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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]

Studying climate change's impact on runoff and drought is crucial for sustainable society and ecosystems. The extent of drought evolution and how droughts would affect society and the environment are not sufficiently considered in Senegal. This study assesses hydrological impacts and future drought using three global climate models (ACCESS-ESM1-5, BCC-CSM2-MR, and MRI-ESM2-0) as part of the Coupled Model Intercomparison Project (CMIP6) in the Aga-Foua-Djilas Basin. To this end, the hydrological impacts of climate change over 20-year periods (2021-2040; 2041-2060; 2061-2080; 2081-2100) at a resolution of 2.5 under four emission scenarios (SSP 126; 245; 370; 585), were investigated, and the drought characteristics are shown below, the SSP 245 and 585 scenarios over the 2021-2100 period. The results highlight a decrease in runoff potential given the drop in rainfall, which fell from 25.2 mm over the 2021-2040 period and under SSP 126 to 2.4 mm towards the end of the century (2081-2100) and under the SSP 585 scenario, changes in the standardized precipitation index (SPI) and the standardized precipitation and evapotranspiration index (SPEI) were first compared, and the SPEI showed larger changes due to its inclusion of temperature effects. The drought zone in the basin is likely to increase at the end of the 21st century with values approaching 80% for SPI and 90% for SPEI under the SSP 245 and SSP 585 scenarios if drought mitigation and adaptation mechanisms are inadequate. The results provide important guidance for improving the identification of causes, minimizing impacts, and building resilience to droughts in Senegal.

Large flood events occurrence such as the 18 March 2019 flood event in the city of Gonbad in Golestan Province has been often associated with socioeconomic and ecologic damages. The aim of this research is to simulate flood hydrograph using the HEC-HMS hydrological model and to evaluate model performance at the Arazkuseh Watershed outlet, located in the vicinity of Gonbad, and also for the upstream tributaries namely the Minodasht and the Nodeh Khandooz Watersheds. The HECHMS model was run by applying the SCS-Curve Number, the SCS-Unit Hydrograph, and the Muskingum-Cunge methods. The parameters of CN, initial abstraction, lag time, and the Manning's roughness coefficient were calibrated for the river gauge stations. The averaged calibrated parameters were used to validate the model at the gauge stations. The sensitivity analysis indicates that CN has the greatest influence on the model performance. The shapes of the simulated hydrographs in the validation stage show that the model underestimates the peak flows for the Arazkuseh Station. Whereas, the statistical indices of NSE, R2 and KGE for the validated hydrographs at the Arazkuseh Station were 0.81, 0.89 and 0.67, for the Nodeh Station were 0.85, 0.91 and 0.74, and for the Lazoreh Station identified as 0.62, 0.72 and 0.61, respectively. The analysis indicates the acceptable performance of the model. Considering the performance of the HEC-HMS model for the Arazkuseh Watershed and its upstream tributaries, the model can be used to predict the hydrological impacts of applying flood risk reduction scenarios in the upstream watersheds of Gonbad. [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. HIGHLIGHTS GCMs in CMIP6 under SSP5-85 show more increase in temperature and precipitation than those in CMIP5 under RCP8.5 in China.; GCMs in CMIP6 and CMIP5 show similar increases in mean and peak streamflow.; GCMs in CMIP6 show less inter-model variability for mean and peak flow in southern and northeastern China, but more in central China.;

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]

This study provides evidence for the multiscale nature of atmospheric rivers (ARs) by differentiating them based on high‐ (HF) and low‐frequency (LF) moisture transports. The HF‐dominant ARs exhibit migratory behavior as they are typically accompanied by extratropical cyclones. Their spatial distribution is seasonally synchronized with midlatitude storm activity. On the other hand, the LF‐dominant ARs stay in place as they are associated with quasi‐stationary circulation. They prevail in the subtropical monsoon regions in the summer hemisphere. The ARs are often jointly affected by HF and LF processes. Such intermediate ARs are frequently observed along the poleward boundary of subtropical highs. The latter two AR types are locally more persistent than the HF‐dominant ARs, implying the importance of LF dynamics in long‐lasting AR impacts. We suggest that multiscale analysis of ARs will offer valuable insights into their diversity and hydrological impacts. Plain Language Summary: Atmospheric rivers (ARs) are narrow corridors of intense water vapor transport often concurrent with extratropical cyclones. Through case studies and climatological analyses, however, this study shows that ARs are not only associated with high‐frequency (HF) moisture transport such as those driven by extratropical cyclones but also related to low‐frequency (LF) moisture transport driven by quasi‐stationary circulation. The HF‐dominant ARs are observed along the midlatitude storm tracks, while the LF‐dominant ARs appear in summer monsoon regions in low latitudes. There are also a non‐negligible number of ARs jointly influenced by HF and LF processes, particularly along the poleward flank of subtropical highs. Noticeably, ARs strongly influenced by LF processes have a longer local duration than others. It implies that LF dynamics, which have received relatively less attention, need to be incorporated for a better understanding and prediction of the long‐lasting AR impacts. This study highlights that ARs have diverse characteristics by HF and LF processes. Taking their multiscale nature into account thus will be helpful when delineating the dynamics and hydrological impacts of ARs. Key Points: High‐frequency moisture transport related to atmospheric rivers (ARs) is synchronized with transient storm activity in midlatitudesThe ARs are also fueled by low‐frequency (LF) moisture transport along the boundary of subtropical highs and in the summer monsoon regionsThe LF moisture transport plays a critical role in locally long‐duration AR events, increasing the risk of high‐rank AR events [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]

Coastal flooding induced by storm surges and heavy rainfall is one of the most frequent climate-related natural hazards along the southeast Australian coast, home to more than 55% of the Australian population. Flooding in this densely populated region is a threat to public safety, coastal infrastructure, ecological systems and the economy. Although climate change is expected to cause an increase in major floods, few studies have quantified the potential changes in flood severity. This study quantifies the changes in flood peak discharge flowing to the Georges River estuary in Australia due to climate-change. An event-based hydrological model, Watershed Bounded Network Model (WBNM), was used to predict flood discharge. This hydrological model was forced by rainfall data obtained from the New South Wales and Australian Capital Territory Regional Climate Modelling Project version 1.5 (NARCliM1.5) for both historical and the Representative Concentration Pathway 8.5 (RCP8.5) conditions. Model calibration for the floods of March 1978 and March 2022 achieved a general agreement between the predicted and observed hydrographs, with an overall average 14% error in the peak values, further demonstrating that the modelling approach is generally reliable in projections of flood severity. Using high resolution climate model projections, the present study observed an increase of 22% in the model ensemble average from historical conditions to the RCP8.5 scenario for the 20-year average recurrence interval (ARI) 24 h extreme rainfall. This heightened extreme rainfall consequently resulted in the changes in flood discharge with an average rise of 55%. This study provides specific assessment of climate-generated risks for densely-populated regions, especially those on Australian east coast. Global studies have suggested that extreme precipitation events will increase under climate change. This study supports and enhances these assertions by using high resolution downscaling to quantify the specific changes within a large catchment.

