Responses of hydrological processes to climate change in the Yarlung Zangbo River basin

ABSTRACT

Climate change alters hydrological processes and results in more extreme hydrological events, e.g. flooding and drought, which threaten human livelihoods. In this study, the large-scale distributed variable infiltration capacity (VIC) model was used to simulate future hydrological processes in the Yarlung Zangbo River basin (YZRB), China, with a combination of the CMIP5 (Coupled Model Intercomparison Project, fifth phase) and MIROC5 (Model for Interdisciplinary Research on Climate, fifth version) datasets. The results indicate that the performance of the VIC model is suitable for the case study, and the variation in runoff is remarkably consistent with that of precipitation, which exhibits a decreasing trend for the period 2046–2060 and an increasing trend for 2086–2100. The seasonality of runoff is evident, and substantial increases are projected for spring runoff, which might result from the increase in precipitation as well as the increase in the warming-induced melting of snow, glaciers and frozen soil. Moreover, evapotranspiration exhibits an increase between 2006–2020 and 2046–2060 over the entire basin, and soil moisture decreases in upstream areas and increases in midstream and downstream areas. For 2086–2100, both evapotranspiration and soil moisture increase slightly in the upstream and midstream areas and decrease slightly in the downstream area. The findings of this study could provide references for runoff forecasting and ecological protection for similar studies in the future.     

Sensitivity of hydrological variables to climate change in the Haihe River basin,China

Using the defined sensitivity index, the sensitivity of streamflow, evapotranspiration and soil moisture to climate change was investigated in four catchments in the Haihe River basin. Climate change contained three parts: annual precipitation and temperature change and the change of the percentage of precipitation in the flood season (P_f). With satisfying monthly streamflow simulation using the variable infiltration capacity model, the sensitivity was estimated by the change of simulated hydrological variables with hypothetical climatic scenarios and observed climatic data. The results indicated that (i) the sensitivity of streamflow would increase as precipitation or P_f increased but would decrease as temperature increased; (ii) the sensitivity of evapotranspiration and soil moisture would decrease as precipitation or temperature increased, but it to P_f varied in different catchments; and (iii) hydrological variables were more sensitive to precipitation, followed by P_f, and then temperature. The nonlinear response of streamflow, evapotranspiration and soil moisture to climate change could provide a reference for water resources planning and management under future climate change scenarios in the Haihe River basin. Copyright © 2011 John Wiley & Sons, Ltd.     

Impact of projected climate change on the hydrology in the headwaters of the Yellow River basin

Located in the northeast of the Tibetan Plateau, the headwaters of the Yellow River basin (HYRB) are very vulnerable to climate change. In this study, we used the Soil and Water Assessment Tool (SWAT) model to assess the impact of future climate change on this region's hydrological components for the near future period of 2013–2042 under three emission scenarios A1B, A2 and B1. The uncertainty in this evaluation was considered by employing Bayesian model averaging approach on global climate model (GCM) multimodel ensemble projections. First, we evaluated the capability of the SWAT model for streamflow simulation in this basin. Second, the GCMs' monthly ensemble projections were downscaled to daily climate data using the bias‐correction and spatial‐disaggregation method and then were utilized as input into the SWAT model. The results indicate the following: (1) The SWAT model exhibits a good performance for both calibration and validation periods after adjusting parameters in snowmelt module and establishing elevation bands in sub‐basins. (2) The projected precipitation suggests a general increase under all three scenarios, with a larger extent in both A1B and B1 and a slight variation for A2. With regard to temperature, all scenarios show pronounced warming trends, of which A2 displays the largest amplitude. (3) In the terms of total runoff from the whole basin, there is an increasing trend in the future streamflow at Tangnaihai gauge under A1B and B1, while the A2 scenario is characterized by a declining trend. Spatially, A1B and B1 scenarios demonstrate increasing trends across most of the region. Groundwater and surface runoffs indicate similar trends with total runoff, whereas all three scenarios exhibit an increase in actual evapotranspiration. Generally, both A1B and B1 scenarios suggest a warmer and wetter tendency over the HYRB in the forthcoming decades, while the case for A2 indicates a warmer and drier trend. Findings from this study can provide beneficial reference to water resource and eco‐environment management strategies for governmental policymakers. Copyright © 2015 John Wiley & Sons, Ltd.     

