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Translating changes in land surface conditions and climate into changes in precipitation, runoff and flood frequencies over a range of catchment scales is a pressing challenge for hydrologic design and flood risk management today. In this paper, we describe a novel approach for modeling areal runoff frequency from heavy-to-extreme precipitation in large urban areas using a simple but general stochastic model for runoff at point scale and bi- and univariate parametric probability distributions for positive point precipitation and areal runoff, respectively. We apply the approach to the Dallas–Fort Worth area using a 22-year historical multisensor precipitation dataset from the National Weather Service to characterize how the different factors that specify the second-order statistics of precipitation, imperviousness and soil water holding capacity at point scale may shape areal runoff frequency, and to assess how changes in precipitation climatology and land surface conditions may change areal runoff frequency as a function of catchment scale and magnitude of precipitation. The results indicate that areal runoff frequency is impacted most significantly by changes in climatological mean and coefficient of variation of positive point precipitation, water holding capacity of soil, imperviousness, and spatial correlation scale of positive point precipitation given the probability of occurrence of heavy-to-extreme precipitation, and that a very small number of low-order statistics of point precipitation may describe areal runoff frequency given the conditional probability distribution models for point precipitation and areal runoff. The approach presented hence offers a parsimonious physically-based alternative to purely numerical approaches based on integrated modeling, or empirical approaches based solely on statistical modeling toward predictive modeling of areal precipitation and runoff frequencies under changing hydroclimatological conditions. [ABSTRACT FROM AUTHOR]

The Yangtze River has been subject to heavy flooding throughout history, and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods. Dams along the river help to manage flood waters, and are important sources of electricity for the region. Being able to forecast high-impact events at long lead times therefore has enormous potential benefit. Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used directly for operational services. The teleconnection from El Niño to Yangtze River basin rainfall meant that the strong El Niño in winter 2015/16 provided a valuable opportunity to test the application of a dynamical forecast system. This paper therefore presents a case study of a real-time seasonal forecast for the Yangtze River basin, building on previous work demonstrating the retrospective skill of such a forecast. A simple forecasting methodology is presented, in which the forecast probabilities are derived from the historical relationship between hindcast and observations. Its performance for 2016 is discussed. The heavy rainfall in the May-June-July period was correctly forecast well in advance. August saw anomalously low rainfall, and the forecasts for the June-July-August period correctly showed closer to average levels. The forecasts contributed to the confidence of decision-makers across the Yangtze River basin. Trials of climate services such as this help to promote appropriate use of seasonal forecasts, and highlight areas for future improvements. [ABSTRACT FROM AUTHOR]

Based on hydrological and climatic data covering the period from 1961 to 2008, this paper studies the hydrological responses to climate change and to human activities in the Ebinur Lake Catchment. The results show that the annual runoff of three rivers in Ebinur Lake Catchment exhibited different change trends. Specifically, in Jinghe River and Kuytun River exhibited a slightly increasing trend, but an adverse trend in Bortala River, and the variation trend has been the most dramatic since the mid-1990s. The observed variation in the runoff was resulted from the elevated alpine precipitation, rather than rising temperature, and that precipitation is a major factor for runoff generation. The runoff CAR model proposed by this paper can be used to predict the annual runoff in three rivers, and demonstrated annual runoff in Bortala River and Jinghe River will display an increased trend, while a less decreasing trend in Kuytun River under the climate change scenarios of warm-humid variation. In addition, the exploitation of the area of cultivated land led to more water resources consumption, primarily for agriculture irrigation, is the cause of the persistently ecoenvironment degradation, which have reached in a critical state thus, a more pressing concern is the development a scientifically reasonable and administratively practical water resource management scheme. [ABSTRACT FROM AUTHOR]

In this study, we analyse possible future climatic changes in three catchments, namely, Pyshma, Vagai and Loktinka located in the Western Siberian lowland region, and the resulting impact on hydrological regimes. It involved downscaling the GCM outputs based on the established statistical relationship between large-scale atmospheric variables and station data and simulating the effects of climate change on hydrological regimes via hydrological modelling. This was done for RCP 2.6, 4.5 and 8.5 based on second-generation Canadian Earth System Model used in the IPCC fifth assessment report. This paper provides the first climate change projections on a local scale in these catchments. The statistical downscaling showed that there will be an increase in both maximum and minimum temperature at all stations under all scenarios. The mean annual daily precipitation increased in Loktinka and Pyshma basins under all scenarios, but there was no clear trend in Vagai basin. The possible increase in annual precipitation is mostly due to the projected increase in autumn and winter precipitation. Annual streamflow tends to increase in all catchments under all scenarios. [ABSTRACT FROM AUTHOR]

Assessments of ecosystem service and function losses of wetlandscapes (i.e., wetlands and their hydrological catchments) suffer from knowledge gaps regarding impacts of ongoing hydro-climatic change. This study investigates hydro-climatic changes during 1976–2015 in 25 wetlandscapes distributed across the world's tropical, arid, temperate and cold climate zones. Results show that the wetlandscapes were subject to precipitation (P) and temperature (T) changes consistent with mean changes over the world's land area. However, arid and cold wetlandscapes experienced higher T increases than their respective climate zone. Also, average P decreased in arid and cold wetlandscapes, contrarily to P of arid and cold climate zones, suggesting that these wetlandscapes are located in regions of elevated climate pressures. For most wetlandscapes with available runoff (R) data, the decreases were larger in R than in P, which was attributed to aggravation of climate change impacts by enhanced evapotranspiration losses, e.g. caused by land-use changes. [ABSTRACT FROM AUTHOR]

