Evaluating different GCMs for predicting spatial recharge in an irrigated arid region

Groundwater systems in arid regions will be particularly sensitive to climate change owing to the strong dependence of rates of evapotranspiration on temperature, and shifts in the precipitation regimes. Irrigation use in these arid regions is typically a large component of the water budget, and may increase due to changes in soil moisture resulting from higher temperatures and changes in the timing of precipitation events. In this study, future predicted climate change scenarios from three global climate models (CGCM1 GHG+A1, CGCM3.1 A2, and HadCM3 A2) are used to determine the sensitivity of recharge to different climate models in an irrigated agricultural region. The arid Oliver region (annual precipitation 300 mm) in the Okanagan Basin, British Columbia, is used to demonstrate the approach. Irrigation return flow, as a contribution to total diffuse recharge, is simulated by calculating the daily applied irrigation based on estimates of seasonal crop water demand and the forecasted precipitation and evaporation data. The relative contribution of irrigation return flow to groundwater recharge under current and future climate conditions is modelled. Temperature data were downscaled using Statistical Downscaling Model (SDSM), while precipitation and solar radiation changes were estimated directly from the GCM data. Shifts in climate, from present to future predicted, were applied to a stochastic weather generator, and used to force a one-dimensional hydrologic model, HELP 3.80D. Results were applied spatially, according to different soil profiles, slope and vegetation, over a 22.5 km by 8.6 km region. Changes to recharge in future time periods for each GCM result in modest increases of recharge with the peak recharge shifting from March to February. Lower recharge rates and higher potential evapotranspiration rates are similarly predicted by all three models for the summer months. All scenarios show that the potential growing season will expand between 3 and 4 weeks due to increases in temperature. However, the magnitude of the change varies considerably between models. CGCM3.1 has the largest increases of recharge rates, CGCM1 has very minor increases, and HadCM3 is relatively stable (as indicated by the near-zero changes between climate states). The significant differences between these three models indicate that prediction of future recharge is highly dependent on the model selected. The minor increase of annual recharge in future predicted climate states is due the shift of peak recharge from increased temperature. Irrigation rates dominate total recharge during the summer months in this arid area. Recharge in irrigated areas is significantly higher than natural recharge, with irrigation return flow between 25% and 58%. A comparison of recharge results for the least efficient and the most efficient irrigation systems indicates that the latter are more sensitive to choice of GCM.     

Evaluating the use of a gridded climate surface for modelling groundwater recharge in a semi‐arid region (Okanagan Basin,Canada)

Spatially distributed groundwater recharge was simulated for a segment of a semi‐arid valley using three different treatments of meteorological input data and potential evapotranspiration (PET). For the same area, timeframe, land cover characteristics and soil properties, groundwater recharge was estimate using (i) single‐station climate data with monthly PET calculated by the Thornthwaite method; (ii) single‐station climate data with daily PET calculated by the Penman–Monteith method; and (iii) daily gridded climate data with spatially distributed PET calculated using the Penman–Monteith method. For each treatment, the magnitude and distribution of actual evapotranspiration (AET) for summer months compared well with those estimated for a 5‐year crop study, suggesting that the near‐surface hydrological processes were replicated and that subsequent groundwater recharge rates are realistic. However, for winter months, calculated AET was near zero when using the Thornthwaite PET method. Mean annual groundwater recharge varied from ～3·2 to 10·0 mm when PET was calculated by the Thornthwaite method, and from ～1·8 to 7·5 mm when PET was calculated by the Penman–Monteith method. Comparisons of bivariate plots of seasonal recharge rates estimated from single‐station versus gridded surface climate reveal that there is greater variability between the different methods for spring months, which is the season of greatest recharge. Furthermore, these seasonal differences are shown to provide different results when compared to the depth to water table, which could lead to different results of evaporative extinction depth. These findings illustrate potential consequences of using different approaches for representing spatial meteorological input data, which could provide conflicting predictions when modelling the influence of climate change on groundwater recharge. Copyright © 2010 John Wiley & Sons, Ltd.     