Climate change impact assessment of a river basin using CMIP5 climate models and the VIC hydrological model

Climate change has significant impacts on water availability in larger river basins. The present study evaluates the possible impacts of projected future daily rainfall (2011–2099) on the hydrology of a major river basin in peninsular India, the Godavari River Basin, (GRB), under RCP4.5 and RCP8.5 scenarios. The study highlights a criteria-based approach for selecting the CMIP5 GCMs, based on their fidelity in simulating the Indian Summer Monsoon rainfall. The nonparametric kernel regression based statistical downscaling model is employed to project future daily rainfall and the variable infiltration capacity (VIC) macroscale hydrological model is used for hydrological simulations. The results indicate an increase in future rainfall without significant change in the spatial pattern of hydrological variables in the GRB. The climate-change-induced projected hydrological changes provide a crucial input to define water resource policies in the GRB. This methodology can be adopted for the climate change impacts assessment of larger river basins worldwide.     

How the performance of hydrological models relates to credibility of projections under climate change

Two approaches can be distinguished in studies of climate change impacts on water resources when accounting for issues related to impact model performance: (1) using a multi-model ensemble disregarding model performance, and (2) using models after their evaluation and considering model performance. We discuss the implications of both approaches in terms of credibility of simulated hydrological indicators for climate change adaptation. For that, we discuss and confirm the hypothesis that a good performance of hydrological models in the historical period increases confidence in projected impacts under climate change, and decreases uncertainty of projections related to hydrological models. Based on this, we find the second approach more trustworthy and recommend using it for impact assessment, especially if results are intended to support adaptation strategies. Guidelines for evaluation of global- and basin-scale models in the historical period, as well as criteria for model rejection from an ensemble as an outlier, are also suggested.     

A hidden Markov model segmentation procedure for hydrological and environmental time series

In this paper we present a procedure for the segmentation of hydrological and enviromental time series. We consider the segmentation problem from a purely computational point of view which involves the minimization of Huberts segmentation cost; in addition this least squares segmentation is equivalent to Maximum Likelihood segmentation. Our segmentation procedure maximizes Likelihood and minimizes Huberts least squares criterion using a hidden Markov model (HMM) segmentation algorithm. This algorithm is guaranteed to achieve a local maximum of the Likelihood. We evaluate the segmentation procedure with numerical experiments which involve artificial, temperature and river discharge time series. In all experiments, the procedure actually achieves the global minimum of the Likelihood; furthermore execution time is only a few seconds, even for time series with over a thousand terms.     

Climate models and hydrological parameter uncertainties in climate change impacts on monthly runoff and daily flow duration curve of a Mediterranean catchment

ABSTRACT

Climate models and hydrological parameter uncertainties were quantified and compared while assessing climate change impacts on monthly runoff and daily flow duration curve (FDC) in a Mediterranean catchment. Simulations of the Soil and Water Assessment Tool (SWAT) model using an ensemble of behavioural parameter sets derived from the Generalized Likelihood Uncertainty Estimation (GLUE) method were approximated by feed-forward artificial neural networks (FF-NN). Then, outputs of climate models were used as inputs to the FF-NN models. Subsequently, projected changes in runoff and FDC were calculated and their associated uncertainty was partitioned into climate model and hydrological parameter uncertainties. Runoff and daily discharge of the Chiba catchment were expected to decrease in response to drier and warmer climatic conditions in the 2050s. For both hydrological indicators, uncertainty magnitude increased when moving from dry to wet periods. The decomposition of uncertainty demonstrated that climate model uncertainty dominated hydrological parameter uncertainty in wet periods, whereas in dry periods hydrological parametric uncertainty became more important.