The Hydrometeorological Sandbox - École de technologie supérieure (HYSETS) is a rich, comprehensive and large-scale database for hydrological modelling covering 14425 watersheds in North America. The database includes data covering the period 1950–2018 depending on the type and source of data. The data include a wide array of hydrometeorological data required to perform hydrological and climate change impact studies: (1) watershed properties including boundaries, area, elevation slope, land use and other physiographic information; (2) hydrometric gauging station discharge time-series; (3) precipitation, maximum and minimum daily air temperature time-series from weather station records and from (4) the SCDNA infilled gauge meteorological dataset; (5) the NRCan and Livneh gridded interpolated products' meteorological data; (6) ERA5 and ERA5-Land reanalysis data; and (7) the SNODAS and ERA5-Land snow water equivalent estimates. All data have been processed and averaged at the watershed scale, and provides a solid basis for hydrological modelling, climate change impact studies, model calibration assessment, regionalization method evaluation and essentially any study requiring access to large amounts of spatiotemporally varied hydrometeorological data. Measurement(s) elevation • temperature • hydrological precipitation process • Fluid Discharge • climate • physiographic feature Technology Type(s) digital curation Sample Characteristic - Environment watershed Sample Characteristic - Location North America Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12600281 [ABSTRACT FROM AUTHOR]

Self-organizing map (SOM) is used to simulate summer daily precipitation over the Yangtze–Huaihe river basin in Eastern China, including future projections. SOM shows good behaviors in terms of probability distribution of daily rainfall and spatial distribution of rainfall indices, as well as consistency of multi-model simulations. Under RCP4.5 Scenario, daily rainfall at most sites (63%) is projected to shift towards larger values. For the early 21st century (2016–2035), precipitation in the central basin increases, yet decreases occur over the middle reaches of the Yangtze River as well as a part of its southeast area. For the late 21st century (2081–2100), the mean precipitation and extreme indices experience an overall increase except for a few southeast stations. The total precipitation in the lower reaches of the Yangtze River and in its south area is projected to increase from 7% at 1.5 °C global warming to 11% at 2 °C, while the intensity enhancement is more significant in southern and western sites of the domain. A clustering allows to regroup all SOM nodes into four distinct regimes. Such regional synoptic regimes show remarkable stability for future climate. The overall intensification of precipitation in future climate is linked to the occurrence-frequency rise of a wet regime which brings longitudinally closer the South Asia High (eastward extended) and the Western Pacific Subtropical High (westward extended), as well as the reduction of a dry pattern which makes the two atmospheric centers of action move away from each other. [ABSTRACT FROM AUTHOR]

Considering the recent extreme precipitation in southeast Europe, it has become necessity to investigate the impact of climate change on extreme precipitation. The aim of this study was to determine the change in precipitation quantiles with longer return periods under changing climate conditions. The study was conducted using the daily records gathered at 11 precipitation stations within the Lim River Basin, Serbia. The simulated precipitation datasets were collected from three regional climate models for the baseline period (1971–2000), as well as the future period (2006–2055) under the 2.6, 4.5 and 8.5 representative concentration pathways. The raw precipitation data from the climate models were transformed by employing four bias correction methods. Using the bias-corrected precipitation, an ensemble of annual maximum daily precipitation was developed. A weighted ensemble approach was applied to estimate the weights of each ensemble member favorizing the members whose quantiles were closer to observed measurements. The mixed general extreme value distribution was used to derive the projected quantiles with 100, 50, 25, 10, five and two year return periods based on the estimated quantiles and the normalized weights of all ensemble members. An overall increase of 69% and 56% for the 100 and 50 year return periods, respectively, can be expected within the northern part of the basin. Similarly, an overall increase of 50–57% and 39–42% for the 100 and 50 year return periods, respectively, may be expected for the central and southern parts of the Lim River Basin. [ABSTRACT FROM AUTHOR]

The remaining wildlands in the North Central US include varying proportions of public, private, and tribal lands across water balance ecotones. These wildlands may be highly vulnerable changing climate impacting their ability to sustain biodiversity and ecosystem functioning. We quantified projected changes in growing season climate (temperature) and water balance (MI: moisture index) in Greater Wildland Ecosystems (GWEs) and land allocation types (public, private, and tribal lands) across Central Plains, Western Plains, and Western Mountains ecoregions of North Central US by using high-resolution climate data from GCM output of 1980–2005 to 2071–2099. We also tested for the evidence of systematic climatic bias on tribal lands, which are often claimed to be distributed non-randomly. We found that the historic temperature was lower for Western Mountains compared to Western and Central Plains' GWEs. The climate model projected drier and warmer GWEs with a narrow difference in increased temperature (4.6 to 5.5 °C). The MI was projected to have the greatest decrease in Central Plains (− 28%) and the least in Western Plains (− -17%) GWEs. Our findings revealed that the GWEs and land allocation types are increasingly vulnerable to changing climate. We conclude that the distribution of tribal and public lands is not climatically biased in the historic period and the projected rates of change in climate are similar among land allocation types within each GWE. All GWEs, however, are projected to warm and undergo increasing aridity, which may challenge management to sustain ecological health and human wellbeing across all land allocation types. [ABSTRACT FROM AUTHOR]

