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In our original paper (Nat Hazards 76:327-346, . doi:), we analyzed hydrological droughts based on the minimum values of the streamflow drought index at different time scales using L-moments. In this paper, we highlight the importance of the magnitude and type of selected drought index for regional frequency analysis and discuss the validity of results only for station clusters considered in response to the commentary by Bahmani and Khorsandi (Nat Hazards, . doi:). [ABSTRACT FROM AUTHOR]

Nature-based solutions (NBSs), a sustainable landscape restoration approach, covers rebuilding ecological functionality and integrity in a watershed. The objective of restoration with NBSs is to revitalize the ecosystems to provide and sustain multiple services. Therefore, it is more than just planting trees or rewetting wetlands. NBSs can provide effective landscape restoration and management tools but should be applied on a methodological basis to get the full benefits. The methodological basis includes the type and nature of NBS, the application principles, and the tools to assess the efficiency of the set of NBS applied. However, most literature on NBSs is theoretical, while practitioners need applicable guidance. In this paper, we reviewed the latest literature on the NBSs and tried to connect the theory with some practical examples. We also underlined that NBSs applied in landscape restoration should relate to watershed processes since streamflow and/or stream quality are significant performance indicators. The NBSs should strengthen the resiliency towards multiple stressors and disturbances in a landscape. The widespread stressors in Türkiye landscapes are related to water balance that compares precipitation and evapotranspiration. Therefore, we suggest Budyko theory application in evaluating NBS options instead of typical climate models. Overall, this paper defines NBSs, provides examples, discusses possible methodologies, and comes up with some practical conclusions. The points we discuss are the resiliency assessment approach, scale, and location of the application, identifying the problems in a watershed through adequate quantitative indicators, and setting up the thresholds planned to be achieved. [ABSTRACT FROM AUTHOR]

EPA SWMM hydraulic modeling requires the estimation of different parameters allowing the determination of the basin's response upon a given precipitation event. Some physical parameters, such as area or perimeter, are measurable and can be accurately determined; however, other parameter estimation presents greater uncertainty, such as the width parameter. For regular and uniform drainage areas, width parameter estimation is relatively simple; however, when a complete irregular basin analysis is required, width determination presents greater uncertainty, and its representativeness becomes complicated to define. Width determination is idealized with the representation of a rectangle, where, for an equal area, a higher width will result in a faster response of the basin, while a lower width will result in a slower response of the basin. This paper attempts to estimate a representative value of width for a realistic, irregularly shaped basin by defining the equivalent rectangle, which takes into account the area, perimeter, and compactness index of the basin. The compactness index can be used to classify the basin by its shape. The shape of the basin is an indicator of how the precipitation histograms are temporally distributed and how the water flows through the basin, i.e., it defines the response speed of the basin, as the width parameter does in modeling. The width parameter has a high sensitivity in the EPA SWMM modeling results; therefore, an inaccurate estimation of the parameter leads to unrepresentative results. For this reason, this study seeks to find an optimal methodology to reduce modeling uncertainty and achieve more accurate simulations of an irregular watershed's hydrological response. [ABSTRACT FROM AUTHOR]

This paper uses hindcasts (1981–2010) to investigate the sources of skill in seasonal hydrological forecasts for Europe. The hindcasts were produced with WUSHP (Wageningen University Seamless Hydrological Prediction system). Skill was identified in a companion paper. In WUSHP, hydrological processes are simulated by running the Variable Infiltration Capacity (VIC) hydrological model forced with an ensemble of bias-corrected output from the seasonal forecast system 4 (S4) of the European Centre for Medium-Range Weather Forecasts (ECMWF). We first analysed the meteorological forcing. The precipitation forecasts contain considerable skill for the first lead month but hardly any significant skill at longer lead times. Seasonal forecasts of temperature have more skill. Skill in summer temperature is related to climate change and is more or less independent of lead time. Skill in February and March is unrelated to climate change. Different sources of skill in hydro-meteorological variables were isolated with a suite of specific hydrological hindcasts akin to ensemble streamflow prediction (ESP). These hindcasts show that in Europe, initial conditions of soil moisture (SM) form the dominant source of skill in run-off. From April to July, initial conditions of snow contribute significantly to the skill. Some remarkable skill features are due to indirect effects, i.e. skill due to forcing or initial conditions of snow and soil moisture at an earlier stage is stored in the hydrological state (snow and/or soil moisture) of a later stage, which then contributes to persistence of skill. Skill in evapotranspiration (ET) originates mostly in the meteorological forcing. For run-off we also compared the full hindcasts (with S4 forcing) with two types of ESP (or ESP-like) hindcasts (with identical forcing for all years). Beyond the second lead month, the full hindcasts are less skilful than the ESP (or ESP-like) hindcasts, because inter-annual variations in the S4 forcing consist mainly of noise which enhances degradation of the skill. [ABSTRACT FROM AUTHOR]