Geochemical quantification of semiarid mountain recharge

Analysis of a typical semiarid mountain system recharge (MSR) setting demonstrates that geochemical tracers help resolve the location, rate, and seasonality of recharge as well as ground water flowpaths and residence times. MSR is defined as the recharge at the mountain front that dominates many semiarid basins plus the often-overlooked recharge through the mountain block that may be a significant ground water resource; thus, geochemical measurements that integrate signals from all flowpaths are advantageous. Ground water fluxes determined from carbon-14 ((14)C) age gradients imply MSR rates between 2 x 10(6) and 9 x 10(6) m(3)/year in the Upper San Pedro Basin, Arizona, USA. This estimated range is within an order of magnitude of, but lower than, prior independent estimates. Stable isotopic signatures indicate that MSR has a 65% +/- 25% contribution from winter precipitation and a 35% +/- 25% contribution from summer precipitation. Chloride and stable isotope results confirm that transpiration is the dominant component of evapotranspiration (ET) in the basin with typical loss of more than 90% of precipitation-less runoff to ET. Such geochemical constraints can be used to further refine hydrogeologic models in similar high-elevation relief basins and can provide practical first estimates of MSR rates for basins lacking extensive prior hydrogeologic measurements.     

Evaluating the impacts of climate change and switchgrass production on a semiarid basin

Climate and land use changes greatly modify hydrologic regimes. In this paper, we modelled the impacts of biofuel cultivation in the US Great Plains on a 1061‐km² watershed using the Soil and Water Assessment Tool (SWAT) hydrologic model. The model was calibrated to monthly discharges spanning 2002–2010 and for the winter, spring, and summer seasons. SWAT was then run for a climate‐change‐only scenario using downscaled precipitation and a projected temperature for 16 general circulation model (GCM) runs associated with the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios A2 scenario spanning 2040–2050. SWAT was also run on a climate change plus land use change scenario in which Alamo switchgrass (Panicum virgatum L.) replaced native range grasses, winter wheat, and rye (89% of the basin). For the climate‐change‐only scenario, the GCMs agreed on a monthly temperature increase of 1–2 °C by the 2042–2050 period, but they disagreed on the direction of change in precipitation. For this scenario, decreases in surface runoff during all three seasons and increases in spring and summer evapotranspiration (eT) were driven predominantly by precipitation. Increased summer temperatures also significantly contributed to changes in eT. With the addition of switchgrass, changes in surface runoff are amplified during the winter and summer, and changes in eT are amplified during all three seasons. Depending on the GCM utilized, either climate change or land use change (switchgrass cultivation) was the dominant driver of change in surface runoff while switchgrass cultivation was the major driver of changes in eT. Copyright © 2014 John Wiley & Sons, Ltd.     

Ecohydrologic Process Modeling of Mountain Block Groundwater Recharge

Regional mountain block recharge (MBR) is a key component of alluvial basin aquifer systems typical of the western United States. Yet neither water scientists nor resource managers have a commonly available and reasonably invoked quantitative method to constrain MBR rates. Recent advances in landscape-scale ecohydrologic process modeling offer the possibility that meteorological data and land surface physical and vegetative conditions can be used to generate estimates of MBR. A water balance was generated for a temperate 24,600-ha mountain watershed, elevation 1565 to 3207 m, using the ecosystem process model Biome-BGC (BioGeochemical Cycles) ( Running and Hunt 1993 ). Input data included remotely sensed landscape information and climate data generated with the Mountain Climate Simulator (MT-CLIM) ( Running et al. 1987 ). Estimated mean annual MBR flux into the crystalline bedrock terrain is 99,000 m³/d, or approximately 19% of annual precipitation for the 2003 water year. Controls on MBR predictions include evapotranspiration (radiation limited in wet years and moisture limited in dry years), soil properties, vegetative ecotones (significant at lower elevations), and snowmelt (dominant recharge process). The ecohydrologic model is also used to investigate how climatic and vegetative controls influence recharge dynamics within three elevation zones. The ecohydrologic model proves useful for investigating controls on recharge to mountain blocks as a function of climate and vegetation. Future efforts will need to investigate the uncertainty in the modeled water balance by incorporating an advanced understanding of mountain recharge processes, an ability to simulate those processes at varying scales, and independent approaches to calibrating MBR estimates.     

