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This paper presents a validation of outputs from some GCMs of the CMIP6 project when used to assess climate projection and hydrological flows at a catchment scale for the case study area of the Lombardy region (Northern Italy). The modeling chain consists of (i) a choice of climatic scenarios from 10 GCMs of the CMIP6, (ii) the application of a stochastic downscaling procedure to make projections usable at the local scale, and (iii) the use of a semi-distributed physically based hydrological model Poli-Hydro for the generation of hydrological scenarios. Data on observed precipitation and temperature were collected from automatic weather stations, and the hydrological budget of four target catchments within the study area was assessed using Poli-Hydro. An ex-post (back-casting) analysis was performed upon the control data series from the GCMs by comparing statistics of relevant climate variables and model-simulated discharges against observed counterparts during the historical period 2002–2014. Then, during 2015–2021, the goodness of projections was assessed using confidence intervals. Our results show that the accuracy of GCMs in representing regional climate is not always reflected in a credible evaluation of local hydrology. The validation of climate patterns provides somewhat poor results; thus, the interaction among climate and hydrology needs to be explored carefully to warrant the credibility of hydrological scenarios. Overall, the spatial and temporal consistency of GCM projections, as explored here climatically and hydrologically, provides a clue about their dependability for basin scale management. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of future research and development needs to assess the effectiveness of nature-based solutions for climate adaptation in watersheds at scale using hydrological models. Two main questions are addressed: to what extent are hydrological model approaches able to support decision making on nature-based solutions and adaptation, and how well is this hydrological analysis embedded in the broader planning process? To support the research, case studies in Bhutan, Zimbabwe and the Netherlands are presented. The Climate Risk Informed Decision Analysis approach is used to structure the planning process. All three case studies demonstrate how the hydrological system and full landscape of land and water use in watersheds can be simulated to better understand hydrometeorological hazards under current and future climate. Also, simulations of nature-based solutions are demonstrated, which need creativity and profound expert knowledge. In contrast to the assessment of grey infrastructure, no rules or guidance exists for the hydrological assessment of nature-based solutions. Physically-based models are better able to support the understanding of the functioning of the ecohydrological system and, therefore, the effectiveness of adaptation using nature-based solutions. There are however trade-offs between the computational complexity, the computation time and the multiple scenarios and sensitivity analyses of adaptation options needed for climate stress testing. Often there is a lack of monitoring data for verification of model outcomes. Several recommendations on how to improve modelling in an adaptation process are given. In addition, it is recommended to develop and rectify a set of nature-based solutions performance indicators, rules and algorithms to be adopted in models in order to quantify the effectiveness of these solutions. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of future research and development needs to assess the effectiveness of nature-based solutions for climate adaptation in watersheds at scale using hydrological models. Two main questions are addressed: to what extent are hydrological model approaches able to support decision making on nature-based solutions and adaptation, and how well is this hydrological analysis embedded in the broader planning process? To support the research, case studies in Bhutan, Zimbabwe and the Netherlands are presented. The Climate Risk Informed Decision Analysis approach is used to structure the planning process. All three case studies demonstrate how the hydrological system and full landscape of land and water use in watersheds can be simulated to better understand hydrometeorological hazards under current and future climate. Also, simulations of nature-based solutions are demonstrated, which need creativity and profound expert knowledge. In contrast to the assessment of grey infrastructure, no rules or guidance exists for the hydrological assessment of nature-based solutions. Physically-based models are better able to support the understanding of the functioning of the ecohydrological system and, therefore, the effectiveness of adaptation using nature-based solutions. There are however trade-offs between the computational complexity, the computation time and the multiple scenarios and sensitivity analyses of adaptation options needed for climate stress testing. Often there is a lack of monitoring data for verification of model outcomes. Several recommendations on how to improve modelling in an adaptation process are given. In addition, it is recommended to develop and rectify a set of nature-based solutions performance indicators, rules and algorithms to be adopted in models in order to quantify the effectiveness of these solutions. [ABSTRACT FROM AUTHOR]

