River water quality response under hypothetical climate change scenarios in Tunga‐Bhadra river,India

Analysis of climate change impacts on streamflow by perturbing the climate inputs has been a concern for many authors in the past few years, but there are few analyses for the impacts on water quality. To examine the impact of change in climate variables on the water quality parameters, the water quality input variables have to be perturbed. The primary input variables that can be considered for such an analysis are streamflow and water temperature, which are affected by changes in precipitation and air temperature, respectively. Using hypothetical scenarios to represent both greenhouse warming and streamflow changes, the sensitivity of the water quality parameters has been evaluated under conditions of altered river flow and river temperature in this article. Historical data analysis of hydroclimatic variables is carried out, which includes flow duration exceedance percentage (e.g. Q90), single low‐flow indices (e.g. 7Q10, 30Q10) and relationships between climatic variables and surface variables. For the study region of Tunga‐Bhadra river in India, low flows are found to be decreasing and water temperatures are found to be increasing. As a result, there is a reduction in dissolved oxygen (DO) levels found in recent years. Water quality responses of six hypothetical climate change scenarios were simulated by the water quality model, QUAL2K. A simple linear regression relation between air and water temperature is used to generate the scenarios for river water temperature. The results suggest that all the hypothetical climate change scenarios would cause impairment in water quality. It was found that there is a significant decrease in DO levels due to the impact of climate change on temperature and flows, even when the discharges were at safe permissible levels set by pollution control agencies (PCAs). The necessity to improve the standards of PCA and develop adaptation policies for the dischargers to account for climate change is examined through a fuzzy waste load allocation model developed earlier. Copyright © 2011 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.     

Assessment of the impact of climate change on the flow regime of the Han River basin using indicators of hydrologic alteration

Most natural disasters are caused by water‐/climate‐related hazards, such as floods, droughts, typhoons, and landslides. In the last few years, great attention has been paid to climate change, and especially the impact of climate change on water resources and the natural disasters that have been an important issue in many countries. As climate change increases the frequency and intensity of extreme rainfall, the number of water‐related disasters is expected to rise. In this regard, this study intends to analyse the changes in extreme weather events and the associated flow regime in both the past and the future. Given trend analysis, spatially coherent and statistically significant changes in the extreme events of temperature and rainfall were identified. A weather generator based on the non‐stationary Markov chain model was applied to produce a daily climate change scenario for the Han River basin for a period of 2001–2090. The weather generator mainly utilizes the climate change SRES A2 scenario driven by input from the regional climate model. Following this, the SLURP model, which is a semi‐distributed hydrological model, was applied to produce a long‐term daily runoff ensemble series. Finally, the indicator of hydrologic alteration was applied to carry out a quantitative analysis and assessment of the impact of climate change on runoff, the river flow regime, and the aquatic ecosystem. It was found that the runoff is expected to decrease in May and July, while no significant changes occur in June. In comparison with historical evidence, the runoff is expected to increase from August to April. A remarkable increase, which is about 40%, in runoff was identified in September. The amount of the minimum discharge over various durations tended to increase when compared to the present hydrological condition. A detailed comparison for discharge and its associated characteristics was discussed. Copyright © 2010 John Wiley & Sons, Ltd.     

Simulating the hydrologic impacts of land-cover and climate changes in a semi-arid watershed

Abstract

Changes in climate and land cover are among the principal variables affecting watershed hydrology. This paper uses a cell-based model to examine the hydrologic impacts of climate and land-cover changes in the semi-arid Lower Virgin River (LVR) watershed located upstream of Lake Mead, Nevada, USA. The cell-based model is developed by considering direct runoff based on the Soil Conservation Service - Curve Number (SCS-CN) method and surplus runoff based on the Thornthwaite water balance theory. After calibration and validation, the model is used to predict LVR discharge under future climate and land-cover changes. The hydrologic simulation results reveal climate change as the dominant factor and land-cover change as a secondary factor in regulating future river discharge. The combined effects of climate and land-cover changes will slightly increase river discharge in summer but substantially decrease discharge in winter. This impact on water resources deserves attention in climate change adaptation planning.