Editor M.C. Acreman; Associate editor S. Kanae     

Macroscale hydrological modelling approach for study of large scale hydrologic impacts under climate change in Indian river basins

In climate‐change studies, a macroscale hydrologic model (MHM) operating over large scales can be an important tool in developing consistent hydrological variability estimates over large basins. MHMs, which can operate at coarse grid resolutions of about 1° latitude by longitude, have been used previously to study climate change impacts on the hydrology of continental scale or global river basins. They can provide a connection between global atmospheric models and water resource systems on large spatial scales and long timescales. In this study, the variable infiltration capacity (VIC) MHM is used to study large scale hydrologic impacts of climate change for Indian river basins. Large‐scale changes in runoff, evapotranspiration and soil moisture for India, as well as station‐scale changes in discharges for three major river basins with distinct climatic and geographic characteristics are examined in this study. Climate model projections for meteorological variables (precipitation, temperature and wind speed) from three general circulation models (GCMs) and three emissions scenarios are used to drive the VIC MHM. GCM projections are first interpolated to a 1° by 1° hydrologic model grid and then bias‐corrected using a quantile–quantile mapping. The VIC model is able to reproduce observed statistics for discharges in the Ganga, Narmada and Krishna basins reasonably well, even at the coarse grid resolution employed using a calibration period for years 1965–1970 and testing period from 1971–1973/1974. An increasing trend is projected for summer monsoon surface runoff, evapotranspiration and soil moisture in most central Indian river basins, whereas a decrease in runoff and soil moisture is projected for some regions in southern India, with important differences arising from GCM and scenario variability. Discharge statistics show increases in mid‐flow and low flow at Farakka station on Ganga River, increased high flows at Jamtara station upstream of Narmada, and increased high, mid‐flow and low flow for Vijayawada station on Krishna River in the future. Copyright © 2013 John Wiley & Sons, Ltd.     

Response of runoff to climate change in the Wei River basin,China

Abstract

Climate change will likely have severe effects on water shortages, flood disasters and the deterioration of aquatic systems. In this study, the hydrological response to climate change was assessed in the Wei River basin (WRB), China. The statistical downscaling method (SDSM) was used to downscale regional climate change scenarios on the basis of the outputs of three general circulation models (GCMs) and two emissions scenarios. Driven by these scenarios, the Soil and Water Assessment Tool (SWAT) was set up, calibrated and validated to assess the impact of climate change on hydrological processes of the WRB. The results showed that the average annual runoff in the periods 2046–2065 and 2081–2100 would increase by 12.4% and 45%, respectively, relative to the baseline period 1961–2008. Low flows would be much lower, while high flows would be much higher, which means there would be more extreme events of droughts and floods. The results exhibited consistency in the spatial distribution of runoff change under most scenarios, with decreased runoff in the upstream regions, and increases in the mid- and lower reaches of the WRB.

Editor Z.W. Kundzewicz; Associate editor D. Yang     

Evaluation of impacts of climate change and human activities on streamflow in the Poyang Lake basin,China

Variations in streamflows of five tributaries of the Poyang Lake basin, China, because of the influence of human activities and climate change were evaluated using the Australia Water Balance Model and multivariate regression. Results indicated that multiple regression models were appropriate with precipitation, potential evapotranspiration of the current month, and precipitation of the last month as explanatory variables. The NASH coefficient for the Australia Water Balance Model was larger than 0.842, indicating satisfactory simulation of streamflow of the Poyang Lake basin. Comparison indicated that the sensitivity method could not exclude the benchmark‐period human influence, and the human influence on streamflow changes was overestimated. Generally, contributions of human activities and climate change to streamflow changes were 73.2% and 26.8% respectively. However, human‐induced and climate‐induced influences on streamflow were different in different river basins. Specifically, climate change was found to be the major driving factor for the increase of streamflow within the Rao, Xin, and Gan River basins; however, human activity was the principal driving factor for the increase of streamflow of the Xiu River basin and also for the decrease of streamflow of the Fu River basin. Meanwhile, impacts of human activities and climate change on streamflow variations were distinctly different at different temporal scales. At the annual time scale, the increase of streamflow was largely because of climate change and human activities during the 1970s–1990s and the decrease of streamflow during the 2000s. At the seasonal scale, climate change was the main factor behind the increase of streamflow in the spring and summer season. Human activities increase the streamflow in autumn and winter, but decrease the streamflow in spring. At the monthly scale, different influences of climate change and human activities were detected. Climate change was the main factor behind the decrease of streamflow during May to June and human activities behind the decrease of streamflow during February to May. Results of this study can provide a theoretical basis for basin‐scale water resources management under the influence of climate change and human activities. Copyright © 2016 John Wiley & Sons, Ltd.     