[Display omitted] • Ten multi-model combination methods (MMCMs) are created from 29 models in 50 basins. • MMCMs improve some performance indicators, especially the Granger-Ramanathan method. • MMCMs do not improve performance in reproducing distributions of hydrological signatures. • Application with series of targeted signatures does not improve MMCM performance. • MMCM performance is improved by selecting more robust candidate models for ensembles. Multi-model combination (averaging) methods (MMCMs) are used to improve the accuracy of hydrological (precipitation-runoff) outputs in simulation or forecasting/prediction modes. In this paper, we examined if the application of MMCMs can improve model performance in reproducing distributions of hydrological signatures, such as annual maxima or minima of varying durations. To this end, ten MMCMs were applied to 29 bucket-type models to simulate runoff in 50 high-latitude catchments. The MMCMs were evaluated by comparing the resulting simulated flows to the reference (i.e., best-performing) individual model, considering various commonly used performance indicators, as well as model performance in reproducing the distributions of signatures. Additionally, we analysed whether (1) the selection of the candidate models, or (2) targeting specific signatures, such as annual maxima or minima, can improve performance of the model combinations. The results suggest that the application of MMCMs can improve accuracy of runoff simulations in terms of traditional performance indicators, but fails to improve performance in reproducing the distributions of signatures. Neither excluding poor-performing models nor applying the MMCMs with the targeted signatures, improves this aspect of model performance. These findings clearly reveal the need for further research aiming at enhancing model performance in reproducing the distributions of hydrological signatures, which is essential for climate-change impact studies. [ABSTRACT FROM AUTHOR]

• Three models were used to cover model structure uncertainty for each catchment. • AET is larger in the karst-dominated than the adjacent nonkarst-dominated catchment. • AET of karst-dominated catchment is more sensitive to the change in climate. • The karst-dominated catchment will experience much drier hydrological projections. Karst systems are well-known for their special features, such as epikarst zone and quick flow, compared to other hydrological systems. However, few studies explored the difference in hydrological responses to climate change between karst and nonkarst catchments. In this paper, two adjacent catchments dominated by karst and nonkarst in Southwest China (subtropical monsoon climate) were selected to investigate their different hydrological behaviors under future climates. To account for potential model structure uncertainties, three different karst hydrological models and three traditional catchment models were used to simulate these two catchments. The results demonstrate that different models yield comparable streamflow simulations within each catchment, allowing for the focus to be on the impact of climate change and catchment hydrological characteristics. The karst-dominated catchment is modeled to have larger actual evapotranspiration (AET) than the nonkarst-dominated catchment under similar climate conditions, with the AET of the former being more sensitive to changes in precipitation and potential evapotranspiration. These differences are primarily due to the presence of the epikarst in the unsaturated zone of the karst system, which can store more infiltration rainwater for evapotranspiration. Both catchments are expected to experience a wetter projection in the wet season and a drier projection in the dry season in the future. However, the karst-dominated catchment will face a drier climate with a significant increase in precipitation in just two months (July and August). Additionally, because of a higher sensitivity of monthly AET to climate change, the karst-dominated catchment will experience a greater monthly discharge reduction in the first two wet months (April and May), a relatively lower discharge increase in other wet months, and a lower monthly discharge in dry months, while the monthly discharge of the nonkarst-dominated catchment increases in the wet season and decrease in the dry season. Furthermore, the karst-dominated catchment will have a much lower annual discharge than the nonkarst-dominated catchment, particularly during extremely dry years in the future period due to its larger AET consumption. These all suggest that the karst-dominated catchment will be more vulnerable to droughts. Overall, due to the drier climate and the different hydrological backgrounds of the karst-dominated catchment, it is expected to have much drier hydrological conditions in the future compared to the nonkarst-dominated catchment. [ABSTRACT FROM AUTHOR]

Summary The effects of climate change on water resources have been studied extensively throughout the world through the use of hydrologic models coupled with General Circulation Model (GCM) output or climate sensitivity scenarios. This paper examines the effects of hydrologic model parameterization uncertainty or equifinality, where multiple unique hydrologic model parameter sets can result in adequate calibration metrics, on hydrologic projections from downscaled GCMs for three snowmelt-dependent watersheds (upper reaches of the Clearwater, Gunnison, and Sacramento River watersheds) in the western United States. The hydrologic model used in this study is the Soil and Water Assessment Tool (SWAT) and is calibrated for discharge at the watershed outlet in each watershed. Despite achieving similar calibration metrics, a majority of hydrologic projections of average annual streamflow during the 2080s were statistically different, with differences in magnitude and direction (increase or decrease) compared to historical annual streamflows. At the average monthly time-scale, a majority of the hydrologic projections varied in peak streamflow timing, peak streamflow magnitude, summer streamflows, as well as overall increases or decreases compared to the historical monthly streamflows. Snowmelt projections from the SWAT model also widely varied, both in depth and snowmelt peak timing, for all watersheds. Since a large portion of the runoff-producing regions in the western United States is snowmelt-dependent, this has large implications for the prediction of the amount and timing of streamflow in the coming century. This paper shows that hydrologic model parameterizations that give similar adequate calibration metrics can lead to statistically significant differences in hydrologic projections under climate change. Therefore, researchers and water resource managers should account for this uncertainty by assembling ensemble projections from both multiple parameter sets and GCMs. [ABSTRACT FROM AUTHOR]