Copyright of Hydrogeology & Engineering Geology / Shuiwendizhi Gongchengdizhi is the property of Hydrogeology & Engineering Geology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents adjustment routines for Geonor totalizing precipitation gauge data collected from the headwaters of the Oldman River, within the southwestern Alberta Canadian Rockies. The gauges are situated at mountain valley and alpine ridge locations with varying degrees of canopy cover. These data are prone to sensor noise and environment-induced measurement errors requiring an ordered set of quality control (QC) corrections using nearby weather station data. Sensor noise at valley sites with single-vibrating wire gauges accounted for the removal of 5% to 8% (49-76 mm) of annual precipitation. This was compensated for by an increase of 6% to 8% (50-76 mm) from under-catch. A three-wire ridge gauge did not experience significant sensor noise; however, the under-catch of snow resulted in 42% to 52% (784-1342 mm) increased precipitation. When all QC corrections were applied, the annual cumulative precipitation at the ridge demonstrated increases of 39% to 49% (731-1269 mm), while the valley gauge adjustments were 􀀀4% to 1% (􀀀39 mm to 13 mm). Public sector totalizing precipitation gauge records often undergo minimal QC. Care must be exercised to check the corrections applied to such records when used to estimate watershed water balance or precipitation orographic enhancement. Systematic errors at open high-elevation sites may exceed nearby valley or forest sites. [ABSTRACT FROM AUTHOR]

The present paper presents the influence of the main factors that generate the maximum flow in the upper basin of the Crisul Negru river. Starting from the three types of flow in the basin (maximum, average and minimum) and selecting among them the most representative from the hydrological point of view - the maximum characteristic leak, data from meteorological and hydrological observations have been used since the 1950s. Characteristic and important, for this type of flow in the basin, are the data collected from the main gauging stations in the catchment area of the upper reception basin of Crişul Negru. Within the paper are presented and analyzed the main elements of the maximum leak as well as the meteorological data recorded in the receiving basin taken into consideration. The characteristic elements of the flow in the riverbeds - flows, levels, hydrological parameters, as well as the determining elements in the formation of the flow - air temperatures and precipitation are taken into account. On the basis of the data processed, analyzed and graphically represented in various forms, the close connection between all these generating elements was emphasized and in some cases they maintain the maximum flow type in the reception area of the upper Crisul Negru basin. [ABSTRACT FROM AUTHOR]

An increasing and wide attention has been paid to the effect of artificial reservoirs on river geomorphology, water ecological environment system and hydrological characteristics. In this paper, two reservoirs on the Shiguan River, a tributary of the Huaihe River Basin, Meishan Reservoir and Nianyushan Reservoir are used as the study area. Samples are taken from the water body of the reservoirs, the Jiangjiaji section in the downstream of the reservoir, the Wangjiaba and Runheji sections at the upstream and downstream sections of the main stream of the Huaihe River in December 2020 to analyze the spatiotemporal variation characteristics of hydrochemistry ion, electrical conductivity, hydrogen and oxygen isotope content, and discuss the impact of reservoir construction on the water cycle of the basin. The results show that the two isotopic compositions of the water body have the same trend along the river direction, and the overall trend is positive. One is the dam interception and the other is the influence of latitude effect. The temporal change of isotopic concentration of the water bodies in the Meishan Reservoir and Nianyushan Reservoir is relatively stable, the isotopic temporal change of the upstream Wangjiaba Station is relatively stable, and that of the two sections on the tributary and the main stream affected by the reservoir fluctuates greatly. Hydrogen and oxygen isotopic composition of the river and the reservoir deviates from the local atmospheric precipitation line, mainly due to the interception effect of the reservoir, so that the evaporation is stronger than that of the ordinary river. The lower reaches of Jiangjiaji and Runheji Cl- and the electrical conductivity are affected by the water discharge from the reservoir, the value of which decreases. Jiangjiaji is closer to the reservoir and has a greater impact. [ABSTRACT FROM AUTHOR]

