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Forest disturbance threshold is defined as a critical disturbance level (e.g., % of forest cover change) in forested landscapes above which significant hydrological impacts are detected. Determining disturbance thresholds is critically important for supporting forest management to ensure the sustaining of ecological and hydrological functions. However, there are very few quantitative evaluations of forest disturbance thresholds globally. In this study, we applied a well‐tested methodology (the modified double mass curve) to derive the long‐term, continuous hydrological response curves and then to quantify forest disturbance thresholds on annual streamflow in 42 forested watersheds in British Columbia, Canada. The results show that forest disturbance thresholds for significant and cumulative hydrological impacts vary from 7% to 52% of cumulative equivalent clear‐cut area with an average of 17% or from 8% to 52% of disturbed area with an average of 19%. Climate (inter‐annual and intra‐annual) and watershed properties exert critical controls on forest disturbance thresholds. Watersheds with greater snowfall proportions (more annual precipitation falling as snow), more desynchronizations (temporal mismatching) of energy demand and water supply at the intra‐annual scale, less diverse ecosystems, and larger watershed sizes have lower forest disturbance thresholds. Given the present forest disturbance levels in the central interior of British Columbia, about half (53%) of the forested watersheds have already crossed the average disturbance threshold. These results highlight that watershed planning and management using forest disturbance thresholds must carefully consider local climate and watershed properties. The methodology can be effectively and robustly extended elsewhere around the globe. Plain Language Summary: This first‐ever study uses the hydrological response curves to quantify forest disturbance thresholds on annual streamflow in 42 forested watersheds in the interior of British Columbia, Canada. We find that forest disturbance thresholds range from 7% to 52% of cumulative equivalent clear‐cut area with the average of 17%. Climate and watershed properties play critical roles in controlling disturbance thresholds. Watersheds characterized by more annual precipitation falling as snow, more mismatching of energy and water at the intra‐annual scale, larger watershed size, and less diverse ecosystems exhibit lower disturbance thresholds. Management implications and future research needs for preserving hydrological functions are discussed. Key Points: A new approach with the hydrological response curves is used to quantify forest disturbance thresholdsForest disturbance thresholds for cumulative impacts on annual streamflow vary from 7% to 52% of cumulative equivalent clear‐cut area with the average of 17%Climate and watershed properties exert critical controls on the thresholds [ABSTRACT FROM AUTHOR]

The Xingu River Basin (XRB) in the Brazilian Amazon region has a great relevance to the development of northern Brazil because of the Belo Monte hydropower plant and its crescent agribusiness expansion. This study aimed to evaluate the potential of the Lavras Simulation of the Hydrology (LASH) model to represent the main hydrological processes in the XRB and simulate the hydrological impacts in the face of land-use change scenarios. Following the trend of the most relevant agribusiness evolution in the XRB, four agribusiness scenarios (S) were structured considering the increase in grasslands (S1: 50% over the native forest; S2: 100% over the native forest) and soybean plantations (S3: 50% over the native forest; S4: 100% over native forest). Average hydrographs were simulated, and the frequency duration curves (FDC) and average annual values of the main hydrological components for each scenario were compared. The results showed that, in general, changes in land use based on deforestation in the XRB would lead to an increase in flood streamflow and a reduction in baseflow. The increases in direct surface runoff varied from 4.4% for S1 to 29.8% for S4 scenarios. The reduction in baseflow varied from −1.6% for S1 to −4.9% for S2. These changes were reduced when the entire XRB was analyzed, but notable for the sub-basins in its headwater region, where the scenarios were more effective. [ABSTRACT FROM AUTHOR]