Global climate change has led to an increase in both the frequency and magnitude of extreme events around the world, the risk of which is especially imminent in tropical regions. Developing hydrological models with better capabilities to simulate streamflow, especially peak flow, is urgently needed to facilitate water resource planning and management as well as climate change mitigation efforts in the tropics. In view of the need, this paper explores the feasibility of improving streamflow simulation performance in the tropical Kelantan River Basin (KRB) of Peninsular Malaysia through coupling a conceptual process-based hydrological model − Soil and Water Assessment Tool (SWAT) with a deep learning model − Bidirectional Long Short-Term Memory (Bi-LSTM) in two ways. All SWAT parameters were set as their default values in one hybrid model (SWAT-D-LSTM), whereas three most sensitive SWAT parameters were calibrated in the other hybrid model (SWAT-T-LSTM). Comparison of daily streamflow simulation results have shown that SWAT-T-LSTM consistently performs better than SWAT-D-LSTM as well as the stand-alone SWAT and Bi-LSTM model throughout the simulation period. Particularly, SWAT-T-LSTM performs considerably better than the other three models in simulating daily peak flow. Based on the latest projection results of five GCMs from the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) under three emission scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5), the best-performed SWAT-T-LSTM was run to assess the potential impacts of climate change on streamflow in the KRB. Ensemble assessment results have concluded that both average and extreme streamflow is much likely to increase considerably in the already wet northeast monsoon season from November to January, which has surely raised the alarm for more frequent flood occurrence in the KRB. • Couple SWAT with Bi-LSTM to simulate daily streamflow in a tropical river basin. • Coupled model simulates streamflow much better than stand-alone SWAT and Bi-LSTM. • Use coupled model to assess impacts of climate change under multiple scenarios. • Both average and extreme streamflow is much likely to increase in monsoon season. [ABSTRACT FROM AUTHOR]

The present study attempts to investigate potential impacts of climate change on floods frequency in Bazoft Basin which is located in central part of Iran. A combination of four general circulation models is used through a weighting approach to assess uncertainty in the climate projections. LARS-WG model is applied to downscale large scale atmospheric data to local stations. The resulting data is in turn used as input of the hydrological model Water and Energy Transfer between Soil, plants and atmosphere (WetSpa) to simulate runoff for present (1971-2000), near future (2020-2049) and far future (2071-2100) conditions. Results demonstrate good performance of both WetSpa and LARS-WG models. In addition in this paper instantaneous peak flow (IPF) is estimated using some empirical equations including Fuller, Sangal and Fill-Steiner methods. Comparison of estimated and observed IPF shows that Fill-Steiner is better than other methods. Then different probability distribution functions are fit to IPF series. Results of flood frequency analysis indicate that Pearson III is the best distribution fitted to IPF data. It is also indicated that flood magnitude will decrease in future for all return periods. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate sources of uncertainty in projected hydrological changes under climate change in twelve large-scale river basins worldwide, considering the mean flow and the two runoff quantiles Q (high flow), and Q (low flow). First, changes in annual low flow, annual high flow and mean annual runoff were evaluated using simulation results from a multi-hydrological-model (nine hydrological models, HMs) and a multi-scenario approach (four Representative Concentration Pathways, RCPs, five CMIP5 General Circulation Models, GCMs). Then, three major sources of uncertainty (from GCMs, RCPs and HMs) were analyzed using the ANOVA method, which allows for decomposing variances and indicating the main sources of uncertainty along the GCM-RCP-HM model chain. Robust changes in at least one runoff quantile or the mean flow, meaning a high or moderate agreement of GCMs and HMs, were found for five river basins: the Lena, Tagus, Rhine, Ganges, and Mackenzie. The analysis of uncertainties showed that in general the largest share of uncertainty is related to GCMs, followed by RCPs, and the smallest to HMs. The hydrological models are the lowest contributors of uncertainty for Q and mean flow, but their share is more significant for Q. [ABSTRACT FROM AUTHOR]

