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Assessing climate change risk to municipal water supplies is often conducted by hydrologic modeling specific to local watersheds and infrastructure to ensure that outputs are compatible with existing planning frameworks and processes. This study leverages the modeling capacity of an operational National Weather Service River Forecast Center to explore the potential impacts of future climate-driven hydrologic changes on factors important to planning at the Salt Lake City Department of Public Utilities (SLC). Hydrologic modeling results for the study area align with prior research in showing that temperature changes alone will lead to earlier runoff and reduced runoff volume. The sensitivity of average annual flow to temperature varies significantly between watersheds, averaging -3.8% °F-1 and ranging from 21.8% to 26.5% flow reduction per degree Fahrenheit of warming. The largest flow reductions occur during the high water demand months of May-September. Precipitation drives hydrologic response more strongly than temperature, with each 1% precipitation change producing an average 1.9% runoff change of the same sign. This paper explores the consequences of climate change for the reliability of SLC's water supply system using scenarios that include hydrologic changes in average conditions, severe drought scenarios, and future water demand test cases. The most significant water management impacts will be earlier and reduced runoff volume, which threaten the system's ability to maintain adequate streamflow and storage to meet late-summer water demands. [ABSTRACT FROM AUTHOR]

Climate change affects both the temperature and precipitation, leading to changes in river runoff. The Bago River basin is one of the most important agricultural regions in the Ayeyarwady Delta of Myanmar, and this paper aims to evaluate the impact of climate change on it. Linear scaling was used as the bias-correction method for ten general circulation models (GCMs) participating in the fifth phase of the Coupled Model Intercomparison Project. Future climate scenarios are predicted for three 27-year periods: the near future (2020–2046), middle future (2047–2073), and far future (2074–2100) with a baseline period of (1981–2005) under two Representative Concentration Pathway (RCP) scenarios: RCP4.5 and RCP8.5 of the IPCC Assessment Report 5 (AR5). The Hydrologic Engineering Center-Hydrologic Modeling System model is used to predict future discharge changes for the Bago River considering future average precipitation for all three future periods. Among the GCMs used to simulate meteorological data in the Ayeyarwady Delta zone, the Model for Interdisciplinary Research on Climate-Earth System is the most suitable. It predicts that average monthly precipitation will fluctuate and that average annual precipitation will increase. Both average monthly and annual temperatures are expected to increase at the end of the 21st century under RCP4.5 and RCP8.5 scenarios. The simulation shows that the Bago River discharge will increase for all three future periods under both scenarios. [ABSTRACT FROM AUTHOR]

The objective of this paper is to quantify the various sources of uncertainty in the assessment of climate change impact on hydrology in the Tamakoshi River Basin, located in the north-eastern part of Nepal. Multiple climate and hydrological models were used to simulate future climate conditions and discharge in the basin. The simulated results of future climate and river discharge were analysed for the quantification of sources of uncertainty using two-way and three-way ANOVA. The results showed that temperature and precipitation in the study area are projected to change in near- (2010-2039), mid- (2040-2069) and far-future (2070-2099) periods. Maximum temperature is likely to rise by 1.75 °C under Representative Concentration Pathway (RCP) 4.5 and by 3.52 °C under RCP 8.5. Similarly, the minimum temperature is expected to rise by 2.10 °C under RCP 4.5 and by 3.73 °C under RCP 8.5 by the end of the twenty-first century. Similarly, the precipitation in the study area is expected to change by − 2.15% under RCP 4.5 and − 2.44% under RCP 8.5 scenarios. The future discharge in the study area was projected using two hydrological models, viz. Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center's Hydrologic Modelling System (HEC-HMS). The SWAT model projected discharge is expected to change by small amount, whereas HEC-HMS model projected considerably lower discharge in future compared to the baseline period. The results also show that future climate variables and river hydrology contain uncertainty due to the choice of climate models, RCP scenarios, bias correction methods and hydrological models. During wet days, more uncertainty is observed due to the use of different climate models, whereas during dry days, the use of different hydrological models has a greater effect on uncertainty. Inter-comparison of the impacts of different climate models reveals that the REMO climate model shows higher uncertainty in the prediction of precipitation and, consequently, in the prediction of future discharge and maximum probable flood. [ABSTRACT FROM AUTHOR]

The objective of this paper was to analyze the temporal and spatial trends in annual and seasonal precipitation in Slovakia utilizing 487 gauging station data collected statewide in the period from 1981 to 2013. The nonparametric Mann-Kendall (MK) statistical test, which has been widely used to assess the significance of trends in hydrological time series, was applied to detect the significant trends. The Theil-Sen (TS) approach was applied to quantify the trend magnitude, and the Sequential Mann-Kendall (SQMK) test was used to detect abrupt temporal trend shifts. In general, precipitation data in the study area have not changed during the last 33 years, and there are no big gaps. However, predominantly increasing trends in precipitation time series were found at most of the gauging stations in Slovakia. The results corroborate previous climatic studies in the area of central Europe. In Slovakia, there is evidence of different rain distribution from the monthly point of view. Decreasing trends were detected in December in the northern part of Slovakia, while the central and southern parts revealed increasing trends. Most of the stations showed increasing summer precipitation trends, especially in July. It is expected that the findings of this comprehensive study of precipitation trends over Slovakia will produce more insights for the understanding of the regional hydrological behavior in Slovakia over the last several decades. [ABSTRACT FROM AUTHOR]

Accurate estimates of the spatial and temporal variation in terrestrial water and energy fluxes and mean states are important for simulating regional hydrology and biogeochemistry in high-latitude regions. Furthermore, it is necessary to develop high-resolution hydroclimatological datasets at finer spatial resolutions than are currently available from global analyses. This study uses a regional climate model (RCM) to develop a hydroclimatological dataset for hydrologic and ecological application in the Western Arctic. The fifth-generation Penn State–NCAR Mesoscale Model (MM5) forced by global reanalysis products at the boundaries is used to perform 12 yr of simulation (1990 through 2001) over the Western Arctic. An analysis that compares the RCM simulations with independent observationally derived data sources is conducted to evaluate the temporal and spatial distribution of the mean states, variability, and trends during the period of simulation. The RCM simulation of sea level pressure agrees well with the reanalysis in terms of mean states, seasonality, and interannual variability. The RCM also simulates major spatial patterns of the observed climatology of surface air temperature (SAT), but RCM SAT is generally colder in the summertime and warmer in the wintertime in comparison with other datasets. Although there are biases in the mean state of SAT, the RCM simulations of the seasonal and interannual variability of SAT are similar to variability in observationally derived datasets. The RCM also simulates general spatial patterns of observed rainfall, but the modeled mean state of precipitation is characterized by large biases relative to observationally derived datasets. In particular, the RCM tends to overestimate coastal region precipitation but underestimates precipitation in the interior of the Western Arctic. The Arctic terrestrial surface climate trends for the period of 1992 to 2001 of the RCM are similar to those derived from observations, with sea level pressure decreasing 0.15 hPa decade-1, SAT increasing 0.10°C decade-1, and precipitation decreasing slightly in the RCM simulations. In summary, the RCM dataset produced in this study represents an improvement over data currently available from large-scale global reanalysis and provides a consistent meteorological forcing dataset for hydrologic and ecological applications. [ABSTRACT FROM AUTHOR]