This paper presents the first study to identity, in historical records, regional changes in the mechanisms of extreme water available for runoff (W). We used a quality‐controlled Snowpack Telemetry data set (1979–2017) combined with the nonparametric regional Kendall test to examine changes in annual maximum W under four hydrometeorological conditions (melt only/rain‐on‐snow/all melt/all melt plus rainfall) over the mountainous regions of the western United States. Under a warming climate, our analyses indicated significant declining trends in annual maximum W at regional scale under all four conditions. The annual maximum of all melt plus rainfall decreased significantly by 15% in the southwestern United States, while the frequency of rain‐on‐snow events increased significantly by 32% in the northwestern United States. The annual maximum snowmelt only decreased significantly by 21% across the entire western United States. Our results confirmed that interaction between regional humidity and solar radiation with warming temperature helps drive these changes. Plain Language Summary: In the western United States, mountain snowmelt generates about 50% of the region's streamflow and plays a critical role in sustaining water resources. It is important to understand how snowpack are changing under warming, as risks related to these changes involve trillions of dollars. This paper presents the first study to identify, in historical records, large‐scale changes in the mechanisms of extreme water available for runoff (W). We used a regional trend analysis to examine spatiotemporal changes in rain‐on‐snow (ROS) frequency and the mechanisms of extreme W from 1979 to 2017, based on our newly developed quality‐controlled observed snow and precipitation data set. We found that, under a significant warming trend, annual maximum W from snowmelt only (not including ROS) has been decreasing by 21% across the western United States. The northwestern United States showed significant increasing trends in ROS frequency by 32%, but the rate of annual maximum ROS showed nonsignificant trends (i.e., more frequent but similar in magnitude). The annual maximum W from all conditions (melt plus rain) has been decreasing significantly by 15% in the southwestern United States. Decreasing trends in the mechanisms of extreme W may have significant ramifications for water management relative to flood risk and public safety. Key Points: Annual maximum snowmelt (not including rain‐on‐snow) decreased significantly by 21% averaged across the snowy regions of the western United StatesThe frequency of rain‐on‐snow events increased significantly by 32% averaged in the higher humidity snowy regions of the northwestern United StatesAnnual maximum water available for runoff (melt + rain) decreased significantly by 15% in the snowy regions of the southwestern United States [ABSTRACT FROM AUTHOR]

This paper proposes a systematic assessment of the performance of an analytical modeling framework for streamflow probability distributions for a set of 25 Swiss catchments. These catchments show a wide range of hydroclimatic regimes, including namely snow-influenced streamflows. The model parameters are calculated from a spatially averaged gridded daily precipitation data set and from observed daily discharge time series, both in a forward estimation mode (direct parameter calculation from observed data) and in an inverse estimation mode (maximum likelihood estimation). The performance of the linear and the nonlinear model versions is assessed in terms of reproducing observed flow duration curves and their natural variability. Overall, the nonlinear model version outperforms the linear model for all regimes, but the linear model shows a notable performance increase with catchment elevation. More importantly, the obtained results demonstrate that the analytical model performs well for summer discharge for all analyzed streamflow regimes, ranging from rainfall-driven regimes with summer low flow to snow and glacier regimes with summer high flow. These results suggest that the model's encoding of dischargegenerating events based on stochastic soil moisture dynamics is more flexible than previously thought. As shown in this paper, the presence of snowmelt or ice melt is accommodated by a relative increase in the discharge-generating frequency, a key parameter of the model. Explicit quantification of this frequency increase as a function of mean catchment meteorological conditions is left for future research. [ABSTRACT FROM AUTHOR]