The paper investigates climate change impacts on streamflow seasonality for a set of eleven representative large river basins covering all continents and a wide range of climatic and physiographic settings. Based on an ensemble of nine regional hydrological models driven by climate projections derived from five global circulation models under four representative concentration pathways, we analyzed the median and range of projected changes in seasonal streamflow by the end of the twenty-first century and examined the uncertainty arising from the different members of the modelling chain. Climate change impacts on the timing of seasonal streamflow were found to be small except for two basins. In many basins, we found an acceleration of the existing seasonality pattern, i.e. high-flows are projected to increase and/or low-flows are projected to decrease. In some basins the hydrologic projections indicate opposite directions of change which cancel out in the ensemble median, i.e., no robust conclusions could be drawn. In the majority of the basins, differences in projected streamflow seasonality between the low emission pathway and the high emission pathway are small with the exception of four basins. For these basins our results allow conclusions on the potential benefits (or adverse effects) of avoided GHG emissions for the seasonal streamflow regime. [ABSTRACT FROM AUTHOR]

This study analyzed changes in hydrology between two recent decades (1980s and 2010s) with the Soil and Water Assessment Tool ( SWAT) in three representative watersheds in South Dakota: Bad River, Skunk Creek, and Upper Big Sioux River watersheds. Two SWAT models were created over two discrete time periods (1981-1990 and 2005-2014) for each watershed. National Land Cover Datasets 1992 and 2011 were, respectively, ingested into 1981-1990 and 2005-2014 models, along with corresponding weather data, to enable comparison of annual and seasonal runoff, soil water content, evapotranspiration ( ET), water yield, and percolation between these two decades. Simulation results based on the calibrated models showed that surface runoff, soil water content, water yield, and percolation increased in all three watersheds. Elevated ET was also apparent, except in Skunk Creek watershed. Differences in annual water balance components appeared to follow changes in land use more closely than variation in precipitation amounts, although seasonal variation in precipitation was reflected in seasonal surface runoff. Subbasin-scale spatial analyses revealed noticeable increases in water balance components mostly in downstream parts of Bad River and Skunk Creek watersheds, and the western part of Upper Big Sioux River watershed. Results presented in this study provide some insight into recent changes in hydrological processes in South Dakota watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series. [ABSTRACT FROM AUTHOR]

This paper investigates the hydrological response of glacierized headwater catchments to future climate change in the Ötztal Alps, Austria. To this end, two conceptual hydrological models, HBV (Hydrologiska Byråns Vattenbalansavdelning) and HQsim, are applied for the simulation of future daily discharge in three (nested) catchments with varying degrees of glaciation. The models are forced with downscaled climate change projections, and outputs from an empirical glacier model, which is able to simulate future glacial evolution. Under the future conditions, the outcomes show initially that runoff increases for all catchments without changes in the runoff regimes. In the long term, summer runoff is expected to decrease and winter/spring runoff is expected to increase in all catchments. These runoff changes are accompanied with regime shifts from glacial/glacio-nival runoff regimes to runoff regimes with a higher nival component. Changing runoff conditions might also lead to changes in the seasonality of annual flood peaks with an earlier appearance of flood peaks, and an increasing appearance of low flow conditions during summer months. The outcomes of the two hydrological models show minor differences. The results of this study provide improved understanding of the future impact of climate change on the water cycle of glacierized Alpine catchments. [ABSTRACT FROM AUTHOR]

Summary: Catchment hydrological models are widely used in climate change impact studies. The considered climate scenarios often involve increases in rainfall intensities. These increases might go beyond the range of historical events used in model calibration and validation. The hydrological impact results of climate change consequently are under these circumstances highly uncertain. This paper presents a method to test the validity of hydrological models for that type of impact analysis. The method is based on the evaluation of peak flow increases due to different levels of rainfall increases. The method is demonstrated, based upon the results of three conceptual rainfall–runoff models (NAM, PDM, VHM) for three catchments in Belgium. It is shown how the performance of the model in predicting impacts of rainfall increases can be integrated in the calibration process and how this method can increase the reliability of climate change impact results on peak flows. The paper addresses the importance of the relation between the soil moisture content and the overland flow coefficient, as it controls the generation of peak flows in the considered rainfall–runoff models. [ABSTRACT FROM AUTHOR]

