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The boreal landscape is a complex, spatio-temporally varying mosaic of forest and mire landscape elements that control surface water hydrology and chemistry. Here, we assess long-term water quality time-series from three nested headwater streams draining upland forest (C2), peat/mire (C4) and mixed (C7) (forest and mire) catchments. Temporal trends in weather and runoff (1981-2008); dissolved organic carbon concentration [DOC] (1993-2010) and other water quality parameters (1987-2011) were assessed. There was no significant annual trend in precipitation or runoff but a significant monotonic increasing trend existed in air temperature and length of growing season. Stream [DOC] was positively correlated with some trace metals (copper, iron and zinc) and negatively with several other chemical parameters (e.g. sulfate, conductivity, calcium). Both sulfate and conductivity showed declining trends, while a significant increase was observed in pH during winter and spring. Calcium and magnesium showed monotonic decreasing trends. The declining trajectories of stream base cation and sulfate concentrations during other times of the year were not accompanied by changes in pH and alkalinity. Water temperature increased significantly both annually and in most months while iron and DOC concentrations showed significant increases in autumn months. Though all streams showed significant positive trends in [DOC] in autumn, only C2 had a significant annual increasing trend. There was also a shift in the magnitude of variability in spring [DOC] and increasing trend of summer baseflow [DOC] in C2 and C7. [ABSTRACT FROM AUTHOR]

The article discusses a proposed model for simulating catchment-scale erosion from rainfall or runoff events. It mentions that computational models on rainfall erosion would require conceptual abstractions to give the complexity of nature into a form that would give estimation on erosion, hydrology, and hydraulics. However, several challenges for modelers outside the innate complexity and temporal variability of any natural catchment and soil had been revealed.

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]

It is important to investigate the hydrological consequences of current climate change. Hydrological responses to climate warming and wetter conditions include changes in discharge (frequency, amplitude, and volume). This paper describes current climate change and its impact on hydrological flow within the Horyn River basin. Daily air temperature and precipitation data obtained from the 17 meteorological stations located in and nearby the Horyn River basin, in combination with hydrological data (such as daily water discharges obtained from 9 water gauges), were used for the analysis of climate variability and its hydrological consequences. Analyses of meteorological variables and water discharges are crucial for the assessment of long-term changes in the river regime. Thiessen polygons were used to determine the area of influence of assigned specific meteorological stations, which affect the river's catchments within the Horyn River basin. As a result of the trend analysis, it was observed that discharge within the Horyn River basin decreased over time. These results were congruent with the trends of precipitation data and air temperature data of the stations determined by the Thiessen polygons and basin boundaries. To understand current changes in the daily flow in the basin, changes in air temperature and precipitation for the period 1991-2020 were compared with the period of the climatic norm (1961-1990). A similar analysis was done for daily water discharges. Increasing air temperature and decreasing precipitation in the current period led to a significant decrease in discharges in the Horyn River basin, especially during the spring flood period. [ABSTRACT FROM AUTHOR]

The investigation of extreme meteorological drought events is crucial for disaster preparedness and regional water management. In this study, trends in extreme drought events, namely annual maximum drought severity (AMDS) and annual maximum drought duration (AMDD), were examined for the Ceyhan Basin. The analyses of extreme events were conducted using the standard precipitation index (SPI) index for multiple-time scales of 1, 3, 6, 9, and 12 months for 23 meteorological stations located in the Ceyhan Basin, Turkey. The Wallis-Moore and Wald-Wolfowitz methods were employed to determine the homogeneity of the data sets, whereas trend analyses were conducted using Mann-Kendall and Spearman Rho tests. The magnitude of trends was defined by Sen's slope and linear regression, and change points were detected using the standard normal homogeneity test, Buishand's range test, and Pettitt's test. Although increasing trends were detected in most of the stations, only in nine of them, statistically significant results were noted at a significance level of 95%. The results of this paper provide valuable information to water resource management decision-makers in the Ceyhan River Basin for evaluating the effect of droughts and preparing for drought mitigation measures to avoid future drought risks. [ABSTRACT FROM AUTHOR]

Physically based distributed hydrological models (hereafter referred to as PBDHMs) divide the terrain of the whole catchment into a number of grid cells at fine resolution and assimilate different terrain data and precipitation to different cells. They are regarded to have the potential to improve the catchment hydrological process simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters. However, unfortunately the uncertainties associated with this model derivation are very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study: the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using particle swarm optimization (PSO) algorithm and to test its competence and to improve its performances; the second is to explore the possibility of improving physically based distributed hydrological model capability in catchment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with the Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improved PSO algorithm is developed for the parameter optimization of the Liuxihe model in catchment flood forecasting. The improvements include adoption of the linearly decreasing inertia weight strategy to change the inertia weight and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be used for the Liuxihe model parameter optimization effectively and could improve the model capability largely in catchment flood forecasting, thus proving that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological models. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for the Liuxihe model catchment flood forecasting are 20 and 30 respectively. [ABSTRACT FROM AUTHOR]

The main sources of uncertainty in hydrological modelling can be summarized as structural errors, parameter errors, and data errors. Operational modellers are generally more concerned with predictive ability than model errors, and this paper presents a new, simple method to improve predictive ability. The method is called parameter-state ensemble thinning (P-SET). P-SET takes a large ensemble of continuous model runs and applies screening criteria to reduce the size of the ensemble. The goal is to find the most promising parameter-state combinations for analysis during the prediction period. Each prediction period begins with the same large ensemble, but the screening criteria are free to select a different sub-set of simulations for each separate prediction period. The case study is from June to October 2014 for a small (1324 km 2) watershed just north of Lake Superior in Ontario, Canada, using a Canadian semi-distributed hydrologic land-surface scheme. The study examines how well the approach works given various levels of certainty in the data, beginning with certainty in the streamflow and precipitation, followed by uncertainty in the streamflow and certainty in the precipitation, and finally uncertainty in both the streamflow and precipitation. The approach is found to work in this case when streamflow and precipitation are fairly certain, while being more challenging to implement in a forecasting scenario where future streamflow and precipitation are much less certain. The main challenge is determined to be related to parametric uncertainty and ideas for overcoming this challenge are discussed. The approach also highlights model structural errors, which are also discussed. [ABSTRACT FROM AUTHOR]