The climate of the circumpolar Boreal forest is changing rapidly, resulting in a growing frequency of wildfires and changing precipitation patterns. These climate-related stressors may influence the cycling of nutrients within, and overall ecosystem condition of, Boreal watersheds. However, long-term perspectives of concurrent climate-related impacts on the cycling of nutrients in watersheds are rare. We present multi-decadal terrestrial and lake mass budgets of nitrogen, phosphorus and carbon within a headwater Boreal Shield watershed that was recovering from an extensive wildfire while experiencing measureable increases in annual precipitation. We used these budgets to quantify associations between nutrient retention in each ecosystem and changes in metrics defining landscape recovery after wildfire or precipitation. The terrestrial watershed retained over half of all nitrogen and phosphorus delivered to it by the atmosphere. Strong nutrient retention occurred despite ongoing landscape recovery from wildfire, measurable increases in precipitation, a forest tent caterpillar defoliation and rising atmospheric deposition. A downstream headwater lake was also a strong and consistent sink of nitrogen and phosphorus, highlighting a whole-watershed resistance to environmental disturbances. However, carbon was strongly lost downstream from the terrestrial ecosystem in close and positive association with precipitation, resulting in a darkening of the headwater lake over time with implications for the functioning of its ecosystem. Long-term mass budget monitoring of a Boreal catchment has provided insight into the resistances and dynamic changes within a northern watershed exposed to concurrent wildfire and increasing precipitation conditions. [ABSTRACT FROM AUTHOR]

This study examines the projections of hydroclimatic regimes and extremes over Andean basins in central Chile (∼ 30-40° S) under a low and high emission scenarios (RCP2.6 and RCP8.5, respectively). A gridded daily precipitation and temperature dataset based on observations is used to drive and validate the VIC macro-scale hydrological model in the region of interest. Historical and future simulations from 19 climate models participating in CMIP5 have been adjusted with the observational dataset and then used to make hydrological projections. By the end of the century, there is a large difference between the scenarios, with projected warming of ∼ + 1.2 °C (RCP2.6), ∼ + 3.5 °C (RCP8.5) and drying of ∼ − 3% (RCP2.6), ∼ − 30% (RCP8.5). Following the strong drying and warming projected in this region under the RCP8.5 scenario, the VIC model simulates decreases in annual runoff of about 40% by the end of the century. Such strong regional effect of climate change may have large implications for the water resources of this region. Even under the low emission scenario, the Andes snowpack is projected to decrease by 35-45% by mid-century. In more snowmelt-dominated areas, the projected hydrological changes under RCP8.5 go together with more loss in the snowpack (75-85%) and a temporal shift in the center timing of runoff to earlier dates (up to 5 weeks by the end of the century). The severity and frequency of extreme hydroclimatic events are also projected to increase in the future. The occurrence of extended droughts, such as the recently experienced mega-drought (2010-2015), increases from one to up to five events per 100 years under RCP8.5. Concurrently, probability density function of 3-day peak runoff indicates an increase in the frequency of flood events. The estimated return periods of 3-day peak runoff events depict more drastic changes and increase in the flood risk as higher recurrence intervals are considered by mid-century under RCP2.6 and RCP8.5, and by the end of the century under RCP8.5. [ABSTRACT FROM AUTHOR]

A slight variation in the magnitude of stream flow can have a substantial influence on the development of water resources. The Songhua River Basin (SRB) serves as a major grain commodity basin and is located in the northeastern region of China. Recent studies have identified a gradual decrease in stream flows, which presents a serious risk to water resources of the region. It is therefore necessary to assess the variation in stream flow and to predict the future of stream flows and droughts to make a comprehensive plan for agricultural irrigation. The simulation of monthly stream flows and the investigation of the influence of climate on the stream flow in the SRB were performed by utilizing the Integrated Water Evaluation and Planning (WEAP) tool coupled with observed precipitation data, as well as the Asian Precipitation-Highly-Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE’s Water Resources) precipitation product. The Nash-Sutcliffe coefficient (NSC) was used to assess the WEAP efficiency. During the time of calibration, NSC was obtained as 0.90 and 0.67 using observed and APHRODITE precipitation data, respectively. The results indicate that WEAP can be used effectively in the SRB. The application of the model suggested a maximum decline in stream flow, reaching 24% until the end of 21st century under future climate change scenarios. The drought indices (standardized drought index and percent of normal index) demonstrated that chances of severe to extreme drought events are highest in 2059, 2060 and 2085, while in the remaining time period mild to moderate drought events may occur in the entire study area. The drought duration, severity and intensity for the period of 2011-2099 under all scenarios, [(A1B: 12, − 1.55, − 0.12), (A2: 12, − 1.41, − 0.09), (max. wetting and warming conditions: 12, − 1.37, − 0.11) and (min. wetting and warming conditions: 12, − 1.69, − 0.19)], respectively. [ABSTRACT FROM AUTHOR]

