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• Effective method is proposed for exploring the fundamental mechanism of SSF. • Soil temperature is proved to be the most fundamental factor for SSF pathways. • The patterns of vertical and lateral source for SSF are analyzed and figured out. The impact of the freeze–thaw process on the active layer is reflected in the changed subsurface flow (SSF) process in cold alpine regions. Identifying sources and pathways of SSF in the freeze–thaw process is critical but difficult, and the related dominant factors and mechanisms are still unknown. In this paper, the effective identification and analysis of SSF are promoted based on field sampling data from the thawing (June) to freezing (September) period of 2022 in the Qinghai Lake basin on the northeastern Qinghai-Tibetan Plateau. By the proposed method with a high sampling frequency and refined sampling spatial scale, the sources and pathways of SSF are clearly identified. The results are as follows: (1) The soil temperature is considered the most fundamental factor affecting the SSF pathways, it influences water infiltration to the deep layer and the effect is extended to the saprolite and weathered bedrock layers. (2) Thawing promotes water to infiltrating into deep layer. 30 cm soil water contributes the most to SSF (2 %–86 %) in the thawing period, while the contribution difference of the water from the 30 cm, 60 cm, and 90 cm layers is small (ranging from 32 %–33 %, 24 %–26 %, and 32 %–35 %, respectively) in the thawed period. (3) Meanwhile, the soil water from different slope positions contribute differently to SSF, and the SSF from deep soil layer is transit in prolong paths and depths. It is caused by the out-of-sync water transit process in the hillslope. With continuing climate warming, we propose that the differences in the water sources of SSF across soil layers may decrease, while the differences in the transit processes of SSF across soil layers may increase. [ABSTRACT FROM AUTHOR]

• We analyzed trends and breakpoints for three streamflow signatures of drying patterns in 540 non-perennial streams over CONUS • Nonlinear changes in streamflow are more common than linear changes for all three stream intermittency signatures. • The past behavior of non-perennial streams might be a poor predictor of future drying patterns Stream drying patterns – including duration, timing, and dry-down rates – affect aquatic ecosystems and nutrient exports in non-perennial streams. Because hydrologic processes are often nonlinear, changes in drying may also be nonlinear, but analyses of historical changes in stream drying to date have not characterized the frequency or functional forms of nonlinear change. Understanding the extent of nonlinear change in non-perennial streams is essential for advancing our fundamental knowledge of hydrological processes, aquatic ecosystems, and watershed functioning under a warming climate. This paper uses a polynomial-based trend detection technique (PolyTrend) to analyze the linear and nonlinear trend behaviors of three intermittency signatures (annual no-flow days specifying longer or shorter drying duration, day of first no-flow occurrence specifying timing of stream drying, and days from peak to no-flow specifying dry-down rates) at 540 non-perennial gage stations over 38 years (1980–2017) across the continental United States (CONUS). Additionally, we carried out a breakpoint analysis to characterize the discontinuities in the time series of each intermittency signature. Analysis of annual no-flow days shows that about 37 % of the total streamflow stations are drying for longer each year, whereas about 22 % are wetter for longer than in the past. The day of first no-flow occurrence analysis shows that 10 % of the streams are drying earlier, and 19 % are drying later. On the other hand, analysis of days from peak to no-flow shows that 14 % of streams are drying faster, and 17 % are drying more slowly. For all these metrics, among the significant trends, at least half of the relationships were nonlinear. For annual no-flow days , the breakpoint analysis shows more discontinuities in the second half of the analysis period (1999 to 2017) than in the first half, with more discontinuities in the Southern Great Plains than in other regions. The other two signatures demonstrate less frequent discontinuities in the second half of the analysis period, suggesting decreased nonlinear dynamics in recent years. Nonlinear no-flow duration trends are common in Mediterranean California, and the dry-down rate has increased in recent decades. Our findings indicate that nonlinear change in stream drying is widespread and must be accounted for in watershed planning and management. [ABSTRACT FROM AUTHOR]