Numerical weather prediction (NWP) models are fundamental to extend forecast lead times beyond the concentration time of a watershed. Particularly for flash flood forecasting in tropical mountainous watersheds, forecast precipitation is required to provide timely warnings. This paper aims to assess the potential of NWP for flood early warning purposes, and the possible improvement that bias correction can provide, in a tropical mountainous area. The paper focuses on the comparison of streamflows obtained from the post-processed precipitation forecasts, particularly the comparison of ensemble forecasts and their potential in providing skilful flood forecasts. The Weather Research and Forecasting (WRF) model is used to produce precipitation forecasts that are post-processed and used to drive a hydrologic model. Discharge forecasts obtained from the hydrological model are used to assess the skill of the WRF model. The results show that post-processed WRF precipitation adds value to the flood early warning system when compared to zeroprecipitation forecasts, although the precipitation forecast used in this analysis showed little added value when compared to climatology. However, the reduction of biases obtained from the post-processed ensembles show the potential of this method and model to provide usable precipitation forecasts in tropical mountainous watersheds. The need for more detailed evaluation of the WRF model in the study area is highlighted, particularly the identification of the most suitable parameterisation, due to the inability of the model to adequately represent the convective precipitation found in the study area. [ABSTRACT FROM AUTHOR]

It is expected that climate warming will be experienced through increases in the magnitude and frequency of extreme events, including droughts. This paper presents an analysis of observed changes and future projections for meteorological drought for four different time scales (1 month, and 3, 6 and 12 months) in the Beijiang River basin, South China, on the basis of the standardized precipitation evapotranspiration index (SPEI). Observed changes in meteorological drought were analysed at 24 meteorological stations from 1969 to 2011. Future meteorological drought was projected based on the representative concentration pathway (RCP) scenarios RCP4.5 and RCP8.5, as projected by the regional climate model RegCM4.0. The statistical significance of the meteorological drought trends was checked with the Mann-Kendall method. The results show that drought has become more intense and more frequent in most parts of the study region during the past 43 years, mainly owing to a decrease in precipitation. Furthermore, long-term dryness is expected to be more pronounced than short-term dryness. Validation of the model simulation indicates that RegCM4.0 provides a good simulation of the characteristic values of SPEIs. During the twenty first century, significant drying trends are projected for most parts of the study region, especially in the southern part of the basin. Furthermore, the drying trends for RCP8.5 (or for long time scales) are more pronounced than for RCP4.5 (or for short time scales). Compared to the baseline period 1971-2000, the frequency of drought for RCP4.5 (RCP8.5) tends to increase (decrease) in 2021-2050 and decrease (increase) in 2051-2080. The results of this paper will be helpful for efficient water resources management in the Beijiang River basin under climate warming. [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]

Copyright of Geomatics & Information Science of Wuhan University is the property of Geomatics & Information Science of Wuhan University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The focus of this paper was to investigate the spatial and temporal variability of dry and wet events using the standard precipitation and evapotranspiration index (SPEI) in the Tana River Basin (TRB) in Kenya. The SPEI is a new drought index which incorporates the effect of evapotranspiration on drought analysis thus making it possible to identify changes in water demand in the context of global warming. The SPEI was computed at 6- and 12-month timescales using a 54-year long monthly rainfall data from the Global Precipitation and Climate Center (GPCC) and temperature data from the Climate Research Unit (CRU) both recorded between 1960 and 2013. Both datasets have a spatial resolution of 0.5° by 0.5° and were extracted for every grid point in the basin. The SPEI was used to assess the temporal and spatial evolution of dry and wet events as well as determine their duration, severity, and intensity. The evolution of significant historical dry and wet events and the frequency of occurrence were clearly identified. The index showed that the period between 1960 and 1980 was dominated by dry events while wet events were dominant in the period between 1990 and 2000. The SPEI6 had the longest duration of dry events of 30 months and severity of 44.67 which was observed at grid 5while the highest intensity was 2.18 observed at grid 31. Grid 19 had the longest duration (52 months) and highest severity (88.08) of dry events for SPEI12 and the intensity was highest (1.94) in grid 31. The longest duration (23) and highest severity (40.03) of wet events for SPEI6 were recorded in grid 39. The highest intensity of wet events for SPEI6 was 1.91 at grid 23 and 1.81 at grid 37 for SPEI12. The principal component analysis (PCA) was applied to the SPEI time series in order to assess the spatial pattern of variability of the dry and wet events in the basin. The PCA showed that there were two leading components which explained over 80% of the spatial variation of dry and wet events in the basin. Further, the continuous wavelet transform (CWT) was applied to the PCA scores in order to capture the time-frequency dynamics. The wavelet transform of the SPEI6 and SPEI12 identified significant periodicities of 1 to 2 years across the spectrum. [ABSTRACT FROM AUTHOR]