Projections of climate change are essential to guide sustainable development plans in the tropical Andean countries such as Peru. This study assessed the projections of precipitation and potential evaporation, rain erosive potential, and precipitation concentration in the Mantaro River Basin, in the Peruvian Andes, which is important for agriculture and energy production in Peru. We assumed the Intergovernmental Panel on Climate Change (IPCC) A1B greenhouse gas emission scenario and simulated the global climate change by the HadCM3 global climate model. Due to the steepness of the mountain slopes and the narrowness of the river valley, this study uses the downscaling of the global model simulations by the regional Eta model down to 20-km resolution. The downscaling projections show decrease in the monthly precipitation with respect to the baseline period, especially during the rainy season, between February and April, until the end of the 21st century. Meanwhile, a progressive increase in the monthly evaporation from the baseline period is projected. The Modified Fournier Index (MFI) shows a statistically significant downward trend in the Mantaro River Basin, which suggests a possible reduction in the rain erosive potential. The Precipitation Concentration Index (PCI) shows a statistically significant increasing trend, which indicates increasingly more irregular temporal distribution of precipitation towards the end of the century. The results of this study allow us to conclude that there should be a gradual increase in water deficit and precipitation concentration. Both changes can be negative for agriculture, power generation, and water supply in the Mantaro River Basin in Peru. [ABSTRACT FROM AUTHOR]

Multi-regression, hydrologic sensitivity and hydrologic model simulations were applied to quantify the climate change and anthropogenic intervention impacts on the Lower Zab River basin (LZRB). The Pettitt, precipitation-runoff double cumulative curve (PR-DCC) and Mann-Kendall methods were used for the change points and significant trend analyses in the annual streamflow. The long-term runoff series from 1979 to 2013 was first divided into two main periods: a baseline (1979-1997) and an anthropogenic intervention period (1998-2013). The findings show that the mean annual streamflow changes were consistent using the three methods. In addition, climate variability was the main driver, which led to streamflow reduction with contributions of 66-97% during 2003-2013, whereas anthropogenic interventions caused reductions of 4-34%. Moreover, to enhance the multi-model combination concept and explore the simple average method (SAM), Hydrologiska Byrans Vattenbalansavdelning (HBV), Génie Rural a Daily 4 parameters (GR4J) and Medbasin models have been successfully applied. [ABSTRACT FROM AUTHOR]

Climate change has become an important issue for scientific community, for its numerous impacts, especially on agriculture and environment. To shed light on this phenomenon, long data-sets of meteorological data as well as temperature and rainfall extreme events are needed, since they are important climate variability indicators. In a small semi-agricultural catchment of the Italian Apennines, drained by the Centonara Stream, weather data have been monitored for 30 years (1986-2015). Here, their trend was identified with Mann-Kendall test, and the temperature and precipitation extremes were characterized by means of specific indices. Data were analyzed at event, daily, seasonal, and annual bases. In addition, to understand implications of rainfall patterns on catchment hydrological response, a total of 388 rainfall-streamflow events (recorded during 1994-2009) were analyzed. Results showed a significant increase of temperature (minimum (Tn), mean (Tm), and maximum (Tx)), both at annual and seasonal base, except for Winter, with an annual mean increase of 0.08, 0.09, and 0.13 °C year for Tn, Tm, and Tx, respectively. Annual rainfall data showed a positive trend for the number of wet days, but not in the quantity. In Winter, the rainfall amount and the number of wet days increased. The annual number of rainfall extreme events ( P > 20.2 mm and D > 18.3 h) significantly increased, especially in spring and autumn. The rainfall-streamflow relationship suggested that the flow response of the Centonara Stream depends mainly on the rainfall amount. So, since the number of extreme events ( P > 20.2 mm) is increasing in spring and autumn, an increase of events with high streamflow in these seasons may occur. [ABSTRACT FROM AUTHOR]

This study analyzes the impact of anthropogenic climate change in the hydroclimatology of Senegal with a focus over the lake of Guiers basin for the middle (2041-2060) and late twenty-first century (2080-2099). To this end, high-resolution multimodel ensemble based on regional climate model experiments considering two Representative Concentration Pathways (RCP4.5 and RCP8.5) is used. The results indicate that an elevated warming, leading to substantial increase of atmospheric water demand, is projected over the whole of Senegal. In the Lake basin, these increases in potential evapotranspiration (PE) range between 10 and 25 % in the near future and for RCP4.5 while for the far future and RCP8.5, they exceed 50 %. In addition, mean precipitation unveils contrasting changes with wetter (10 to 25 % more) conditions by the middle of the century and drier conditions (more than 50 %) during the late twenty-first century. Such changes cause more/less evapotranspiration and soil moisture respectively during the two future periods. Furthermore, surface runoff shows a tendency to increase in most areas amid few locations including the Lake basin with substantial reduction. Finally, it is found that while semi-arid climates develop in the RCP4.5 scenario, generalized arid conditions prevail over the whole Senegal for RCP8.5. It is thus evident that these future climate conditions substantially threaten freshwater availability for the country and irrigated cropping over the Lake basin. Therefore, strong governmental politics are needed to help design response options to cope with the challenges posed by the projected climate change for the country. [ABSTRACT FROM AUTHOR]