Editor Z.W. Kundzewicz     

Automatic calibration of HEC‐HMS using single‐objective and multi‐objective PSO algorithms

This study presents single‐objective and multi‐objective particle swarm optimization (PSO) algorithms for automatic calibration of Hydrologic Engineering Center‐ Hydrologic Modeling Systems rainfall‐runoff model of Tamar Sub‐basin of Gorganroud River Basin in north of Iran. Three flood events were used for calibration and one for verification. Four performance criteria (objective functions) were considered in multi‐objective calibration where different combinations of objective functions were examined. For comparison purposes, a fuzzy set‐based approach was used to determine the best compromise solutions from the Pareto fronts obtained by multi‐objective PSO. The candidate parameter sets determined from different single‐objective and multi‐objective calibration scenarios were tested against the fourth event in the verification stage, where the initial abstraction parameters were recalibrated. A step‐by‐step screening procedure was used in this stage while evaluating and comparing the candidate parameter sets, which resulted in a few promising sets that performed well with respect to at least three of four performance criteria. The promising sets were all from the multi‐objective calibration scenarios which revealed the outperformance of the multi‐objective calibration on the single‐objective one. However, the results indicated that an increase of the number of objective functions did not necessarily lead to a better performance as the results of bi‐objective function calibration with a proper combination of objective functions performed as satisfactorily as those of triple‐objective function calibration. This is important because handling multi‐objective optimization with an increased number of objective functions is challenging especially from a computational point of view. Copyright © 2012 John Wiley & Sons, Ltd.     

Modeling the effects of climate change projections on streamflow in the Nooksack River basin,Northwest Washington

The Nooksack River has its headwaters in the North Cascade Mountains and drains an approximately 2000 km² watershed in northwestern Washington State. The timing and magnitude of streamflow in a snowpack‐dominated drainage basin such as the Nooksack River basin are strongly influenced by temperature and precipitation. Projections of future climate made by general circulation models (GCMs) indicate increases in temperature and variable changes in precipitation for the Nooksack River basin. Understanding the response of the river to climate change is crucial for regional water resources planning because municipalities, tribes, and industry depend on the river for water use and for fish habitat. We combine three different climate scenarios downscaled from GCMs and the Distributed‐Hydrology‐Soil‐Vegetation Model to simulate future changes to timing and magnitude of streamflow in the higher elevations of the Nooksack River. Simulations of future streamflow and snowpack in the basin project a range of magnitudes, which reflects the variable meteorological changes indicated by the three GCM scenarios and the local natural variability employed in the modeling. Simulation results project increased winter flows, decreased summer flows, decreased snowpack, and a shift in timing of the spring melt peak and maximum snow water equivalent. These results are consistent with previous regional studies, but the magnitude of increased winter flows and total annual runoff is higher. Increases in temperature dominate snowpack declines and changes to spring and summer streamflow, whereas a combination of increases in temperature and precipitation control increased winter streamflow. Copyright © 2013 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.     

Regional impacts of climate change on irrigation water demands

This paper presents an approach to model the expected impacts of climate change on irrigation water demand in a reservoir command area. A statistical downscaling model and an evapotranspiration model are used with a general circulation model (GCM) output to predict the anticipated change in the monthly irrigation water requirement of a crop. Specifically, we quantify the likely changes in irrigation water demands at a location in the command area, as a response to the projected changes in precipitation and evapotranspiration at that location. Statistical downscaling with a canonical correlation analysis is carried out to develop the future scenarios of meteorological variables (rainfall, relative humidity (RH), wind speed (U₂), radiation, maximum (Tmax) and minimum (Tmin) temperatures) starting with simulations provided by a GCM for a specified emission scenario. The medium resolution Model for Interdisciplinary Research on Climate GCM is used with the A1B scenario, to assess the likely changes in irrigation demands for paddy, sugarcane, permanent garden and semidry crops over the command area of Bhadra reservoir, India. Results from the downscaling model suggest that the monthly rainfall is likely to increase in the reservoir command area. RH, Tmax and Tmin are also projected to increase with small changes in U₂. Consequently, the reference evapotranspiration, modeled by the Penman–Monteith equation, is predicted to increase. The irrigation requirements are assessed on monthly scale at nine selected locations encompassing the Bhadra reservoir command area. The irrigation requirements are projected to increase, in most cases, suggesting that the effect of projected increase in rainfall on the irrigation demands is offset by the effect due to projected increase/change in other meteorological variables (viz., Tmax and Tmin, solar radiation, RH and U₂). The irrigation demand assessment study carried out at a river basin will be useful for future irrigation management systems. Copyright © 2012 John Wiley & Sons, Ltd.     