• Transition zones are the hotspots of bioclimatic changes under global warming. • Global warming extends growing season lengths but increases heat and water stresses. • Sustainable grasslands in China shrink and shift northwestward with global warming. Bioclimatic response to global warming is a key linkage between anthropogenic climate change and ecosystem sustainability, particularly for the impact-prone climate transition zones. This paper examines changes in heat-water conditions from 2006 to 2100 across China, using the fifth generation climate reanalysis from the European Centre for Medium-Range Weather Forecasts (ERA5) and bias-adjusted climate projections by the Coupled Model Intercomparison Project Phase 5 (CMIP5). We then assess the effects of these changes on habitat suitability for responsive ecosystems using a species distribution model. The results reveal significant changes in bioclimatic environments across dry–wet climate transition zones under the present-day climate and the RCP8.5 scenario. By the end of the 21st century, local growing season length (GSL) could extend by 60 days and 30 % of the GSL could be under heat stress. Water conditions worsen overall in both the air and the soil, despite some improvements in the middle parts of transition zones. With altered heat-water conditions, sustainable grasslands shift northwestward, with a reduction of approximately 131 million km2 (46.6 % relative to 2006–2010) in total area. These changes primarily arise from alterations in winter and spring heat-water conditions. Our findings highlight the climate transition zones as hotspots of ecosystem vulnerability demanding particular attention in impact assessment and adaptation studies. [ABSTRACT FROM AUTHOR]

[Display omitted] • The drought pattern in China is closely related to the basin distribution and multiple teleconnection factors. • The intensity and frequency of drought in China exhibited an increasing trend. • The ENSO-AO had important positive effects in the major basins in China. • Multiple wavelet coherence helps identify the processes controlling drought changes. Due to increasing global warming and the frequent occurrence of severe drought risk in recent decades, many studies have investigated drought in China. However, the spatiotemporal heterogeneities of droughts are complicated, and a comprehensive analysis of the driving forces has not been thoroughly explored. In this paper, we studied the temporal and spatial patterns of drought in China from 1960 to 2018 and disclosed its relationship with multiple teleconnection factors on different time scales. The results show that (1) Drought in China has exhibited a fluctuating increasing trend over the past 59 years, with a standardized precipitation–evapotranspiration index (SPEI) rate of change of –0.12/10 a, and the most severe droughts occurred during 2000–2010. (2) There was a significant abrupt change in China's meteorological droughts induced by climate change around 1997. (3) The trend in China was characterized by drought in spring and autumn and humidification in winter, while the trend in the Southwest River Basin was characterized by drought. (4) A combination of factors can best explain the drought variations from basin to basin, and the El Niño-Southern Oscillation (ENSO)-Arctic Oscillation (AO) was most commonly the best predictor. The use of multiple wavelet coherence helps to identify the dominant drought change processes. [ABSTRACT FROM AUTHOR]

Summary: In a globally warming climate, observed rates of atmospheric evaporative demand have declined over recent decades. Several recent studies have shown that declining rates of evaporative demand are primarily governed by trends in the aerodynamic component (primarily being the combination of the effects of wind speed (u) and atmospheric humidity) and secondarily by changes in the radiative component. A number of these studies also show that declining rates of observed near-surface u (termed ‘stilling’) is the primary factor contributing to declining rates of evaporative demand. One objective of this paper was to review and synthesise the literature to assess whether stilling is a globally widespread phenomenon. We analysed 148 studies reporting terrestrial u trends from across the globe (with uneven and incomplete spatial distribution and differing periods of measurement) and found that the average trend was −0.014ms−1 a−1 for studies with more than 30 sites observing data for more than 30years, which confirmed that stilling was widespread. Assuming a linear trend this constitutes a −0.7ms−1 change in u over 50years. A second objective was to confirm the declining rates of evaporative demand by reviewing papers reporting trends in measured pan evaporation (E pan) and estimated crop reference evapotranspiration (ET o); average trends were −3.19mma−2 (n =55) and −1.31mma−2 (n =26), respectively. A third objective was to assess the contribution to evaporative demand trends that the four primary meteorological variables (being u; atmospheric humidity; radiation; and air temperature) made. The results from 36 studies highlighted the importance of u trends. We also quantified the sensitivity of rates of evaporative demand to changes in u and how the relative contributions of the aerodynamic and radiative components change seasonally over the globe. Our review: (i) shows that terrestrial stilling is widespread across the globe; (ii) confirms declining rates of evaporative demand; and (iii) highlights the contribution u has made to these declining evaporative rates. Hence we advocate that assessing evaporative demand trends requires consideration of all four primary meteorological variables (being u, atmospheric humidity, radiation and air temperature). This is particularly relevant for long-term water resource assessment because changes in u exert greater influence on energy-limited water-yielding catchments than water-limited ones. [ABSTRACT FROM AUTHOR]