In recent decades, the Sahel has witnessed a paradoxical increase in surface water despite a general precipitation decline. This phenomenon, commonly referred to as "the Sahelian paradox", is not completely understood yet. The role of cropland expansion due to the increasing food demand by a growing population has been often put forward to explain this situation for the cultivated Sahel. However, this hypothesis does not hold in pastoral areas where the same phenomenon is observed. Several other processes, such as the degradation of natural vegetation following the major droughts of the 1970s and the 1980s, the development of crusted topsoils, the intensification of the rainfall regime and the development of the drainage network, have been suggested to account for this situation. In this paper, a modeling approach is proposed to explore, quantify and rank different processes that could be at play in pastoral Sahel. The kinematic runoff and erosion model (KINEROS-2) is applied to the Agoufou watershed (245km2), in the Gourma region in Mali, which underwent a significant increase of surface runoff during the last 60 years. Two periods are simulated, the "past" case (1960-1975) preceding the Sahelian drought and the "present" case (2000-2015). Surface hydrology and land cover characteristics for these two periods are derived by the analysis of aerial photographs, available in 1956, and high-resolution remote sensing images in 2011. The major changes identified are (1) a partial crusting of isolated dunes, (2) an increase of drainage network density, (3) a marked decrease in vegetation with the nonrecovery of tiger bush and vegetation growing on shallow sandy soils, and (4) important changes in soil properties with the apparition of impervious soils instead of shallow sandy soil. The KINEROS-2 model was parameterized to simulate these changes in combination or independently. The results obtained by this model display a significant increase in annual discharge between the "past" and the "present" case (p value<0.001), which is consistent with observations, despite a slight overestimation of the past discharge. Mean annual discharges are estimated at 0.5 ×106m³ (2. mmyr-1) and 3.29×106m³ (13.4mmyr-1) for past and present, respectively. Changes in soil properties and vegetation cover (tiger bush thickets and grassland on shallow sandy soil) are found to be the main factors causing this increase of simulated runoff, with the drainage network development contributing to a lesser extent but with a positive feedback. These results shed a new light on the Sahelian paradox phenomenon in the absence of land use change and call for further tests in other areas and/or with other models. The synergetic processes highlighted here could play a role in other Sahelian watersheds where runoff increase has been also observed. [ABSTRACT FROM AUTHOR]

Important hydrological changes are observed in Serbia, as well as in many parts of the world. Many national and international projects and studies address climate change and its impact on water resources. Some focus solely on the impact of climate change, while others also assess the impact of land use changes and/or changes in human use of water. Due to differences in climate change and human activities, the different climate and hydrological trends are obtained for the different regions in Serbia. This paper presents the past longterm temperature, precipitation and river discharge trends across Serbia. Second, more important aim of the research, is to assess and forecast average relationships between an increase in air temperature and changes in river discharges and precipitation. This relation could help us to find appropriate regional climate and hydrological models. Even within a single catchment, depending on the regional models used, the initial and other assumptions made, and the impacts assessed, the differences between the results can be small but often significant, too. The reliability of the projections receives little or no consideration. This paper also discusses this topic and attempts to provide some guidelines. [ABSTRACT FROM AUTHOR]

Planning adaptation strategies in response to climate change (CC) can be a daunting task, especially in regions such as the Koshi Basin in the Himalayas, where CC impacts are still uncertain. This paper recommends targeting adaptation strategies by focusing on changes in variability between the past and future climates at smaller scales. The Soil and Water Assessment Tool (SWAT) and the Indicators of Hydrologic Alteration (IHA) are used for analysis. The results show: (a) higher maximum precipitation during monsoon and post-monsoon, and lower maximum precipitation during winter; (b) increase in precipitation and flows in the Trans-mountain region during all seasons, except for flows during monsoon; (c) increase in post-monsoon precipitation and routed flow volumes; (d) decrease in precipitation during winter and routed flow volumes in all the regions, except the Trans-mountain region; and (e) increase in frequency of high peak flows and decrease in baseflows.Editor Z.W. Kundzewicz Associate editor S. Kanae; [ABSTRACT FROM AUTHOR]

Because of the limitations of coarse-resolution general circulation models (GCMs), delta change (DC) methods are generally used to derive scenarios of future climate as inputs into impact models. In this paper, the impact of future climate change on irrigation was investigated over China using the Community Land Model, version 4 (CLM4), which was calibrated against observed irrigation water demand (IWD) at the provincial level. The results show large differences in projected changes of IWD variability, extremes, timing, and regional responses between the DC and bias-corrected (BC) methods. For example, 95th-percentile IWD increased by 62% in the BC method compared to only a 28% increase in the DC method. In addition, a shift of seasonal IWD peaks (averaged over the country) to one month later in the year was projected when using the BC method, whereas no evident changes were predicted when using the DC method. Furthermore, low-percentile runoff has larger impacts in the BC method compared with proportional changes in the DC method, indicating that hydrological droughts seem to be exacerbated by increased climate variability. The discrepancies between the two methods were potentially due to the inability of the DC method to capture the changes in precipitation variability. Therefore, the authors highlight the potential effects of climate variability and the sensitivity to the choice of particular strategy-adjusting climate projection in assessing climate change impacts on irrigation. Some caveats, however, should be placed around interpretation of simulated percentage changes for all of China since a large model bias was found in southern China. [ABSTRACT FROM AUTHOR]

Potential evapotranspiration (PET) is the water that would be lost by plants through evaporation and transpiration if water was not limited in the soil, and it is commonly used in conceptual hydrological modelling in the calculation of runoff production and hence river discharge. Future changes of PET are likely to be as important as changes in precipitation patterns in determining changes in river flows. However PET is not calculated routinely by climate models so it must be derived independently when the impact of climate change on river flow is to be assessed. This paper compares PET estimates from 12 equations of different complexity, driven by the Hadley Centre's HadRM3-Q0 model outputs representative of 1961-1990, with MORECS PET, a product used as reference PET in Great Britain. The results show that the FAO56 version of the Penman-Monteith equations reproduces best the spatial and seasonal variability of MORECS PET across GB when driven by HadRM3-Q0 estimates of relative humidity, total cloud, wind speed and linearly bias-corrected mean surface temperature. This suggests that potential biases in HadRM3-Q0 climate do not result in significant biases when the physically based FAO56 equations are used. Percentage changes in PET between the 1961-1990 and 2041-2070 time slices were also calculated for each of the 12 PET equations from HadRM3-Q0. Results show a large variation in the magnitude (and sometimes direction) of changes estimated from different PET equations, with Turc, Jensen-Haise and calibrated Blaney-Criddle methods systematically projecting the largest increases across GB for all months and Priestley- Taylor, Makkink, and Thornthwaite showing the smallest changes. We recommend the use of the FAO56 equation as, when driven by HadRM3-Q0 climate data, this best reproduces the reference MORECS PET across Great Britain for the reference period of 1961-1990. Further, the future changes of PET estimated by FAO56 are within the range of uncertainty defined by the ensemble of 12 PET equations. The changes show a clear northwest-southeast gradient of PET increase with largest (smallest) changes in the northwest in January (July and October) respectively. However, the range in magnitude of PET changes due to the choice of PET method shown in this study for Great Britain suggests that PET uncertainty is a challenge facing the assessment of climate change impact on hydrology mostly ignored up to now. [ABSTRACT FROM AUTHOR]