This paper presents a detailed analysis of how future climate change may affect water availability in a typical arid endorheic river basin, the Heihe River basin (HRB), in northwest China. The analysis is based on the improved Soil Water Assessment Tool (SWAT), which is calibrated and validated with historical streamflow data from the upper HRB and is used to predict future hydrological responses. Six general circulation models (GCMs), under two emission scenarios (RCP4.5 and RCP8.5), are downscaled to construct future climate change scenarios. The results suggest that the climate of the upper HRB will likely become warmer and wetter in the near future (2021-50), with the largest increase in precipitation occurring in the summer. Correspondingly, the basinwide evapotranspiration, snowmelt, and runoff are projected to increase over the same period. The mean temperature in the near future is projected to rise, relative to the recent 30 years (1981-2010), by 1.2°-1.7°C under scenario RCP4.5 and by 1.4°-2.1°C under scenario RCP8.5. The mean precipitation is projected to increase by 10.0%-16.6% under scenario RCP4.5, and by 10.5%-22.0% under scenario RCP8.5. The mean values of evapotranspiration, snowmelt, and runoff are expected to increase by 14.2%, 4.3%, and 11.4%, respectively, under scenario RCP4.5 and to increase by 18.7%, 5.8%, and 12.8%, respectively, under scenario RCP8.5. Though the model simulations forecast an increase in streamflows in the headwater region of the HRB, future water availability varies significantly over space and time. The findings of this study will help to frame more effective water management strategies for the HRB under changing climatic conditions. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the uncertainty ranges of high flows under climate change in Jinhua River basin, eastern China. Four representative concentration pathways (RCPs), three global climate models (GCMs), 10 downscaling parameter sets and three hydrologic models are applied to simulate future discharges. Changes of annual maximum discharges are assessed for the baseline period (1961-1990) and future period (2011-2040). The uncertainties of annual maximum discharges are calculated for each uncertainty source and compared with different combinations of them. The minimum temperature will probably increase all year round in the future period and maximum temperature would increase in most cases. The changes of precipitation showed different directions by different models and emission scenarios. The annual maximum discharges would decrease for all RCPs. The order of uncertainty ranges of high flows due to different uncertainty sources from high to low is: hydrologic models, GCMs, parameter sets in the downscaling method and emission scenarios. It must be noted that the small uncertainty contribution from different emission scenarios is due to the study period when the differences in increase of radiative forcing and greenhouse gas concentration are less obvious between different RCPs compared to the second half of the 21st century. [ABSTRACT FROM AUTHOR]

A significant decrease in mean river flow as well as shifts in flood regimes have been reported at several locations along the River Niger. These changes are the combined effect of persistent droughts, damming and increased consumption of water. Moreover, it is believed that climate change will impact on the hydrological regime of the river in the next decades and exacerbate existing problems. While decision makers and stakeholders are aware of these issues, it is hard for them to figure out what actions should be taken without a quantitative estimate of future changes. In this paper, a Soil and Water Assessment Tool (SWAT) model of the Niger River watershed at Koulikoro was successfully calibrated, then forced with the climate time series of variable length generated by nine regional climate models (RCMs) from the AMMA-ENSEMBLES experiment. The RCMs were run under the SRES A1B emissions scenario. A combination of quantile-quantile transformation and nearest-neighbour search was used to correct biases in the distributions of RCM outputs. Streamflow time series were generated for the 2026–2050 period (all nine RCMs), and for the 2051–2075 and 2076–2100 periods (three out of nine RCMs) based on the availability of RCM simulations. It was found that the quantile-quantile transformation improved the simulation of both precipitation extremes and ratio of monthly dry days/wet days. All RCMs predicted an increase in temperature and solar radiation, and a decrease in average annual relative humidity in all three future periods relative to the 1981–1989 period, but there was no consensus among them about the direction of change of annual average wind speed, precipitation and streamflow. When all model projections were averaged, mean annual precipitation was projected to decrease, while the total precipitation in the flood season (August, September, October) increased, driving the mean annual flow up by 6.9% (2026–2050), 0.9% (2051–2075) and 5.6% (2076–2100). At-test showed that changes in multi-model annual mean flow and annual maximum monthly flow between all four periods were not statistically significant at the 95% confidence level. [ABSTRACT FROM PUBLISHER]

The first objective of this paper is to analyse the trends and change points in the hydroclimatic time series of five representative sub-catchments of the Macta basin, which lies in western Algeria. The second objective is to quantify the role of climate on the trends observed in annual flow time series. This is achieved using hydrological modelling at the multi-annual time step using the Schreiber formulation. The results showed no significant trends on annual rainfall in the 1975–2005 period, a significant increase of temperature and different flow responses to the latter, depending on the catchment considered. Two out of five catchments considered presented a significant flow decrease in the 1975–2005 period with a change point at the beginning of the 1990s. Modelling results suggest that the increase of air temperature is not the sole factor explaining the decrease of annual flow time series in these two catchments. [ABSTRACT FROM AUTHOR]