Uncertainty sources in climate change impact studies can be addressed in two distinct phases, climate modelling and impact assessment. Generally, uncertainty from the climate modelling phase is the larger contributor and the impact phase uncertainty is sometimes marginalized. This paper aims to develop integrated uncertainty analysis approaches that deal with uncertainties at the impact level with all sources included. The existing uncertainty analysis method of Reliability Ensemble Averaging (REA) is modified for impact studies by bracketing the hydrological model parameter uncertainty. A novel probabilistic approach referred to as Bootstrapped Ensemble Uncertainty Modelling (BEUM) is also proposed for uncertainty analysis at the impact phase. Modified REA and BEUM are applied to streamflow projections of the Hulu Langat basin with uncertainties stemming from emission scenarios, general circulation models (GCM), downscaling method, and a hydrological model parametrization for a comprehensive integrated uncertainty assessment. The modified REA increased the reliability measure of each streamflow scenario and improved the uncertainty coverage percentage when compared with the original REA. The REA eliminated the projections of the less reliable GCMs, and therefore reduced uncertainty bands compared to the BEUM. The BEUM can create a large ensemble of streamflow projections through nonparametric bootstrapping of the limited impact scenarios and define the streamflow distribution for every quantile. Therefore, BEUM is able to encompass larger uncertainty intervals and explain the behavior of ensemble members through probabilistic distributions that can assist in decision making for climate change mitigation and adaptation planning. [ABSTRACT FROM AUTHOR]

Global climate model (GCM) outputs from Coupled Model Inter-comparison Project Phase 5 (CMIP5) were widely used to investigate climate change impacts last 10 years. It is important to know whether Coupled Model Inter-comparison Project Phase 6 (CMIP6) is more reliable than CMIP5. Number of studies compared GCMs from two CMIPs in simulating climate variables, but they are not in the field of hydrology for large quantities of watersheds. The objective of this study is to compare CMIP5 and CMIP6 climate model projections in projecting hydrological changes between future (2071-2100) and historical (1976-2005) periods and inter-model variability of hydrological impacts for the future period over 343 catchments in China's mainland. The results show that the GCMs in CMIP6 show more increase in daily mean temperature and mean annual precipitation. However, GCMs in CMIP6 and CMIP5 show similar increases in mean and peak streamflow. Moreover, GCMs in CMIP6 show less inter-model variability for streamflow in southern and northeastern China, but more in central China, which is consistent to that for precipitation after bias correction. Overall, this comparison provides the consistency of future change and uncertainty in predicted streamflow with climate simulations, which bring confidence for hydrological impact studies using CMIP6. [ABSTRACT FROM AUTHOR]

A warmer climate impacts streamflows and these changes need to be quantified to assess future risk, vulnerability, and to implement efficient adaptation measures. The climate simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), which have been the basis of most such assessments over the past decade, are being gradually superseded by the more recent Coupled Model Intercomparison Project Phase 6 (CMIP6). Our study portrays the added value of the CMIP6 ensemble over CMIP5 in a first North America wide comparison using 3,107 catchments. Results show a reduced spread of the CMIP6 ensemble compared to the CMIP5 ensemble for temperature and precipitation projections. In terms of flow indicators, the CMIP6 driven hydrological projections result in a smaller spread of future mean and high flow values, except for mountainous areas. Overall, we assess that the CMIP6 ensemble provides a narrower band of uncertainty of future climate projections, bringing more confidence for hydrological impact studies. Plain Language Summary: Greenhouse gas emissions are causing the climate to warm significantly, which in turn impacts flows in rivers worldwide. To adapt to these changes, it is essential to quantify them and assess future risk and vulnerability. Climate models are the primary tools used to achieve this. The main data set that provides scientists with state‐of‐the‐art climate model simulations is known as the Coupled Model Intercomparison Project (CMIP). The fifth phase of that project (CMIP5) has been used over the past decade in multiple hydrological studies to assess the impacts of climate change on streamflow. The more recent sixth phase (CMIP6) has started to generate projections, which brings the following question: is it necessary to update the hydrological impact studies performed using CMIP5 with the new CMIP6 models? To answer this question, a comparison between CMIP5 and CMIP6 using 3,107 catchments over North America was conducted. Results show that there is less spread in temperature and precipitation projections for CMIP6. This translates into a smaller spread of future mean, high and low flow values, except for mountainous areas. Overall, we assess that using the CMIP6 data set would provide a more concerted range of future climate projections, leading to more confident hydrological impact studies. Key Points: A comparison of hydrological impacts using Coupled Model Intercomparison Project version 5 (CMIP5) and Coupled Model Intercomparison Project Phase 6 (CMIP6) ensembles is performed over 3,107 catchments in North AmericaThe CMIP6 ensembles provide a narrower band of uncertainty for hydrological indicators in the futureIt is recommended to update hydrological impact studies performed using CMIP5 with the CMIP6 ensemble [ABSTRACT FROM AUTHOR]