This paper proposes a protocol to assess the space–time consistency of 12 satellite-based precipitation products (SPPs) according to various indicators, including (i) direct comparison of SPPs with 72 precipitation gauges; (ii) sensitivity of streamflow modelling to SPPs at the outlet of four basins; and (iii) the sensitivity of distributed snow models to SPPs using a MODIS snow product as reference in an unmonitored mountainous area. The protocol was applied successively to four different time windows (2000–2004, 2004–2008, 2008–2012 and 2000–2012) to account for the space–time variability of the SPPs and to a large dataset composed of 12 SPPs (CMORPH–RAW v.1, CMORPH–CRT v.1, CMORPH–BLD v.1, CHIRP v.2, CHIRPS v.2, GSMaP v.6, MSWEP v.2.1, PERSIANN, PERSIANN–CDR, TMPA–RT v.7, TMPA–Adj v.7 and SM2Rain–CCI v.2), an unprecedented comparison. The aim of using different space scales and timescales and indicators was to evaluate whether the efficiency of SPPs varies with the method of assessment, time window and location. Results revealed very high discrepancies between SPPs. Compared to precipitation gauge observations, some SPPs (CMORPH–RAW v.1, CMORPH–CRT v.1, GSMaP v.6, PERSIANN, and TMPA–RT v.7) are unable to estimate regional precipitation, whereas the others (CHIRP v.2, CHIRPS v.2, CMORPH–BLD v.1, MSWEP v.2.1, PERSIANN–CDR, and TMPA–Adj v.7) produce a realistic representation despite recurrent spatial limitation over regions with contrasted emissivity, temperature and orography. In 9 out of 10 of the cases studied, streamflow was more realistically simulated when SPPs were used as forcing precipitation data rather than precipitation derived from the available precipitation gauge networks, whereas the SPP's ability to reproduce the duration of MODIS-based snow cover resulted in poorer simulations than simulation using available precipitation gauges. Interestingly, the potential of the SPPs varied significantly when they were used to reproduce gauge precipitation estimates, streamflow observations or snow cover duration and depending on the time window considered. SPPs thus produce space–time errors that cannot be assessed when a single indicator and/or time window is used, underlining the importance of carefully considering their space–time consistency before using them for hydro-climatic studies. Among all the SPPs assessed, MSWEP v.2.1 showed the highest space–time accuracy and consistency in reproducing gauge precipitation estimates, streamflow and snow cover duration. [ABSTRACT FROM AUTHOR]

Hydrological functions of river basins are summarized as collection, storage and discharge, which can be characterized by the dynamics of hydrological variables including precipitation, evaporation, storage and runoff. The temporal patterns of each variable can be indicators of the functionality of a basin. In this paper we introduce a measure to quantify the degree of similarity in intra-annual variations at monthly scale at different years for the four main variables. We introduce this measure under the term of recurrence and define it as the degree to which a monthly hydrological variable returns to the same state in subsequent years. The degree of recurrence in runoff is important not only for the management of water resources but also for the understanding of hydrologic processes, especially in terms of how the other three variables determine the recurrence in runoff. The main objective of this paper is to propose a simple hydrologic classification framework applicable to large basins at global scale based on the combinations of recurrence in the four variables using a monthly scale time series. We evaluate it with lagged autocorrelation (AC), fast Fourier transforms (FFT) and Colwell's indices of variables obtained from the EU-WATCH data set, which is composed of eight global hydrologic model (GHM) and land surface model (LSM) outputs. By setting a threshold to define high or low recurrence in the four variables, we classify each river basin into 16 possible classes. The overview of recurrence patterns at global scale suggested that precipitation is recurrent mainly in the humid tropics, Asian monsoon area and part of higher latitudes with an oceanic influence. Recurrence in evaporation was mainly dependent on the seasonality of energy availability, typically high in the tropics, temperate and sub-arctic regions. Recurrence in storage at higher latitudes depends on energy/water balances and snow, while that in runoff is mostly affected by the different combinations of these three variables. According to the river basin classification, 10 out of the 16 possible classes were present in the 35 largest river basins in the world. In the humid tropic region, the basins belong to a class with high recurrence in all the variables, while in the subtropical region many of the river basins have low recurrence. In the temperate region, the energy limited or water limited in summer characterizes the recurrence in storage, but runoff exhibits generally low recurrence due to the low recurrence in precipitation. In the sub-arctic and arctic regions, the amount of snow also influences the classes; more snow yields higher recurrence in storage and runoff. Our proposed framework follows a simple methodology that can aid in grouping river basins with similar characteristics of water, energy and storage cycles. The framework is applicable at different scales with different data sets to provide useful insights into the understanding of hydrologic regimes based on the classification. [ABSTRACT FROM AUTHOR]

Drought is an extended period of deficient precipitation that causes damage to crops and reducing their performance, causes temporary scarcity of water for human/livestock consumption. Over the years, various indices have been proposed to identify onset, characterize and quantify the attributes of meteorological, hydrological and agricultural drought by various researchers. Because of the spatial and temporal variability and multiple impacts of drought, it is necessary to develop an integrated index for assessment of vulnerability of this natural phenomenon. The aim of this paper is presenting an integrated index for assessment of vulnerability to drought using multiple factors which includes hydrological, meteorological, land use and other factors. Spatial information of various factors was categorized in to various sub-classes and maps were prepared in spatial domain using Geographic Information System (GIS). This study has been carried out in the Zayandehrood River basin located in west-central Iran with semi-arid region. Due to continue droughts at recent decade, this area has been chosen as a case study. The long-term climate data (1991-2011) used for assessment. The results show that Zayandehrood River basin has experienced 11 dry years, 4 normal years, and 6 wet years in the 21 years. The results have been validated with intensive field surveys. [ABSTRACT FROM AUTHOR]

