed heterogeneity and increasing the level of model output uncertainty are inevitable when minor HRU combinations are disproportionately eliminated. This study examined 20 scenarios by running the model with various HRU threshold settings to understand the mechanism of HRU threshold effects on watershed representation as well as streamflow predictions and identify the appropriate HRU thresholds. Findings show that HRU numbers decrease sharply with increasing HRU thresholds. Among different HRU threshold scenarios, the composition of land-use, soil, and slope all contribute to notable variations which are directly related to the model input parameters and consequently affect the streamflow predictions. Results indicate that saturated hydraulic conductivity, average slope of the HRU, and curve number are the three key factors affecting stream discharge when changing the HRU thresholds. It is also found that HRU thresholds have little effect on monthly model performance, while evaluation statistics for daily discharges are more sensitive than monthly results. For daily streamflow predictions, thresholds of 5%/5%/5%(land-use/soil/slope) are the optimum HRU threshold level for the watershed to allow full consideration of model accuracy and efficiency in the present work. Besides, the results provide strategies for selecting appropriate HRU thresholds based on the modelling goal.

The Linkage between Two Types of El Ni?o Events and Summer Streamflow over the Yellow and Yangtze River Basins

It is generally agreed that El Nino can be classified into East Pacific(EP)and Central Pacific(CP)types.Nevertheless,little is known about the relationship between these two types of El Ni?o and land surface climate elements.This study investigates the linkage between EP/CP El Ni?o and summer streamflow over the Yellow and Yangtze River basins and their possible mechanisms.Over the Yellow River basin,the anomalous streamflow always manifests as positive(negative)in EP(CP)years,with a correlation coefficient of 0.39(-0.37);while over the Yangtze River basin,the anomalous streamflow shows as positive in both EP and CP years,with correlation coefficients of 0.72 and 0.48,respectively.Analyses of the surface hydrological cycle indicate that the streamflow is more influenced by local evapotranspiration(ET)than precipitation over the Yellow River basin,while it is dominantly affected by precipitation over the Yangtze River basin.The different features over these two river basins can be explained by the anomalous atmospheric circulation,which is cyclonic(anticyclonic)north(south)of 30°N over East Asia.EP years are dominated by two anticyclones,which bring strong water vapor convergence and induce more precipitation but less ET,and subsequently increase streamflow and flooding risks.In CP years,especially over the Yellow River basin,two cyclones dominate and lead to water vapor divergence and reduce moisture arriving.Meanwhile,the ET enhances mainly due to local high surface air temperature,which further evaporates water from the soil.As a result,the streamflow decreases,which will then increase the drought risk.

Possible Impacts of Climate Change on Daily Streamflow and Extremes at Local Scale in Ontario, Canada. Part II: Future Projection

The paper forms the second part of an introduction to possible impacts of climate change on daily streamflow and extremes in the Province of Ontario, Canada. Daily streamflow simulation models developed in the companion paper (Part I) were used to project changes in frequency of future daily streamflow events. To achieve this goal, future climate information (including rainfall) at a local scale is needed. A regression-based downscaling method was employed to downscale eight global climate model (GCM) simulations (scenarios A2 and B1) to selected weather stations for various meteorological variables (except rainfall). Future daily rainfall quantities were projected using daily rainfall simulation models with downscaled future climate information. Following these projections, future daily streamflow volumes can be projected by applying daily streamflow simulation models. The frequency of future daily high-streamflow events in the warm season (May–November) was projected to increase by about 45%-55% late this century from the current condition, on average of eight-GCM A2 projections and four selected river basins. The corresponding increases for future daily low-streamflow events and future daily mean streamflow volume could be about 25%-90% and 10%-20%, respectively. In addition, the return values of annual one-day maximum streamflow volume for various return periods were projected to increase by 20%-40%, 20%-50%, and 30%-80%, respectively for the periods 2001-50, 2026-75, and 2051-2100. Inter-GCM and interscenario uncertainties of future streamflow projections were quantitatively assessed. On average, the projected percentage increases in frequency of future daily high-streamflow events are about 1.4-2.2 times greater than inter-GCM and interscenario uncertainties.