Abstract: This paper reviews the possible future situation of the Rhone River in the Swiss part of its catchment. Physical processes in the Alps govern the behaviour of the Rhone from its source (Rhone Glacier) to the Lake of Geneva, and substantial changes are expected to occur in the amount and seasonality of precipitation, and in the response of snow and glaciers to a warming climate. As a result, discharge in the alpine part of the Rhone River is likely to undergo an increase in winter and early spring, but strongly decreases from late spring to late autumn. These changes in water regimes will certainly be accompanied by more frequent geomorphic hazards, related to increases in heavy precipitation events and the melting of permanently frozen grounds. The direct and indirect impacts of a warming climate will affect key economic sectors such as tourism, hydropower, and agriculture, while shifts in extreme events will have an impact on the vulnerability of infrastructure and a range of economic sectors and services. Projections of the future course of events can help in advance planning and decision making in order to alleviate some of the more negative consequences of climate and hydrological impacts on key economic sectors in the region. This paper will thus discuss issues related to current and future water governance in the region, whether water-related policies are sufficiently robust today to cope with what may be rapid changes in water availability and water use in coming decades, and to resolve possible rivalries between economic sectors that may be increasingly confronted with problems of water availability at critical times of the year. [Copyright &y& Elsevier]

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The integration of climate change projections into hydrological and other response models used for water resource planning and management is challenging given the varying spatial resolutions of the different models. In general, climate models are generated at spatial ranges of hundreds of kilometers, while hydrological models are generally watershed specific and based on input at the station or local level. This paper focuses on techniques applied to downscale large-scale climate model simulations to the spatial scale required by local response models (hydrological, agricultural, soil). Specifically, results were extracted from a regional climate model (RegCM) simulation focused on the Middle East, which was downscaled to a scale appropriate for input into a local watershed model [the Hydrological Model for Karst Environment (HYMKE)] calibrated for the upper Jordan River catchment. With this application, the authors evaluated the effect of future climate change on the amount and form of precipitation (rain or snow) and its effect on streamflow in the Jordan River and its tributaries—the major water resources in the region. They found that the expected changes in the form of precipitation are nearly insignificant in terms of changing the timing of streamflow. Additionally, the results suggest a future increase in evaporation and decrease in average annual rainfall, supporting expected changes based on global models in this region. [ABSTRACT FROM AUTHOR]

Central Europe, the focus region of this study, is a region in transition, climatically from maritime to continental and politically from formerly more planning-oriented to more market-oriented management regimes, and in terms of climate change from regions of increasing precipitation in the west and north of Europe to regions of decreasing precipitation in central and southern Europe. The Elbe basin, a trans-boundary catchment flowing from the Czech Republic through Germany into the North Sea, was selected to investigate the possible impacts of global change on crop yields and water resources in this region. For technical reasons, the paper has been split into two parts, the first showing the overall model concept, the model set-up for the agricultural sector, and first results linking eco-hydrological and agro-economic tools for the German part of the basin. The second part describes the model setup for simulating water supply and demand linking ecohydrological and water management tools for the entire basin including the Czech part. [ABSTRACT FROM AUTHOR]

Integrated surface water–groundwater (SW–GW) models could be used to assess the impacts of climate change or variability on the hydrological cycle. However, the damping effects of the hydrological system have rarely been explored via integrated SW–GW modeling. This paper presents an integrated modeling study in a typical humid area, the Miho catchment in Korea, using an integrated model called Groundwater and Surface-water FLOW (GSFLOW). The major findings of this study are as follows: (1) The simulated results from 2005 to 2014 indicate that the temporal variability in the streamflow, stream-groundwater interactions and groundwater recharge are dominated by the precipitation, while the temporal variability in the evapotranspiration (ET) is controlled by the energy conditions; (2) Damping effects can affect the hydrological cycle across different temporal and spatial scales. At the catchment scale, the soil zone and aquifer play a dominant role in damping the precipitation on monthly and annual time scales, respectively; (3) Variability in the capacity to buffer earlier precipitation is found at small spatial scales, such as streams, and larger spatial scales, such as the whole catchment. This variability could affect the water balance at larger spatial scales and affect the hydrography recession at smaller spatial scales. [ABSTRACT FROM AUTHOR]

This paper presents the first comprehensive nationwide trend detection of mean discharges in Croatia. Over the last 30 years, global climate change has manifested itself largely in the rise of the average annual temperature, which has resulted in the changes of evapotranspiration and precipitation patterns. The consequences of those changes have been varied spatial impacts on river discharge (flow). We analysed the changes in mean river discharges in Croatia at 53 gauging hydrological stations over the most recent period from 1990 to 2009. To assess the trend, the Kendall-Theil (Sen) non-parametric trend test was carried out for the yearly and seasonal mean discharge values. We found evidence of redistribution of discharge throughout the year, an increase in autumn and winter discharges (especially on the rivers dominantly fed by snowmelt) and a decrease in summer discharge values. Furthermore, we detected a change in the month of the appearance of mean discharge maxima and minima. In most cases the changes can be explained by the changes in the regime of climate elements (temperature, precipitation, evapotranspiration) although that information should be treated with care because of the shortness of the time-series. The results are consistent with the ones from the upstream countries, i.e. Slovenia and Austria. [ABSTRACT FROM AUTHOR]

Homogeneous time series of meteorological variables are necessary for hydrologic and climate studies. Dependability of historical precipitation data is subjected to keen evaluation prior to every study in water resources, hydrology, and climate change fields. This study aims to characterize the homogeneity of long-term Turkish precipitation data in order to ensure that they can be reliably used. The homogeneity of monthly precipitation data set was tested using the standard normal homogeneity test, Buishand test, Von Neumann ratio test, and Pettitt test at the 5% significance level across Turkey. Our precipitation records including the most updated observations, extracted from 160 meteorological stations, for the periods 1974-2014 were analyzed by all the four homogeneity tests. According to the results of all tests, five out of 160 stations have an inhomogeneity. With regard to our strict confirmation rule, 44 out of 160 stations are said to be inhomogeneous since they failed from at least one of the four tests. The breaks captured by the Buishand and Pettitt tests usually tend to appear in the middle of the precipitation series, whereas the ability of standard normal homogeneity test is in favor of identifying inhomogeneities mostly at the beginning or at the end of the records. Our results showed that 42 out of 44 inhomogeneous stations passed all the four tests after applying a correction procedure based on the double mass curve analysis. Available metadata was used to interpret the detected inhomogeneity. [ABSTRACT FROM AUTHOR]

In this study, the Providing Regional Climates for Impacts Studies (PRECIS) and the Regional Climate Model (RegCM) system as well as the Variable Infiltration Capacity (VIC) macroscale hydrologic model were integrated into a general framework to investigate impacts of future climates on the hydrologic regime of the Athabasca River basin. Regional climate models (RCMs) including PRECIS and RegCM were used to develop ensemble high-resolution climate projections for 1979–2099. RCMs were driven by the boundary conditions from the Hadley Centre Global Environment Model, version 2 with Earth system configurations (HadGEM2-ES); the Second Generation Canadian Earth System Model (CanESM2); and the Geophysical Fluid Dynamics Laboratory Earth System Model with MOM (GFDL-ESM2M) under the representative concentration pathways (RCPs). The ensemble climate simulations were validated through comparison with observations for 1984–2003. The RCMs project increases in temperature, precipitation, and wind speed under RCPs across most of the Athabasca River basin. Meanwhile, VIC was calibrated using the University of Arizona Shuffled Complex Evolution method (SCE-UA). The performance of the VIC model in replicating the characteristics of the observed streamflow was validated for 1994–2003. Changes in runoff and streamflow under RCPs were then simulated by the validated VIC model. The validation results demonstrate that the ensemble-RCM-driven VIC model can effectively reproduce historical climatological and hydrological patterns in the Athabasca River basin. The ensemble-RCM-driven VIC model shows that monthly streamflow is projected to increase in the 2050s and 2080s under RCPs, with notably higher flows expected in the spring for the 2080s. This will have substantial impacts on water balance on the Athabasca River basin, thus affecting the surrounding industry and ecosystems. The developed framework can be applied to other regions for exploration of hydrologic impacts under climate change. [ABSTRACT FROM AUTHOR]