• An improved SEBAL model (Y-SEBAL) was established to simulate regional actual ET. • The model mechanism comparison between the Y-SEBAL, SEBAL, SEBALI, and SSEBop model. • The calculation of sensible heat flux was improved. • The improved SEBAL model can estimate regional ET more accurately. The global food and water crises caused by climate warming are becoming increasingly significant. One of the important aspects of surface water transfer is evapotranspiration. The accurate estimation of evapotranspiration (ET) is of great significance in water resource management. However, accurate estimation of large-scale ET is challenging due to the adequate selection of the hot and cold pixels, the heterogeneity of the subsurface and the instability of the lower atmosphere. Therefore, in this paper, a surface energy balance model (Y-SEBAL) was proposed based on the SEBAL model and improved sensible heat flux calculation, and used to simulate large-scale actual evapotranspiration. Based on the principle of surface energy balance, this model introduced the empirical formula of sensible heat flux and simplifies the selection of limit to address the challenge of calculating the sensible heat flux of the crucial variable in the SEBAL model. The study simulated the spatial and temporal evolution of regional evapotranspiration with the model and verified the model simulation performance. In addition, the sensitivity of the model-driven data was quantified. The results showed that the simulation value of the Y-SEBAL model was highly consistent with the eddy covariance measurement data. In the verification results, the R value was 0.82, the index of agreement was 0.90, and the root mean square error was 0.81 mm·d−1. The performance verification indices were better than the SEBAL model, MOD16 model, and SSEBop model. And the model had the highest sensitivity to wind speed, reaching 0.714. The Y-SEBAL model improved the simulation performance of the original model and simulated the actual evapotranspiration. The study can provide a new solution for improving the retrieval of evapotranspiration by remote sensing at the regional scale. [ABSTRACT FROM AUTHOR]

Summary Soil moisture plays an increasingly important role in the cycle of energy–water exchange, climate change, and hydrologic processes. It is usually measured at a point site, but regional soil moisture is essential for validating remote sensing products and numerical modeling results. In the study reported in this paper, the minimal number of required sites (NRS) for establishing a research observational network and the representative single sites for regional soil moisture estimation are discussed using the soil moisture data derived from the “Maqu soil moisture observational network” (101°40′–102°40′E, 33°30′–35°45′N), which is supported by Chinese Academy of Science. Furthermore, the best up-scaling method suitable for this network has been studied by evaluating four commonly used up-scaling methods. The results showed that (1) Under a given accuracy requirement R ⩾ 0.99, RMSD ⩽ 0.02 m 3 /m 3 , NRS at both 5 and 10 cm depth is 10. (2) Representativeness of the sites has been validated by time stability analysis (TSA), time sliding correlation analysis (TSCA) and optimal combination of sites (OCS). NST01 is the most representative site at 5 cm depth for the first two methods; NST07 and NST02 are the most representative sites at 10 cm depth. The optimum combination sites at 5 cm depth are NST01, NST02, and NST07. NST05, NST08, and NST13 are the best group at 10 cm depth. (3) Linear fitting, compared with other three methods, is the best up-scaling method for all types of representative sites obtained above, and linear regression equations between a single site and regional soil moisture are established hereafter. “Single site” obtained by OCS has the greatest up-scaling effect, and TSCA takes the second place. (4) Linear fitting equations show good practicability in estimating the variation of regional soil moisture from July 3, 2013 to July 3, 2014, when a large number of observed soil moisture data are lost. [ABSTRACT FROM AUTHOR]

Summary Areal reduction factors (ARFs) are commonly used to transform point design rainfall to represent the average design rainfall for a catchment area. While there has been considerable attention paid in the research and engineering communities to the likely changes in rainfall intensity in future climates, the issue of changes to design areal rainfall has been largely ignored. This paper investigates the impact of climate change on ARFs. A new methodology for estimating changes in ARFs is presented. This method is used to assess changes in ARFs in the greater Sydney region using a high-resolution regional climate model (RCM). ARFs under present (1990–2009) and future (2040–2059) climate conditions were derived and compared for annual exceedance probabilities (AEPs) from 50% to 5% for durations ranging from 1 h to 120 h. The analysis shows two main trends in the future changes in ARFs. For the shortest duration events (1-h) the ARFs are found to increase which implies that these events will tend to have a larger spatial structure in the future than the current climate. In contrast, storms with durations between 6 and 72 h are likely to have decreased ARFs in the future, suggesting a more restricted spatial coverage of storms under a warming climate. The extent of the decrease varies with event frequency and catchment size. The largest decreases are found for large catchments and rare events. Although the results here are based on a single RCM and need to be confirmed in future work with multiple models, the framework that is proposed will be useful for future studies considering changes in the areal extent of rainfall extremes. [ABSTRACT FROM AUTHOR]