Projection of extreme flood inundation in the Mekong River basin under 4K increasing scenario using large ensemble climate data

Projecting changes in the frequency and intensity of future precipitation and flooding is critical for the development of social infrastructure under climate change. The Mekong River is among the world's large-scale rivers severely affected by climate change. This study aims to define the duration of precipitation contributing to peak floods based on its correlation with peak discharge and inundation volume in the Lower Mekong Basin (LMB). We assessed the changes in precipitation and flood frequency using a large ensemble Database for Policy Decision-Making for Future Climate Change (d4PDF). River discharge in the Mekong River Basin (MRB) and flood inundation in the LMB were simulated by a coupled rainfall-runoff and inundation (RRI) model. Results indicated that 90-day precipitation counting backward from the day of peak flooding had the highest correlation with peak discharge (R² = .81) and inundation volume (R² = .81). The ensemble mean of present simulation of d4PDF (1951–2010) showed good agreement with observed extreme flood events in the LMB. The probability density of 90-day precipitation shifted from the present to future climate experiments with a large variation of mean (from 777 to 900 mm) and SD (from 57 to 96 mm). Different patterns of sea surface temperature significantly influence the variation of precipitation and flood inundation in the LMB in the future (2051–2110). Extreme flood events (50-year, 100-year, and 1,000-year return periods) showed increases in discharge, inundation area, and inundation volume by 25%–40%, 19%–36%, and 23%–37%, respectively.     

Shift trend and step changes for runoff time series in the Shiyang River basin,northwest China

Shift trend and step changes were detected for runoff time series in the Shiyang River basin, one of the inland river basins in north‐west China. Annual runoff data from eight tributaries as well as both annual and monthly runoff from the mainstream from 1958 to 2003 were used. Seven statistical test methods were employed to identify the shift trends and step changes in the study. Mann–Kendall test, Spearman's Rho test, linear regression and Hurst exponent were used to detect past and future shift trends for runoff time series, while the distributed‐free CUSUM test, cumulative deviations and the Worsley likelihood ratio test were used to detect step changes for the same time series. Results showed that the annual runoff from Zamu, Huangyang and Gulang rivers, as well as both annual and monthly runoff from the mainstream, show statistically significant decreasing trends. Future tendency of runoff for both tributaries and mainstream were consistent with that from 1958 to 2003. Step changes probably occurred in 1961 for the runoff from Huangyang, Gulang and Dajing rivers according to the Worsley likelihood ratio test, but no similar results were found using the other two test methods. Three change points (1979, 1974 and 1973) were detected for the mainstream using different methods. These change points were close to the years that reservoirs started to be operated. Both climate change and human activities, especially the latter, contributed to the decreasing runoff in the study area. Between 21% and 79% of the reduction in runoff from the mainstream was due to the impact of human activities during the past few decades. Copyright © 2008 John Wiley & Sons, Ltd.     