An increase in extreme precipitation is projected for many areas worldwide in the coming decades. To assess the impact of increased precipitation intensity on water security, we applied a regional-scale hydrological and soil erosion model, forced with regional climate model projections. We specifically considered the impact of climate change on the distribution of water between soil (green water) and surface water (blue water) compartments. We show that an increase in precipitation intensity leads to a redistribution of water within the catchment, where water storage in soil decreases and reservoir inflow increases. This affects plant water stress and the potential of rainfed versus irrigated agriculture, and increases dependency on reservoir storage, which is potentially threatened by increased soil erosion. This study demonstrates the crucial importance of accounting for the fact that increased precipitation intensity leads to water redistribution between green and blue water, increased soil erosion, and reduced water security. Ultimately, this has implications for design of climate change adaptation measures, which should aim to increase the water holding capacity of the soil (green water) and to maintain the storage capacity of reservoirs (blue water), benefiting rainfed and irrigated agriculture. [ABSTRACT FROM AUTHOR]

The Colorado River basin (CRB) is one of the most important watersheds for energy, water, and food security in the United States. CRB water supports 15% of U.S. food production, more than 50 GW of electricity capacity, and one of the fastest growing populations in the United States. Energy–water–food nexus impacts from climate change are projected to increase in the CRB. These include a higher incidence of extreme events, widespread snow-to-rain regime shifts, and a higher frequency and magnitude of climate-driven disturbances. Here, we empirically show how the historical annual streamflow maximum and hydrograph centroid timing relate to temperature, precipitation, and snow. In addition, we show how these hydroclimatic relationships vary with elevation and how the elevation dependence has changed over this historical observational record. We find temperature and precipitation have a relatively weak relation (|r| < 0.3) to interannual variations in streamflow timing and extremes at low elevations (<1500 m), but a relatively strong relation (|r| > 0.5) at high elevations (>2300 m) where more snow occurs in the CRB. The threshold elevation where this relationship is strongest (|r| > 0.5) is moving uphill at a rate of up to 4.8 m yr−1 (p = 0.11) and 6.1 m yr−1 (p = 0.01) for temperature and precipitation, respectively. Based on these findings, we hypothesize where warming and precipitation-related streamflow changes are likely to be most severe using a watershed-scale vulnerability map to prioritize areas for further research and to inform energy, water, and food resource management in the CRB. [ABSTRACT FROM AUTHOR]

Western United States wildfire increases have been generally attributed to warming temperatures, either through effects on winter snowpack or summer evaporation. However, near-surface air temperature and evaporative demand are strongly influenced by moisture availability and these interactions and their role in regulating fire activity have never been fully explored. Here we show that previously unnoted declines in summer precipitation from 1979 to 2016 across 31-45%of the forested areas in the western United States are strongly associated with burned area variations. The number of wetting rain days (WRD; days with precipitation ≥2.54 mm) during the fire season partially regulated the temperature and subsequent vapor pressure deficit (VPD) previously implicated as a primary driver of annual wildfire area burned. We use path analysis to decompose the relative influence of declining snowpack, rising temperatures, and declining precipitation on observed fire activity increases. After accounting for interactions, the net effect of WRD anomalies on wildfire area burned was more than 2.5 times greater than the net effect of VPD, and both the WRD and VPD effects were substantially greater than the influence of winter snowpack. These results suggest that precipitation during the fire season exerts the strongest control on burned area either directly through its wetting effects or indirectly through feedbacks to VPD. If these trends persist, decreases in summer precipitation and the associated summertime aridity increases would lead to more burned area across the western United States with farreaching ecological and socioeconomic impacts. [ABSTRACT FROM AUTHOR]

Accounting for climate change, GCM-based projections and their uncertainty are relevant to study potential impacts on hydrological regimes as well as to analyze, operate, and design water infrastructure. Traditionally, several downscaled and/or bias-corrected GCM projections are individually or jointly used to map the raw GCMs' changes to local stations and evaluate uncertainty. However, the preservation of GCMs' statistical attributes is by no means guaranteed, and thus alternative methods to cope with this issue are needed. This work develops an ensemble technique for the unbiased mapping of GCM changes to local stations, which preserves local climate variability and the GCMs' statistics. In the approach, trend percentiles are extracted from the GCMs to represent the range of future long-term climate conditions to which local climatic variability is added. The approach is compared against a method in which each GCM is individually used to build future climatic scenarios from which percentiles are computed. Both approaches were compared to study future precipitation conditions in three Chilean basins under future climate projections based on 45 GCM runs under the RCP8.5 scenario. Overall, the approaches produce very similar results, even if a few trend percentiles are adopted in the GCM preanalysis. In fact, using 5–10 percentiles produces a mean absolute difference of 0.4% in the estimation of the probabilities of consecutive years under different precipitation thresholds, which is ~60% less than the error obtained using the median trend. Thus, the approach successfully preserves the GCM's statistical attributes while incorporating the range of projected climates. [ABSTRACT FROM AUTHOR]

Drought and vegetation conditions within the Damqu River Basin, part of the Yangtze River Source Region (YRSR), are assessed here using the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), the normalized difference vegetation index (NDVI), and the leaf area index (LAI). We utilized Sen’s method, least squares regression method, linear regression and Pearson’s correlation analysis to study variations in drought and vegetation indices and the drought effect on vegetation between 1988 and 2015. Results reveal that droughts occurred at a 25% frequency over this period; SPI and SPEI analyses show that 1994, 1999, 2005, and 2010 were change points and that the basin was characterized by varying drought and humidity trends. Subsequent to 2010, both SPI and SPEI decreased within the basin, while 1995, 2000, 2004, and 2010 were change points for NDVI and LAI while the watershed exhibited variable trends in vegetation reduction and increase. The NDVI-annual values of 63.36% regions and the LAI-summer values of 68.39% areas within the basin were decreased during 1988–2015 and 2000–2015, respectively. Subsequent to 2010, both NDVI and LAI decreased within the basin and significant positive correlations at inter-annual and inter-summer time scales were seen in both drought and vegetation indices; drought has exerted a lag effect on vegetation as shown by significant positive correlations between annual SPI/SPEI values and following year NDVI/LAI values. [ABSTRACT FROM AUTHOR]

A baseflow separation methodology combining the outcomes of the flow-duration curve and the digital filtering algorithms to cope with the restrictions of traditional procedures has been assessed. Using this methodology as well as the monitored and simulated hydro-climatological data, the baseflow annual variations due to climate change and human-induced activities were determined. The outcomes show that the long-term baseflow index at the upstream sub-basin is nearly half of that at the downstream from October to April, whereas they are close to each other for the remaining months. Some of the groundwater reacts to precipitation and an evident rise in the groundwater contribution was detected for the hydrological years 1998-2001 and 2006-2008. The contrary was recorded for1987. The water released from the reservoir in the dry periods led to distinctions in the detected baseflow index between the pre-damming and post-damming periods of the river. [ABSTRACT FROM AUTHOR]