Distributed modelling of future changes in hydrological processes of Spencer Creek watershed

The hydrologic impact of climate change has been largely assessed using mostly conceptual hydrologic models. This study investigates the use of distributed hydrologic model for the assessment of the climate change impact for the Spencer Creek watershed in Southern Ontario (Canada). A coupled MIKE SHE/MIKE 11 hydrologic model is developed to represent the complex hydrologic conditions in the Spencer Creek watershed, and later to simulate climate change impact using Canadian global climate model (CGCM 3·1) simulations. Owing to the coarse resolution of GCM data (daily GCM outputs), statistical downscaling techniques are used to generate higher resolution data (daily precipitation and temperature series). The modelling results show that the coupled model captured the snow storage well and also provided good simulation of evapotranspiration (ET) and groundwater recharge. The simulated streamflows are consistent with the observed flows at different sites within the catchment. Using a conservative climate change scenario, the downscaled GCM scenarios predicted an approximately 14–17% increase in the annual mean precipitation and 2–3 °C increase in annual mean maximum and minimum temperatures for the 2050s (i.e., 2046–2065). When the downscaled GCM scenarios were used in the coupled model, the model predicted a 1–5% annual decrease in snow storage for 2050s, approximately 1–10% increase in annual ET, and a 0·5–6% decrease in the annual groundwater recharge. These results are consistent with the downscaled temperature results. For future streamflows, the coupled model indicated an approximately 10–25% increase in annual streamflows for all sites, which is consistent with the predicted changes in precipitation. Overall, it is shown that distributed hydrologic modelling can provide useful information not only about future changes in streamflow but also changes in other key hydrologic processes such as snow storage, ET, and groundwater recharge, which can be particularly important depending on the climatic region of concern. The study results indicate that the coupled MIKE SHE/MIKE 11 hydrologic model could be a particularly useful tool for understanding the integrated effect of climate change in complex catchment scale hydrology. Copyright © 2010 John Wiley & Sons, Ltd.     

Changes in potential evapotranspiration and surface runoff in 1981–2010 and the driving factors in Upper Heihe River Basin in Northwest China

Changes in potential evapotranspiration and surface runoff can have profound implications for hydrological processes in arid and semiarid regions. In this study, we investigated the response of hydrological processes to climate change in Upper Heihe River Basin in Northwest China for the period from 1981 to 2010. We used agronomic, climatic and hydrological data to drive the Soil and Water Assessment Tool model for changes in potential evapotranspiration (ET₀) and surface runoff and the driving factors in the study area. The results showed that increasing autumn temperature increased snow melt, resulting in increased surface runoff, especially in September and October. The spatial distribution of annual runoff was different from that of seasonal runoff, with the highest runoff in Yeniugou River, followed by Babaohe River and then the tributaries in the northern of the basin. There was no evaporation paradox at annual and seasonal time scales, and annual ET₀ was driven mainly by wind speed. ET₀ was driven by relative humidity in spring, sunshine hour duration in autumn and both sunshine hour duration and relative humility in summer. Surface runoff was controlled by temperature in spring and winter and by precipitation in summer (flood season). Although surface runoff increased in autumn with increasing temperature, it depended on rainfall in September and on temperature in October and November. Copyright © 2016 John Wiley & Sons, Ltd.     