Hydrology cycle of river basins and available water resources in arid and semi-arid regions are highly affected by climate changes. In recent years, the increment of temperature due to excessive increased emission of greenhouse gases has led to an abnormality in the climate system of the earth. The main objective of this study is to survey the future climate changes in one of the biggest mountainous watersheds in northeast of Iran (i.e., Kashafrood). In this research, by considering the precipitation and temperature as two important climatic parameters in watersheds, 14 models evolved in the general circulation models (GCMs) of the newest generation in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used to forecast the future climate changes in the study area. For the historical period of 1992-2005, four evaluation criteria including Nash-Sutcliffe (NS), percent of bias (PBIAS), coefficient of determination ( R ) and the ratio of the root-mean-square-error to the standard deviation of measured data (RSR) were used to compare the simulated observed data for assessing goodness-of-fit of the models. In the primary results, four climate models namely GFDL-ESM2G, IPSL-CM5A-MR, MIROC-ESM, and NorESM1-M were selected among the abovementioned 14 models due to their more prediction accuracies to the investigated evaluation criteria. Thereafter, climate changes of the future periods (near-century, 2006-2037; mid-century, 2037-2070; and late-century, 2070-2100) were investigated and compared by four representative concentration pathways (RCPs) of new emission scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP8.5. In order to assess the trend of annual and seasonal changes of climatic components, Mann-Kendall non-parametric test (MK) was also employed. The results of Mann-Kendall test revealed that the precipitation has significant variable trends of both positive and negative alterations. Furthermore, the mean, maximum, and minimum temperature values had significant positive trends at 90, 99, and 99.9 % confidence level. On the other hand, in all parts of the Kashafrood Watershed (KW), the average temperature of watershed will be increased up to 0.56-3.3 °C and the mean precipitation will be decreased up to 10.7 % by the end of the twenty-first century comparing to the historical baselines. Also, in seasonal scale, the maximum and minimum precipitations will occur in spring and summer, respectively, and the mean temperature is higher than the historical baseline in all seasons. The maximum and minimum values of the mean temperature will occur in summer and winter, respectively, and the amount of seasonal precipitation in these seasons will be reduced. [ABSTRACT FROM AUTHOR]

Projections of changes in climate are important in assessing the potential impacts of climate change on natural and social systems. However, current knowledge on assembling different GCMs to estimate future climate change over the Pear River basin is still limited so far. This study examined the capability of BMA and arithmetic mean (AM) method in assembling precipitation and temperature from CMIP5 under RCP2.6, RCP4.5 and RCP8.5 scenarios over the Pearl River basin. Results show that the BMA outperforms the traditional AM method. Precipitation tends to increase over the basin under RCP2.6 and RCP4.5 scenarios, whereas decrease under RCP8.5. The most remarkable increase of precipitation is found in the northern region under RCP2.6 scenario. The linear trend of the monthly mean near-surface air temperature increases with the growing CO concentration. The warming trends in four seasons are distinct. The warming rate is prominent in summer and spring than that in other season, meanwhile it is larger in western region than in other parts of the basin. The findings can provide beneficial reference to water resources and agriculture management strategies, as well as the adaptation and mitigation strategies for floods and droughts under the context of global climate change. [ABSTRACT FROM AUTHOR]

Impact of spatial data availability on the temperature and precipitation prediction characteristics of Weyib River basin in Ethiopia has been investigated using CMIP5-CanESM2 model for the RCP8.5, RCP4.5 and RCP2.6 scenarios. The objective of the present study is to characterize how future temperatures and precipitation prediction under CMIP5-CanESM2 model output varies against diverse averaged arbitrary spatial weather stations found in the basin. The statistical downscaling model tested and verified using the observed daily data for twelve, six and three averaged arbitrary spatial weather stations as well as for a single weather station was used to predict the future climate scenarios. The results revealed that the mean annual daily maximum and minimum temperature and precipitation for twelve, six and three arbitrary spatial stations have revealed an increasing trend in the upcoming periods until the end of the century. In single station analysis, the trend itself has changed from increasing trend to decreasing trend in case of maximum and minimum temperature. In case of precipitation, no visible trend has been observed in case of single station analysis. Therefore, the variation in amount and distribution of precipitation and temperature among the four averaged spatial stations in the same study area might affect the water resources and agriculture of the basin and also instead of using a single weather station to predict future climate variables for a particular study basin, it is more reliable using averages of numerous spatial weather stations data. [ABSTRACT FROM AUTHOR]