Urbanization is a global process that has taken billions of people from the rural countryside to concentrated urban centers, adding pressure to existing water resources. Many cities are specifically reliant on renewable freshwater regularly refilled by precipitation, rather than fossil groundwater or desalination. A precipitationshed can be considered the “watershed of the sky” and identifies the origin of precipitation falling in a given region. In this paper, we use this concept to determine the sources of precipitation that supply renewable water in the watersheds of the largest cities of the world. We quantify the sources of precipitation for 29 megacities and analyze their differences between dry and wet years. Our results reveal that 19 of 29 megacities depend for more than a third of their water supply on evaporation from land. We also show that for many of the megacities, the terrestrial dependence is higher in dry years. This high dependence on terrestrial evaporation for their precipitation exposes these cities to potential land-use change that could reduce the evaporation that generates precipitation. Combining indicators of water stress, moisture recycling exposure, economic capacity, vegetation-regulated evaporation, land-use change, and dry-season moisture recycling sensitivity reveals four highly vulnerable megacities (Karachi, Shanghai, Wuhan, and Chongqing). A further six megacities were found to have medium vulnerability with regard to their water supply. We conclude that understanding how upwind landscapes affect downwind municipal water resources could be a key component for understanding the complexity of urban water security. [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]

The first part of this paper demonstrated the existence of bias in GCM-derived precipitation series, downscaled using either a statistical technique (here the Statistical Downscaling Model) or dynamical method (here high resolution Regional Climate Model HadRM3) propagating to river flow estimated by a lumped hydrological model. This paper uses the same models and methods for a future time horizon (2080s) and analyses how significant these projected changes are compared to baseline natural variability in four British catchments. The UKCIP02 scenarios, which are widely used in the UK for climate change impact, are also considered. Results show that GCMs are the largest source of uncertainty in future flows. Uncertainties from downscaling techniques and emission scenarios are of similar magnitude, and generally smaller than GCM uncertainty. For catchments where hydrological modelling uncertainty is smaller than GCM variability for baseline flow, this uncertainty can be ignored for future projections, but might be significant otherwise. Predicted changes are not always significant compared to baseline variability, less than 50% of projections suggesting a significant change in monthly flow. Insignificant changes could occur due to climate variability alone and thus cannot be attributed to climate change, but are often ignored in climate change studies and could lead to misleading conclusions. Existing systematic bias in reproducing current climate does impact future projections and must, therefore, be considered when interpreting results. Changes in river flow variability, important for water management planning, can be easily assessed from simple resampling techniques applied to both baseline and future time horizons. Assessing future climate and its potential implication for river flows is a key challenge facing water resource planners. This two-part paper demonstrates that uncertainty due to hydrological and climate modelling must and can be accounted for to provide sound, scientifically-based advice to decision makers. [ABSTRACT FROM AUTHOR]

The paper presents an analysis of the hydrological risk parameters registered in June 2016 in the catchment area of the Tazlăul Sărat River. The studies and researches were carried out on the upper course of the river, in the area between Zemeş and Toderaş, the commune of Zemeş, Bacau county. The river basin of the Tazlăul Sărat River has been affected by several floods in recent years. The floods have morphologically modified the minor and the major river bed, which has influenced the stability of the county road and the river construction. The study focused on the analysis of precipitation and liquid flows over a period of 20 years. Processing of liquid flow data revealed more flood flows in the same year. In 2016 there was a flow of 342 m3 / s (probability of 3%). The effects of the floods have materialized through the excessive degradation of shore defence works until their total destruction. The degradation of shore defence works has contributed to breaking the county road and limiting the road traffic. Parameters of hydroclimatic risk highlighted by research impose special conditions when designing shore defence works and protecting the road adjacent to the river. [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]

We present CAMELS-CH (Catchment Attributes and MEteorology for Large-sample Studies – Switzerland), a large-sample hydro-meteorological data set for hydrologic Switzerland in central Europe. This domain covers 331 basins within Switzerland and neighboring countries. About one-third of the catchments are located in Austria, France, Germany and Italy. As an Alpine country, Switzerland covers a vast diversity of landscapes, including mountainous environments, karstic regions, and several strongly cultivated regions, along with a wide range of hydrological regimes, i.e., catchments that are glacier-, snow- or rain dominated. Similar to existing data sets, CAMELS-CH comprises dynamic hydro-meteorological variables and static catchment attributes. CAMELS-CH (; available at 10.5281/zenodo.7784632) encompasses 40 years of data between 1 January 1981 and 31 December 2020, including daily time series of stream flow and water levels, and of meteorological data such as precipitation and air temperature. It also includes daily snow water equivalent data for each catchment starting from 2 September 1998. Additionally, we provide annual time series of land cover change and glacier evolution per catchment. The static catchment attributes cover location and topography, climate, hydrology, soil, hydrogeology, geology, land use, human impact and glaciers. This Swiss data set complements comparable publicly accessible data sets, providing data from the "water tower of Europe". [ABSTRACT FROM AUTHOR]

In this paper we combined a multimodel ensemble based on 15 regional climate models with a multicatchment approach to explore the hydrologic sensitivity of 14 neighboring and rather similar catchments to changing climate conditions. Current (1982-2010) and future (2062-2090) streamflow was simulated with the HBV model. A diagnostic approach was used, which considered major behavioral catchment functions by using hydrologically relevant signatures related to overall water balance, flow duration curves and hydrograph attributes. Projected increases in temperature and precipitation resulted in increased total available streamflow, with lower spring and summer flows, but substantially higher winter streamflow. Furthermore, significant changes in flow durations with lower chances of both high and low flows can be expected in boreal Sweden in the future. This overall trend in projected streamflow pattern changes was comparable among the analyzed catchments but the magnitude of change differed considerably. This suggests that catchments belonging to the same region can show distinctly different degrees of hydrological responses to the same external climate change signal. We reason that differences in spatially distributed physical catchment properties within catchments are not only of great importance for current streamflow behavior, but also play a major role in the sensitivity of catchments to changing climate conditions. [ABSTRACT FROM AUTHOR]