Anthropogenic activities such as damming have caused an alteration in the natural flow regime in many rivers around the world. In this study, the role of constructing a hydroelectric dam on the natural flow regime of the Kor River, Iran, is investigated. Nine different methods, which fall into the category of hydrological methods, were used to determine the environmental water requirement (EWR) of the Kor River. In addition, two indices are introduced to evaluate the environmental flow allocation in anthropogenic rivers. The results show that although the supply of environmental flow in some months is in relatively acceptable conditions on average, there is a deficiency in the allocation of EWR in the range of 1.92–30.2% in the spawning period of the dominant fish species. The proposed indicators can provide a general picture of the status of environmental flow allocation in rivers where little ecological data is available and the hydrological regime has changed due to human activities, particularly in rivers with hydropower plants. Moreover, after the construction of the dam, no major floods have occurred in the river, which has led to the loss of the morpho-ecological balance in the river and disruption of the natural state of habitats. Therefore, the negative impact of dam construction on the environmental conditions of the river should be considered in the active management of the dam outlets. [ABSTRACT FROM AUTHOR]

Little Ruaha catchment has been recognized for its potential to support multi-projects including irrigated schemes, urban water supply and providing significant inflow to Mtera reservoir for hydropower generation and ultimately Julius Nyerere Hydropower Plant (JNHPP). Despite the potential, the catchment has experienced declining flows in the recent years. This study assessed the likely changes in streamflow due to future climate change in the Little Ruaha catchment for the period 2025-2060. General Circulation Model (GCM) datasets from ACCESS1.0, CNRM-CM5 and BCC-CSM1 models and RCP4.5 and RCP8.5 greenhouse gas concentration scenarios were selected as the representative scenarios. Impact of climate change on stream flows was assessed using the calibrated NAM hydrological model. The impact assessment results show that under the climate change scenario (2025–2060), the monthly maximum and minimum temperatures will increase in the range of 0.8 °C to 2 °C for both RCP4.5 and RCP8.5 scenarios. For the case of rainfall, average annual rainfall is expected to increase by about 10% compared to the baseline. However, the inter-annual variability of rainfall for the period between 2025 and 2060 shows the decreasing trend for RCP 8.5. The simulation results show that streamflow will decrease by about 30% and 6% for RCP4.5 and RCP8.5, respectively. [ABSTRACT FROM AUTHOR]

Climate change is likely to manifest in river flow changes across the globe, which could have wide‐ranging consequences for society and the natural environment. A number of previous studies used the UK Climate Projections 2009 (UKCP09) to investigate the potential impacts on river flows in Britain, but these projections were recently updated by the release of UKCP18, thus there is a need to update flow studies. Here, the UKCP18 Regional (12 km) projections are applied using a national‐scale grid‐based hydrological model, to investigate potential future changes in seasonal mean river flows across Great Britain. Analysis of hydrological model performance using baseline climate model data (1980–2010) shows relatively good agreement with use of observation‐based data, particularly after application of a monthly precipitation bias‐correction. Analysis of seasonal mean flow changes for two future time‐slices (2020–2050 and 2050–2080) suggests large decreases in summer flows across the country (median −45% by 2050–2080), but possible increases in winter flows (median 9% by 2050–2080), especially in the north and west. Information on the potential range of flow changes using the latest projections is necessary to develop appropriate adaptation strategies, and comparisons with previous projections can help update existing plans, although such comparisons are often not straightforward. [ABSTRACT FROM AUTHOR]