Hydrological projections of future climate change over the source region of Yellow River and Yangtze River in the Tibetan Plateau: A comprehensive assessment by coupling RegCM4 and VIC model

Understanding climate change impacts on hydrological regime and assessing future water supplies are essential to effective water resources management and planning, which is particularly true for the Tibetan Plateau (TP), one of the most vulnerable areas to climate change. In this study, future climate change in the TP was projected for 2041–2060 by a high‐resolution regional climate model, RegCM4, under 3 representative concentration pathways (RCPs): 2.6, 4.5, and 8.5. Response of all key hydrological elements, that is, evapotranspiration, surface run‐off, baseflow, and snowmelt, to future climate in 2 typical catchments, the source regions of Yellow and Yangtze rivers, was further investigated by the variable infiltration capacity microscale hydrological model incorporated with a 2‐layer energy balance snow model and a frozen soil/permafrost algorithm at a 0.25°×0.25° spatial scale. The results reveal that (a) spatial patterns of precipitation and temperature from RegCM4 agree fairly well with the data from China Meteorological Forcing Dataset, indicating that RegCM4 well reproduces historical climatic information and thus is reliable to support future projection; (b) precipitation increase by 0–70% and temperature rise by 1–4 °C would occur in the TP under 3 RCPs. A clear south‐eastern–north‐western spatial increasing gradient in precipitation would be seen. Besides, under RCP8.5, the peak increase in temperature would approach to 4 °C in spring and autumn in the east of the TP; (c) evapotranspiration would increase by 10–60% in 2 source regions due to the temperature rise, surface run‐off and baseflow in higher elevation region would experience larger increase dominantly due to the precipitation increase, and streamflow would display general increases by more than 3% and 5% in the source regions of Yellow and Yangtze rivers, respectively; (d) snowmelt contributes 11.1% and 16.2% to total run‐off in the source regions of Yellow and Yangtze rivers, respectively, during the baseline period. In the source region of Yangtze River, snowmelt run‐off would become more important with increase of 17.5% and 18.3%, respectively, under RCP2.6 and RCP4.5 but decrease of 15.0% under RCP8.5.     

Uncertainty in water resource model parameters used for climate change impact assessment

Despite their acknowledged limitations, lumped conceptual models continue to be used widely for climate‐change impact assessments. Therefore, it is important to understand the relative magnitude of uncertainties in water resource projections arising from the choice of model calibration period, model structure, and non‐uniqueness of model parameter sets. In addition, external sources of uncertainty linked to choice of emission scenario, climate model ensemble member, downscaling technique(s), and so on, should be acknowledged. To this end, the CATCHMOD conceptual water balance model was used to project changes in daily flows for the River Thames at Kingston using parameter sets derived from different subsets of training data, including the full record. Monte Carlo sampling was also used to explore parameter stability and identifiability in the context of historic climate variability. Parameters reflecting rainfall acceptance at the soil surface in simpler model structures were found to be highly sensitive to the training period, implying that climatic variability does lead to variability in the hydrologic behaviour of the Thames basin. Non‐uniqueness of parameters for more complex model structures results in relatively small variations in projected annual mean flow quantiles for different training periods compared with the choice of emission scenario. However, this was not the case for subannual flow statistics, where uncertainty in flow changes due to equifinality was higher in winter than summer, and comparable in magnitude to the uncertainty of the emission scenario. Therefore, it is recommended that climate‐change impact assessments using conceptual water balance models should routinely undertake sensitivity analyses to quantify uncertainties due to parameter instability, identifiability and non‐uniqueness. Copyright © 2005 John Wiley & Sons, Ltd.     

The responses of hydrological processes and sediment yield to land‐use and climate change in the Be River Catchment,Vietnam