Abstract This study provides evidence for the multiscale nature of atmospheric rivers (ARs) by differentiating them based on high‐ (HF) and low‐frequency (LF) moisture transports. The HF‐dominant ARs exhibit migratory behavior as they are typically accompanied by extratropical cyclones. Their spatial distribution is seasonally synchronized with midlatitude storm activity. On the other hand, the LF‐dominant ARs stay in place as they are associated with quasi‐stationary circulation. They prevail in the subtropical monsoon regions in the summer hemisphere. The ARs are often jointly affected by HF and LF processes. Such intermediate ARs are frequently observed along the poleward boundary of subtropical highs. The latter two AR types are locally more persistent than the HF‐dominant ARs, implying the importance of LF dynamics in long‐lasting AR impacts. We suggest that multiscale analysis of ARs will offer valuable insights into their diversity and hydrological impacts.

Appropriate adaptation planning is contingent upon information about the potential future impacts of climate change, and hydrological impact assessments are of particular importance. The UKSCAPE-G2G datasets were produced, as part of the NERC UK-SCAPE programme, to contribute to this information requirement. They use the Grid-to-Grid (G2G) national-scale hydrological model configured for both Great Britain and Northern Ireland (and the parts of the Republic of Ireland that drain to rivers in NI). Six separate datasets are provided, for two sets of driving data -- one observation-based (1980-2011) and one climate projection-based (1980-2080) -- for both river flows and soil moisture on 1 km x 1 km grids across GB and NI. The river flow datasets include grids of monthly mean flow, annual maxima of daily mean flow, and annual minima of 7-day mean flow (m³s-1). The soil moisture datasets are grids of monthly mean soil moisture content (m water/m soil), which should be interpreted as depth-integrated values for the whole soil column. The climate projection-based datasets are produced using data from the 12-member 12km regional climate model ensemble of the latest UK climate projections (UKCP18), which uses RCP8.5 emissions. The production of the datasets is described, along with details of the file format, and how the data should be used. Example maps are provided, as well as simple UK-wide analyses of the various outputs. These suggest potential future decreases in summer flows, annual minimum 7-day flows, and summer/autumn soil moisture, along with possible future increases in winter flows and annual maximum flows. References are given for published papers providing more detailed spatial analyses, and some further potential uses of the data are suggested. [ABSTRACT FROM AUTHOR]

There is a high demand for openly accessible hydroclimatic data for climate change adaptation. Different data sources are available, however, discrepancy between the data can confuse users and should be evaluated and explained. This study, investigates how climate impact indicators (CIIs) developed for global users in the Copernicus Climate Change Service (C3S) are comparable to other openly available global data for water and climate. We found that, for temperature, datasets are comparable and climate impacts are thus considered robust. Important discrepancies arise in the precipitation indicators. Of the CIIs analysed in this study, the hydrological CIIs differ most so they should be used with care. These differences are probably caused by model uncertainty (hydrological model, HM; global climate model, GCM), ensemble size and model selection. A HM ensemble, as well as a GCM ensemble combined with improved model performance and selection criteria, should be used to ensure high-quality global water and climate services. [ABSTRACT FROM AUTHOR]

Development of robust reclamation designs would require understanding the relative effects of climate change on the water budget of reclaimed Athabasca oil sands landforms (Alberta, Canada). A surplus water budget is critical to sustain pit lakes and periodically freshen localized surface water ponds within the closure landscape. In this study, four hypothetical future climate scenarios were developed from statistically downscaled RCP2.6 and RCP8.5 climate projections and used in a hydrological model to investigate the potential effects of climate change on the water budget of an in-pit reclaimed oil sands mine landform. The four scenarios allowed the assessment of climate change effects for endpoints that bracket a range of future climate conditions on the water balance of the landform. Surface water and groundwater flow and chloride transport were simulated for the 2024–2100 period using daily climate forcing and the results were compared with equivalent responses under historical climate (1944–2020). The results suggest that the hydrological behavior under historical and RCP2.6 scenarios is similar. The climatic water deficit (potential evapotranspiration exceeding precipitation) will rise significantly under the RCP8.5 scenario. However, the modeling suggests that the water budget of the landform will not be too different from the early 21st century prolonged dry climate period. The chloride released from the landform under the different projected and historical climate scenarios also remained similar. Although evapotranspiration increases and leads to relatively drier conditions, a modest increase in precipitation helps maintain a surplus water budget in most years. The results demonstrate that incorporating future climate projections into water balance analyses is crucial to understand the potential reductions in runoff depths.

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.

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]

Aim: We studied the distribution of freshwater macroinvertebrate taxa and traits to distinguish ecological gradients among the mining‐controlled and natural headwaters, and rural and urban economic activity influences. Location: In 2016's dry season, macroinvertebrate samples were collected at 40 locations in the Mashcon watershed, northern Peruvian Andes. Six locations were in the headwaters directly influenced by mining, eight near‐pristine tributary headwaters, 14 agricultural locations at midstream and 12 urban locations downstream. Methods: Eight traits (five biological and three ecological) were selected according to data availability, and modalities scores were assigned using the weighted and the dominant‐trait approaches. The traits relative abundances and abiotic conditions were compared among watershed sections. The ecological interpretability of the ungrouped data was verified with a distance‐based redundancy analysis. Results: The high‐altitude mining section had fewer taxa types and abundance, and distinct body forms distributions and prevalent body sizes in macroinvertebrate communities, relatable to the control of the mining headwaters. Physiological and ecological traits (respiration, mobility and attachment, food sources, feeding habits, saprobity and pH preferenda) differed among traits quantification approaches and were less informative at high altitudes. The ecological conditions from the near‐pristine tributaries recovered in the vegetated midstream section, to again be affected in the downstream urban section. Main Conclusions: Our results suggest the presence of ecological impairment despite the excellent physicochemical quality of the water discharged by the mine. The obtainment of autecological information at a higher taxonomic resolution, e.g. for ubiquitous taxa like Acari and Chironomidae, would be needed to advance the freshwater quality assessment of ecologically and hydrogeochemically complex Andean mining ecosystems. [ABSTRACT FROM AUTHOR]