Hydrologic impact of regional climate change for the snow‐fed and glacier‐fed river basins in the Republic of Tajikistan: statistical downscaling of global climate model projections

Climate change due to global warming is a public concern in Central Asia. Because of specific orography and climate conditions, the republic of Tajikistan is considered as the main glacial center of Central Asia. In this study, regional climate change impacts in the two large basins of Tajikistan, Pyanj and Vaksh River basins located in the upstream sector of the Amu Darya River basin are analysed. A statistical regression method with model output statistics corrections using the ground observation data, Willmott archived dataset and GSMaP satellite driven dataset, was developed and applied to the basins to downscale the Global Climate Model Projections at a 0.1‐degree grid and to assess the regional climate change impacts at subbasin scale. It was found that snow and glacier melting are of fundamental importance for the state of the future water resources and flooding at the target basins since the air temperature had a clearly increasing trend toward the future. It was also found that the snowfall will decrease, but the rainfall will increase because of the gradual increase in the air temperature. Such changes may result in an increase in flash floods during the winter and the early spring, and in significant changes in the hydrological regime during a year in the future. Furthermore, the risks of floods in the target basins may be slightly increasing because of the increase in the frequencies and magnitudes of high daily precipitation and the increase in the rapid snowmelt with high air temperatures toward the future. Copyright © 2012 John Wiley & Sons, Ltd.     

Perturbation study of climate change impacts in a snow‐fed river basin

A physically based distributed hydrological model developed at the University of Yamanashi based on block‐wise use of TOPMODEL and the Muskingum–Cunge method (YHyM/BTOPMC), integrated with a simple degree‐day–based snow accumulation/melt sub‐model, was applied to evaluate hydrological responses under changing climatic conditions in the snow‐fed Kali Gandaki River Basin (KGRB) in Western Nepal. Rainy season precipitation (June to September) in the basin takes up about 80% of the annual precipitation, and dry season runoff is largely contributed by snowmelt. Climate change is likely to increase the probability of extreme events and problems related to water availability. Therefore, the study aimed to simulate runoff pattern under changing climatic conditions, which will be helpful in the management of water resources in the basin. Public domain global data were widely used in this study. The model was calibrated and validated with an acceptable degree of accuracy. The results predicted that the annual average discharge will increase by 2.4%, 3.7%, and 5.7% when temperature increases by 1, 2, and 3 °C compared with the reference scenario. Similarly, maximum, minimum, and seasonal discharges in the monsoon and pre‐monsoon seasons will also increase with rising temperature. Snowmelt runoff is found sensitive to temperature changes in the KGRB. Increasing temperature will cause a faster snowmelt, but precipitation will increase the snowpack and also shed a positive effect on the total annual and monsoonal discharge. For the combined scenarios of increasing temperature and precipitation, the annual average discharge will increase. In contrast, discharge during the increasing temperature and decreasing precipitation will tend to decrease. Copyright © 2012 John Wiley & Sons, Ltd.     

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.     

Assessment of climate change impacts on the hydrology of the Peruvian Amazon–Andes basin

In this article, we propose an investigation of the modifications of the hydrological response of two Peruvian Amazonas–Andes basins in relationship with the modifications of the precipitation and evapotranspiration rates inferred by the IPCC. These two basins integrate around 10% of the total area of the Amazonian basin. These estimations are based on the application of two monthly hydrological models, GR2M and MWB3, and the climatic projections come from BCM2, CSMK3 and MIHR models for A1B and B1 emission scenarios (SCE A1B and SCE B1). Projections are approximated by two simple scenarios (anomalies and horizon) and annual rainfall rates, evapotranspiration rates and discharge were estimated for the 2020s (2008–2040), 2050s (2041–2070) and 2080s (2071–2099). Annual discharge shows increasing trend over Requena basin (Ucayali river), Puerto Inca basin (Pachitea river), Tambo basin (Tambo river) and Mejorada basin (Mantaro river) while discharge shows decreasing trend over the Chazuta basin (Huallaga river), the Maldonadillo basin (Urubamba river) and the Pisac basin (Vilcanota river). Monthly discharge at the outlet of Puerto Inca, Tambo and Mejorada basins shows increasing trends for all seasons. Trends to decrease are estimated in autumn discharge over the Requena basin and spring discharge over Pisac basin as well as summer and autumn discharges over both the Chazuta and the Maldonadillo basins. Copyright © 2011 John Wiley & Sons, Ltd.     