Snowmelt run-off model (SRM) based on degree-day approach has been employed to evaluate the change in snow-cover depletion and corresponding streamflow under different projected climatic scenarios for an eastern Himalayan catchment in India. Nuranang catchment located at Tawang district of Arunachal Pradesh with an area of 52 km is selected for the present study with an elevation range of 3143-4946 m above mean sea level. Satellite images from October to June of the selected hydrological year 2006-2007 were procured from National Remote Sensing Centre, Hyderabad. Snow cover mapping is done using NDSI method. Based on long term meteorological data, temperature and precipitation data of selected hydrological year are normalized to represent present climatic condition. The projected temperature and precipitation data are downloaded from NCAR's GIS data portal for different emission scenarios (SRES), viz., A1B, A2, B1; and IPCC commitment (non-SRES) scenario for different future years (2020, 2030, 2040 and 2050). Projected temperature and precipitation data are obtained at desired location by spatially interpolating the gridded data and then by statistical downscaling using linear regression. Snow depletion curves for all projected scenarios are generated for the study area and compared with conventional depletion curve for present climatic condition. Changes in cumulative snowmelt depth for different future years are highest under A1B and lowest under IPCC commitment, whereas A2 and B1 values are in-between A1B and IPCC commitment. Percentage increase in streamflow for different future years follows almost the same trend as change in precipitation from present climate under all projected climatic scenarios. Hence, it was concluded that for small catchments having seasonal snow cover, the total streamflow under projected climatic scenarios in future years will be primarily governed by the change in precipitation and not by change in snowmelt depth. Advancing of depletion curves for different future years are highest under A1B and lowest under IPCC commitment. A2 and B1 values are in-between A1B and IPCC commitment. [ABSTRACT FROM AUTHOR]

Climate change is receiving more attention from researchers as the frequency of occurrence of severe natural disasters is getting higher. Tropical countries like Malaysia have no distinct four seasons; rainfall has become the popular parameter to assess climate change. Conventional ways that determine rainfall trends can only provide a general result in single direction for the whole study period. In this study, rainfall series were modelled using additive Holt-Winters method to examine the rainfall pattern in Langat River Basin, Malaysia. Nine homogeneous series of more than 25 years data and less than 10% missing data were selected. Goodness of fit of the forecasted models was measured. It was found that seasonal rainfall model forecasts are generally better than the monthly rainfall model forecasts. Three stations in the western region exhibited increasing trend. Rainfall in southern region showed fluctuation. Increasing trends were discovered at stations in the south-eastern region except the seasonal analysis at station 45253. Decreasing trend was found at station 2818110 in the east, while increasing trend was shown at station 44320 that represents the north-eastern region. The accuracies of both rainfall model forecasts were tested using the recorded data of years 2010-2012. Most of the forecasts are acceptable. [ABSTRACT FROM AUTHOR]

Six global climate models (GCMs) from Coupled Model Intercomparison Project Phase 5 under three Respectively Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5) were used to assess the impact of climate change on streamflow for the Huangnizhuang catchment (HNZ) in China. Change factor method was used for bias correction between GCM outputs and observations and the SWAT model was used to simulate the hydrological processes. The results indicated that the SWAT model performed well in the study catchment with a monthly Nash-Sutcliffe efficiency (NS) of 0.93 and 0.91 and daily NS of 0.63 and 0.68 for calibration and validation periods respectively. Their corresponding relative errors were −2.2 and 8.9, and −2.6 and 8.5 % respectively. The ensemble of multi-GCMs projected an increase of precipitation in the middle and end of twenty-first century over the HNZ, ranging from −2.4 to 9 %. However, streamflow is likely to decline in the future, ranging −6.9 to 0.8 %, mainly due to an increase of evapotranspiration in a warming world, as air temperature shows steadily increases for all the GCMs and RCPs. Average monthly streamflow from six GCMs are likely to increase in August and September but decline from October to June. The associated uncertainties of the reported results were also discussed. It includes, but is not limit to, different GCMs, emissions scenarios, downscaling techniques as well as hydrological simulations. The results of this study can inform planning of long-term basin water management strategies taking into account global change scenarios. [ABSTRACT FROM AUTHOR]

Climate change is always occurring. Its impacts on the environment are still uncertain, especially due to the difficulty of simulating the earth's climate accurately. However, the global circulation climate models have been the only scientific tool to assess such impacts and their results have been well accepted. This study aimed to analyze the possible impacts on rainfall erosive potential throughout the twenty-first century for the A1B climate change scenario, in the Grande River Basin (GRB) headwaters, Southeastern Brazil. The results from Eta-CPTEC/HadCM3 model were taken into account to calculate the climatic erosivity indicators 'Modified Fournier Index' (MFI) and 'Precipitation Concentration Index' (PCI). Based on three meteorological stations, which are monitoring the weather in GRB headwaters since 2005, every 10 min, a statistical relationship between annual rainfall erosivity (EI) and the respective MFI was adjusted to infer about EI in the future. The results have showed an increase in annual amount of precipitation for most months of the year, except for September and October, throughout the twenty-first century. The greatest impacts on EI are associated with the projected increase in precipitation for December and January, which can reach up to 49 %. A significant increase in MFI and PCI was observed over the twenty-first century in relation to the present climate. These results demonstrate a potential increase in rainfall erosive power, which causes special concerns due to predominance of shallow soils, associated with undulated to strongly undulated relief in the studied region. [ABSTRACT FROM AUTHOR]