Assessing the long-term impact of climatic variability and human activities on the water resources of a meso-scale Mediterranean catchment

Abstract

This article addresses the critical need for a better quantitative understanding of how water resources from the Hérault River catchment in France have been influenced by climate variability and the increasing pressure of human activity over the last 50 years. A method is proposed for assessing the relative impacts of climate and growing water demand on the decrease in discharge observed at various gauging stations in the periods 1961–1980 and 1981–2010. An annual water balance at the basin scale was calculated first, taking into account precipitation, actual evapotranspiration, water withdrawals and water discharge. Next, the evolution of the seasonal variability in hydroclimatic conditions and water withdrawals was studied. The catchment was then divided into zones according to the main geographical characteristics to investigate the heterogeneity of the climatic and human dynamics. This delimitation took into account the distribution of climate, topography, lithology, land cover and water uses, as well as the availability of discharge series. At the area scale, annual water balances were calculated to understand the internal changes that occurred in the catchment between both past periods. The decrease in runoff can be explained by the decrease in winter precipitation in the upstream areas and by the increase during summer in both water withdrawals and evapotranspiration in the downstream areas, mainly due to the increase in temperature. Thus, water stress increased in summer by 35%. This work is the first step of a larger research project to assess possible future changes in the capacity to satisfy water demand in the Hérault River catchment, using a model that combines hydrological processes and water demand.

Editor Z.W. Kundzewicz     

Isotopic variation in groundwater across the conterminous United States – Insight into hydrologic processes

Groundwater supplies a significant proportion of water use in the United States and is critical to the maintenance of healthy ecosystems and environmental processes, thus characterizing aquifer hydrology is important to managing and preserving these resources. While groundwater isotopes provide insight into hydrologic and ecologic processes, their application is limited to where measurements exist. To help overcome this limitation, we used the random forest algorithm to develop a predictive model for shallow groundwater isotopes in the conterminous United States. Our model uses environmental variables (e.g. temperature, elevation, precipitation isotopes) as predictors. We used our model to develop the first shallow groundwater isoscape of δ²H and δ¹⁸O for the conterminous United States. We describe the patterns in groundwater isotopes using both observations and our modelled isoscape. We find that throughout much of the Eastern United States, groundwater isotopes are close to annual amount weighted precipitation, while groundwater isotopes are significantly depleted relative precipitation across much of the High Plains and Western United States. Furthermore, we compare the observations compiled for this study to isotopes of precipitation, which allows us to determine the relative recharge efficiency (i.e. ratio of groundwater recharge to precipitation) between seasons and the proportion of annual recharge that occurs in a given season. Our findings suggest that winter recharge is generally more efficient than summer recharge; however, the dominant recharge season is more varied as it is the product of both seasonal recharge efficiency and the seasonal timing of precipitation. Parts of the central United States have summer dominant recharge, which is likely the result of heavy summer precipitation/nocturnal summer precipitation. Interestingly, parts of coastal California appear to have summer dominant recharge, which we suggest could be due to recharge from fog-drip. Our results summarize spatial patterns in groundwater isotopes across the conterminous United States, provide insight into the hydrologic processes affecting shallow groundwater, and are valuable information for future ecologic and hydrologic studies.     

Groundwater recharge in arid regions: Review and critique of estimation methods

Arid-site recharge, while generally low, can be highly variable. Recharge under similar climate and soil conditions but with different plant cover and topography can vary from zero to more than the annual precipitation. Simple estimates of recharge based on fixed fractions of annual precipitation are misleading because they do not reflect the plant and soil factors controlling recharge. Detailed water balance models, successful for irrigated agriculture, fail to predict evapotranspiration accurately under conditions where plants suffer seasonal water stress and cover is sparse. Recharge, when estimated as a residual in water balance models, may be in error by as much as an order of magnitude. Similar errors can occur when soil water flow models are used with measured or estimated soil hydraulic conductivities and tension gradients. Lysimetry and tracer tests offer the best hope for evaluating recharge at arid sites, particularly in siting waste disposal facilities, where reliable recharge estimates are needed. Quantification of drainage using lysimetry over several years under a given set of soil, plant, and climate conditions for a specific site can provide a basis for calibrating models for recharge prediction. Tracer tests using such long-lived tracers as ³⁶Cl or perhaps stable isotopes (¹⁸0, deuterium) can provide qualitative estimates of recent recharge at a given site.     