In this study, we investigated the responses of hydrology and sediment yield with impacts of land‐use and climate change scenarios in the Be River Catchment, using the Soil and Water Assessment Tool (SWAT) hydrological model. The calibration and validation results indicated that the SWAT model is a powerful tool for simulating the impact of environmental change on hydrology and sediment yield in this catchment. The hydrologic and sediment yield responses to land‐use and climate changes were simulated based on the calibrated model. The results indicated that a 16.3% decrease in forest land is likely to increase streamflow (0.2 to 0.4%), sediment load (1.8 to 3.0%), and surface runoff (SURQ) (4.8 to 10.7%) and to decrease groundwater discharge (GW_Q) (3.5 to 7.9%). Climate change in the catchment leads to decreases in streamflow (0.7 to 6.9%) and GW_Q (3.0 to 8.4%), increase in evapotranspiration (0.5 to 2.9%), and changes in SURQ (?5.3 to 2.3%) and sediment load (?5.3 to 4.4%). The combined impacts of land‐use and climate changes decrease streamflow (2.0 to 3.9%) and GW_Q (12.3 to 14.0%), increase evapotranspiration (0.7 to 2.8%), SURQ (8.2 to 12.4%), and sediment load (2.0 to 7.9%). In general, the separate impacts of climate and land‐use changes on streamflow, sediment load, and water balance components are offset each other. However, SURQ and some component of subsurface flow are more sensitive to land‐use change than to climate change. Furthermore, the results emphasized water scarcity during the dry season and increased soil erosion during the wet season. Copyright © 2012 John Wiley & Sons, Ltd.     

Finding the most suitable slope stability model for the assessment of the impact of climate change on a ­landslide in southeast France

The response of a landslide near Barcelonnette (southeast France) to climatic factors was simulated with three slope stability models: a fully empirical gross precipitation threshold, a semi‐empirical threshold model for net precipitation, and a fully conceptual slope stability model. The three models performed with similar levels in reproducing the present‐day temporal pattern of landslide reactivation, using dendrogeomorphological information as test data. The semi‐empirical and conceptual models were found to be overparameterized, because more than one parameter setting matching the test data was identified. In the case of the conceptual model, this resulted in strongly divergent scenarios of future landslide activity, using downscaled climate scenarios as inputs to the model. The uncertainty of the landslide scenarios obtained with the semi‐empirical model was much lower. In addition, the simulation of strongly different scenarios by the fully empirical threshold was attributed to its incomplete representation of the site‐specific landslide reactivation mechanism. It is concluded that the semi‐empirical model constitutes the best compromise between conceptual representation and model robustness. Copyright © 2000 John Wiley & Sons, Ltd.     

Quantitative assessment of the impact of climate variability and human activities on runoff changes: a case study in four catchments of the Haihe River basin,China

Quantitative evaluation of the effect of climate variability and human activities on runoff is of great importance for water resources planning and management in terms of maintaining the ecosystem integrity and sustaining the society development. In this paper, hydro‐climatic data from four catchments (i.e. Luanhe River catchment, Chaohe River catchment, Hutuo River catchment and Zhanghe River catchment) in the Haihe River basin from 1957 to 2000 were used to quantitatively attribute the hydrological response (i.e. runoff) to climate change and human activities separately. To separate the attributes, the temporal trends of annual precipitation, potential evapotranspiration (PET) and runoff during 1957–2000 were first explored by the Mann–Kendall test. Despite that only Hutuo River catchment was dominated by a significant negative trend in annual precipitation, all four catchments presented significant negative trend in annual runoff varying from ?0.859 (Chaohe River) to ?1.996 mm a^?1 (Zhanghe River). Change points in 1977 and 1979 are detected by precipitation–runoff double cumulative curves method and Pettitt's test for Zhanghe River and the other three rivers, respectively, and are adopted to divide data set into two study periods as the pre‐change period and post‐change period. Three methods including hydrological model method, hydrological sensitivity analysis method and climate elasticity method were calibrated with the hydro‐climatic data during the pre‐change period. Then, hydrological runoff response to climate variability and human activities was quantitatively evaluated with the help of the three methods and based on the assumption that climate and human activities are the only drivers for streamflow and are independent of each other. Similar estimates of anthropogenic and climatic effects on runoff for catchments considered can be obtained from the three methods. We found that human activities were the main driving factors for the decline in annual runoff in Luanhe River catchment, Chaohe River catchment and Zhanghe River catchment, accounting for over 50% of runoff reduction. However, climate variability should be responsible for the decrease in annual runoff in the Hutuo River catchment. Copyright © 2012 John Wiley & Sons, Ltd.     