Integrating downscaled CMIP5 data with a physically based hydrologic model to estimate potential climate change impacts on streamflow processes in a mixed‐use watershed

Climatic changes have altered surface water regimes worldwide, and climate projections suggest that such alterations will continue. To inform management decisions, climate projections must be paired with hydrologic models to develop quantitative estimates of watershed scale water regime changes. Such modeling approaches often involve downscaling climate model outputs, which are generally presented at coarse spatial scales. In this study, Coupled Model Intercomparison Project Phase 5 climate model projections were analyzed to determine models representing severe and conservative climate scenarios for the study watershed. Based on temperature and precipitation projections, output from GFDL‐ESM2G (representative concentration pathway 2.6) and MIROC‐ESM (representative concentration pathway 8.5) were selected to represent conservative (Δ_C) and severe (Δ_S) change scenarios, respectively. Climate data were used as forcing for the soil and water assessment tool to analyze the potential effects of climate change on hydrologic processes in a mixed‐use watershed in central Missouri, USA. Results showed annual streamflow decreases ranging from ?5.9% to ?26.8% and evapotranspiration (ET) increases ranging from +7.2% to +19.4%. During the mid‐21st century, sizeable decreases to summer streamflow were observed under both scenarios, along with large increases of fall, spring, and summer ET under Δ_S. During the late 21st century period, large decreases of summer streamflow under both scenarios, and large increases to spring (Δ_S), fall (Δ_S) and summer (Δ_C) ET were observed. This study demonstrated the sensitivity of a Midwestern watershed to future climatic changes utilizing projections from Coupled Model Intercomparison Project Phase 5 models and presented an approach that used multiple climate model outputs to characterize potential watershed scale climate impacts.     

Impacts of climate change in three hydrologic regimes in British Columbia,Canada

Hydrologic modelling has been applied to assess the impacts of projected climate change within three study areas in the Peace, Campbell and Columbia River watersheds of British Columbia, Canada. These study areas include interior nival (two sites) and coastal hybrid nival–pluvial (one site) hydro‐climatic regimes. Projections were based on a suite of eight global climate models driven by three emission scenarios to project potential climate responses for the 2050s period (2041–2070). Climate projections were statistically downscaled and used to drive a macro‐scale hydrology model at high spatial resolution. This methodology covers a large range of potential future climates for British Columbia and explicitly addresses both emissions and global climate model uncertainty in the final hydrologic projections. Snow water equivalent is projected to decline throughout the Peace and Campbell and at low elevations within the Columbia. At high elevations within the Columbia, snow water equivalent is projected to increase with increased winter precipitation. Streamflow projections indicate timing shifts in all three watersheds, predominantly because of changes in the dynamics of snow accumulation and melt. The coastal hybrid site shows the largest sensitivity, shifting to more rainfall‐dominated system by mid‐century. The two interior sites are projected to retain the characteristics of a nival regime by mid‐century, although streamflow‐timing shifts result from increased mid‐winter rainfall and snowmelt, and earlier freshet onset. Copyright © 2012 John Wiley & Sons, Ltd.     

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.     

Numerical modelling of climate change impacts on Saint‐Lawrence River tributaries

The impacts of climate‐induced changes in discharge and base level in three tributaries of the Saint‐Lawrence River, Québec, Canada, are modelled for the period 2010–2099 using a one‐dimensional morphodynamic model. Changes in channel stability and bed‐material delivery to the Saint‐Lawrence River over this period are simulated for all combinations of seven tributary hydrological regimes (present‐day and those predicted using three global climate models and two greenhouse gas emission scenarios) and three scenarios of how the base level provided by the Saint‐Lawrence River will alter (no change, gradual fall, step fall). Even with no change in base level the projected discharge scenarios lead to an increase in average bed material delivery for most combinations of river and global climate model, although the magnitude of simulated change depends on the choice of global climate model and the trend over time seems related to whether the river is currently aggrading, degrading or in equilibrium. The choice of greenhouse gas emission scenario makes much less difference than the choice of global climate model. As expected, a fall in base level leads to degradation in the rivers currently aggrading or in equilibrium, and amplifies the effects of climate change on sediment delivery to the Saint‐Lawrence River. These differences highlight the importance of investigating several rivers using several climate models in order to determine trends in climate change impacts. Copyright © 2010 John Wiley & Sons, Ltd.     

Assessing the uncertainties of hydrologic model selection in climate change impact studies

The uncertainties associated with atmosphere‐ocean General Circulation Models (GCMs) and hydrologic models are assessed by means of multi‐modelling and using the statistically downscaled outputs from eight GCM simulations and two emission scenarios. The statistically downscaled atmospheric forcing is used to drive four hydrologic models, three lumped and one distributed, of differing complexity: the Sacramento Soil Moisture Accounting (SAC‐SMA) model, Conceptual HYdrologic MODel (HYMOD), Thornthwaite‐Mather model (TM) and the Precipitation Runoff Modelling System (PRMS). The models are calibrated based on three objective functions to create more plausible models for the study. The hydrologic model simulations are then combined using the Bayesian Model Averaging (BMA) method according to the performance of each models in the observed period, and the total variance of the models. The study is conducted over the rainfall‐dominated Tualatin River Basin (TRB) in Oregon, USA. This study shows that the hydrologic model uncertainty is considerably smaller than GCM uncertainty, except during the dry season, suggesting that the hydrologic model selection‐combination is critical when assessing the hydrologic climate change impact. The implementation of the BMA in analysing the ensemble results is found to be useful in integrating the projected runoff estimations from different models, while enabling to assess the model structural uncertainty. Copyright © 2011 John Wiley & Sons, Ltd.     