Summary Both drought and aridity indicate imbalance in water availability. While drought is a natural temporal hazard, aridity is a constant climatic feature. This paper investigates the changes in drought characteristics across different aridity zones with and without consideration of potential evapotranspiration (PET), as a means to better assess drought in a warming climate. Two drought indexes are employed: (1) Standardized precipitation index (SPI), which is solely based on precipitation; and (2) Reconnaissance drought index (RDI), which, in addition to precipitation, takes PET into account. The two indexes are first employed to observed precipitation and PET data for the period 1960–2009 from the CRU (Climate Research Unit, University of East Anglia) TS 3.1 database. The results indicate that although all the aridity zones experience both downward and upward drought trends, no significant trend is found over large parts of the zones. However, the agreement between SPI and RDI reduces from the hyper-arid zone on one extreme toward the humid zone on the other. In the three more humid zones (i.e. semi-arid, sub-humid, and humid), the indexes exhibit different trends, with RDI showing more decreasing trends (i.e. becoming drier). While SPI generally shows more drought prone areas than RDI for the pre-1998 period, the opposite is observed for the post-1998 period. Given the known changes to PET in observed records, and also expected increases as global warming intensifies, these results suggest that RDI will be consistently different to the SPI as global warming intensifies. This hypothesis is further tested for historic and future climate projections from the CSIRO (Commonwealth Scientific and Industrial Research Organisation, Australia) Mk3.6 global climate model (GCM), with use of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and RCP8.5 (Representative Concentration Pathways). In this case, PET is calculated using FAO56-PM model for assessment of RDI. The results suggest that agreement between SPI and RDI is affected and decreases remarkably over time (between 1850 and 2100). All these lead to the conclusion that, in the face of climate change, PET, an important component in the hydrologic cycle, should not be ignored in drought modeling. [ABSTRACT FROM AUTHOR]

Summary Integrated Water Resources Management (IWRM) was introduced in 1980s to better optimise water uses between different water demanding sectors. However, since it was introduced water systems have become more complicated due to changes in the global water cycle as a result of climate change. The realization that climate change will have a significant impact on water availability and flood risks has driven research and policy making on adaptation. This paper discusses the main similarities and differences between climate change adaptation and IWRM. The main difference between the two is the focus on current and historic issues of IWRM compared to the (long-term) future focus of adaptation. One of the main problems of implementing climate change adaptation is the large uncertainties in future projections. Two completely different approaches to adaptation have been developed in response to these large uncertainties. A top-down approach based on large scale biophysical impacts analyses focussing on quantifying and minimizing uncertainty by using a large range of scenarios and different climate and impact models. The main problem with this approach is the propagation of uncertainties within the modelling chain. The opposite is the bottom up approach which basically ignores uncertainty. It focusses on reducing vulnerabilities, often at local scale, by developing resilient water systems. Both these approaches however are unsuitable for integrating into water management. The bottom up approach focuses too much on socio-economic vulnerability and too little on developing (technical) solutions. The top-down approach often results in an “explosion” of uncertainty and therefore complicates decision making. A more promising direction of adaptation would be a risk based approach. Future research should further develop and test an approach which starts with developing adaptation strategies based on current and future risks. These strategies should then be evaluated using a range of future scenarios in order to develop robust adaptation measures and strategies. [ABSTRACT FROM AUTHOR]