Temporal shifts in precipitation and runoff regime curves appear throughout the continental United States, but differ from region to region. This paper explores these regime shifts by building upon a hydroclimatic classification system that partitions the United States into clusters of similarly behaved catchments using four simple hydroclimatic indicators. Hydroclimate data from over four hundred catchments over a 55 year period (belonging to the MOPEX data set) are analyzed to reveal how the indicators have shifted before and after 1970, before and after 1975, and before and after 1980. Statistically significant hydroclimatic changes in these indicators are explored qualitatively, suggesting which catchments today might resemble other catchments tomorrow. Thus, a preview of current locations in one class under future conditions is provided by observing existing locations of another class. The classification system structure enables organization of these data, allowing patterns of regime change to emerge without highly specified models at each individual site. Regional analyses explore changes in mean seasonal precipitation/runoff regimes, including shifts in the daily variability of precipitation and runoff. Additionally, changes in regime curves of minimum and maximum precipitation/runoff observations are analyzed and discussed. Results indicate that after 1980, classifications typically found in the southeastern quarter of the United States have expanded northward and westward. Regionally, the Midwest and Rocky Mountains seem to demonstrate more frequent, but less intense storms after 1980, while southeastern catchments receive much less water in the form of precipitation and runoff than in previous years. [ABSTRACT FROM AUTHOR]

Retrieving precipitation data from a rain gauge network is a classical and common practice in hydrology and climatology. These data represent the key input in hydrological modeling to reproduce, for example, the characteristics of a flood phenomenon. The accuracy of the model results is strongly dependent on the consistency of the monitoring network in terms of spatial scale, i.e., network density and location of the rain gauges and time resolution. In this context, several studies have been carried out to analyze how the rainfall sampling influences the estimation of total runoff volume. The aim of this paper is to use a physically based and distributed-parameter hydrologic model to investigate how the number and the spatial distribution of a rain gauge network influence the estimation of the hydrograph and its characteristics in conjunction with different spatial and temporal characteristics of rainfall forcing and different soil-type characteristics. The TIN-based real-time integrated basin simulator (tRIBS) hydrologic model was used to simulate hydrologic response at Baron Fork Basin, Oklahoma. Downscaled next-generation radar (NEXRAD) measurements were assumed to represent the true precipitation distribution over the basin. Additional precipitation fields have been derived from the interpolation of eight fictitious rain gauges randomly placed in the area. The hydrological response from tRIBS that is driven by these precipitation fields has been compared with the response of the model forced with NEXRAD precipitation. The analysis has been carried out assuming first simplified spatial distributions of soil characteristics and then the real soil-type distribution. Results have shown the dependence of the best rain gauges configuration for the estimation of runoff on the spatiotemporal characteristics of storm events and the soil-type distribution. [ABSTRACT FROM AUTHOR]

This paper introduces a methodology for the construction of probabilistic inflow forecasts for multiple catchments and lead times. A postprocessing approach is used, and a Gaussian model is applied for transformed variables. In operational situations, it is a straightforward task to use the models to sample inflow ensembles which inherit the dependencies between catchments and lead times. The methodology was tested and demonstrated in the river systems linked to the Ulla-Førre hydropower complex in southern Norway, where simultaneous probabilistic forecasts for five catchments and ten lead times were constructed. The methodology exhibits sufficient flexibility to utilize deterministic flow forecasts from a numerical hydrological model as well as statistical forecasts such as persistent forecasts and sliding window climatology forecasts. It also deals with variation in the relative weights of these forecasts with both catchment and lead time. When evaluating predictive performance in original space using cross-validation, the case study found that it is important to include the persistent forecast for the initial lead times and the hydrological forecast for medium-term lead times. Sliding window climatology forecasts become more important for the latest lead times. Furthermore, operationally important features in this case study such as heteroscedasticity, lead time varying between lead time dependency and lead time varying between catchment dependency are captured. [ABSTRACT FROM AUTHOR]

Changes in precipitation can be expected to have a major influence on the frequency and severity of flooding in the Taihu Basin. As part of an integrated assessment of flood risk in the Taihu Basin, this paper addresses the hydrological conditions and the potential impacts of climate change on Taihu Lake water levels. The hydrological system is simulated by using the distributed hydrological model VIC ( Variable Infiltration Capacity), with future climate scenarios generated by the regional climate model PRECIS (Providing Regional Climates for Impacts Studies). The results indicate that maximum and mean flood water levels under the A2 and B2 scenarios for 2021-2050 will be higher than the levels during the baseline period (1961-1990), with larger increases under the B2 scenario than for the A2 scenario. The storm return periods leading to extreme water levels in the Taihu Lake in the future is projected to decrease significantly in comparison to the baseline period, implying the potential for the more frequent occurrence of major floods. These results indicate the importance of planning for future flood control in the Taihu Basin. [ABSTRACT FROM AUTHOR]

This paper presents an evaluation of the spatio-temporal patterns of hydrologic alteration induced by dam construction and precipitation variability in the Lancang River Basin of southwest China from 1957 to 2000. Analyses were conducted using the linear regression method, the Mann-Kendall test, and the Range of Variability Approach. The results indicate that there was considerable variation in the average monthly precipitation between the pre- and post-dam periods in the Lancang River Basin. Second, the magnitude of monthly runoff was strongly related to precipitation, which showed an up-down annual variation, and was significantly altered by dam construction and precipitation variability. In the modified series (hydrologic series with the precipitation impacts removed), runoff deviations between the pre- and post-dam periods became larger. Third, the extreme runoff cycles were influenced by dam construction and precipitation variability downstream from the dam, and the monthly maximum runoff increased from the pre-dam to post-dam period at all hydrologic stations. Fourth, the degree of hydrologic alteration (DHA) indicates that the precipitation variability not only affected the hydrologic regime of unregulated river reach but also modified the negative impacts of dam construction, which could provide a modest mitigation of the hydrologic alterations induced by dam construction, possibly decreasing the level of DHA. Last, the overall degree of hydrologic alteration in the observed series reached 25.2, 25.3, and 29.1 % for the upstream, midstream, and downstream areas, respectively. These results show that the hydrologic regimes of the Lancang River during the 1957-2000 period were affected by damming and precipitation variability, but the hydrologic alteration was relatively low in the upstream areas of the river without a dam. [ABSTRACT FROM AUTHOR]