The statistical characteristics of precipitation play an extremely important role in the risk assessment of drought and flood disasters and water resource management. In this paper, the precipitation concentration degree (PCD), precipitation concentration period (PCP) and precipitation concentration index (PCI) were used to analyse the spatiotemporal variation in precipitation concentration characteristics in China from 1960 to 2015. In addition, the cross-wavelet transform was used to analyse the possible dependencies and spatial characteristics between these three precipitation concentration indices (PCD, PCP and PCI) and monsoon indices (East Asian summer monsoon index, EASMI; South Asian summer monsoon index, SASMI; and South China Sea summer monsoon index, SCSSMI) of nine river basins in China. The results show that the spatial distribution of precipitation concentration indices in China has obvious north-south and east-west variability. China's precipitation concentration indices are generally declining, with weak volatility. Among these indices, the PCD (P < 0.05) and PCI (P < 0.01) have decreased significantly at rates of − 0.005/10 year and − 0.006/10 year, respectively, while there has been no obvious decrease in the PCP. Compared with the PCD before 1978, the PCD in the rainy season after 1978 has decreased. In most areas, the rainy season is concentrated in July every year; however, the rainy season has been delayed in the middle and lower reaches of the Yangtze River and has advanced mainly in the other basins. The PCI has declined since 1978, indicating a decreasing contribution of heavy precipitation to the total annual precipitation, but this change in the PCI has occurred mainly at high-value stations (PCI > 0.7), and the PCI at low-value stations has increased. Most of China's precipitation concentration indices and monsoon indices, as well as the NWRB, have small-scale (2–4 years) or medium-scale (12–15 years) oscillation periods. The oscillation periods between the precipitation concentration indices and monsoon indices in the Yangtze and Pearl River basins are more significant than those in other basins. The results of this study can help to understand the differences among the precipitation concentration characteristics in different basins in China and the intrinsic relationship between these characteristics and the summer monsoon and provide a reference for further research. [ABSTRACT FROM AUTHOR]

Watershed management, disaster warning, and hydrological modeling require accurate spatiotemporal precipitation data sets. This paper presents a comprehensive assessment of a gauge-satellite-based precipitation product that merges the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) satellite precipitation product (SPP) and ground precipitation data at 134 rain gauges in the Xijiang River basin, South China. Two regression-based schemes, principal component regression (PCR) and multiple linear regression (MLR), were used to combine the gauge-based precipitation data and PERSIANN-CDR SPP and were compared at daily and annual scales. Furthermore, a hydrological model Variable Infiltration Capacity was used to calculate streamflow and to evaluate the impact of four different precipitation interpolation methods on the results of the hydrological model at the daily scale. The result shows that the PCR method performs better than MLR and can effectively eliminate the interpolation anomalies caused by terrain differences between observation points and surrounding areas. On the whole, the combined scheme consistently exhibits good performance and thus serves as a suitable tool for producing high-resolution gauge-and satellite-based precipitation datasets. [ABSTRACT FROM AUTHOR]