The impacts of climate change on future river flows are a growing concern. Typically, impacts are simulated by driving hydrological models with climate model ensemble data. The U.K. Climate Projections 2009 (UKCP09) provided probabilistic projections, enabling a risk‐based approach to decision‐making under climate change. Recently, an update was released—UKCP18—so there is a need for information on how impacts may differ. The probabilistic projections from UKCP18 and UKCP09 are here applied using the change factor method with catchment‐based hydrological modelling for 10 catchments across England. Projections of changes in median, mean, high, and low flows are made for the 2050s, using the A1B emissions scenario from UKCP09 and UKCP18 as well as the RCP4.5 and RCP8.5 emissions scenarios from UCKP18. The results show that, in all catchments for all flow measures, the central estimate of change under UKCP18 is similar to that from UKCP09 (A1B emissions). However, the probabilistic uncertainty ranges from UKCP18 are, in all cases, greater than from UKCP09, despite UKCP18 having a smaller ensemble size than UKCP09. Although there are differences between the central estimates of change using UKCP18 RCP4.5, RCP8.5 and A1B emissions, there is considerable overlap in the uncertainty ranges. The results suggest that existing assessments of hydrological impacts remain relevant, though it will be necessary to evaluate sensitive decisions using the latest projections. The analysis will aid development of advice to users of current guidance based on UKCP09 and help make decisions about the prioritization of further hydrological impacts work using UKCP18, which should also apply other products from UKCP18 like the 12‐km regional data. [ABSTRACT FROM AUTHOR]

Precipitation extremes play a key role in flooding risks over the Huaihe River Basin, which is important to understand their hydrological impacts. Based on observed daily precipitation and streamflow data from 1958 to 2009, eight precipitation indices and three streamflow indices were calculated for the study of hydrological impacts of precipitation extremes. The results indicate that the wet condition intensified in the summer wet season and the drought condition was getting worse in the autumn dry season in the later years of the past 50 years. The river basin had experienced higher heavy rainfall-related flooding risks in summer and more severe drought in autumn in the later of the period. The extreme precipitation events or consecutive heavy rain day events led to the substantial increases in streamflow extremes, which are the main causes of frequent floods in the Huaihe River Basin. The large inter-annual variation of precipitation anomalies in the upper and central Huaihe River Basin are the major contributor for the regional frequent floods and droughts. [ABSTRACT FROM AUTHOR]

Using updated hydrological datasets from three stations, including Cuntan, Yichang and Hankou, covering the period of January 1992-December 2008, the influence of Three Gorges Dam (TGD) on streamflow and sediment load of the Yangtze River was investigated. Results indicated that TGD did not seem to exert a significant influence on streamflow occurring at three stations and changes in streamflow can be mainly attributed to streamflows of tributaries. However, a sharp decrease in the sediment load after the impoundment of TGD was observed. Clear water after the impoundment caused erosion of riverbed and resulted in more sediment at the Hankou station than at the Yichang station. No distinct changes in the annual and monthly maximum sediment loads were observed before and after the impoundment. Therefore, annual and monthly maximum sediment load changes should be subjected mainly to river hydraulics. This study has practical relevance for understanding the influence of large hydraulic structures on the hydrological processes of large rivers. [ABSTRACT FROM AUTHOR]

Small dams represent an important local-scale resource designed to increase water supply reliability in many parts of the world where hydrological variability is high. There is evidence that the number of farm dams has increased substantially over the last few decades. These developments can have a substantial impact on downstream flow volumes and patterns, water use and ecological functioning. The study reports on the application of a hydrological modelling approach to investigate the uncertainty associated with simulating the impacts of farm dams in several South African catchments. The focus of the study is on sensitivity analysis and the limitations of the data that would be typically available for water resources assessments. The uncertainty mainly arises from the methods and information that are available to estimate the dam properties and the water use from the dams. The impacts are not only related to the number and size of dams, but also the extent to which they are used for water supply as well as the nature of the climate and the natural hydrological regimes. The biggest source of uncertainty in South Africa appears to be associated with a lack of reliable information on volumes and patterns of water abstraction from the dams. Citation Hughes, D. A. & Mantel, S. K. (2010) Estimating the uncertainty in simulating the impacts of small farm dams on streamflow regimes in South Africa. Hydrol. Sci. J. 55(4), 578-592. [ABSTRACT FROM AUTHOR]