Highly accurate and high-quality precipitation products that can act as substitutes for ground precipitation observations have important significance for research development in the meteorology and hydrology of river basins. In this paper, statistical analysis methods were employed to quantitatively assess the usage accuracy of three precipitation products, China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS), next-generation Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) and Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), for the Jinsha River Basin, a region characterized by a large spatial scale and complex terrain. The results of statistical analysis show that the three kinds of data have relatively high accuracy on the average grid scale and the correlation coefficients are all greater than 0.8 (CMADS:0.86, IMERG:0.88 and TMPA:0.81). The performance in the average grid scale is superior than that in grid scale. (CMADS: 0.86(basin), 0.6 (grid); IMERG:0.88 (basin),0.71(grid); TMPA:0.81(basin),0.42(grid)). According to the results of hydrological applicability analysis based on SWAT model, the three kinds of data fail to obtain higher accuracy on hydrological simulation. CMADS performs best (NSE:0.55), followed by TMPA (NSE:0.50) and IMERG (NSE:0.45) in the last. On the whole, the three types of satellite precipitation data have high accuracy on statistical analysis and average accuracy on hydrological simulation in the Jinsha River Basin, which have certain hydrological application potential. [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]

Summary: Hillslope hydrological response to precipitation is extremely complex and poorly modeled. One possible approach for reducing the complexity of hillslope response and its mathematical parameterization is to look for macroscale hydrological behavior. Hillslope threshold response to storm precipitation is one such macroscale behavior observed at field sites across the globe. Nevertheless, the relative controls on the precipitation–discharge threshold poorly known. This paper presents a combined model development, calibration and testing experiment study to investigate the primary controls on the observed precipitation–discharge threshold relationship. We focus on the dominant hydrological processes revealed in part one of this two-part paper and with our new numerical model, replicate the threshold response seen in the discharge record and other hydrometric and tracer data available at the site. We then present a series of virtual experiments designed to probe the controls on the threshold response. We show that the threshold behavior is due to a combination of environmental (storm spacing and potential evapotranspiration) and geologic (bedrock permeability and bedrock topography) factors. The predicted precipitation–discharge threshold subsumes the complexity of plot-scale soil water response. We then demonstrate its use for prediction of whole-catchment storm discharge at other first order catchments at Maimai and the HJ Andrews Experimental Forest in Oregon. [ABSTRACT FROM AUTHOR]

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The most important climatological inputs required for the calibration and validation of hydrological models are temperature and precipitation that can be derived from observational records or alternatively from regional climate models (RCMs). In this paper, meteorological station observations and results of the PRECIS (Providing REgional Climate for Impact Studies) RCM driven by the outputs of reanalysis ERA 40 data and HadAM3P general circulation model (GCM) results are used as input in the hydrological model. The objective is to investigate the effect of precipitation and temperature simulated with the PRECIS RCM nested in these two data sets on discharge simulated with the HBV model for three river basins in the Hindukush-Karakorum-Himalaya (HKH) region. Six HBV model experiments are designed: HBV-Met, HBV-ERA and HBV-Had, HBV-MetCRU-corrected, HBV-ERABenchmark and HBV-HadBenchmark where HBV is driven by meteorological stations data, data from PRECIS nested in ERA-40 and HadAM3P, meteorological stations CRU corrected data, ERA-40 reanalysis and HadAM3P GCM data, respectively. Present day PRECIS simulations possess strong capacity to simulate spatial patterns of present day climate characteristics. However, also some quantitative biases exist in the HKH region, where PRECIS RCM simulations underestimate temperature and overestimate precipitation with respect to CRU observations. The calibration and validation results of the HBV model experiments show that the performance of HBV-Met is better than the HBV models driven by other data sources. However, using input data series from sources different from the data used in the model calibration shows that HBV-Had is more efficient than other models and HBV-Met has the least absolute relative error with respect to all other models. The uncertainties are higher in least efficient models (i.e. HBV-MetCRU-corrected and HBV-ERABenchmark) where the model parameters are also unrealistic. In terms of both robustness and uncertainty ranges the HBV models calibrated with PRECIS output performed better than other calibrated models except for HBV-Met which has shown a higher robustness. This suggests that in data sparse regions such as the HKH region data from regional climate models may be used as input in hydrological models for climate scenarios studies. [ABSTRACT FROM AUTHOR]

Accurate parameter estimation is important for reliable rainfall-runoff modeling. Previous studies emphasize that a sufficient length of continuous events is required for model calibration to overcome the effect of initial conditions. This paper investigates the feasibility of calibrating rainfall-runoff models over a number of limited storm flow events. For a subcatchment having a moderate influence from initial soil moisture conditions, this study shows that rainfall-runoff models could still be calibrated reliably over a set of representative events provided that the events cover a wide range of peak flow, total runoff volume, and initial soil moisture conditions. This approach could provide an alternative calibration strategy for a small watershed that has a limited data length but consists of runoff events with a wide range of magnitudes. Compared to continuous-event calibration, event-based calibration appears to perform better in simulating the overall shape of hydrograph, peak flow and time to peak. However, continuous-event calibration was found to be more reliable in providing runoff volume, suggesting that continuous-event calibration should still be used when runoff volume is the main concern of a study. [ABSTRACT FROM AUTHOR]

Alpine regions are particularly affected by seasonal variations in water demand and water availability. Especially the winter period is critical from an operational point of view, as being characterised by high water demands due to tourism and low water availability due to the temporal storage of precipitation as snow and ice. The clear definition of summer and winter periods is thus an essential prerequisite for water resource management in alpine regions. This paper presents a GIS-based multi criteria method to determine the winter season. A snow cover duration dataset serves as basis for this analysis. Different water demand stakeholders, the alpine hydrology and the present day water supply infrastructure are taken into account. Technical snow-making and (winter) tourism were identified as the two major seasonal water demand stakeholders in the study area, which is the Kitzbueheler region in the Austrian Alps. Based upon different geographical datasets winter was defined as the period from December to March, and summer as the period from April to November. By determining potential regional water balance deficits or surpluses in the present day situation and in future, important management decisions such as water storage and allocation can be made and transposed to the local level. [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]