Hydrological modelling using data from monthly GCMs in a regional catchment

This study demonstrates the use of spatially downscaled, monthly general circulation model (GCM) rainfall and temperature data to drive the established HyMOD hydrological model to evaluate the prospective effects of climate change on the fluvial run‐off of the River Derwent basin in the UK. The evaluation results of this monthly hydrological model using readily available, monthly GCM data are consistent with studies on nearby catchments employing high‐temporal resolution data, indicating that useful hydro‐climatic planning studies may be possible using standard datasets and modest computational resources. HyMOD was calibrated against 5 km² gridded UK Climate Projections dataset data and then driven using monthly spatially interpolated (~5 km²) outputs from Hadley Centre Coupled Model, version 3 and the Canadian Centre for Climate Modelling and Analysis for Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC‐SRES) A2a and B2a covering the 2020s, 2050s and 2080s. Results for both GCMs project a decrease in annual run‐off in both GCM models and scenarios with higher values in the summer/autumn months, whereas an increase in the later winter months. Both Hadley Centre Coupled Model, version 3 and the Canadian Centre for Climate Modelling and Analysis show higher ranges of uncertainty during the winter season with higher values of run‐off associated with December in all three simulation periods and two scenarios. A seasonal comparison of run‐off simulations shows that both GCMs give similar results in summer and autumn, whereas disparities due to GCM uncertainties are more conspicuous in winter and spring. In this study, both the GCMs under A2a scenario have demonstrated the high possibility of time shift in monthly average peak run‐offs in the Derwent River by 2080s in comparison with the early 21st century. Copyright © 2013 John Wiley & Sons, Ltd.     

Remote sensing and ground‐based measurements of evapotranspiration in an extreme cold Patagonian desert

Accurate estimates of seasonal evapotranspiration (ET) at different temporal and spatial scales are essential for understanding the biological and environmental determinants of ecosystem water balance in arid regions and the patterns of water utilization by the vegetation. For this purpose, remote sensing ET estimates of a Patagonian desert in Southern Argentina were verified with field measurements of soil evaporation and plant transpiration using an open top chamber. Root distribution and seasonal variation in soil volumetric water content were also analysed. There was a high correlation between remote sensing and field measurements of ecosystem water fluxes. A substantial amount of the annual ET occurred in spring and early summer (73.4 mm) using winter rain stored in the soil profile and resulting in water content depletion of the upper soil layers. A smaller amount of annual ET was derived from few rainfall events occurring during the mid or late summer (41.4 mm). According to remote sensing, the 92.9% of the mean annual precipitation returns to the atmosphere by transpiration or evaporation from the bare soil and by canopy interception. Only 7.1% infiltrates to soil layers deeper than 200 cm contributing to the water table recharge. Fourier time series analysis, cross‐correlation methods and multiple linear regression models were used to analyse 11 years of remote sensing data to assess determinants of water fluxes. A linear model predicts well the variables that drive complex ecosystem processes such as ET. Leaf area index and air temperature were not linearly correlated to ET because of the multiple interaction among variables resulting in time lags with ET variations and thus these two variables were not included in the linear model. Soil water content, the fraction of photosynthetic active radiation and precipitation explained 86% of the ET monthly variations. The high volumetric water content and the small seasonal variations at 200‐cm depth were probably the result of little water uptake from deeper soil horizons by roots with low hydraulic conductivity. Copyright © 2016 John Wiley & Sons, Ltd.     

Effects of mid‐twenty‐first century climate and land cover change on the hydrology of the Puget Sound basin,Washington

The distributed hydrology–soil–vegetation model (DHSVM) was used to study the potential impacts of projected future land cover and climate change on the hydrology of the Puget Sound basin, Washington, in the mid‐twenty‐first century. A 60‐year climate model output, archived for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4), was statistically downscaled and used as input to DHSVM. From the DHSVM output, we extracted multi‐decadal averages of seasonal streamflow, annual maximum flow, snow water equivalent (SWE), and evapotranspiration centred around 2030 and 2050. Future land cover was represented by a 2027 projection, which was extended to 2050, and DHSVM was run (with current climate) for these future land cover projections. In general, the climate change signal alone on sub‐basin streamflow was evidenced primarily through changes in the timing of winter and spring runoff, and slight increases in the annual runoff. Runoff changes in the uplands were attributable both to climate (increased winter precipitation, less snow) and land cover change (mostly reduced vegetation maturity). The most climatically sensitive parts of the uplands were in areas where the current winter precipitation is in the rain–snow transition zone. Changes in land cover were generally more important than climate change in the lowlands, where a substantial change to more urbanized land use and increased runoff was predicted. Both the annual total and seasonal distribution of freshwater flux to Puget Sound are more sensitive to climate change impacts than to land cover change, primarily because most of the runoff originates in the uplands. Both climate and land cover change slightly increase the annual freshwater flux to Puget Sound. Changes in the seasonal distribution of freshwater flux are mostly related to climate change, and consist of double‐digit increases in winter flows and decreases in summer and fall flows. Copyright © 2010 John Wiley & Sons, Ltd.     