Assessing the potential impacts of climate change on river flows is critically important for adaptation. Data from global or nested regional climate models (GCMs/RCMs) are frequently used to drive hydrological models, but now there are also very high-resolution convection-permitting models (CPMs). Here, data from the first CPM climate ensemble for the UK, along with the RCM ensemble within which the CPM is nested, are used to drive a grid-based hydrological model. The performance for simulating baseline (1981–2000) river flows is compared between the RCM and the CPM, and the projections of future changes in seasonal mean flows and peak flows are compared across Britain (1981–2000 to 2061–2080). The baseline performance assessment shows that (before bias correction) the CPM generally performs better than the RCM, and bias correction of precipitation makes both the RCM and CPM perform more similarly to use of observation-based driving data. The analysis of future changes in flows shows that the CPM almost always gives higher flow changes than the RCM. If reliable, these differences in flow projections suggest that adaptation planning for high flows based on use of regional data may be insufficient, although planning for low flows may be slightly over-cautious. However, the availability of CPM data only for one RCM/GCM is a limitation for use in adaptation as it under-samples the uncertainty range. There are significant challenges to the wider application of CPM ensembles, including the high computational and data storage demands. [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]

The West Flowing River Basins from Tadri to Kanyakumari (WFRB-2), India, is a highly complex hydrological system witnessing hydrological extremes frequently. In this study, the impacts of climate/Land Use Land Cover (LULC) changes on hydrology in WFRB-2 are investigated on a 0.25° spatial scale for a historic (1979–2018) time period. Six major river basins are chosen in the upper, middle and lower regions of WFRB-2 and the variable infiltration capacity (VIC) model is calibrated using SCE-UA (Shuffle Complex Evolution) algorithm. The linear trend analysis showed a significant increase in premonsoon/monsoon rainfall in the lower region and a 13% increase in the percentage of very wet years, while dry years completely disappeared in the recent past. Sensitivity analysis shows that annual mean surface runoff (SR) increases by 125 mm and evapotranspiration (ET) decreases by 562 mm when a fully forested grid was transformed into a fully built-up grid. Similarly, sensitivity towards rainfall alone is showing an increase of SR and ET by 54 mm (6%) and 64 mm (6%) respectively. Overall impact results in a reduction in the annual mean total runoff by 48 mm in the upper and 100 mm in the middle and a rise of 53 mm in the lower regions. This shows that in the lower region, with an increase in precipitation coupled with increasing urbanization, there is a possibility of greater magnitude flood peaks. This study is useful to understand the complex hydrological impacts due to climate/LULC changes for management decisions on a regional scale. [ABSTRACT FROM AUTHOR]

It is imperative to understand the interconnectedness of water use and hydrological impacts for water policy design underlying varying hydrological conditions across space and over time. However, such analysis remains difficult, constrained by the lack of appropriate modeling tools that fully integrate water policies, water use, and hydrological processes with high spatiotemporal resolutions. To address this challenge, this study proposes a distributed policy design scheme featuring spatially variable and temporally dynamic policies for conjunctive surface water‐groundwater management in large river basins. A fully integrated modeling framework is developed to tightly couple (a) an agent‐based model for farmers' water use under distributed water policies and (b) a physically based hydrological model for surface water‐groundwater processes. The modeling framework is applied to the Heihe River Basin to assess water use and hydrological impacts under distributed water policies. By using the distributed policy scheme to adjust a water policy (e.g., groundwater tax) across space and over time, we found that hydrological outcomes can be improved without adversely reducing agricultural water supply. For example, by shifting the implementation of a high groundwater tax from dry to wet years, a rise of the water table by 0.28 m (0.03–0.95 m across different irrigation districts) can be achieved while the total water supply is maintained at a similar level. Furthermore, hydrological externality effects among nearby districts can be explicitly identified and quantified based on assessments of spatially varying water policies. This study highlights the need for water policy design to consider spatiotemporal variations in the physical hydrological system. Key Points: This study proposes and evaluates a distributed policy design scheme featuring spatially variable and temporally dynamic water policiesIt is possible to mitigate aquifer depletion without reducing the total water supply by adjusting water policies between dry and wet yearsHydrological externality effects among nearby districts are explicitly quantified by assessing spatially varying water management policies [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]

Study region: Northern Ireland (NI), and sub-catchments in the Republic of Ireland that drain to NI rivers, Study focus: Information on the potential future impacts of climate change on river flows is necessary for adaptation planning. There have been many such studies for Great Britain, but fewer for NI. Here, a grid-based hydrological model is configured for NI, and used to investigate changes in seasonal mean, extreme high and extreme low flows. New Hydrological Insights: When driven by observed climate data, the model shows good performance for a wide range of catchments, particularly where artificial influences are limited. When driven by ensemble data from the UKCP18 Regional (12 km) projections, model performance for the baseline period (1981–2010) is similar to that using observed data, especially when using a simple precipitation bias-correction. Model projections for a future time-slice (2051–2080) generally suggest decreases in spring–autumn mean flows, especially in summer (median −44%), but possible increases in winter mean flows (median 9%), with some variation between ensemble members, particularly in winter when some show large increases to the west. Consistent with this are large projected reductions in 10-year return period low flows everywhere (median −45%), and large increases in 10-year return period high flows for some locations and ensemble members (median 16%). Future applications could include expanding the range of climate data applied.

Study region: Catchments: Wölzerbach, Raab; Styria; Austria. Study focus: The study was carried out to investigate the fitness for purpose of the high-resolution Austrian National Climate datasets (ÖKS15) in hydrological applications. Provided as a standard for climate impact studies in Austria in 2016, the potential of the ÖKS15 data for hydrological impact studies has not previously been assessed. To fill this research gap, we evaluated the ÖKS15 datasets for the recent climate period (1961–2005) to determine their suitability for hydrological analyses. Hydro-meteorological indicators of the ÖKS15 datasets, as well as of the data used to obtain them by bias correcting and downscaling the EURO-CORDEX models, were assessed at different spatio-temporal scales and compared to the raw EURO-CORDEX data. The hydrological model WaSiM was driven with the different datasets to generate the hydrological simulations used for validation against long-term observations. New hydrological insights for the region: Hydro-meteorological indicators obtained from ÖKS15 models are comparable to observations and associated with less uncertainty than the raw EURO-CORDEX data. We thus consider the ÖKS15 dataset basically appropriate for hydrological impact studies. However, despite bias correction, some biases in the ÖKS15 data remain and differences in timing, magnitude and spatial characteristics lead to deviations in hydrological indicators at different scales.