Extreme precipitation can cause flooding and may result in great economic losses and deaths. The return level is a commonly used measure of extreme precipitation events and is required for hydrological engineer designs, including those of sewerage systems, dams, reservoirs and bridges. In this paper, we propose a two-step method to estimate the return level and its uncertainty for a study region. In the first step, we use the generalized extreme value distribution, the L-moment method and the stationary bootstrap to estimate the return level and its uncertainty at the site with observations. In the second step, a spatial model incorporating the heterogeneous measurement errors and covariates is trained to estimate return levels at sites with no observations and to improve the estimates at sites with limited information. The proposed method is applied to the daily rainfall data from 273 weather stations in the Haihe river basin of North China. We compare the proposed method with two alternatives: the first one is based on the ordinary Kriging method without measurement error, and the second one smooths the estimated location and scale parameters of the generalized extreme value distribution by the universal Kriging method. Results show that the proposed method outperforms its counterparts. We also propose a novel approach to assess the two-step method by comparing it with the at-site estimation method with a series of reduced length of observations. Estimates of the 2-, 5-, 10-, 20-, 50- and 100-year return level maps and the corresponding uncertainties are provided for the Haihe river basin, and a comparison with those released by the Hydrology Bureau of Ministry of Water Resources of China is made. [ABSTRACT FROM AUTHOR]

The dump catchments water regime optimization is one of fundamental recultivation operations in areas devastated after surface coal mining. Two dump catchments (at Radovesice and Loket in the Krušné hory Mts., Czech Republic) were selected to study whether their hydrological balance allows to keep life in them on a sufficiently natural level. The WBCM-6 water balance model was implemented. Different hydrological conditions of the mentioned dump catchments located ca. 90 km apart were compared. The Radovesice catchment lies in a precipitation shadow and suffers from a much greater precipitation deficiency than the Loket one. Its long-term annual precipitation deficit makes about 100 mm. Based on the analysis of the dry year 2003 growing season, biotechnical hydrological measures, in particular cascades of small reservoirs, were proposed. [ABSTRACT FROM AUTHOR]

Summary The multisensor Quantitative Precipitation Estimates (MQPEs) created by the US National Weather Service (NWS) are subject to a non-stationary bias. This paper quantifies the impacts of climatological adjustment of MQPEs alone, as well as the compound impacts of adjustment and model calibration, on the accuracy of simulated flood peak magnitude and that in detecting flood events. Our investigation is based on 19 watersheds in the mid-Atlantic region of US, which are grouped into small (<500 km 2 ) and large (>500 km 2 ) watersheds. NWS archival MQPEs over 1997–2013 for this region are adjusted to match concurrent gauge-based monthly precipitation accumulations. Then raw and adjusted MQPEs serve as inputs to the NWS distributed hydrologic model-threshold frequency framework (DHM-TF). Two experiments via DHM-TF are performed. The first one examines the impacts of adjustment alone through uncalibrated model simulations, whereas the second one focuses on the compound effects of adjustment and calibration on the detection of flood events. Uncalibrated model simulations show broad underestimation of flood peaks for small watersheds and overestimation those for large watersheds. Prior to calibration, adjustment alone tends to reduce the magnitude of simulated flood peaks for small and large basins alike, with 95% of all watersheds experienced decline over 2004–2013. A consequence is that a majority of small watersheds experience no improvement, or deterioration in bias (0% of basins experiencing improvement). By contrast, most (73%) of larger ones exhibit improved bias. Outcomes of the detection experiment show that the role of adjustment is not diminished by calibration for small watersheds, with only 25% of which exhibiting reduced bias after adjustment with calibrated parameters. Furthermore, it is shown that calibration is relatively effective in reducing false alarms (e.g., false alarm rate is down from 0.28 to 0.19 after calibration for small watersheds with calibrated parameters); but its impacts on detection rate are mixed. As an example, the detection rate of 2-Y events in fact declines for small watersheds after calibration is performed (from 0.4 to 0.28, and from 0.28 to 0.19 with raw and adjusted MQPE, respectively). These mixed outcomes underscore the complex interplays between errors in MQPEs, conditional bias in the reference gauge-based analysis, and structural deficiencies of the hydrologic model. [ABSTRACT FROM AUTHOR]

The aim of this paper is to assess the impacts of projected climate change on a Mediterranean catchment, and to analyze the effects of a suite of representative land use practices as an adaptation tool to reduce climate change-driven erosion and hydrologic extremes. Relevant climatic variables from the ERA-Interim global atmospheric reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) were downscaled for the study area, and perturbed with the anomalies of 23 global circulation models for three emission scenarios (B1, A1B and A2). Both a projected daily rainfall time series for the period 2010–2100, and a single precipitation event with a one-hundred year return period were used to assess the impact of climate change. The downscaled data were fed into a distributed hydro-sedimentary model (TETIS) with five land use configurations representative of future demographic tendencies, geographical characteristics and land management policies (e.g. European Union CAP). The projected changes showed a general decrease in runoff and sediment production by the end of the century regardless of land use configuration. Sediment production showed a positive relationship with an increase in agricultural land and a decrease in natural land under present day agricultural management. According to our simulations, some conservation practices in agriculture can effectively reduce net erosion while maintaining agricultural production. As such, they can play a critical role as an adaptation tool to reduce climate change impacts in the 21st century. [ABSTRACT FROM AUTHOR]