Summary: The effect of future climate scenarios on surface water and groundwater resources has been shown to have a consequent impact on water-dependent ecosystems. A regional-scale analysis of changes in water resources as a result of changing climate was undertaken in south-western Australia; a region with a large number of nationally and internationally recognised water-dependent ecosystems. The paper examines the potential environmental impacts of a substantial reduction in rainfall and an increase in temperature as projected by global climate models (GCMs) on river and groundwater-dependent terrestrial vegetation by 2030. Climate change effects on environmentally significant flow regimes were evaluated by applying the climate projections from 15 GCMs under three global warming ‘scenarios to rainfall–runoff and groundwater models. It was estimated that under a dry future climate scenario, the frequency of river flow rates important for ecological communities is likely to be reduced by up to 2months per year, which is likely to cause a significant level of stress to ecological communities. Additionally, the duration of no-flow periods may increase by more than 120days in some streams. Under a dry future climate scenario, groundwater-dependent vegetation is projected to be at a high risk in over 19% of its current habitat area. Water-dependent ecosystems are also projected to be affected by an increase in groundwater abstraction. The results indicate that the projected impacts of future climate conditions are not likely to be uniform across the region but overall they could cause a continuing threat to water-dependent ecosystems. The implementation of water management plans should place particular emphasis on the ecological water requirements in 6 of the 13 river catchments in south-western Australia and in areas where groundwater abstraction is high. The climate projections and ecological impacts are a continuation of the trends that have taken place in the past three decades. [Copyright &y& Elsevier]

Summary: This paper presents the results of computer simulations of runoff from 13 major fresh and brackish river basins in south-western Australia (SWA) under climate projections obtained from 15 GCMs with three future global warming scenarios equivalent to global temperature rises of 0.7°C, 1.0°C and 1.3°C by 2030. The objective was to apply an efficient methodology, consistent across a large region, to examine the implications of the best available projections in climate trends for future surface water resources. An ensemble of rainfall-runoff models was calibrated on stream flow data from 1975 to 2007 from 106 gauged catchments distributed throughout the basins of the study area. The sensitivity of runoff to projected changes in mean annual rainfall is examined using the climate ‘elasticity’ concept. Averaged across the study area, all 15 GCMs project declines in rainfall under all global warming scenarios with a median decline of 8% resulting in a median decline in runoff of 25%. Such uniformity in projections from GCMs is unusual. Over SWA the average annual runoff under the 5th wettest and 5th driest of the 45 projections of the 2030 climate declines by 10 and 42%, respectively. Under the 5th driest projection the runoff decline ranges from 53% in the northern region to 40% in the southern region. Strong regional variations in climate sensitivity are found with the proportional decline in runoff greatest in the northern region and the greatest volumetric declines in the wetter basins in the south. Since the mid 1970s stream flows into the major water supply reservoirs in SWA have declined by more than 50% following a 16% rainfall reduction. This has already had major implications for water resources planning and for the preservation of aquatic and riparian ecosystems in the region. Our results indicate that this reduction in runoff is likely to continue if future climate projections eventuate. [Copyright &y& Elsevier]

Summary: The effect of future climate scenarios on surface water and groundwater resources has been shown to have a consequent impact on water-dependent ecosystems. A regional-scale analysis of changes in water resources as a result of changing climate was undertaken in south-western Australia; a region with a large number of nationally and internationally recognised water-dependent ecosystems. The paper examines the potential environmental impacts of a substantial reduction in rainfall and an increase in temperature as projected by global climate models (GCMs) on river and groundwater-dependent terrestrial vegetation by 2030. Climate change effects on environmentally significant flow regimes were evaluated by applying the climate projections from 15 GCMs under three global warming ‘scenarios to rainfall–runoff and groundwater models. It was estimated that under a dry future climate scenario, the frequency of river flow rates important for ecological communities is likely to be reduced by up to 2months per year, which is likely to cause a significant level of stress to ecological communities. Additionally, the duration of no-flow periods may increase by more than 120days in some streams. Under a dry future climate scenario, groundwater-dependent vegetation is projected to be at a high risk in over 19% of its current habitat area. Water-dependent ecosystems are also projected to be affected by an increase in groundwater abstraction. The results indicate that the projected impacts of future climate conditions are not likely to be uniform across the region but overall they could cause a continuing threat to water-dependent ecosystems. The implementation of water management plans should place particular emphasis on the ecological water requirements in 6 of the 13 river catchments in south-western Australia and in areas where groundwater abstraction is high. The climate projections and ecological impacts are a continuation of the trends that have taken place in the past three decades. [Copyright &y& Elsevier]