Summary Spatial variability of climate can negatively affect catchment streamflow predictions if it is not explicitly accounted for in hydrologic models. In this paper, we examine the changes in streamflow predictability when a hydrologic model is run with spatially variable (distributed) meteorological inputs instead of spatially uniform (lumped) meteorological inputs. Both lumped and distributed versions of the EXP-HYDRO model are implemented at 41 meso-scale (500–5000 km 2 ) catchments in the Pacific Northwest region of USA. We use two complementary metrics of long-term spatial climate variability, moisture homogeneity index ( I M ) and temperature variability index ( I TV ), to analyze the performance improvement with distributed model. Results show that the distributed model performs better than the lumped model in 38 out of 41 catchments, and noticeably better (>10% improvement) in 13 catchments. Furthermore, spatial variability of moisture distribution alone is insufficient to explain the observed patterns of model performance improvement. For catchments with low moisture homogeneity ( I M < 80%), I M is a better predictor of model performance improvement than I TV ; whereas for catchments with high moisture homogeneity ( I M > 80%), I TV is a better predictor of performance improvement than I M . Based on the results, we conclude that: (1) catchments that have low homogeneity of moisture distribution are the obvious candidates for using spatially distributed meteorological inputs, and (2) catchments with a homogeneous moisture distribution benefit from spatially distributed meteorological inputs if they also have high spatial variability of precipitation phase (rain vs. snow). [ABSTRACT FROM AUTHOR]

This paper presents an application of the Variable Infiltration Capacity (VIC) model to the Fraser River basin (FRB) of British Columbia (BC), Canada, over the latter half of the twentieth century. The Fraser River is the longest waterway in BC and supports the world's most abundant Pacific Ocean salmon populations. Previous modeling and observational studies have demonstrated that the FRB is a snow-dominated system, but with climate change, it may evolve to a pluvial regime. Thus, the goal of this study is to evaluate the changing contribution of snow to the hydrology of the FRB over the latter half of the twentieth century. To this end, a 0.25° atmospheric forcing dataset is used to drive the VIC model from 1949 to 2006 (water years) at a daily time step over a domain covering the entire FRB. A model evaluation is first conducted over 11 major subwatersheds of the FRB to quantitatively assess the spatial variations of snow water equivalent (SWE) and runoff ( R). The ratio of the spatially averaged maximum SWE to R ( RSR) is used to quantify the contribution of snow to the runoff in the 11 subwatersheds of interest. From 1949 to 2006, RSR exhibits a significant decline in 9 of the 11 subwatersheds (with p < 0.05 according to the Mann-Kendall test statistics). To determine the sensitivity of RSR, the air temperature and precipitation in the forcing dataset are then perturbed. The ratio RSR decreases more significantly, especially during the 1990s and 2000s, when air temperatures have warmed considerably compared to the 1950s. On the other hand, increasing precipitation by a multiplicative factor of 1.1 causes RSR to decrease. As the climate continues to warm, ecological processes and human usage of natural resources in the FRB may be substantially affected by its transition from a snow to a hybrid (nival/pluvial) and even a rain-dominated system. [ABSTRACT FROM AUTHOR]

Long-term changes in the water budget of lakes in the Tibetan Plateau due to climate change are of great interest not only for the importance of water management, but also for the critical challenge due to the lack of observations. In this paper, the water budget of Nam Co Lake during 1980-2010 is simulated using a dynamical monthly water balance model. The simulated lake level is in good agreement with field investigations and the remotely sensed lake level. The long-term hydrological simulation shows that from 1980 to 2010, lake level rose from 4718.34 to 4724.93 m, accompanied by an increase of lake water storage volume from 77.33 × 109 to 83.66 × 109 m3. For the net lake level rise (5.93 m) during the period 1980-2010, the proportional contributions of rainfall-runoff, glacier melt, precipitation on the lake, lake percolation, and evaporation are 104.7%, 56.6%, 41.7%, −22.2%, and −80.9%, respectively. A positive but diminishing annual water surplus is found in Nam Co Lake, implying a continuous but slowing rise in lake level as a hydrological consequence of climate change. [ABSTRACT FROM AUTHOR]