1990s以来气候变化和人类活动对洪湖流域径流影响的定量辨识

为针对性地提出洪湖流域水资源适应与应对气候变化和人类活动影响的措施,保护洪湖流域生态资源,促进其可持续发展,采取分布式水文模型SWAT定量辨识了1990s流域城镇快速发展以来气候变化和人类活动对洪湖流域地表径流的影响程度.结果表明:近20年来,人类活动是洪湖流域地表径流减少的主要原因,其影响量占径流减少量的63.72%,气候变化的影响占36.28%.但不同阶段人类活动与气候变化对流域径流影响的程度不同,1990s气候变化对流域径流的影响量高于人类活动,2000s气候变化对流域径流的影响量低于人类活动,近20年来的水土保持措施已经发挥了较好的径流调节和保水效益.     

A framework for quantifying the impacts of climate change and human activities on hydrological drought in a semiarid basin of Northern China

Climate change and human activities are two major driving forces affecting the hydrologic cycle, which further influence the stationarity of the hydrologic regime. Hydrological drought is a substantial negative deviation from the normal hydrologic conditions affected by these two phenomena. In this study, we propose a framework for quantifying the effects of climate change and human activities on hydrological drought. First, trend analysis and change‐point test are performed to determine variations of hydrological variables. After that, the fixed runoff threshold level method (TLM) and the standardized runoff index (SRI) are used to verify whether the traditional assessment methods for hydrological drought are applicable in a changing environment. Finally, two improved drought assessment methods, the variable TLM and the SRI based on parameter transplantation are employed to quantify the impacts of climate change and human activities on hydrological drought based on the reconstructed natural runoff series obtained using the variable infiltration capacity hydrologic model. The results of a case study on the typical semiarid Laohahe basin in North China show that the stationarity of the hydrological processes in the basin is destroyed by human activities (an obvious change‐point for runoff series is identified in 1979). The traditional hydrological drought assessment methods can no longer be applied to the period of 1980–2015. In contrast, the proposed separation framework is able to quantify the contributions of climate change and human activities to hydrological drought during the above period. Their ranges of contributions to hydrological drought calculated by the variable TLM method are 20.6–41.2% and 58.8–79.4%, and the results determined by the SRI based on parameter transplantation method are 15.3–45.3% and 54.7–84.7%, respectively. It is concluded that human activities have a dominant effect on hydrological drought in the study region. The novelty of the study is twofold. First, the proposed method is demonstrated to be efficient in quantifying the effects of climate change and human activities on hydrological drought. Second, the findings of this study can be used for hydrological drought assessment and water resource management in water‐stressed regions under nonstationary conditions.     

Uncertainty in hydrologic modelling for estimating hydrologic response due to climate change (Santiam River,Oregon)

This paper explores the predicted hydrologic responses associated with the compounded error of cascading global circulation model (GCM) uncertainty through hydrologic model uncertainty due to climate change. A coupled groundwater and surface water flow model (GSFLOW) was used within the differential evolution adaptive metropolis (DREAM) uncertainty approach and combined with eight GCMs to investigate uncertainties in hydrologic predictions for three subbasins of varying hydrogeology within the Santiam River basin in Oregon, USA. Predictions of future hydrology in the Santiam River include increases in runoff in the fall and winter months and decreases in runoff for the spring and summer months. One‐year peak flows were predicted to increase whereas 100‐year peak flows were predicted to slightly decrease. The predicted 10‐year 7‐day low flow decreased in two subbasins with little groundwater influences but increased in another subbasin with substantial groundwater influences. Uncertainty in GCMs represented the majority of uncertainty in the analysis, accounting for an average deviation from the median of 66%. The uncertainty associated with use of GSFLOW produced only an 8% increase in the overall uncertainty of predicted responses compared to GCM uncertainty. This analysis demonstrates the value and limitations of cascading uncertainty from GCM use through uncertainty in the hydrologic model, offers insight into the interpretation and use of uncertainty estimates in water resources analysis, and illustrates the need for a fully nonstationary approach with respect to calibrating hydrologic models and transferring parameters across basins and time for climate change analyses. Copyright © 2012 John Wiley & Sons, Ltd.