Information about the formation, destruction, and duration of river ice regimes is especially important for hydropower, shipping, fisheries, etc. Research into modern trends in river ice regimes and their spatial and temporal fluctuations is essential, especially in a changing climate. This study examines the trends and fluctuations of air temperature and ice regimes based on series of observations in the Prypiat River basin within Ukraine. Air temperature data from 17 meteorological stations and ice data from 29 water gauges were analyzed. A complex analytical approach involving statistical and graphical methods was employed. The Mann-Kendall statistical test, mass curve, residual mass curve, and combined graphs were used in the study. In the Prypiat River basin within Ukraine, observations of mean monthly air temperature, ice occurrence, freeze-up, and their duration are homogeneous (quasi-homogeneous) and stationary (quasi-stationary). The quasi-homogeneous and quasi-stationary characteristics are explained by the presence in the observation series of only increasing and decreasing phases of long-term cyclical fluctuations, which are incomplete. The trends of air temperature and ice regime correspond strongly, indicating the defining role of air temperature in the formation of ice occurrence and freeze-up. Since the end of the 1990s, the warming phase of air temperature in the autumn-winter period determines the appearance of ice and freeze-up later in the year. In March, the warming trend in air temperature, which began after 1988, determines the freezeup, break-up, and disappearance of ice earlier in the year. Thus, the duration of ice and freeze-up on the rivers has decreased. [ABSTRACT FROM AUTHOR]

Evaluating the hydrological application of reanalysis datasets is of practical importance for the design of water resources management and flood controlling facilities in regions with sparse meteorological data. This paper compared a new reanalysis dataset named CMADS with gauge observations and investigated the performance of the hydrological application of CMADS on daily streamflow, evapotranspiration, and soil moisture content simulations. The results show that: CMADS can represent meteorological elements including precipitation, temperature, relative humidity, and wind speed reasonably for both daily and monthly temporal scales while underestimates precipitation compared with gauge observations slightly (<15%). The hydrological model using CMADS dataset as meteorological inputs can capture the daily streamflow chracteristics well overall (with a NS value of 0.56 during calibration period and 0.61 during validation period) but underestimates streamflow obviously (with a BIAS of − 42.42 % during calibration period and a BIAS of − 33.29 % during validation period). The underestimation of streamflow simulated with CMADS dataset is more seriously in dry seasons ( − 48.40 %) than that in wet seasons ( − 39.41 %) for calibration period. The model driven by CMADS estimates evapotranspiration and soil moisture content well compared with the model driven by gauge observations. [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]

Increase of precipitation intensity is the most definite and detectable hydrological consequence of a warmer climate. Among all U.S. regions, the Northeast has witnessed the strongest increase of extreme precipitation in the past five decades. This study examines the impact of climate changes during 1950–2011 on hydrological processes in the Northeast using the Connecticut River Basin as a case study. In addition to precipitation and river discharge data from observations, the Variable Infiltration Capacity (VIC) hydrological model is used to derive hydrological variables for which long-term observational data are not readily available. Our results show a clear increase of precipitation intensity, with substantial increase in both the number of days with greater than 10 mm precipitation and the simple daily intensity index. From 1950 to 2011, extreme precipitation amount (which is the total amount of precipitation from the upper 1% of daily precipitation) increased substantially, by 240% relative to the 1950 level. The weight of extreme precipitation as a fraction of total precipitation also increased, from about 10.6% in the 1950s to 30.4% in the 2000s. Despite the increase of precipitation extremes, the consecutive dry days experienced a slight decrease. Mean trend analysis shows indications of increasing precipitation amount, increasing discharge, increasing runoff ratios, increasing soil moisture, and a negligible evapotranspiration trend. Our simulations suggest that the basin is entering a wetter regime more subject to meteorological flood conditions than to drought conditions. A companion paper will investigate how these trends may persist or differ in the mid-21st century under continued warming. [ABSTRACT FROM AUTHOR]

This paper summarizes 12 years of snow water equivalent (SWE) observations collected in the data-sparse region of Arctic Alaska, United States. The In situ observations are distributed across a 200 x 300 km domain that includes the Kuparuk River watershed from the Brooks Range to the Beaufort Sea coast. Data collection methods and analyses were classified to distinguish between snow observation sites representing regional- and local-scale variability. Average SWE for the entire domain ranges from 92 mm in 2008 to 148 mm in 2011. Regional end-of-winter SWE indicates that both the extreme high SWE in 2009 and 2011 and the extreme low SWE in 2008 occurred during recent and alternating years, suggesting the limitations of 12 years of data for detecting SWE trends. By assimilating the observational datasets into SnowModel, hourly 100 m gridded SWE distributions for the central Alaska Arctic were created to provide a best-fit to the observations where and when they occur. The model simulations highlight how observed SWE data can be used as a surrogate for the more problematic winter precipitation measurements. The resulting SWE distributions are readily available to support ecological and hydrologic studies in this region. [ABSTRACT FROM AUTHOR]

Summary: The Mekong River Basin in South East Asia has experienced in recent decades large inter-annual variations between large floods and severe droughts. The general perception is that climate variability has increased in the region. In this paper our aim was to examine the role of El Niño-Southern Oscillation (ENSO) on these recent climate variations. To achieve our aim, we analysed the influence of ENSO on precipitation (over period 1981–2005) and discharge (1910–2008) by using spatial GIS analyses and statistical methods, such as linear correlations, spectral analysis and stochastic regression models. We found that the Mekong’s hydrology was significantly influenced by ENSO, particularly in the decay year of ENSO events. The influence was strongest in the southern parts of the basin. The precipitation and discharge decreased (increased) during El Niño (La Niña) and the annual flood period was shorter (longer) during El Niño (La Niña). We found also decadal variations in the ENSO-discharge relationship. Our findings indicate high potential for developing prediction methods for ENSO induced hydrological anomalies. These findings may significantly improve the possibility of preparing for extreme hydrological events, either drought or exceptional floods, and thus potentially improve water resources management in the basin. [ABSTRACT FROM AUTHOR]