Climate change projections show that temperature and precipitation increases can alter the exchange of greenhouse gases between the atmosphere and high latitude landscapes, including their freshwaters. Dissolved organic carbon (DOC) plays an important role in greenhouse gas emissions, but the impact of catchment productivity on DOC release to subarctic waters remains poorly known, especially at regional scales. We test the hypothesis that increased terrestrial productivity, as indicated by the normalized difference vegetation index (NDVI), generates higher stream DOC concentrations in the Stordalen catchment in subarctic Sweden. Furthermore, we aimed to determine the degree to which other generic catchment properties (elevation, slope) explain DOC concentration, and whether or not land cover variables representing the local vegetation type (e.g., mire, forest) need to be included to obtain adequate predictive models for DOC delivered into rivers. We show that the land cover type, especially the proportion of mire, played a dominant role in the catchment’s release of DOC, while NDVI, slope, and elevation were supporting predictor variables. The NDVI as a single predictor showed weak and inconsistent relationships to DOC concentrations in recipient waters, yet NDVI was a significant positive regulator of DOC in multiple regression models that included land cover variables. Our study illustrates that vegetation type exerts primary control in DOC regulation in Stordalen, while productivity (NDVI) is of secondary importance. Thus, predictive multiple linear regression models for DOC can be utilized combining these different types of explanatory variables. [ABSTRACT FROM AUTHOR]

Land surface water and energy fluxes from the ensemble mean of the Atmospheric Model Intercomparison Project (AMIP) simulations of a Geophysical Fluid Dynamics Laboratory (GFDL) high-resolution climate model (AM2.5) were evaluated using offline simulations of a calibrated land surface model [Princeton Global Forcing (PGF)/VIC] and intercompared with three reanalysis datasets: MERRA-Land, ERA-Interim/Land, and CFSR. Using PGF/VIC as the reference, the AM2.5 precipitation, evapotranspiration, and runoff showed a global positive bias of ~0.44, ~0.27, and ~0.15 mm day−1, respectively. For the energy budget, while the AM2.5 net radiation agreed very well with the PGF/VIC, the AM2.5 improperly partitioned the net radiation, with the latent heat showing positive bias and sensible heat showing negative bias. The AM2.5 net radiation, latent heat, and sensible heat relative to the PGF/VIC had a global negative bias of ~1.42 W m−2, positive bias of ~7.8 W m−2, and negative bias of ~8.7 W m−2, respectively. The three reanalyses show greater biases in net radiation, likely due to the deficiencies in cloud parameterizations. At a regional scale, the biases of the AM2.5 water and energy budget components are mostly comparable to the three reanalyses and PGF/VIC. While the AM2.5 well simulated the actual values of water and energy fluxes, the temporal anomaly correlations of the three reanalyses with PGF/VIC were mostly greater than the AM2.5, partly due to the ensemble mean of the AM2.5 members averaging out the intrinsic variability of the land surface fluxes. The discrepancies among land surface model simulations, reanalyses, and high-resolution climate model simulations demonstrate the challenges in estimating and evaluating land surface hydrologic fluxes at regional-to-global scales. [ABSTRACT FROM AUTHOR]

There is a growing research interest in the detection of changes in hydrologic and climatic time series. Stationarity can be assessed using the autocorrelation function, but this is not yet common practice in hydrology and climate. Here, we use a global land-based gridded annual precipitation (hereafter P) database (1940-2009) and find that the lag 1 autocorrelation coefficient is statistically significant at around 14% of the global land surface, implying nonstationary behavior (90% confidence). In contrast, around 76% of the global land surface shows little or no change, implying stationary behavior. We use these results to assess change in the observed P over the most recent decade of the database. We find that the changes for most (84%) grid boxes are within the plausible bounds of no significant change at the 90% CI. The results emphasize the importance of adequately accounting for natural variability when assessing change. [ABSTRACT FROM AUTHOR]

Hydro-meteorological extremes such as drought and heavy precipitation can have large impacts on society and the economy. With potentially increasing risks associated with such events due to climate change, properly assessing the associated impacts and uncertainties is critical for adequate adaptation. However, the application of riskbased approaches often requires large sets of extreme events, which are not commonly available. Here, we present such a large set of hydro-meteorological time series for recent past and future conditions for the United Kingdom based on weather@home 2, a modelling framework consisting of a global climate model (GCM) driven by observed or projected sea surface temperature (SST) and sea ice which is downscaled to 25 km over the European domain by a regional climate model (RCM). Sets of 100 time series are generated for each of (i) a historical baseline (1900-2006), (ii) five nearfuture scenarios (2020-2049) and (iii) five far-future scenarios (2070-2099). The five scenarios in each future time slice all follow the Representative Concentration Pathway 8.5 (RCP8.5) and sample the range of sea surface temperature and sea ice changes from CMIP5 (Coupled Model Intercomparison Project Phase 5) models. Validation of the historical baseline highlights good performance for temperature and potential evaporation, but substantial seasonal biases in mean precipitation, which are corrected using a linear approach. For extremes in low precipitation over a long accumulation period (> 3 months) and shorter-duration high precipitation (1-30 days), the time series generally represents past statistics well. Future projections show small precipitation increases in winter but large decreases in summer on average, leading to an overall drying, consistently with the most recent UK Climate Projections (UKCP09) but larger in magnitude than the latter. Both drought and high-precipitation events are projected to increase in frequency and intensity in most regions, highlighting the need for appropriate adaptation measures. Overall, the presented dataset is a useful tool for assessing the risk associated with drought and more generally with hydro-meteorological extremes in the UK. [ABSTRACT FROM AUTHOR]

A semi-distributed hydrological model of the Upper Niger and the Inner Niger Delta is used to investigate the RCP 4.5 scenario for 41 CMIP5 GCMs in the 2050s and 2080s. In percentage terms, the range of change in precipitation is around four times as large as for potential evapotranspiration, which increases for most GCMs over most sub-catchments. Almost equal numbers of sub-catchment–GCM combinations experience positive and negative precipitation change. River discharge changes are equally uncertain. Inter-GCM range in mean discharge exceeds that of precipitation by three times in percentage terms. Declining seasonal flooding within the Inner Delta is dominant; 78 and 68% of GCMs project declines in October and November for the 2050s and 2080s, respectively. The 10- and 90-percentile changes in mean annual peak inundation range from −6136 km2(−43%) to +987 km2(+7%) for the 2050s and −6176 km2(−43%) to +1165 km2(+8.2%) for the 2080s. [ABSTRACT FROM PUBLISHER]

This study is an attempt to determine the trends in monthly, annual and monsoon total precipitation series over India by applying linear regression, the Mann-Kendall (MK) test and discrete wavelet transform (DWT). The linear regression test was applied on five consecutive classical 30-year climate periods and a long-term precipitation series (1851–2006) to detect changes. The sequential Mann-Kendall (SQMK) test was applied to identify the temporal variation in trend. Wavelet transform is a relatively new tool for trend analysis in hydrology. Comparison studies were carried out between decomposed series by DWT and original series. Furthermore, visualization of extreme and contributing events was carried out using the wavelet spectrum at different threshold values. The results showed that there are significant positive trends for annual and monsoon precipitation series in North Mountainous India (zone NMI) and North East India (NEI), whereas negative trends were detected when considering India as whole. EDITOR A. Castellarin ASSOCIATE EDITOR S. Kanae [ABSTRACT FROM PUBLISHER]