This study aimed to assess the hydrological and erosive effects of different levels of the fire severity in the drainage basin of the Trionto River (Calabria, southern Italy), which was partially burned by intense fires during the summer 2017. The analysis focused on the identification of wildfire areas using a supervised classification of remote sensing images with the minimum distance algorithm. The level of severity of each fire was then discriminated based on a procedure proposed by the U.S. Department of Agriculture and adapted to the study area. To evaluate how wildfire occurrence affects the hydrological behaviour at the basin scale, the SCS-Curve Number model was used to document pre- and post-fire conditions in relation with the level of fire severity. Finally, the influence on erosion was analysed for analogous conditions at the basin scale using the RUSLE equation. The effects on hydrological balance and soil loss were evaluated by comparing the pre-fire value with three different post-fire scenarios: (a) different levels of severity on the surface covered by the fire (real case); (b) maximum level of severity on the surface covered by the fire; (c) total loss of the canopy and formation of a hydrophobic layer on the surface soil. The results confirmed that the level of severity of the forest fires, combined with climatic factors, morphological conditions, and the pedological characteristics of the basin, significantly influence changes to the hydrology and rates of erosion. Moreover, these impacts proved to be mainly dependent on the consequent, often notable, heterogeneity in the spatial distribution of burned areas with different severity.

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]

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 The quantification of climate change impacts on hydrology is subjected to multiple uncertainty sources. Large ensembles of hydrological simulations based on multimodel ensembles (MMEs) have been commonly applied to represent overall uncertainty of hydrological impacts. However, as increasing numbers of global climate models (GCMs) are being developed, how many GCMs in MMEs are sufficient to characterize overall uncertainty is not clear. Therefore, this study investigates the influences of GCM quantity on quantifying overall uncertainty and uncertainty contributions of multiple sources in hydrological impacts. Large ensembles of hydrological simulations are obtained through the permutation of 3 greenhouse gas emission scenarios, 22 GCMs, 6 downscaling techniques, 5 hydrological models (HMs), and 5 sets of HM parameters, which enables to decompose uncertainty components using analysis of variance. The influences of GCM quantity are investigated by repeatedly conducting uncertainty decomposition for hydrological simulations from subsets with different numbers of GCMs. The results show that GCMs are the leading uncertainty sources in evaluating changes in annual and peak streamflows, while for changes in low flow, other uncertainty sources except HM parameters also have large contributions to overall uncertainty. Furthermore, on the condition of using no more than five GCMs, there are large possibilities that the overall uncertainty and GCMs' uncertainty contribution are underestimated. Using around 10 GCMs can ensure that the median of different combinations generates similar uncertainty components as the whole ensemble. Therefore, it is recommended to use at least 10 GCMs in studies of climate change impacts on hydrology to thoroughly quantify uncertainty.

This study aims to assess the potential impacts of climate change on hydrometeorological variables and drought characteristics in the Ethiopian Bilate watershed. Climate projections under two Representative Concentration Pathways (RCP4.5 and RCP8.5) were obtained from the Coordinated Regional Downscaling Experiment (CORDEX) Africa for the near future (2021–2050) and far future (2071–2100) periods. The Soil and Water Assessment Tool (SWAT) model was applied to assess changes in watershed hydrology with the CORDEX-Africa data. The Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI), and Reconnaissance Drought Index (RDI) were calculated to identify the characteristics of meteorological, hydrological, and agricultural droughts, respectively. Due to a significant rise in temperature, evapotranspiration will increase by up to 16.8% by the end of the 21st century. Under the RCP8.5 scenario, the annual average rainfall is estimated to decrease by 38.3% in the far future period, inducing a reduction of streamflow of up to 37.5%. Projections in reduced diurnal temperature range might benefit crop growth but suggest elevated heat stress. Probabilities of drought occurrence are expected to be doubled in the far future period, with increased intensities for all three types of droughts. These projected impacts will exacerbate water scarcity and threaten food securities in the study area. The study findings provide forward-looking quantitative information for water management authorities and decision-makers to develop adaptive measures to cope with the changing climate.

Soil moisture, typically defined as the amount of water in the unsaturated soil layer, is a central component of the hydrological cycle. The potential impacts of climate change on soil moisture have been less specifically studied than those on river flows, despite soil moisture deficits/excesses being a factor in a range of natural hazards, as well as having obvious importance for agriculture. Here, 1 km grids of monthly mean soil moisture content are simulated using a national-scale grid-based hydrological model, more typically applied to look at changes in river flows across Britain. A comparison of the soil moisture estimates from an observation-based simulation, with soil moisture deficit data from an operational system developed by the UK Met Office (Meteorological Office Rainfall and Evaporation Calculation System; MORECS), shows relatively good correspondence in soil drying and wetting dates, and in the month when soils are driest. The UK Climate Projections 2018 Regional projections are then used to drive the hydrological model, to investigate changes in occurrence of indicative soil moisture extremes and changes in typical wetting and drying dates of soils across the country. Analyses comparing baseline (December 1981–November 2011) and future (December 2050–November 2080) time-slices suggest large increases in the spatial occurrence of low soil moisture levels, along with later soil wetting dates, although changes to soil drying dates are less clear. Such information on potential future changes in soil moisture is important to enable the development of appropriate adaptation strategies for a range of sectors vulnerable to soil moisture levels.

This study focuses on quantifying future anthropogenic changes in surface runoff associated with extreme precipitation in California's Sierra Nevada. The method involves driving a land surface model with output from a high resolution regional atmospheric simulation of the most extreme atmospheric rivers (ARs). AR events were selected from an ensemble of global climate model simulations of historical and late 21st century climate under the "high‐emission" RCP8.5 scenario. Average precipitation during the future ARs increases by ~25% but a much lower proportion falls as snow. The resulting future runoff increase is dramatic—nearly 50%, reflecting both the precipitation increase and simultaneous conversion of snow to rain. The "double whammy" impact on runoff is largest in the 2,000–2,500 m elevation band, where the snowfall loss and precipitation increase are both especially large. This huge increase in runoff during the most extreme AR events could present major flood control challenges for the region. Key Points: Atmospheric river storm events will become more extreme and result in intensified surface runoff along with reduced snowfallThe "double whammy" impact on runoff is dramatic in the future—nearly 50% on average, easily double and higher in certain locationsThe disproportionately enlarged runoff during extremes could raise significant challenges for water resource management and flood control [ABSTRACT FROM AUTHOR]