Summary: The European Alps are one region of the world where climate-driven changes are already perceptible, as exemplified by the general retreat of mountain glaciers over past decades. Temperatures have risen by up to 2°C since 1900 particularly at high elevations, a rate that is roughly three times the global-average 20th century warming. Regional climate models suggest that by 2100, winters in Switzerland may warm by 3–5°C and summers by 6–7°C according to greenhouse-gas emissions scenarios, while precipitation is projected to increase in winter and sharply decrease in summer. The impacts of these levels of climatic change will affect both the natural environment and a number of economic activities. Alpine glaciers may lose between 50% and 90% of their current volume and the average snowline will rise by 150m for each degree of warming. Hydrological systems will respond in quantity and seasonality to changing precipitation patterns and to the timing of snow-melt in the Alps, with a greater risk of flooding during the spring and droughts in summer and fall. The direct and indirect impacts of a warming climate will affect key economic sectors such as tourism, hydropower, agriculture and the insurance industry that will be confronted to more frequent natural disasters. This paper will thus provide an overview of the current state of knowledge on climatic change and its impacts on the Alpine world. [ABSTRACT FROM AUTHOR]

Summary: Nam Co Lake is the highest lake in the central Tibetan Plateau, and existing research on water storage and water level variations are lacking. This paper provides a method for estimating the lake water storage based on historical meteorological records from 1976 to 2009, remote sensing images scattered in this period, in situ bathymetric survey, and GIS techniques, and presents a comprehensive 34-year analysis of intra-annual and inter-annual variations of Nam Co Lake water storage. The multi-year mean water storage of Nam Co Lake is 842.36×108 m3, with the maximum water depth of about 98m. During 1976–2009, the lake water storage increased from 786.06×108 m3 to 870.30×108 m3, with a tendency value of 2.67×108 m3/a; the lake area enlarged from 1927.48km2 to 2015.12km2, with a tendency value of 2.71km2/a. The lake area fluctuations annually, increasing from April of each year until late September and early October, then decreasing until March of the next year. Climate change has a significant impact on the water storage variation of the lake. A general pattern of warming temperature is evident with the regional annual mean air temperature increasing significantly by 0.404°C/10a. Preliminary analysis indicates that the enlarging status of Nam Co Lake water storage is closely related to increasing of precipitation and stream runoff especially coming from the input of glacial meltwater. By combining this data with other research, it can be presented that under the trend of global warming, on Tibetan Plateau, the inland lakes which depend on the rainfall and river supply in the basin are shrinking, while the lakes which depend on glacial meltwater supply are enlarging. Climate change is an important factor promoting the lake variation. [ABSTRACT FROM AUTHOR]

Summary: This paper presents an approach to quantify evapotranspiration under changing climates, using field observations, theoretical evaporation models and meteorological predictions from global climate models. We analyzed evaporation and meteorological data from three riparian sites located in a semi-arid watershed in southern Arizona USA and found that the surface resistance to water vapor transport was closely related to the vapor pressure deficit. From this, we developed a relatively simple daily conductance model and included a growing season index to accurately replicate the onset and the end of the growing season. After the model was calibrated with observations from January 2003 to December 2007, it was used to predict daily evapotranspiration rates from 2000 to 2100 using Penman–Monteith equation and meteorological projections from the IPCC fourth assessment report climate model runs. Results indicate that atmospheric demand will be greater and lead to increased reference crop evaporation, but evapotranspiration rates at the studied field sites will remain largely unchanged due to stomatal regulation. However, the length of the growing season will increase leading to a greater annual riparian water use. These findings of increased riparian water use and atmospheric demand, likely affecting recharge processes, will lead to greater groundwater deficits and decreased streamflow and have important implications for water management in semi-arid regions. [Copyright &y& Elsevier]

Summary: The future rainfall series used to drive hydrological models in many climate change impact on runoff studies are informed by rainfall simulated by global climate models (GCMs). This paper assesses how the choice of GCMs based on their abilities to reproduce the observed historical rainfall can affect runoff impact assessment. The 23 GCMs used in IPCC 4AR are considered together with 1961–2000 observed rainfall data over southeast Australia. The results indicate that most of the GCMs can reproduce the observed spatial mean annual rainfall pattern, but the errors in the mean seasonal and annual rainfall amounts can be significant. The future mean annual rainfall projections averaged across southeast Australia range from −10% to +3% change per degree global warming, which is amplified as −23% to +4% change in the future mean annual runoff. There is no clear difference in the future rainfall projections between the better and poorer GCMs based on their abilities to reproduce the observed historical rainfall, therefore using only the better GCMs or weights to favour the better GCMs give similar runoff impact assessment results as the use of all the 23 GCMs. The range of future runoff in impact assessment studies is probably best determined using future rainfall projections from the majority of available archived GCM simulations. [Copyright &y& Elsevier]