The south of Brazil is a territory where different weather systems act, contributing to a non-homogeneity of the rainfall distribution in the region. This paper presents a characterization of rainfall occurring in the Itajaí River Basin, Santa Catarina, located in the south of Brazil. Through the use of daily rainfall data, we propose a review of the rainfall analysis using 10 climatic indexes created by the ETCCDI (Expert Team, ET, On Climate Change Detection and Indexes). The time period data from 1983 to 2014, originated from 31 meteorological stations, were analysed after an intense quality control and accurate historical research. Cluster technical analysis was performed to identify climatic areas within the basin. The results indicate that three climatic regions were identified with similar total annual precipitation but different seasonal distribution in the studied area. The analysis performed by the climatic indices confirms that an increase in total precipitation was recorded in almost all stations analysed and extreme precipitation was the main contributor to such additions. In this sense, the significant increase in total annual precipitation is mainly related to values above 95‰, that is, higher rainfall rates, as well as higher precipitation events above 10 and 20 mm/day. The present article presented alarming results and the possibility of future studies and research on the effects of variability, climate change and assessment of the vulnerability of the Itajaí River Basin. [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]

It is firmly established in the hydrologic literature that flooding depends on both antecedent watershed wetness and precipitation. One could phrase this relationship as 'heavy precipitation does not necessarily lead to high stream discharge', but rarely do studies directly affirm this statement. We have observed several non-hydrologists mistake trends in heavy precipitation as a proxy for trends in riverine flooding. If the relationship between heavy precipitation and high discharge was more often explicitly presented, heavy precipitation may less often be misinterpreted as a proxy for discharge. In this paper, we undertake such an analysis for 390 watersheds across the contiguous U.S. We found that 99th percentile precipitation only results in 99th percentage discharge 36 % of the time. However, when conditioned on soil moisture from the Variable Infiltration Capacity model, 62 % of 99th percentile precipitation results in 99th percentile discharge during wet periods and only 13 % during dry periods. When relating trends in heavy precipitation to hydrologic response, precipitation data should, therefore, be segregated based on concurrent soil moisture. Taking this approach for climate predictions, we found that CMIP-5 atmosphere-ocean global circulation model (AOGCM) simulations for a RCP 6.0 forcing project increases in concurrence of greater than median soil wetness and extreme precipitation in the northern United States and a decrease in the south, suggesting northern regions could see an increase in very high discharges while southern regions could see decreases despite both regions having an increase in extreme precipitation. While the actual outcome is speculative given the uncertainties of the AOGCM's, such an analysis provides a more sophisticated framework from which to evaluate the output as well as historic climate data. [ABSTRACT FROM AUTHOR]

Surface runoff is a major component of the hydrological cycle, and it is essential for supporting the ecosystem services provided by grassland and forest ecosystems. It is of practical importance to understand the mechanisms and the dynamic processes of runoff in a river's basin, and in this study, we focused on the restored montane Pailugou Basin in the Qilian Mountains, Gansu Province, China, since its water status is extremely important for the large arid area and local economies therein. Our purpose was to determine the annual variation in the surface runoff in the Pailugou Basin because it is important to understand the influence of climate fluctuations on surface water resources and the economy of the basin. In addition, little is known about the annual variations in precipitation and runoff in this region of the world. Daily atmospheric precipitation, air temperature and runoff data from 2000 to 2019 were analyzed by the calculation of the uneven annual distribution of surface runoff, the calculation of the complete adjustment coefficient, and the vector accumulation expressed by the concentration degree. We also used the cumulative anomaly approach to determine the interannual variation trend of runoff, while the change trend was quantified by the sliding average method. Finally, we used the Mann–Kendall mutation test method and regression analysis to establish the time-series trend for precipitation and runoff and to determine the period of abrupt runoff changes. The results indicated concentrated and positive distributions of surface runoff on an annual basis, with a small degree of dispersion, and an explicit concentration of extreme flows. The relative variation ranges exhibited a decreasing trend, and the distribution of the surface runoff gradually was uniform over the year. The runoff was highest from July to September (85% of the annual total). We also determined that annual surface runoff in the basin fluctuated over the 20-year period but showed an overall increasing trend, increasing by 3.94 × 105 m3, with an average increase rate of 0.42 × 105 m3 every ten years. From 2005 to 2014, the annual runoff and the proportion of runoff in the flood season (July to September) to the annual runoff fluctuated greatly. The correlation between the runoff and precipitation was significant (r = 0.839, p < 0.05), whereas the correlation between air temperature and surface runoff was low (r = 0.421, p < 0.05). [ABSTRACT FROM AUTHOR]