Global warming will have direct impacts on regional water resources by accelerating the hydrological cycle. Hydrological simulation is an important approach to studying climate change impacts. In this paper, a snowmelt-based water balance model (SWBM) was used to simulate the effect of climate change on runoff in the Kuye River catchment of the Loess Plateau, China. Results indicated that the SWBM is suitable for simulating monthly discharge into arid catchments. The response of runoff in the Kuye River catchment to climate change is nonlinear, and runoff is more sensitive to changes in precipitation than to changes in temperature. The projections indicated that the Kuye River catchment would undergo more flooding in the 2020s, and global warming would probably shorten the main flood season in the catchment, with greater discharge occurring in August. Although projected changes in annual runoff are uncertain, the possibilities of regional water shortages and regional flooding are essential issues that need to be fully considered. [ABSTRACT FROM AUTHOR]

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

Summary: This paper investigates the uncertainty of hydrological predictions due to rainfall-runoff model parameters in the context of climate change impact studies. Two sources of uncertainty were considered: (i) the dependence of the optimal parameter set on the climate characteristics of the calibration period and (ii) the use of several posterior parameter sets over a given calibration period. The first source of uncertainty often refers to the lack of model robustness, while the second one refers to parameter uncertainty estimation based on Bayesian inference. Two rainfall-runoff models were tested on 89 catchments in northern and central France. The two sources of uncertainty were assessed in the past observed period and in future climate conditions. The results show that, given the evaluation approach followed here, the lack of robustness was the major source of variability in streamflow projections in future climate conditions for the two models tested. The hydrological projections generated by an ensemble of posterior parameter sets are close to those associated with the optimal set. Therefore, it seems that greater effort should be invested in improving the robustness of models for climate change impact studies, especially by developing more suitable model structures and proposing calibration procedures that increase their robustness. [ABSTRACT FROM AUTHOR]

Impacts on water resources produced by climate change can be exacerbated when occurring in regions already presenting low water resources levels and frequent droughts, and subject to imbalances between water demands and available resources. Within Europe, according to existing climate change scenarios, water resources will be severely affected in Spain. However, the detection of those effects is not simple, because the natural variability of the water cycle and the effects of water abstractions on flow discharges complicate the establishment of clear trends. Therefore, there is a need to improve the assessment of climate change impacts by using hydrological simulation models. This paper reviews water resources and their variability in Spain, the recent modelling studies on hydrological effects of climate change, expected impacts on water resources, the implications in river basins and the current policy actions. Editor Z.W. Kundzewicz Citation Estrela, T., Pérez-Martin, M.A., and Vargas, E., 2012. Impacts of climate change on water resources in Spain. Hydrological Sciences Journal, 57 (6), 1154–1167. [ABSTRACT FROM AUTHOR]

The majority of the world's population growth to 2050 is projected to occur in the tropics. Hence, there is a serious need for robust methods for undertaking water resource assessments to underpin the sustainable management of water in tropical regions. This paper describes the largest and most comprehensive assessment of the future impacts of runoff undertaken in a tropical region using conceptual rainfall-runoff models (RRMs). Five conceptual RRMs were calibrated using data from 115 streamflow gauging stations, and model parameters were regionalized using a combination of spatial proximity and catchment similarity. Future rainfall and evapotranspiration projections (denoted here as GCMES) were transformed to catchment-scale variables by empirically scaling (ES) the historical climate series, informed by 15 global climate models (GCMs), to reflect a 1°C increase in global average surface air temperature. Using the best-performing RRM ensemble, approximately half the GCMES used resulted in a spatially averaged increase in mean annual runoff (by up to 29%%) and half resulted in a decrease (by up to 26%%). However, ~70%% of the GCMES resulted in a difference of within ±5%% of the historical rainfall (1930-2007). The range in modeled impact on runoff, as estimated by five RRMs (for individual GCMES), was compared to the range in modeled runoff using 15 GCMES (for individual RRMs). For mid- to high runoff metrics, better predictions will come from improved GCMES projections. A new finding of this study is that in the wet-dry tropics, for extremely large runoff events and low flows, improvements are needed in both GCMES and rainfall-runoff modeling. [ABSTRACT FROM AUTHOR]