Daytime (0800-2000 Beijing time) and nighttime (2000-0800 Beijing time) precipitation at approximately 2100 stations in China from 1979 to 2014 was used to evaluate eight current reanalyses. Daytime, nighttime, and nighttime-daytime contrast of precipitation were examined in aspects of climatology, seasonal cycle, interannual variability, and trends. The results show that the ECMWF interim reanalysis (ERA-Interim), ERA-Interim/Land, Japanese 55-year Reanalysis (JRA-55), and NCEP Climate Forecast System Reanalysis (CFSR) can reproduce the observed spatial pattern of nighttime-daytime contrast in precipitation amount, exhibiting a positive center over the eastern Tibetan Plateau and a negative center over southeastern China. All of the reanalyses roughly reproduce seasonal variations of nighttime and daytime precipitation, but not always nighttime-daytime contrast. The reanalyses overestimate drizzle and light precipitation frequencies by greater than 31.5% and underestimate heavy precipitation frequencies by less than −30.8%. The reanalyses successfully reproduce interannual synchronizations of daytime and nighttime precipitation frequencies and amounts with an averaged correlation coefficient r of 0.66 against the observed data but overestimate their year-to-year amplitudes by approximately 64%. The trends in nighttime, daytime, and nighttime-daytime contrast of the observed precipitation amounts are mainly dominated by their frequencies ( r = 0.85). Less than moderate precipitation frequency has exhibited a significant downward trend (−2.5% decade−1 during nighttime and −1.7% decade−1 during daytime) since 1979, which is roughly captured by the reanalyses. However, only JRA-55 captures the observed trend of nighttime precipitation intensity (2.4% decade−1), while the remaining reanalyses show negative trends. Overall, JRA-55 and CFSR provide the best reproductions of the observed nighttime-daytime contrast in precipitation intensity, although they have considerable room for improvement. [ABSTRACT FROM AUTHOR]

For 14 alternative climate futures, water yield and snow water equivalent (SWE) throughout the contiguous United States (CONUS) were projected over the twenty-first century using the Variable Infiltration Capacity model (VIC). The futures correspond to climate projections from seven CMIP5 models each forced by two representative concentration pathways for greenhouse gases (RCP4.5 and RCP8.5). With both RCPs, decreases in water yields are projected for roughly two-thirds of the CONUS, and in 60% of that area-mainly at more northern latitudes, where the greatest temperature increases are expected-this occurs despite projected increases in precipitation. The greatest relative decreases in yield are projected for the southern Great Plains and the Southwest, where temperature and precipitation changes combine to decrease yield. Snow accumulation is projected to decrease almost everywhere by the latter half of the century, with the time of peak SWE in some basins projected to occur up to 2 months earlier than it now does. These changes, should they come to pass, will challenge the adaptation capacity of future water management. [ABSTRACT FROM AUTHOR]

Future climate forcing data at the temporal and spatial scales needed to drive hydrologic models are not readily available. Simple methods to derive these data from historical data or General Circulation Model (GCM) results may not adequately capture future hydrological variability. This study assessed streamflow response to daily future climate forcing data produced by a new method using subsets of multi-model GCM ensembles for the mid-21st century period in northeast Kansas. Daily timeseries of precipitation and temperature were developed for six future climate scenarios: stationary, uniform 10% changes in precipitation; shifts based on a 15-GCM ensemble-mean; and shifts based on three seasonally-consistent subsets of GCMs representing Spring-Summer combinations that were wetter or drier than the historical period. The analysis of daily streamflow and hydrologic index statistics were conducted. Stationary 10% precipitation shifts generally bounded the monthly mean streamflow projections of the other scenarios, and the 15-GCM ensemble-mean captured non-stationary effects of annual and seasonal hydrological response, but did not identify important intra-annual shifts in drought and flood characteristics. The seasonally-consistent subset ensembles produced a range of distinct monthly streamflow trends, particularly for extreme low-flow and high-flow events. Meaningful water management and planning for the future will require hydrological impact simulations that reflect the range of possible future climates. Use of GCM ensemble-mean climate forcing data without consideration of the range of seasonal patterns among models was demonstrated to remove important seasonal hydrologic patterns that were retained in the subset ensemble-mean approach. [ABSTRACT FROM AUTHOR]

The outputs from general circulation models (GCMs) provide useful information about the rate and magnitude of future climate change. The temperature variable is more reliable than other variables in GCM outputs. However, hydrological variables (e.g., precipitation) from GCM outputs for future climate change possess an uncertainty that is too high for practical use. Therefore, a method called intentionally biased bootstrapping (IBB), which simulates the increase of the temperature variable by a certain level as ascertained from observed global warming data, is proposed. In addition, precipitation data were resampled by employing a block-wise sampling technique associated with the temperature simulation. In summary, a warming temperature scenario is simulated, along with the corresponding precipitation values whose time indices are the same as those of the simulated warming temperature scenario. The proposed method was validated with annual precipitation data by truncating the recent years of the record. The proposed model was also employed to assess the future changes in seasonal precipitation in South Korea within a global warming scenario as well as in weekly timescales. The results illustrate that the proposed method is a good alternative for assessing the variation of hydrological variables such as precipitation under the warming condition. [ABSTRACT FROM AUTHOR]

Drought is a multi-attribute hazard that impacts environment and economy, both during and after the event. Drought can be characterised by its severity (S), duration (D) and frequency (F). Drought severity and duration are commonly defined using measures such as the Standardized Precipitation Index (SPI). The objectives of this study were to model the joint severity-duration distribution using a nonparametric density estimator and combine this distribution with frequency to derive drought SDF curves. We used a copula to model the joint drought duration-severity distribution and frequency to generate SDF curves for six locations in different climatic regions (three locations in the North Island and three locations in the South Island) of New Zealand. The copula model was fitted to drought duration and severity by means of a bivariate beta kernel-based function. Based on this bivariate-fitted model for duration and severity, drought SDF curves for various recurrence intervals were derived. The observed interdependence structure between severity and duration suggested a bivariate model was appropriate to use for drought analysis. We found that North Island locations experienced more dry spells than the South Island locations. The SDF curves developed for the six locations in the study provide a comprehensive understanding of occurrence and duration of dry conditions, and can be a useful tool for natural resource managers in developing short and longterm drought mitigation strategies for water management and conservation. [ABSTRACT FROM AUTHOR]

Global warming accelerates water cycle with features of regional difference. However, little is known about the physical mechanism behind the phenomenon. To reveal the links between water cycle and climatic environment, we analyzed the changes of water cycle elements and their relationships with climatic and environmental factors. We found that when global warming was significant during the period of 1986-2003, the precipitation in Tarim mountains as well as Xinjiang increased rapidly except for Tarim plains, which indicated that there existed a signal of acceleration for water cycle in Xinjiang. The speed of water cycle is mainly affected by altitude, latitude, longitude, slope direction, and the most fundamental element is temperature. Moreover, according to Clausius-Kela Bai Lung relation, we found that the climate change induced the increase of temperature and accelerated the local water cycle only for the wet places. Our results provide a possible physical mechanisms of water cycle and thus well link the climate change to water circulation. [ABSTRACT FROM AUTHOR]

The aerial hydrological cycle response to CO2 doubling from a Lagrangian, rather than Eulerian, perspective is evaluated using information from numerical water tracers implemented in a global climate model. While increased surface evaporation (both local and remote) increases precipitation globally, changes in transport are necessary to create a spatial pattern where precipitation decreases in the subtropics and increases substantially at the equator. Overall, changes in the convergence of remotely evaporated moisture are more important to the overall precipitation change than changes in the amount of locally evaporated moisture that precipitates in situ. It is found that CO2 doubling increases the fraction of locally evaporated moisture that is exported, enhances moisture exchange between ocean basins, and shifts moisture convergence within a given basin toward greater distances between moisture source (evaporation) and sink (precipitation) regions. These changes can be understood in terms of the increased residence time of water in the atmosphere with CO2 doubling, which corresponds to an increase in the advective length scale of moisture transport. As a result, the distance between where moisture evaporates and where it precipitates increases. Analyses of several heuristic models further support this finding. [ABSTRACT FROM AUTHOR]