The quantification of climate change impacts on hydrology is subjected to multiple uncertainty sources. Large ensembles of hydrological simulations based on multimodel ensembles (MMEs) have been commonly applied to represent overall uncertainty of hydrological impacts. However, as increasing numbers of global climate models (GCMs) are being developed, how many GCMs in MMEs are sufficient to characterize overall uncertainty is not clear. Therefore, this study investigates the influences of GCM quantity on quantifying overall uncertainty and uncertainty contributions of multiple sources in hydrological impacts. Large ensembles of hydrological simulations are obtained through the permutation of 3 greenhouse gas emission scenarios, 22 GCMs, 6 downscaling techniques, 5 hydrological models (HMs), and 5 sets of HM parameters, which enables to decompose uncertainty components using analysis of variance. The influences of GCM quantity are investigated by repeatedly conducting uncertainty decomposition for hydrological simulations from subsets with different numbers of GCMs. The results show that GCMs are the leading uncertainty sources in evaluating changes in annual and peak streamflows, while for changes in low flow, other uncertainty sources except HM parameters also have large contributions to overall uncertainty. Furthermore, on the condition of using no more than five GCMs, there are large possibilities that the overall uncertainty and GCMs' uncertainty contribution are underestimated. Using around 10 GCMs can ensure that the median of different combinations generates similar uncertainty components as the whole ensemble. Therefore, it is recommended to use at least 10 GCMs in studies of climate change impacts on hydrology to thoroughly quantify uncertainty. Plain Language Summary: Simulating hydrological responses to climate change involves multiple steps, which contribute uncertainty. Although climate model simulations are often found to be one of the major sources of uncertainty, how many simulations are needed to thoroughly estimate the uncertainty of hydrological responses is still not clear. Facing the growing number of climate simulations, using all of them will also pose a large computational burden in studying hydrological impacts of climate change. Therefore, we proposed a framework to evaluate how the numbers of climate simulations affect the quantification of uncertainty. Our results show that using insufficient numbers of global climate models leads to the underestimation of uncertainty. It is recommended to use at least 10 global climate models to adequately consider the uncertainty resulting from climate models. Our findings are helpful in the selection of sufficient climate simulations in simulating hydrological responses under climate change. Key Points: A framework to quantify the uncertainty contribution of GCMs over multiple sources in hydrological impacts of climate change is proposedUsing an insufficient number of GCMs may result in the underestimation of overall uncertainty and GCMs' contribution to uncertaintyIt is recommended to use at least 10 GCMs in studies of hydrological climate change impacts to thoroughly quantify uncertainty [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]

The consequences of climate change on food security in arid and semi-arid regions can be serious. Understanding climate change impacts on water balance is critical to assess future crop performance and develop sustainable adaptation strategies. This paper presents a climate change impact study on the water balance components of an agricultural watershed in the Mediterranean region. The restructured version of the Soil and Water Assessment Tool (SWAT+) model was used to simulate the hydrological components in the Sulcis watershed (Sardinia, Italy) for the baseline period and compared to future climate projections at the end of the 21st century. The model was forced using data from two Regional Climate Models under the representative concentration pathways RCP4.5 and RCP8.5 scenarios developed at a high resolution over the European domain. River discharge data were used to calibrate and validate the SWAT+ model for the baseline period, while the future hydrological response was evaluated for the mid-century (2006–2050) and late-century (2051–2098). The model simulations indicated a future increase in temperature, decrease in precipitation, and consequently increase in potential evapotranspiration in both RCP scenarios. Results show that these changes will significantly decrease water yield, surface runoff, groundwater recharge, and baseflow. These results highlight how hydrological components alteration by climate change can benefit from modelling high-resolution future scenarios that are useful for planning mitigation measures in agricultural semi-arid Mediterranean regions.

Regional climate model (RCM) results could not be duly represented by the IPCC 2013 Report, focusing mostly on global climate models (GCM). The aim of our study is to provide a literature insight into these types of results, based on the recent Report by the EEA (2017). After a brief comparison of the GCMs and RCMs, averages of short- and long-term projections of temperature and precipitation changes are provided. Hydrological changes are represented by run-off, mountain glaciers and snow mass. These and other, non-hydrological impacts are also listed from the Report. This short review, delimited by the length, page size and colouring of the hardcopy, is finishing by the experienced destruction caused by the weather extremes over Europe. The original sources, together with the EEA quotations are referred.

Approximately 70% of all the electric energy produced in Brazil comes from hydropower plants. In this context, the Grande River Basin (GRB) stands out in Brazil. Some studies have been carried out to investigate the impacts of climate change in tropical regions to support water resources’ management and planning. This study aims to project the changes in the runoff that feed the Furnas Hydropower Plant (FHP) reservoir (GRB-Furnas basin), the largest and most important facility in Southeast Brazil. The lavras simulation of hydrology model (LASH) was used to project the impacts on runoff and hydrological droughts over the century in GRB-Furnas. The regional climate models (RCMs) Eta-HadGEM-ES, Eta-MIROC5, and Eta-CanESM2 forced the LASH model from 2007 to 2099, taking the representative concentration pathways (RCPs) 4.5 and 8.5. LASH simulated the runoff adequately for the baseline period (1961–2005) using the RCMs’ outputs. A noticeable reduction in precipitation was identified in the wet season, especially in the 2007–2040 period for RCP4.5 and in the 2071–2099 period for RCP8.5. As a result, a significant reduction in the runoff, mainly in the baseflow, and an increase in droughts’ severity were projected throughout the XXI Century, which may compromise the water security to the FHP reservoir.