Quantification of uncertainty in the assessment of future streamflow under changing climate conditions

Climate change has a significant influence on streamflow variation. The aim of this study is to quantify different sources of uncertainties in future streamflow projections due to climate change. For this purpose, 4 global climate models, 3 greenhouse gas emission scenarios (representative concentration pathways), 6 downscaling models, and a hydrologic model (UBCWM) are used. The assessment work is conducted for 2 different future time periods (2036 to 2065 and 2066 to 2095). Generalized extreme value distribution is used for the analysis of the flow frequency. Strathcona dam in the Campbell River basin, British Columbia, Canada, is used as a case study. The results show that the downscaling models contribute the highest amount of uncertainty to future streamflow predictions when compared to the contributions by global climate models or representative concentration pathways. It is also observed that the summer flows into Strathcona dam will decrease, and winter flows will increase in both future time periods. In addition to these, the flow magnitude becomes more uncertain for higher return periods in the Campbell River system under climate change.     

The relative impacts of climate change and urbanization on the hydrological response of a Korean urban watershed

We assessed the relative hydrological impacts of climate change and urbanization using an integrated approach that links the statistical downscaling model (SDSM), the Hydrological Simulation Program—Fortran (HSPF) and the impervious cover model (ICM). A case study of the Anyangcheon watershed, a representative urban region in Korea, illustrates how the proposed framework can be used to analyse the impacts of climate change and urbanization on water quantity and quality. The evaluation criteria were measurements of low flow (99, 95, and 90 percentile flow), high flow (10, 5, and 1 percentile value), pollutant concentration (30, 10, and 1 percentile value), and the numbers of days required to satisfy the target water quantity and quality for a sensitive comparison of subtle impacts of variations in these measures. Nine scenarios, including three climate scenarios (present conditions, A1B, and A2) and three land use change scenarios, were analysed using the HSPF model. The impacts of climate change on low flow (34·1–59·8% increase) and high flow (29·1–37·1% increase) were found to be much greater than those on the biochemical oxygen demand (BOD) (3·8–10·0% decrease). On the other hand, the impacts of urbanization on water quality (19·0–44·6% increase) are more significant than those on high (1·0–4·4% increase) and low flow (11·4–25·6% decrease). Furthermore, low flows are more sensitive to urbanization than high flows. The number of days required to satisfy the target water quantity and quality can be a sensitive criterion to compare the subtle impacts of climate and urbanization on human society, especially as they are much more sensitive than low flow and pollutant concentration. Finally, urbanization has a potent impact on BOD while climate change has a high impact on flow rate. Therefore, the impacts of both climate change and urbanization must be included in watershed management and water resources planning for sustainable development. Copyright © 2010 John Wiley & Sons, Ltd.     

Assessment of future water provisioning and sediment load under climate and LULC change scenarios in a peninsular river basin,India

Assessment of the impact of changes in climate and land use and land cover (LULC) on ecosystem services (ES) is important for planning regional-scale strategies for sustainability and restoration of ES. The Upper Narmada River Basin (UNRB) in peninsular India has undergone rapid LULC change due to recent agricultural expansion. The impact of future climate and LULC change on ES in the UNRB is quantified and mapped using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST 3.3.0) tool. Our results show that water yield is projected to increase under climate change (about 43% for representative concentration pathway 4.5 for 2031–2040), whereas it is projected to decrease under the LULC change scenario. Sediment export is projected to increase (by 54.53%) under LULC change for 2031–2040. Under the combined effect of climate and LULC change, both water yield and sediment export are expected to increase. Climate change has a greater impact on projected water yield than LULC change, whereas LULC has greater impact on sediment export. Spatial analysis suggests a similar trend of variation in relative difference (RD) of ES in adjacent sub-basins. The quantified changes in ES provisioning will benefit future land management, particularly for operation of the Rani Avanti Bai Sagar Reservoir downstream of the UNRB.