Postprocessing of climate model outputs is usually performed to remove biases prior to performing climate change impact studies. The evaluation of the performance of bias correction methods is routinely done by comparing postprocessed outputs to observed data. However, such an approach does not take into account the inherent uncertainty linked to natural climate variability and may end up recommending unnecessary complex postprocessing methods. This study evaluates the performance of bias correction methods using natural variability as a baseline. This baseline implies that any bias between model simulations and observations is only significant if it is larger than the natural climate variability. Four bias correction methods are evaluated with respect to reproducing a set of climatic and hydrological statistics. When using natural variability as a baseline, complex bias correction methods still outperform the simplest ones for precipitation and temperature time series, although the differences are much smaller than in all previous studies. However, after driving a hydrological model using the bias-corrected precipitation and temperature, all bias correction methods perform similarly with respect to reproducing 46 hydrological metrics over two watersheds in different climatic zones. The sophisticated distribution mapping correction methods show little advantage over the simplest scaling method. The main conclusion is that simple bias correction methods appear to be just as good as other more complex methods for hydrological climate change impact studies. While sophisticated methods may appear more theoretically sound, this additional complexity appears to be unjustified in hydrological impact studies when taking into account the uncertainty linked to natural climate variability. [ABSTRACT FROM AUTHOR]

Projections of regional climate, net basin supply (NBS), and water levels are developed for the mid- and late twenty-first century across the Laurentian Great Lakes basin. Two state-of-the-art global climate models (GCMs) are dynamically downscaled using a regional climate model (RCM) interactively coupled to a one-dimensional lake model, and then a hydrologic routing model is forced with time series of perturbed NBS. The dynamical downscaling and coupling with a lake model to represent the Great Lakes create added value beyond the parent GCM in terms of simulated seasonal cycles of temperature, precipitation, and surface fluxes. However, limitations related to this rudimentary treatment of the Great Lakes result in warm summer biases in lake temperatures, excessive ice cover, and an abnormally early peak in lake evaporation. While the downscaling of both GCMs led to consistent projections of increases in annual air temperature, precipitation, and all NBS components (overlake precipitation, basinwide runoff, and lake evaporation), the resulting projected water level trends are opposite in sign. Clearly, it is not sufficient to correctly simulate the signs of the projected change in each NBS component; one must also account for their relative magnitudes. The potential risk of more frequent episodes of lake levels below the low water datum, a critical shipping threshold, is explored. [ABSTRACT FROM AUTHOR]

Understanding the heterogeneity of climate change and its impacts on annual and seasonal discharge and the difference between median flow and extreme flow in different climate regions is of utmost importance to successful water management. To quantify the spatial and temporal heterogeneity of climate change impacts on hydrological processes, this study simulated river discharge in the River Huangfuchuan in semi-arid northern China and in the River Xiangxi in humid southern China. The study assessed the uncertainty in projected discharge for three time periods (2020s, 2050s and 2080s) using seven equally weighted GCMs (global climate models) for the SRES (Special Reports on Emissions Scenarios) A1B scenario. Climate projections that were applied to semi-distributed hydrological models (Soil Water Assessment Tools, SWAT) in both catchments showed trends toward warmer and wetter conditions, particularly for the River Huangfuchuan. Results based on seven GCMs' projections indicated changes from -1.1 to 8.6 °C and 0.3 to 7.0 °C in seasonal temperature and changes from -29 to 139% and -32 to 85%in seasonal precipitation in the rivers Huangfuchuan and Xiangxi, respectively. The largest increases in temperature and precipitation in both catchments were projected in the spring and winter seasons. The main projected hydrologic impact was a more pronounced increase in annual discharge in the River Huangfuchuan than in the River Xiangxi. Most of the GCMs projected increased discharge in all seasons, especially in spring, although the magnitude of these increases varied between GCMs. The peak flows were projected to appear earlier than usual in the River Huangfuchuan and later than usual in the River Xiangxi, while the GCMs were fairly consistent in projecting increased extreme flows in both catchments with varying magnitude compared to median flows. For the River Huangfuchuan in the 2080s, median flow changed from -2 to 304 %, compared to a -1 to 145% change in high flow (Q05 exceedance threshold). For the River Xiangxi, low flow (Q95 exceedance threshold) changed from -1 to 77% and high flow changed from -1 to 62 %, while median flow changed from -4 to 23 %. The uncertainty analysis provided an improved understanding of future hydrologic behavior in the watershed. Furthermore, this study indicated that the uncertainty constrained by GCMs was critical and should always be considered in analysis of climate change impacts and adaptation. [ABSTRACT FROM AUTHOR]

Recent analyses of extreme hydrological events across the United States, including those summarized in the recent U.S. Third National Climate Assessment (May 2014), show that extremely large (extreme) precipitation and streamflow events are increasing over much of the country, with particularly steep trends over the northeastern United States. The authors demonstrate that the increase in extreme hydrological events over the northeastern United States is primarily a warm season phenomenon and is caused more by an increase in frequency than magnitude. The frequency of extreme warm season events peaked during the 2000s; a secondary peak occurred during the 1970s; and the calmest decade was the 1960s. Cold season trends during the last 30-50 yr are weaker. Since extreme precipitation events in this region tend to be larger during the warm season than during the cold season, trend analyses based on annual precipitation values are influenced more by warm season than by cold season trends. In contrast, the magnitude of extreme streamflow events at stations used for climatological analyses tends to be larger during the cold season: therefore, extreme event analyses based on annual streamflow values are overwhelmingly influenced by cold season, and therefore weaker, trends. These results help to explain an apparent discrepancy in the literature, whereby increasing trends in extreme precipitation events appear to be significant and ubiquitous across the region, while trends in streamflow appear less dramatic and less spatially coherent. [ABSTRACT FROM AUTHOR]

Trend tests, linear regression, and canonical correlation analysis were used to quantify changes in National Weather Service Cooperative Observer (COOP) snow depth data and derived quantities, precipitation, snowfall, and temperature over the study period 1950-2010. Despite widespread warming, historical trends in snowfall and snow depth are generally mixed owing to competing influences of trends in precipitation. Trends toward later snow-cover onset in the western half of the conterminous United States and earlier onset in the eastern half and a widespread trend toward earlier final meltoff of snow cover combined to produce trends toward shorter snow seasons in the eastern half of the United States and in the west and longer snow seasons in the Great Plains and southern Rockies. The annual total number of days with snow cover exhibited a widespread decline. Monthly trend patterns show the dominant influence of temperature trends on occurrence of snow cover in the warmer snow-season months and a combination of temperature and precipitation trends in the colder months. A canonical correlation analysis indicated that most trends presented here took hold in the 1970s, consistent with the temporal pattern of global warming during the study period. [ABSTRACT FROM AUTHOR]

The aridity of a terrestrial climate is often quantified using the dimensionless ratio of annual precipitation ( P) to annual potential evapotranspiration (PET). In this study, the climatological patterns and greenhouse warming responses of terrestrial P, Penman-Monteith PET, and are compared among 16 modern global climate models. The large-scale climatological values and implied biome types often disagree widely among models, with large systematic differences from observational estimates. In addition, the PET climatologies often differ by several tens of percent when computed using monthly versus 3-hourly inputs. With greenhouse warming, land P does not systematically increase or decrease, except at high latitudes. Therefore, because of moderate, ubiquitous PET increases, decreases (drying) are much more widespread than increases (wetting) in the tropics, subtropics, and midlatitudes in most models, confirming and expanding on earlier findings. The PET increases are also somewhat sensitive to the time resolution of the inputs, although not as systematically as for the PET climatologies. The changes in the balance between P and PET are also quantified using an alternative aridity index, the ratio , which has a one-to-one but nonlinear correspondence with . It is argued that the magnitudes of changes are more uniformly relevant than the magnitudes of changes, which tend to be much higher in wetter regions. The ratio and its changes are also found to be excellent statistical predictors of the land surface evaporative fraction and its changes. [ABSTRACT FROM AUTHOR]