A key motivation for managing invasive alien plant (IAP) species is their impacts on streamflows, which, for the wetter half of South Africa, are about 970 m³∙ha−1∙a−1 or 1 444 mill. m³∙a−1 (2.9% of naturalised mean annual runoff), comparable to forest plantations. However, the implications of these reductions for the reliability of yields from large water supply systems are less well known. The impacts on yields from the WCWSS were modelled under three invasion scenarios: ‘Baseline’ invasions; increased invasions by 2045 under ‘No management’; and under ‘Effective control’ (i.e. minimal invasions). Monthly streamflow reductions (SFRs) by invasions were simulated using the Pitman rainfall−runoff catchment model, with taxon-specific mean annual and low-flow SFR factors for dryland (upland) invasions and crop factors for riparian invasions. These streamflow reduction sequences were input into the WCWSS yield model and the model was run in stochastic mode for the three scenarios. The 98% assured total system yields were predicted to be ±580 million m³∙a−1 under ‘Effective control’, compared with ±542 million m³∙a−1 under ‘Baseline’ invasions and ±450 mill. m³∙a−1 in 45 years’ time with ‘No management’. The ‘Baseline’ invasions already reduce the yield by 38 mill. m³∙a−1 (two thirds of the capacity of the Wemmershoek Dam) and, in 45 years’ time with no clearing, the reductions would increase to 130 mill. m³∙a−1 (capacity of the Berg River Dam). Therefore IAP-related SFRs can have significant impacts on the yields of large, complex water supply systems. A key reason for this substantial impact on yields is that all the catchments in the WCWSS are invaded, and the invasions are increasing. Invasions also will cost more to clear in the future. So, the best option for all the water-users in the WCWSS is a combined effort to clear the catchments and protect their least expensive source of water. [ABSTRACT FROM AUTHOR]

Abstract Ensuring water is available for human use usually requires dams and reservoirs that severely affect river ecosystems. Hydrological alteration by river damming represents one of the most prominent human impacts on freshwater ecosystems. This paper presents a methodological approach to assessing the natural patterns of flow variability and hydrological alterations in Mediterranean rivers. The methodology first defines the admissible range of flow variability under a natural flow regime. Then, the methodology measures the environmental impact of flow regulation according to the inferred hydrological alteration and classifies rivers into homogeneous groups according to the magnitude, frequency, duration and seasonality of the impacts. This paper applies the proposed methodology to thirty-three river segments below large reservoirs located in the three largest Spanish watersheds (Duero, Ebro and Tajo). For each segment, this study evaluates the general impoundment characteristics and geographical contexts and calculates the flow impacts and the divergence between the circulating flows and the reference area of admissible flow variability on a daily basis for the period 2000–2010. This assessment of dam regulation impacts provides a reference to plan measures for mitigating these impacts. The advantages of this flow regulation impact analysis over other analyses are discussed in terms of the implementation of environmental water costs as suggested by the European Water Framework Directive. This approach expands the current understanding of water environmental costs and represents a practical management tool for decreasing the environmental impacts of flow regulation and for increasing water-use efficiency. Highlights • Natural range of flow variability discriminates distinct hydrologic regime patterns. • Flow regulation impacts are not significantly influenced by climate or geomorphology. • Flow regulation impacts strongly depend on dam operation and water use. • Flow reductions in winter and increases in summer are common in Mediterranean rivers. • Deviations from natural flow variability should inform damming environmental costs. [ABSTRACT FROM AUTHOR]

Abstract The river flow regime and water resources are highly important for economic growths, flood security, and ecosystem dynamics in the Mekong basin – an important transboundary river basin in South East Asia. The river flow, although remains relatively unregulated, is expected to be increasingly perturbed by climate change and rapidly accelerating socioeconomic developments. Current understanding about hydrological changes under the combined impacts of these drivers, however, remains limited. This study presents projected hydrological changes caused by multiple drivers, namely climate change, large-scale hydropower developments, and irrigated land expansions by 2050s. We found that the future flow regime is highly susceptible to all considered drivers, shown by substantial changes in both annual and seasonal flow distribution. While hydropower developments exhibit limited impacts on annual total flows, climate change and irrigation expansions cause changes of +15% and −3% in annual flows, respectively. However, hydropower developments show the largest seasonal impacts characterized by higher dry season flows (up to +70%) and lower wet season flows (−15%). These strong seasonal impacts tend to outplay those of the other drivers, resulting in the overall hydrological change pattern of strong increases of the dry season flow (up to +160%); flow reduction in the first half of the wet season (up to −25%); and slight flow increase in the second half of the wet season (up to 40%). Furthermore, the cumulative impacts of all drivers cause substantial flow reductions during the early wet season (up to −25% in July), posing challenges for crop production and saltwater intrusion in the downstream Mekong Delta. Substantial flow changes and their consequences require careful considerations of future development activities, as well as timely adaptation to future changes. Graphical abstract Unlabelled Image Highlights • Climate change, hydropower and irrigation developments strongly alter the Mekong's future flows. • Total annual flows changes (-3% to 15%) are primarily driven by irrigation expansions and climate change. • Hydropower developments show strongest impacts on seasonal flows: up to +70% (dry season) and -15% (wet season). • Future flow changes pose serious consequences, requiring strategic development planning and effective adaptation. [ABSTRACT FROM AUTHOR]

Highlights • Impacts of future climate change scenarios on net aquifer recharge from rainfall. • Application in continental Spain, a varied territory sensitive to climate change. • Generation of potential climate scenarios by different ensembles of prediction. • Multi-criteria analysis of statistical downscaling techniques. • Simulation of climate scenarios within a distributed rainfall-recharge model. Abstract Climate change will modify the availability of groundwater resources in the future. Thus the evaluation of average aquifer recharge from precipitation, and its uncertainty, becomes a key subject in determining suitable countrywide water policies. The confident prediction of renewable groundwater resources requires an accurate evaluation of aquifer recharge over time and space, especially in large territories with varied conditions for aquifer recharge such as continental Spain. This study asses impacts of future potential climatic change scenarios on distributed net aquifer recharge (NAR) from precipitation over continental Spain. For this, the used method (1) generates future time series of climatic variables (precipitation, temperature) spatially distributed over the territory for potential aquifer recharge (PAR), and (2) simulates them within previously calibrated spatial PAR or NAR recharge models from the available historical information to provide distributed PAR or NAR time series. The information employed comes from the Spain02 project for the historical climatic data, from Alcalá and Custodio (2014, 2015) for the historical spatial NAR, and from the CORDEX EU project (2013) regional climate models (RCMs) simulations for the future climate scenarios. A distributed empirical precipitation-recharge model is defined by using a regular 10 km × 10 km grid, and assuming that precipitation (P) and temperature (T) are the most important climatic variables determining PAR, while their spatiotemporal variabilities determine the impacts of future potential climatic scenarios on renewable groundwater resources. Potential plausible pictures of future climate scenarios are defined by combining information coming from different RCMs and General Circulation models (GCMs), downscaling techniques, and ensemble hypothesis. These scenarios were simulated within the used precipitation-recharge model to estimate impacts on NAR. The results show that global mean NAR decreases by 12% on average over continental Spain. Over 99.8% of the territory, a variable degree of recharge reduction is obtained; the reduction is quite heterogeneously distributed in line with the variety of conditions for aquifer recharge over continental Spain. The standard deviation of annual mean NAR will increase by 8% on average in the future. The dependence of these changes regarding potential explanatory variables, such as elevation and latitude was also analysed. [ABSTRACT FROM AUTHOR]