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

Summary: This paper investigates the effects of model structure and parameter equifinality on the uncertainty related to hydrological modelling in climate change impact studies. The study is conducted on a snow-dominated watershed located in the southern part of the province of Quebec (Canada). Hydrological model structure uncertainty is examined through the use of two very different simulation tools, one lumped conceptual model and one spatially-distributed physically-based model. Parameter equifinality is examined by performing multiple automatic calibrations with both hydrological models. The analysis is first carried out under recent past climate and then under modified climate conditions following two contrasted projections that are analysed separately. The delta change approach is used to build the two climate projections. Overall, this study reveals that the impact of hydrological model structure uncertainty is more significant than the effect of parameter uncertainty, under recent past climate as well as future climate conditions. Ultimately, the use of hydrological models with different levels of complexity should be considered as part of the global uncertainty related to hydrological model structure. [Copyright &y& Elsevier]

Among the processes most affected by global warming are the hydrological cycle and water resources. Regions where the majority of runoff consists of snowmelt are very sensitive to climate change. It is significant to express the relationship between climate change and snow hydrology and it is imperative to perform climate change impact studies on snow hydrology at global and regional scales. Climate change impacts on the mountainous Upper Euphrates Basin were investigated in this paper. First, historical data trend analysis of significant hydro-meteorological data is presented. Available future climate data are then explained, and, finally, future climate data are used in hydrological models, which are calibrated and validated using historical hydro-meteorological data, and future streamflow is projected for the period 2070–2100. The hydrological model outcomes indicate substantial runoff decreases in summer and spring season runoff, which will have significant consequences on water sectors in the Euphrates Basin. Citation Yilmaz, A.G. & Imteaz, M.A. (2011) Impact of climate change on runoff in the upper part of the Euphrates basin. Hydrol. Sci. J. 56(7), 1265–1279. [ABSTRACT FROM AUTHOR]

Based on the changes in the size of closed basin lakes, the author shows that water availability has undergone large fluctuations in response to conditions experienced during full glacial time and during the period of deglaciation. Based on these observations, the author concludes that as the planet warms in response to the buildup of fossil fuel CO2, the distribution of available water will shift. The resulting changes will be particularly noticeable in the world''s drylands. In this paper, the author attempts to invert the response to cold glacial conditions and to interhemispheric temperature differences, which occurred during the interval of deglaciation, to predict how the hydrologic conditions in the western United States might evolve over the next half-century. The tentative conclusion on both scores is that this region will likely undergo a progressive drying. However, because both the glacial and deglacial hydrologic shifts were certainly influenced by the presence of excess ice, as well as by colder temperatures, the author admits that the validity of this inversion is subject to challenge. [ABSTRACT FROM AUTHOR]

Summary: This paper presents results from a modelling study carried out to investigate whether the calibrated parameter values for rainfall–runoff models based on historical observed data can be used to reliably predict runoff responses to changes in future climate inputs. The modelling experiments are carried out for four rainfall–runoff models using long records of historical daily climate and streamflow data from 61 catchments in southeast Australia. The results indicate that the models, when calibrated using more than 20years of data, can generally be used for climate impact studies where the future mean annual rainfall is not more than 15% drier or 20% wetter than the mean annual rainfall in the model calibration period. It is generally more difficult for a model calibrated over a wet period to predict runoff over a dry period compared to a model calibrated over a dry period to predict runoff over a wet period. For southeast Australia, there is a good reason to use the recent records to calibrate rainfall–runoff models to represent the current prolonged drought over the region and for climate change impact studies where the large majority of climate models predict a drier future across this region. [ABSTRACT FROM AUTHOR]

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

This paper draws on interviews with Washington State Watershed Planning Leads (Planning Leads) and interactions with local watershed planning units to identify factors that may influence the inclusion of climate change in watershed planning efforts in Washington State. These factors include the interest of individual planning unit members in climate change; Planning Lead familiarity with climate impacts; the influence of trust, leadership, and ‘genetic knowledge’ on planning units; and perceptions of strategic gain. The research also identifies aspects of the planning process that may create opportunities for addressing climate impacts in future planning. These aspects include continuation of watershed planning units after plans are developed; commitment to updating watershed plans; recognition of climate impacts in planning documentation; dedicated incentive funding; and the availability of hydrologic modeling tools for assessing hydrologic impacts. Additional types of technical assistance that could support integration of climate impacts are also identified. It is hoped that the insight provided by this analysis will help individuals involved in stakeholder-based watershed planning recognize the various dynamics potentially affecting the inclusion of climate change in watershed planning and in doing so, contribute to the development of planning approaches and tools that will support local efforts to adapt to climate impacts. [ABSTRACT FROM AUTHOR]