According to the Intergovernmental Panel on Climate Change report released in September 2014, unprecedented changes in temperature and precipitation patterns have been recorded globally in recent decades and further change is predicted to occur in the near future, mainly as the result of human activity. In particular, projections show that the Mediterranean climate zone will be markedly affected with significant implications for lake water levels and salinity. This may be exacerbated by increased demands for irrigation water. Based on long-term data from seven lakes and reservoirs covering a geographical gradient of 52° of latitudes and a literature review, we discuss how changes in water level and salinity related to climate change and water abstraction affect the ecosystem structure, function, biodiversity and ecological state of lakes and reservoirs. We discuss mitigation measures to counteract the negative effects on ecological status that are likely to result from changes in climate and water abstraction practices. Finally, we highlight research required to improve knowledge of the impacts of anthropogenically induced changes on lake water level and consequent changes in salinity. [ABSTRACT FROM AUTHOR]

There have been many published studies aiming to identify temporal changes in river flow time series, most of which use monotonic trend tests such as the Mann-Kendall test. Although robust to both the distribution of the data and incomplete records, these tests have important limitations and provide no information as to whether a change in variability mirrors a change in magnitude. This study develops a new method for detecting periods of change in a river flow time series, using temporally shifting variograms (TSVs) based on applying variograms to moving windows in a time series and comparing these to the long-term average variogram, which characterises the temporal dependence structure in the river flow time series. Variogram properties in each moving window can also be related to potential meteorological drivers. The method is applied to 91 UK catchments which were chosen to have minimal anthropogenic influences and good quality data between 1980 and 2012 inclusive. Each of the four variogram parameters (range, sill and two measures of semi-variance) characterise different aspects of the river flow regime, and have a different relationship with the precipitation characteristics. Three variogram parameters (the sill and the two measures of semi-variance) are related to variability (either day-to-day or over the time series) and have the largest correlations with indicators describing the magnitude and variability of precipitation. The fourth (the range) is dependent on the relationship between the river flow on successive days and is most correlated with the length of wet and dry periods. Two prominent periods of change were identified: 1995-2001 and 2004-2012. The first period of change is attributed to an increase in the magnitude of rainfall whilst the second period is attributed to an increase in variability of the rainfall. The study demonstrates that variograms have considerable potential for application in the detection and attribution of temporal variability and change in hydrological systems. [ABSTRACT FROM AUTHOR]

A hydrometeorological model chain is applied to investigate climate change effects on natural and artificial snow conditions in the Schladming region in Styria (Austria). Four dynamically refined realizations of the IPCC A1B scenario covering the warm/cold and wet/dry bandwidth of projected changes in temperature and precipitation in the winter half-year are statistically downscaled and bias corrected prior to their application as input for a physically based, distributed energy-balance snow model. However, owing to the poor skills in the reproduction of past climate and snow conditions in the considered region, one realization had to be removed from the selection to avoid biases in the results of the climate change impact analysis. The model's capabilities in the simulation of natural and artificial snow conditions are evaluated and changes in snow conditions are addressed by comparing the number of snow cover days, the length of the ski season, and the amounts of technically produced snow as simulated for the past and the future. The results for natural snow conditions indicate decreases in the number of snow cover days and the ski season length of up to >25 and >35 days, respectively. The highest decrease in the calculated ski season length has been found for elevations between 1600 and 2700 m MSL, with an average decrease rate of ~2.6 days decade−1. For the exemplary ski site considered, the ski season length simulated for natural snow conditions decreases from >50 days at present to ~40 days in the 2050s. Technical snow production allows the season to be prolonged by ~80 days and hence allows ski season lengths of ~120 days until the end of the scenario period in 2050. [ABSTRACT FROM AUTHOR]

A new technique for statistically downscaling climate model simulations of daily temperature and precipitation is introduced and demonstrated over the western United States. The localized constructed analogs (LOCA) method produces downscaled estimates suitable for hydrological simulations using a multiscale spatial matching scheme to pick appropriate analog days from observations. First, a pool of candidate observed analog days is chosen by matching the model field to be downscaled to observed days over the region that is positively correlated with the point being downscaled, which leads to a natural independence of the downscaling results to the extent of the domain being downscaled. Then, the one candidate analog day that best matches in the local area around the grid cell being downscaled is the single analog day used there. Most grid cells are downscaled using only the single locally selected analog day, but locations whose neighboring cells identify a different analog day use a weighted combination of the center and adjacent analog days to reduce edge discontinuities. By contrast, existing constructed analog methods typically use a weighted average of the same 30 analog days for the entire domain. By greatly reducing this averaging, LOCA produces better estimates of extreme days, constructs a more realistic depiction of the spatial coherence of the downscaled field, and reduces the problem of producing too many light-precipitation days. The LOCA method is more computationally expensive than existing constructed analog techniques, but it is still practical for downscaling numerous climate model simulations with limited computational resources. [ABSTRACT FROM AUTHOR]

Future climate projections robustly indicate that the Mediterranean region will experience a significant decrease of mean annual precipitation and an increase in temperature. These changes are expected to seriously affect the hydrologic regime, with a limitation of water availability and an intensification of hydrologic extremes, and to negatively impact local economies. In this study, we quantify the hydrologic impacts of climate change in the Rio Mannu basin (RMB), an agricultural watershed of 472.5 km² in Sardinia, Italy. To simulate the wide range of runoff generation mechanisms typical of Mediterranean basins, we adopted a physically based, distributed hydrologic model. The high-resolution forcings in reference and future conditions (30- year records for each period) were provided by four combinations of global and regional climate models, bias-corrected and downscaled in space and time (from ~25 km, 24 h to 5 km, 1 h) through statistical tools. The analysis of the hydrologic model outputs indicates that the RMB is expected to be severely impacted by future climate change. The range of simulations consistently predict (i) a significant diminution of mean annual runoff at the basin outlet, mainly due to a decreasing contribution of the runoff generation mechanisms depending on water available in the soil; (ii) modest variations in mean annual runoff and intensification of mean annual discharge maxima in flatter sub-basins with clay and loamy soils, likely due to a higher occurrence of infiltration excess runoff; (iii) reduction of soil water content and actual evapotranspiration in most areas of the basin; and (iv) a drop in the groundwater table. Results of this study are useful to support the adoption of adaptive strategies for management and planning of agricultural activities and water resources in the region. [ABSTRACT FROM AUTHOR]

Assessment of the reliability and quality of historical precipitation data is required in the modeling of hydrology and water resource processes and for climate change studies. The homogeneity of the annual and monthly precipitation data sets throughout Iran was tested using the Bayesian, Cumulative Deviations, and von Neumann tests at a significance level of 0.05. The precipitation records from 41 meteorological stations covering the years between 1966 and 2005 were considered. The annual series of Iranian precipitation were found to be homogeneous by applying the Bayesian and Cumulative Deviations tests, while the von Neumann test detected inhomogeneities at seven stations. Almost all the monthly precipitation data sets are homogeneous and considered as 'useful.' The outputs of the statistical tests for the homogeneity analysis of the precipitation time series had discrepancies in some cases which are related to different sensitivities of the tests to break in the time series. It was found that the von Neumann test is more sensitive than the Bayesian and Cumulative Deviations tests in the determination of inhomogeneity in the precipitation series. [ABSTRACT FROM AUTHOR]