The aim of this work is to investigate the soil water budget across China by means of hydrological modeling under current and future climate conditions and to evaluate the sensitivity to soil parameters. For this purpose, observed precipitation and temperature data (1981–2010) and climate simulations (2021–2050, 2071–2100) at high resolution (about 14 km) on a large part of China are used as weather forcing. The simulated weather forcing has been bias corrected by means of the distribution derived quantile mapping method to eliminate the effects of systematic biases in current climate modeling on water cycle components. As hydrological models, two 1D models are tested: TERRA-ML and HELP. Concerning soil properties, two datasets, provided respectively by Food and Agriculture Organization and U.S. Department of Agriculture, are separately tested. The combination of two hydrological models, two soil parameter datasets and three weather forcing inputs (observations, raw and bias corrected climate simulations) results in five different simulation chains. The study highlights how the choice of some approaches or soil parameterizations can affect the results both in absolute and in relative terms and how these differences could be highly related to weather forcing in inputs or investigated soil. The analyses point out a decrease in average water content in the shallower part of the soil with different extents according to climate zone, concentration scenario and soil/cover features. Moreover, the projected increase in temperature and then in evapotranspirative demand do not ever result in higher actual evapotranspiration values, due to the concurrent variations in precipitation patterns.

Assessing future challenges in water resources management is crucial to the Melka Kuntrie (MK) subbasin suffering water shortage. Impact assessments are evaluated by the HBV hydrological model with six scenarios, including two GCMs of AR4-A2 and two GCMs of AR5-RCP4.5 and RCP8.5, for the time periods 2021–2050 and 2071–2100. Evapotranspiration is expected to increase under all scenarios—due to rising temperature—and induce more water stress on rainfed agriculture of the area. However, the increase in the monthly minimum temperature is beneficial to crops against chilling damages. Five out of six projections show significant increases of rainfall and streamflow in both annual and major rainy seasons, except ECHAM-A2. Annual rainfall (streamflow) is expected to increase by 38% (23%) and 57% (49%) during 2021–2050 and 2071–2100, respectively, under RCP8.5 scenarios. Greater flashflood risk is a concern because of the projected increase in streamflow. The projection of decreased streamflow with ECHAM-A2 will exacerbate the existing water shortage, especially in the minor rainy season. Water harvesting during the major rainy season would be vital to enhance water management capacities and reduce flashflood risks. Lacking sufficient hydraulic and irrigation infrastructures, the MK subbasin will be more vulnerable to the impacts of climate change.

Abstract: Knowledge about flood generating processes can be beneficial for numerous applications. Especially in the context of climate change impact assessment, daily patterns of meteorological and catchment state conditions leading to flood events (i.e., storylines) may be of value. Here, we propose an approach to identify storylines of flood generation using daily weather and snow cover observations. The approach is tested for and applied to a typical pre‐Alpine catchment in the period between 1961 and 2014. Five precipitation parameters were determined that describe temporal and spatial characteristics of the flood associated precipitation events. The catchment's snow coverage was derived using statistical relationships between a satellite‐derived snow cover climatology and station snow measurements. Moreover, (pre‐) event snow melt sums were estimated using a temperature‐index model. Based on the precipitation and catchment state parameters, 5 storylines were identified with a cluster analysis: These are (a) long duration, low intensity precipitation events with high precipitation depths, (b) long duration precipitation events with high precipitation depths and episodes of high intensities, (c) shorter duration events with high or (d) low precipitation intensity, respectively, and (e) rain‐on‐snow events. The event groups have distinct hydrological characteristics that can largely be explained by the storylines' respective properties. The long duration, high intensity storyline leads to the most adverse hydrological response, namely, a combination of high peak magnitudes, high volumes, and long durations of threshold exceedance. The results show that flood generating processes in mesoscale catchments can be distinguished on the basis of daily meteorological and catchment state parameters and that these process types can explain the hydrological flood properties in a qualitative way. Hydrological simulations of daily resolution can thus be analysed with respect to flood generating processes. [ABSTRACT FROM AUTHOR]

Abstract: The 2015/2016 El Niño has been classified as one of the three most severe on record. El Niño teleconnections are commonly associated with droughts in southern Africa and high precipitation in eastern Africa. Despite their relatively frequent occurrence, evidence for their hydrological effects and impacts beyond agriculture is limited. We examine the hydrological response and impact pathways of the 2015/2016 El Niño in eastern and southern Africa, focusing on Botswana, Kenya, and Zambia. We use in situ and remotely sensed time series of precipitation, river flow, and lake levels complemented by qualitative insights from interviews with key organizations in each country about awareness, impacts, and responses. Our results show that drought conditions prevailed in large parts of southern Africa, reducing runoff and contributing to unusually low lake levels in Botswana and Zambia. Key informants characterized this El Niño through record high temperatures and water supply disruption in Botswana and through hydroelectric load shedding in Zambia. Warnings of flood risk in Kenya were pronounced, but the El Niño teleconnection did not materialize as expected in 2015/2016. Extreme precipitation was limited and caused localized impacts. The hydrological impacts in southern Africa were severe and complex, strongly exacerbated by dry antecedent conditions, recent changes in exposure and sensitivity and management decisions. Improved understanding of hydrological responses and the complexity of differing impact pathways can support design of more adaptive, region‐specific management strategies. [ABSTRACT FROM AUTHOR]

Regional climate model (RCM) results could not be duly represented by the IPCC 2013 Report, focusing mostly on global climate models (GCM). The aim of our study is to provide a literature insight into these types of results, based on the recent Report by the EEA (2017). After a brief comparison of the GCMs and RCMs, averages of short- and long-term projections of temperature and precipitation changes are provided. Hydrological changes are represented by run-off, mountain glaciers and snow mass. These and other, non-hydrological impacts are also listed from the Report. This short review, delimited by the length, page size and colouring of the hardcopy, is finishing by the experienced destruction caused by the weather extremes over Europe. The original sources, together with the EEA quotations are referred. [ABSTRACT FROM AUTHOR]