Climate change affects natural systems, leading to increased acceleration of global water cycle and substantial impacts on the productivity of tropical rivers and the several ecosystem functions they provide. However, the anticipated impacts of climate change in terms of frequency and intensity of extreme events (e.g., droughts and floods) on hydrological systems across regions could be substantially different. This study therefore aims to assess the impacts of climate change on the streamflow of a large river basin located in central Australia (Cooper Creek-Bulloo River Basin). Modified version of the hydrological model Hydrologiska Byråns Vattenbalansavdelning (HBV) was used in this study to generate daily streamflow. This model was first calibrated (2001–2010) and then validated for two independent periods (1993–1997 and 2011–2015). The model depicted a good performance in simulating observed streamflow. Climate projection data from multiple general circulation models (ACCESS1.0, CanESM2, CESM1-CAM5, CNRM-CM5, GFDL-ESM2M, HadGEM2-CC, MIROC5, NorESM1-M, ACCESS1-0, ACCESS1-3, CCSM4, CNRM-CM5, CSIRO-Mk3.6, GFDL-CM3, GFDL-ESM2M, HadGEM2, MIROC5, MPI-ESM-LR, and NorESM1-M) in various forms (raw, statistically downscaled, dynamically downscaled, and bias adjusted) were considered in this study. Results showed that three high resolution dynamically downscaled and bias adjusted models (ACCESS1-3, CNRM-CM5, and MPI-ESM-LR) from Terrestrial Ecosystem Research Network (TERN) dataset (v1.0.2) have better performance than other models considered, that is, in terms of capturing observed precipitation over the basin. Future climate projections of ensemble of these three models forced with RCP 4.5 and RCP 8.5 emission scenarios were then used to generate streamflow for 2050s (2040–2069) and 2080s (2070–2099). Results of the study indicated that mean annual precipitation was projected to decrease by up to −8% in 2050s and temperature was projected to increase by up to 4.66 °C in 2080s under the average and extreme emission scenarios, respectively. Mean annual, mean seasonal (December–February, March–May, June–August, September–November), and mean monthly streamflow were projected to decrease under different emission scenarios in 2050s and 2080s. These results indicate decreased water availability in the future as well as water cycle intensification. These changes in streamflow might have impacts on agriculture, natural ecosystem, and could lead to water restrictions. The outcome of this study can directly feed into frameworks for sustainable management of water resources and support adaptation strategies that rely on science and policy to improve water resources allocation in the region. [ABSTRACT FROM AUTHOR]

• Applied grid-based hydrological model and latest UK global and regional projections. • Clustering applied to highlight typical changes in high and low flows. • Generally decreases in low flows and increases in high flows to end of century. • Significant variation in results for different regions of Great Britain. Changes in river flows, especially extreme high and low flows, could be a particularly important impact of climate change in terms of the hazard to people and the environment. Here, a national-scale grid-based hydrological model is applied, with ensembles of global and regional climate projections from UK Climate Projections 2018, to investigate the potential future changes in both floods and droughts in a consistent way across the whole of Great Britain (gauged and ungauged locations). Using hydrological model outputs for the climate projection ensembles, a clustering technique is applied to highlight 'typical' sets of changes in individual indicators of floods or droughts, but also to look at concurrent changes in pairs of flood and drought indicators. The results for regions across the country generally indicate decreases in low flows combined with increases in high flows up to the end of the 21st century. There is significant variation in results for different regions, with those to the south/east tending to show greater decreases in low flows and a greater range of uncertainty in the projections for high flows. A grid-based cluster analysis also shows potentially important variation within regions, likely related to catchment properties. The potential future changes in derived climate hazards, such as the frequency or severity of floods and droughts, is a key piece of information required for adaptation planning, and the consideration of potential concurrent changes in a range of related hazards/risks, rather than viewing each in isolation, could be vital to avoid maladaptation. [ABSTRACT FROM AUTHOR]