Summary: Studies of hydro-meteorological time series have identified decadal and inter-decadal oscillations with quasi-cyclic components as part of long-term natural variations in the data. Concerns over impacts of global warming and climate change have led to many studies of sustainable development and adaptation strategies, involving historic trend estimations in order to forecast future trends. This paper demonstrates the impacts of natural oscillations of quasi-cyclic components on the Mann–Kendal and Thiel–Sen tests, the most common methods used for analyzing data trends. Tests on synthetic and real instrumental hydroclimate records suggest that the Mann–Kendall and Thiel–Sen tests are sensitive to oscillations of quasi-cyclic components. Data record length relative to the periodicity of cycles, magnitude, and phase of the longest quasi-cyclic component are the three most important factors affecting these tests. If the length of the record is greater than three cycle lengths, the impact on the M–K and T–S tests should be minimal. Given the predominance of 45–60 year climate cycles observed in instrumental records, trend analyses of time series records <60 years should be done with caution. These results provide insight for appropriate temporal trend analyses of hydroclimate and associate time series. [Copyright &y& Elsevier]

• Depending on stream temperature model, different warming of streamwater is projected. • Projection from particular model occasionally differ from the majority of models. • A number of stream temperature models should be used together for future climates. • Stream temperature in analyzed streams is to be warmed by 2–3.5 °C by 2100 (RCP 8.5). • In specific streams marginal cooling in projected in some months until 2050. In the majority of studies aiming at stream temperature warming due to climate change just a single water temperature model is used. Choosing a single model may highly impact the conclusions from the study. In this paper four relatively different empirical or semi-empirical models: perceptron neural networks, product unit networks, extended logistic regression and air2stream were applied to project the impact of climate change on water temperature in rivers located in temperate climatic zones of the USA and Poland. The models were driven by daily air temperature and streamflow projected by the rainfall-runoff model. In the first step, the models were calibrated and validated. Then the projections of water temperature were derived for the historical periods and two future periods taking into account: (a) climate simulations from the CORDEX initiative (NA-CORDEX and EURO-CORDEX), (b) the GR4J rainfall-runoff model and (c) different water temperature models. The obtained results indicate that due to global warming, the stream temperatures are expected to increase by about 1–2 °C for 2021–2050 and by 2–3 °C for 2071–2100 periods. These changes are not uniformly distributed throughout the year. The largest warming in the USA is found in the summertime, in Poland – in spring and autumn. For some months the discrepancies in the projected stream temperature between various stream temperature models are large. Product unit neural network, logistic regression-based model or air2stream occasionally led to projections that differ from those obtained by the majority of models even by 2 °C. We strongly recommend using at least a few stream temperature models for analysing the impact of climate change on water temperatures or the fate of the aquatic ecosystem. [ABSTRACT FROM AUTHOR]

Summary: Understanding the process of groundwater recharge is fundamental to the management of groundwater resources. Quantifying the future evolution of recharge over time requires not only the reliable forecasting of changes in key climatic variables, but also modelling their impact on the spatially varying recharge process. This paper presents a physically based methodology that can be used to characterize both the temporal and spatial effect of climate change on groundwater recharge. The method, based on the hydrologic model HELP3, can be used to estimate potential groundwater recharge at the regional scale with high spatial and temporal resolution. In this study, the method is used to simulate the past conditions, with 40years of actual weather data, and future changes in the hydrologic cycle of the Grand River watershed. The impact of climate change is modelled by perturbing the model input parameters using predicted changes in the regions climate. The results of the study indicate that the overall rate of groundwater recharge is predicted to increase as a result of climate change. The higher intensity and frequency of precipitation will also contribute significantly to surface runoff, while global warming may result in increased evapotranspiration rates. Warmer winter temperatures will reduce the extent of ground frost and shift the spring melt from spring toward winter, allowing more water to infiltrate into the ground. While many previous climate change impact studies have focused on the temporal changes in groundwater recharge, our results suggest that the impacts can also have high spatial variability. [Copyright &y& Elsevier]