In this investigation, hydrological time series of three ponds located in the province of Córdoba (southern Spain) at a daily scale has been analyzed. For the first time, a detailed evolution of the water level of Jarales, Conde, and Amarga ponds has been acquired by means of the installation of level loggers in the deepest point of each of the ponds. We have modeled the water level evolution using a simple one-dimensional model. Calibration of the model was very satisfactory in two of the ponds. The model was then setup and simulated for two future Scenarios: A (IPCC climate change scenario) and B (climate change + groundwater withdrawal within the basin). Two ponds were classified as discharge ponds, which are the hydrological regime of the majority of southern Spain's continental ponds. One was classified as a recharge pond. With regard to the results obtained in the simulations for Scenarios A and B, our results showed that IPCC scenario will reduce hydroperiod significantly in the three ponds, with a reduction of approximately 500 cm in the water level. With respect to groundwater withdrawal within the basins, results show a very high impact in the hydroperiod in Amarga and Conde ponds. [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]

The question of which climate model bias correction methods and spatial scales for correction are optimal for both projecting future hydrological changes as well as removing initial model bias has so far received little attention. For 11 climate models (CMs), or GCM/RCM - Global/Regional Climate Model pairing, this paper analyses the relationship between complexity and robustness of three distribution-based scaling (DBS) bias correction methods applied to daily precipitation at various spatial scales. Hydrological simulations are forced by CM inputs to assess the spatial uncertainty of groundwater head and stream discharge given the various DBS methods. A unique metric is devised, which allows for comparison of spatial variability in climate model bias and projected change in precipitation. It is found that the spatial variability in climate model bias is larger than in the climate change signals. The magnitude of spatial bias seen in precipitation inputs does not necessarily correspond to the magnitude of biases seen in hydrological outputs. Variables that integrate basin responses over time and space are more sensitive to mean spatial biases and less so on extremes. Hydrological simulations forced by the least parameterized DBS approach show the highest error in mean and maximum groundwater heads; however, the most highly parameterised DBS approach shows less robustness in future periods compared with the reference period it was trained in. For hydrological impacts studies, choice of bias correction method should depend on the spatial scale at which hydrological impacts variables are required and whether CM initial bias is spatially uniform or spatially varying. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Climate change investigation at a watershed-scale plays a significant role in revealing the historical evolution and future trend of the runoff variation in watershed. This study examines the multisource hydrological and meteorological variables over the source area of the Yellow River (SAYR) from 1961 to 2012 and the future climate scenarios in the region during 2006-2100 based on the CMIP5 projection data. It recognizes the significant characteristics of the recent climate change in the SAYR and predicts the change trend of future flow in the region. It is found that (1) The climate in the SAYR has experienced a significant warm-wet change since the early 2000s, which is very different from the antecedent warm-dry trend since the late 1980s; (2) The warm-wet trend in the northwestern SAYR (the headwater area of the Yellow River (HAYR), is more obvious than that in the whole SAYR; (3) With precipitation increase, the runoff in the region also experienced an increasing process since 2006. The runoff variations in the region are sensitive to the changes of precipitation, PET and maximum air temperature, but not very sensitive to changes in mean and minimum air temperatures; (4) Based on the CMIP5 projection data, the warm-wet climate trend in SAYR are likely to continue until 2049 if considering three different (i.e. RCP2.6, RCP4.5 and RCP8.5) greenhouse gas emission scenarios, and the precipitation in SAYR will not be less than the current level before 2100; however, it is estimated that the recent flow increase in the SAYR is likely to be the decadal change and it will at most continue until the 2020s; (5) The inter-annual variations of the East Asian winter monsoon are found to be closely related to the variations of annual precipitation in the region. Meanwhile, the increased precipitation as well as the increase of potential evapotranspiration (PET) being far less than that of precipitation in the recent period are the main climate causes for the flow increase in the region. [ABSTRACT FROM AUTHOR]

Response of leaf area index (LAI) is the key determinant for predicting impacts of the elevated CO2 (eCO2) on water budgets. Importance of the changes in functional attributes of vegetation associated with eCO2 for predicting responses of LAI has rarely been addressed. In this study, the WAter Vegetation Energy and Solute (WAVES) model was applied to simulate ecohydrological effects of the eCO2 at two free-air CO2 enrichment (FACE) experimental sites with contrasting vegetation.One was carried out by the Oak Ridge National Laboratory on the forest (ORNL FACE). The other one was conducted by the University of Minnesota on the grass (BioCON FACE). Results demonstrated that changes in functional attributes of vegetation (including reduction in specific leaf area, changes in carbon assimilation and allocation characteristics) and availability of nutrients are important for reproducing the responses of LAI, transpiration and soil moisture at both sites. Predicted LAI increased slightly at both sites because of fertilization effects of the eCO2. Simulated transpiration decreased 10⋅5% at ORNL site and 13⋅8% at BioCON site because of reduction in the stomatal conductance. Predicted evaporation from interception and soil surface increased slightly (<1⋅0 mm year-1) at both sites because of increased LAI and litter production, and increased soil moisture resulted from reduced transpiration. All components of run-off were predicted to increase because of significant decrease in transpiration. Simulated mean annual evapotranspiration decreased about 8⋅7% and 10⋅8%, and mean annual run-off increased about 11⋅1%(59⋅3mm year-1) and 9⋅5%(37⋅6mmyear-1) at the ORNL and BioCON FACE sites, respectively. [ABSTRACT FROM AUTHOR]

ABSTRACT Climate change is almost certain to affect snow and ice processes. Even at lower latitudes, changes in snow cover at high altitudes can significantly affect catchment hydrology. This article uses data from a transient Regional Climate Model projection ( HadRM3Q0) for 1950-2099 ( A1B emissions) to drive hydrological models for three nested catchments on the river Dee in north-east Scotland, to assess potential changes in flood frequency and timing using annual maxima and moving-window analyses. Some results are also shown for an upland catchment in northern England. Modelling is performed both with and without a snow module, to demonstrate the effects of snowfall/melt and how these change through time and vary between catchments. Modelled changes in flood magnitude and timing are nonlinear, with most changes for daily mean flows not significant. For longer duration (30-day) flows with snow there are significant decreases in peak magnitude, particularly for the smaller higher altitude Dee catchments, with peaks occurring months earlier in future (changes without snow are generally not significant). There is a general convergence in results with and without snow later in the period, as snow processes become less important, but convergence occurs at different times for different catchments and occurs differently for daily and 30-day peak flows due to the differential effects of snow at different durations. This not only highlights the importance of including snow processes for such catchments, particularly for longer duration flows, but also highlights the complexity of interactions: Physical catchment properties, the balance between precipitation occurrence and temperature, and how this balance alters as the climate changes will each be critical in determining the impact on the magnitude and timing of peak flows, making it hard to generalize results. [ABSTRACT FROM AUTHOR]