Assessing groundwater sustainability under changing climate using isotopic tracers and climate modelling,southwest Ohio,USA

Groundwater, an essential resource, is likely to change with global warming because of changes in the CO₂ levels, temperature and precipitation. Here, we combine water isotope geochemistry with climate modelling to examine future groundwater recharge in southwest Ohio, USA. We first establish the stable isotope profiles of oxygen and deuterium in precipitation and groundwater. We then use an isotope mass balance model to determine seasonal groundwater recharge from precipitation. Climate model output is used to project future changes in precipitation and its seasonal distribution under medium and high climate change scenarios. Finally, these results are combined to examine future changes in groundwater recharge. We find that 76% of the groundwater recharge occurs in the cool season. Climate models project precipitation increase in the cool season and decrease in the warm season. The total groundwater recharge is expected to increase by 3.2% (8.8%) under the medium (high) climate change scenarios.     

A watershed-scale study of climate change impacts on groundwater recharge (Annapolis Valley,Nova Scotia,Canada)

Abstract

The potential impacts of future climate change on the evolution of groundwater recharge are examined at a local scale for a 546-km² watershed in eastern Canada. Recharge is estimated using the infiltration model Hydrologic Evaluation of Landfill Performance (HELP), with inputs derived from five climate runs generated by a regional climate model in combination with the A2 greenhouse gas emissions scenario. The model runs project an increase in annual recharge over the 2041–2070 period. On a seasonal basis, however, a marked decrease in recharge during the summer and a marked increase during the winter are observed. The results suggest that increased evapotranspiration resulting from higher temperatures does not offset the large increase in winter infiltration. In terms of individual water budget components, clear differences are obtained for the different climate change scenarios. Monthly recharge values are also found to be quite variable, even for a given climate scenario. These findings are compared with results from two regional-scale studies.

Editor D. Koutsoyiannis; Associate editor M. Besbes     

Interannual climate variability in South America: impacts on seasonal precipitation, extreme events, and possible effects of climate change

Interannual variability is an important modulator of synoptic and intraseasonal variability in South America. This paper seeks to characterize the main modes of interannual variability of seasonal precipitation and some associated mechanisms. The impact of this variability on the frequency of extreme rainfall events and the possible effect of anthropogenic climate change on this variability are reviewed. The interannual oscillations of the annual total precipitation are mainly due to the variability in austral autumn and summer. While autumn is the dominant rainy season in the northern part of the continent, where the variability is highest (especially in the northeastern part), summer is the rainy season over most of the continent, thanks to a summer monsoon regime. In the monsoon season, the strongest variability occurs near the South Atlantic Convergence Zone (SACZ), which is one of the most important features of the South American monsoon system. In all seasons but summer, the most important source of variability is ENSO (El Ni?o Southern Oscillation), although ENSO shows a great contribution also in summer. The ENSO impact on the frequency of extreme precipitation events is also important in all seasons, being generally even more significant than the influence on seasonal rainfall totals. Climate change associated with increasing emission of greenhouse gases shows potential to impact seasonal amounts of precipitation in South America, but there is still great uncertainty associated with the projected changes, since there is not much agreement among the models’ outputs for most regions in the continent, with the exception of southeastern South America and southern Andes. Climate change can also impact the natural variability modes of seasonal precipitation associated with ENSO.     