Individual impacts of climate change, land use/coverage change, the regulation of water reservoir and water use to intra-annual distribution of streamflow of the Dongjiang River basin, South China, are quantitatively separated. Data on precipitation, streamflow, regulation of water reservoirs, and water use are used in the analysis. Changes in the concentration degree and non-uniformity coefficient of intra-annual distribution of streamflow over time scales from daily to monthly are evaluated. Trend and change point analyses are applied to determine characteristics of intra-annual distribution of streamflow. By comparison with the difference among region precipitation, naturalized streamflow and observed streamflow, the contribution of main impact factors to the intra-annual distribution of streamflow are quantified. Results demonstrate the non-uniformity coefficient decreases with a negative logarithmic linear function of the time scale. Change points of the concentration degree and non-uniformity coefficient occurred in 1973 exhibited a significant downward trend. In the period posterior to the change point the former and the latter decrease approximately by 15-34 % and by 29-40 %, respectively. The decrease in concentration degree and non-uniformity coefficient is due to the regulation of water reservoirs and land use/cover change; while the increase is the result of water use and climate change. The individual contributions to the impact on the intra-annual distribution of streamflow from regulation of water reservoirs, land use/cover change, water use, and climate change are approximately −33.5, −9.0, 4.5 and 1.0 %. It is observed that the impacts of the regulations of the Xinfengjiang, Fengshuba, and Baipenzhu reservoirs account for −21, −10, and −2 %, respectively. There is an increasing tendency in the impacts of land use/cover change and water use in the past 30 years. [ABSTRACT FROM AUTHOR]

Much attention has recently been focused on the effects of climate variability and human activities on the runoff. In this study, we analyzed 56-yr (1957-2012) runoff change and patterns in the Jinghe River Basin (JRB) in the arid region of northwest China. The nonparametric Mann-Kendall test and the precipitation-runoff double cumulative curve (PRDCC) were used to identify change trend and abrupt change points in the annual runoff. It was found that the runoff in the JRB has periodically fluctuated in the past 56 yr. Abrupt change point in annual runoff was identified in the JRB, which occurred in the years around 1964 and 1996 dividing the long-term hydrologic series into a natural period (1957-1964) and a climate and man-induced period (1965-1996 and 1997-2012). In the 1965-1996 period, human activities were the main factor that decreased runoff with contribution of 88.9%, while climate variability only accounted for 11.1%. However, the impact of climate variability has been increased from 11.1% to 47.5% during 1997-2012, showing that runoff in JRB is more sensitive to climate variability during global warming. This study distinguishes the effect of climate variability from human activities on runoff, which can do duty for a reference for regional water resources assessment and management. [ABSTRACT FROM AUTHOR]

The West Rapti River (WRR), one of the dynamic and economically important basins of Nepal, was focused in this study to understand the impact of climate change in localized scale. The adopted methodology was a community-based field survey followed by a hydrological modeling to estimate present and future flood damages for households and agriculture. Flood disaster occurred in 2007 was simulated and discussed. High-resolution atmospheric general circulation model's precipitation outputs for emission scenario A1B were utilized with their bias corrections to obtain the precipitation patterns over lower WRR basin for Present (1979-2003) and Future (2075-2099) periods. A conceptual hydrologic model was employed to obtain the time series of daily river runoffs for the above-mentioned time durations followed by frequency analyses for probable flood discharges of 25- and 50-year return periods. Flood inundation simulations of 50-year return period events for Present and Future were carried out with the rainfall-runoff-inundation model followed by a flood damage assessment for household and agriculture based on the inundation simulation results, and field survey data over the target area and potential flood damages were discussed. Integration of hydrological modeling and socioeconomic approach to foresee potential flood damages was achieved, and the adopted damage assessment methodology was systematically explained. The total increments of household and agriculture damages due to climate change were estimated for Present as 1.80 and 1.95, and for Future, it was 2.40 and 2.27, respectively, compared to 2007 flood disaster. Future flood frequencies, intensities, and consequent damages in the area show a significant increment compared to the present situation despite limitations and uncertainties. [ABSTRACT FROM AUTHOR]

This study evaluates projected changes to characteristics of winter, spring, summer and fall seasonal precipitation and rain and snow dominated daily precipitation extremes for 47 watersheds, located mainly in the Alberta, Saskatchewan and Manitoba provinces of Canada, using a multi-Regional Climate Model (RCM) ensemble available through the North American Regional Climate Change Assessment Program. The set of simulations considered includes those performed with the six participating RCMs for the 1980-2004 period driven by National Centre for Environmental Prediction reanalysis II and those driven by four Atmosphere-Ocean General Circulation Models (AOGCMs) for the 1971-2000 and 2041-2070 periods. For precipitation extremes, regional frequency analysis is used to develop projected changes to selected 10-, 30- and 50-year return levels of rain and snow dominated extremes (i.e. RDEs and SDEs) separately. The uncertainties due to internal dynamics and physics of the RCMs and those due to the lateral boundary data from driving AOGCMs are studied at the watershed level and evaluated in terms of coefficient of variation on the basis of a multi-RCM ensemble. In general, the structural uncertainty appears to be larger than that associated with the choice of the driving AOGCM for most of the precipitation characteristics considered. Analyses of multi-RCM ensemble-averaged projected changes to mean seasonal precipitation and various return levels of RDEs and SDEs show an increase over nearly all the study domain. The changes to seasonal precipitation are not generally found statistically significant at 5 % significance level but those for RDEs and SDEs are found significant more often for return levels of smaller return period (10-year) compared to those of larger return period (50-year). It is expected that changes in seasonal and extreme precipitation characteristics will have important implications for managing regional water security-related issues in the Canadian Prairie Provinces. [ABSTRACT FROM AUTHOR]