Both climate change and human activities are known to have induced changes to hydrology. Consequently, quantifying the net impact of human contribution to the streamfiow change is a challenge. In this paper, a decomposition method based on the Budyko hypothesis is used to quantify the climate (i.e., precipitation and potential evaporation change) and direct human impact on mean annual streamflow (MAS) for 413 watersheds in the contiguous United States. The data for annual precipitation, runoff, and potential evaporation are obtained from the international Model Parameter Estimation Experiment (MOPEX), which is often assumed to only include gauges unaffected by human interferences. The data are split into two periods (1948-1970 and 1971-2003) to quantify the change over time. Although climate is found to affect MAS more than direct human impact, the results show that assuming the MOPEX data set to be unaffected by human activities is far from realistic. Climate change causes increasing MAS in most watersheds, while the direct human-induced change is spatially heterogeneous in the contiguous United States, with strong regional patterns, e.g., human activities causing increased MAS in the Midwest and significantly decreased MAS in the High Plains. The climate- and human-induced changes are found to be more severe in arid regions, where water is limited. Comparing the results to a collection of independent data sets indicates that the estimated direct human impacts on MAS in this largely nonurban set of watersheds might be attributed to several human activities, such as cropland expansion, irrigation, and the construction of reservoirs. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of precipitation changes in the main Hydrological Divisions (HDs; 'Cuencas Hidrográficas', Water Planning Divisions) in Spain from 1946-2005. Trend analysis revealed several monthly long-term variations and important spatial differences that should be taken into account for any national water-planning scheme. The most spatially coherent signals were a negative trend observed in March and June, affecting all catchments (HDs), and a positive trend in October, which was particularly evident in the northwestern catchments. These caused a redistribution of precipitation throughout the year, with a reduction in the length of the wet season (due to the negative trend in March) and a concentration of precipitation at the beginning of the wet season in October. A running trend analysis revealed variability in the long-term tendency which, although quite persistent, changed in strength between sub-periods. [ABSTRACT FROM AUTHOR]

Relationships between environmental variables associated with the spread of vector-borne pathogens, such as RNA viruses transmitted to humans and animals, remain poorly understood. Vesicular stomatitis (VS) is caused by a vector-borne, zoonotic RNA virus (VSV) and is the most common vesicular disease affecting livestock (domestic horses, cattle, pigs) throughout the Americas. This investigation focused on explaining patterns of more than 1500 VS-infected livestock premises in the western USA from 2004 to 2016 related to the ecology of the host-vector-virus-environment system. We investigated the relationship between VS incidents and habitat characteristics expected to be important to insect vectors: stream location, streamflow conditions, climate, and vegetation. Results show that VS incidents were distributed near the stream network with 72% located within 1 km of lotic habitat. Monthly incidents were closest to lotic habitat in April (x = 525 m) and furthest from lotic habitat in November, December and January (1843, 2141 and 4807 m) indicating that initial infection near streams may spread away from these locations. All first incidents (n = 35) occurred following peak annual streamflow, with 89% (31 of 35) of these occurring after streams returned to baseflow. This finding indicated that surveillance for VS could be targeted spatially in locally relevant geographic areas (that is, near streams) and temporally relative to local streamflow conditions which can be remotely monitored via existing web-accessible information networks. Habitat modeling of 11 subwatersheds revealed somewhat different models for each watershed with several factors important in multiple watersheds. In nine of the 11 watersheds, the highest model PC (31-71%) represented either higher-than-average long-term mean temperature or lower-than-average long-term mean precipitation. Approaching habitat modeling on a watershed basis reveals information to support additional research. These spatial and temporal relationships showcase the importance of hydrologic contributions to the emergence and distribution of an arthropod-borne disease in the western USA. [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]

Tropical high‐elevation lakes are considered sentinels of global climate change. This work characterizes the hydrological conditions of tropical alpine glacial lakes located in the highlands of Chirripó, Costa Rica, using a unique data set of water stable isotopes (δ2H and δ18O) in precipitation, stream water, and lake water between September 2015 and July 2017. A combined dataset of bathymetric, hydrometric, and isotope data collected between July 2016 and July 2017 on Lake Ditkevi was used to calculate the annual water balance of the lake. Evaporation to inflow ratios from three lake systems was estimated using a linear resistance model, the experimentally estimated local evaporation line of Chirripó, and the first glacial lake water evaporation lines in the region. The temporal isotopic variations (δ18O, d‐excess, and lc‐excess) confirm variations in the dry and wet season evaporative conditions for the glacial lakes and consistently average annual low evaporation to inflow (E/I) ratios in the range of 2.0 ± 0.8% and 18.1 ± 12.2%. Lake Ditkevi's water balance indicates annual steady‐state conditions, with an estimated evaporation loss of 650 mm/year (10.0 ± 5.0% of inflow), a high‐water contribution to the catchment (90% of inflow), a residence time of 0.53 ± 0.27 years, and a catchment scale (0.289 km2) water yield or depth equivalent run‐off of 278 mm/yr. These results provide novel information about water balance and evaporation losses in tropical alpine glacial lakes, which can serve as baseline information for future isotope‐based hydro‐climate research in high‐elevation regions in the tropics and elsewhere. [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]

While many studies on tribal water resources of individual tribal lands in the United States (US) have been conducted, the importance of tribal water resources at a national scale has largely gone unrecognized because their combined totals have not been quantified. Thus, we sought to provide a numerical estimate of major water budget components on tribal lands within the conterminous US and on USGS hydrologic unit codes (HUC2) regions. Using existing national-scale data and models, we estimated mean annual precipitation, evapotranspiration, excess precipitation, streamflow, and water use for the period 1971–2000. Tribal lands represent about 3.4 percent of the total land area of the conterminous US and on average account for 1.9 percent of precipitation, 2.4 percent of actual evapotranspiration, 0.95 percent of excess precipitation, 1.6 percent of water use, and 0.43 percent of streamflow origination. Additionally, approximately 9.5 and 11.3 percent of US streamflow flows through or adjacent as boundaries to tribal lands, respectively. Streamflow through or adjacent to tribal lands accounts for 42 and 48 percent of streamflow in the Missouri region, respectively; and for 86 and 88 percent in the Lower Colorado region, respectively. On average, 5,600 million cubic meters of streamflow per year was produced on tribal lands in the Pacific Northwest region, nearly five times greater than tribal lands in any other region. Tribal lands in the Great Lakes, Missouri, Arkansas-White-Red, and California regions all produced between 1,000 and 1,400 million cubic meters per year. [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]

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]