Assessment of future runoff trends under multiple climate change scenarios in the Willamette River Basin,Oregon, USA

We investigated trends in future seasonal runoff components in the Willamette River Basin (WRB) of Oregon for the twenty‐first century. Statistically downscaled climate projections by Climate Impacts Group (CIG), eight different global climate model (GCM) simulations with two different greenhouse gas (GHG) emission scenarios, (A1B and B1), were used as inputs for the US Geological Survey's Precipitation Runoff Modelling System. Ensemble mean results show negative trends in spring (March, April and May) and summer (June, July and August) runoff and positive trends in fall (September, October and November) and winter (December, January and February) runoff for 2000–2099. This is a result of temperature controls on the snowpack and declining summer and increasing winter precipitation. With temperature increases throughout the basin, snow water equivalent (SWE) is projected to decline consistently for all seasons. The decreases in the centre of timing and 7‐day low flows and increases in the top 5% flow are caused by the earlier snowmelt in spring, decreases in summer runoff and increases in fall and winter runoff, respectively. Winter runoff changes are more pronounced in higher elevations than in low elevations in winter. Seasonal runoff trends are associated with the complex interactions of climatic and topographic variables. While SWE is the most important explanatory variable for spring and winter runoff trends, precipitation has the strongest influence on fall runoff. Spatial error regression models that incorporate spatial dependence better explain the variations of runoff trends than ordinary least‐squares (OLS) multiple regression models. Our results show that long‐term trends of water balance components in the WRB could be highly affected by anthropogenic climate change, but the direction and magnitude of such changes are highly dependent on the interactions between climate change and land surface hydrology. This suggests a need for spatially explicit adaptive water resource management within the WRB under climate change. Copyright © 2010 John Wiley & Sons, Ltd.     

Response of streamflow to climate change and human activity in Xitiaoxi river basin in China

In recent years, the Xitiaoxi river basin in China has experienced intensified human activity, including city expansion and increased water demand. Climate change also has influenced streamflow. Assessing the impact of climate variability and human activity on hydrological processes is important for water resources planning and management and for the sustainable development of eco‐environmental systems. The non‐parametric Mann–Kendall test was employed to detect the trends of climatic and hydrological variables. The Mann–Kendall–Sneyers test and the moving t‐test were used to locate any abrupt change of annual streamflow. A runoff model, driven by precipitation and potential evapotranspiration, was employed to assess the impact of climate change on streamflow. A significant downward trend was detected for annual streamflow from 1975 to 2009, and an abrupt change occurred in 1999, which was consistent with the change detected by the double mass curve test between streamflow and precipitation. The annual precipitation decreased slightly, but upward trends of annual mean temperature and potential evapotranspiration were significant. The annual streamflow during the period 1999–2009 decreased by 26.19% compared with the reference stage, 1975–1998. Climate change was estimated to be responsible for 42.8% of the total reduction in annual streamflow, and human activity accounted for 57.2%. Copyright © 2012 John Wiley & Sons, Ltd.     

Relative effects of multi-decadal climatic variability and changes in the mean and variability of climate due to global warming: future streamflows in Britain

Climate change impact assessments conventionally assess just the implications of a change in mean climate due to global warming. This paper compares such effects of such changes with those due to natural multi-decadal variability, and also explores the effects of changing the year-to-year variability in climate as well as the mean. It estimates changes in mean monthly flows and a measure of low flow (the flow exceeded 95% of the time) in six catchments in Britain, using the UKCIP98 climate change scenarios and a calibrated hydrological model. Human-induced climate change has a different seasonal effect on flows than natural multi-decadal variability (an increase in winter and decrease in summer), and by the 2050s the climate change signal is apparent in winter and, in lowland Britain, in summer. Superimposing natural multi-decadal variability onto the human-induced climate change increases substantially the range in possible future streamflows (in some instances counteracting the climate change signal), with important implications for the development of adaptation strategies. Increased year-to-year variability in climate leads to slight increases in mean monthly flows (relative to changes due just to changes in mean climate), and slightly greater decreases in low flows. The greatest effect on low flows occurs in upland catchments.     

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.