We present an assessment of climate change impacts on the hydrologic regime of the 600,000 km Upper Paraguay River basin, located in central South America based on predictions of 20 Atmospheric/Ocean General Circulation Models (AOGCMs). We considered two climate change scenarios from the Intergovernmental Panel on Climate Change (IPCC) and two 30-years time intervals centered at 2030 and 2070. Projected temperature and precipitation anomalies estimated by the AOGCMs for the study site are spatially downscaled. Time series of projected temperature and precipitation were estimated using the delta change approach. These time series were used as input to a detailed coupled hydrologic-hydraulic model aiming to estimate projected streamflow in climate change scenarios at several control points in the basin. Results show that impacts on streamflow are highly dependent on the AOGCM used to obtain the climate predictions. Patterns of temperature increase persist over the entire year for almost all AOGCMs resulting in an increase in the evapotranspiration rate of the hydrological model. The precipitation anomalies show large dispersion, being projected as either an increase or decrease in precipitation rates. Based on these inputs, results from the coupled hydrologic-hydraulic model show nearly one half of projections as increasing river discharge, and other half as decreasing river discharge. If the mean or median of the predictions is considered, no discernible change in river discharge should be expected, despite the dispersion among results of the AOGCMs that reached +/−10 % in the short horizon and +/− 20 % in the long horizon, at several control points. [ABSTRACT FROM AUTHOR]

For 50 years of long observation period (1960-2009), on a high level of statistical significance (95 %), a decreasing trend of annual precipitation amounts and an increasing trend of the number of rainy days during the year (64 %) were found. For the seasonal changes (V-X), similarly, there was found a statistically significant (94 %) decreasing precipitation amount trend and an increasing trend of the number of rainy days (50 %). As far as the intensity of maximum precipitation is concerned, a very statistically significant increasing trend (95 %) was found. Taking as the basis, the model for a trend, defined for the period of 1960-2009, the increase of weighted average interval values of maximum precipitation amounts ( h ≥ 0.75 t) in the year 2059 was estimated to be about 26 %, in comparison with the starting year 1960. An increasing trend of maximum precipitation frequency in Wrocław was also proved. To a safe sewerage systems designing in Wrocław according to current standards (EN 752 ; DWA-A118 ), the precipitation frequency to the simulations of excessive accumulation occurrences to the land level should be changed. [ABSTRACT FROM AUTHOR]

Projected climate change over Turkey has been analyzed by using the reference (1961-1990) and future (2071-2100) climate simulations produced by ICTP-RegCM3. Since examining Turkey as a single region could be misleading due to the existence of complex topography and different climatic regions, Turkey has been separated into seven climatic regions to evaluate the surface temperature and precipitation changes. Comparison of the reference simulation with observations was made spatially by using a monthly gridded data set and area-averaged surface data compiled from 114 meteorological stations for each climatic region of Turkey. In the future simulation, warming over Turkey's climatic regions is in the range of 2-5 °C. Summer warming over western regions of Turkey is 3 °C higher than the winter warming. During winter, in the future simulation, precipitation decreases very significantly over southeastern Turkey (24 %), which covers most of the upstream of Euphrates and Tigris river basin. This projected decrease could be a major source of concern for Turkey and the neighboring countries. Our results indicate that a significant increase (48 %) in the autumn season precipitation is simulated over southeastern Turkey, which may help to offset the winter deficit and therefore reduce the net change during the annual cycle. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to evaluate the impacts of climate change on Izmir-Tahtali freshwater basin, which is located in the Aegean Region of Turkey. For this purpose, a developed strategy involving statistical downscaling and hydrological modeling is illustrated through its application to the basin. Prior to statistical downscaling of precipitation and temperature, the explanatory variables are obtained from National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis data set. All possible regression approach is used to establish the most parsimonious relationship between precipitation, temperature, and climatic variables. Selected predictors have been used in training of artificial neural networks-based downscaling models and the trained models with the obtained relationships have been operated to produce scenario precipitation and temperature from the simulations of third Generation Coupled Climate Model. Biases from downscaled outputs have been reduced after downscaling process. Finally, the corrected downscaled outputs have been transformed to runoff by means of a monthly parametric hydrological model GR2M to assess the probable impacts of temperature and precipitation changes on runoff. According to the A1B climate scenario results, statistically significant trends are foreseen for precipitation, temperature, and runoff in the study basin. [ABSTRACT FROM AUTHOR]