The article presents the research results aimed at determining the impact of meteorological droughts on groundwater droughts in the Gwda River catchment (northern Poland). The analysis was based on the Standardised Precipitation Index (SPI) and Standardised Groundwater Index (SGI) in various cumulation periods (1, 6, 12, 18, 24, 30 and 36 months) from 1986-2015. Monthly groundwater levels measured in wells and monthly sums of precipitation from meteorological stations in the vicinity of those wells were used to assess the relationships between droughts. During the study period from 1986-2015, three to 43 meteorological droughts and one to five groundwater droughts were identified. Meteorological droughts were most numerous for the shortest cumulation period (1 month), while droughts for the longer accumulation of 24 to 36 months were less numerous. The SPI and SGI indices were most strongly correlated over the annual cycle in the upper part of the catchment (between the Sępólno Wielkie station and well I-33_1). The correlation coefficient r was highest (0.69) between SPI-18 and SGI-1. Correlations were much lower in the middle of the catchment, where the maximum annual r coefficient was 0.39. There was no correlation between droughts in the lower catchment (r=0.14). The correlations presented for the Gwda catchment indicate that the relationship between droughts is not clear. [ABSTRACT FROM AUTHOR]

This study presents the precipitation changes of the Heihe River Basin (HRB), Northwest China, using a long-term (1980–2014) and highly resolved modeling (up to 3 km by 3 km) with the Regional Integrated Environment Modeling System (RIEMS) forced by ERA-Interim reanalysis data. Firstly, the added value of high-resolution RIEMS simulation nested with ERA-Interim reanalysis was presented by comparisons among the RIEMS simulation results, site-based ground measurements, satellite-retrieved precipitation from TRMM 3B43 (V7), and the EAR-interim reanalysis data. The bias of the ERA-Interim reanalysis was largely corrected by the RIEMS simulation, although a little bias existed in the RIEMS simulation. RIEMS simulation showed that there was an increasing trend in the precipitation of the HRB from 1980 to 2014 with a rate of increase of approximately 3%/year for summer and 5%/year for autumn in the southeast part of the HRB. The increased precipitation mainly resulted from more precipitation days and the strengthening of daily precipitation. Upward motion from strengthened convergence over the eastern part of the HRB was the common reason for increased precipitation in summer and autumn, which was partly offset by decreased water vapor supply in summer while it was strengthened by increased water vapor supply in autumn. This paper presents precipitation changes for the HRB associated with global warming since 1980 and provides a higher-resolution climatological data set useful for reference climate impact studies. [ABSTRACT FROM AUTHOR]

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]

In this paper, we study the relationship between the covariability of the Indian summer monsoon (ISM) and East Asian summer monsoon (EASM) and the rainy season precipitation anomaly in the Mekong River basin (MRB) using ERA-Interim reanalysis data and precipitation from the Climate Hazards Group Infrared Precipitation station for 1981–2016. The results indicate that the interannual variability of the rainy season precipitation in the MRB is significantly modulated by the ISM and EASM covariability. Herein, the ISM mainly influences the rainy season precipitation west of the MRB, and the EASM mainly influences the rainy season precipitation over the southeastern MRB. When the Bay of Bengal (BOB) and South China Sea (SCS) are dominated by positive anomalies of diabatic heating associated with a stronger ISM and EASM, the anomalous westerly winds in the BOB and significantly anomalous easterly winds in the SCS, which carry more warm-wet air, induce a stronger than normal convergence and upward motion in the MRB. This results in much heavier rainy season precipitation in the MRB. Model runs with a linear baroclinic model confirm the observational analysis results. [ABSTRACT FROM AUTHOR]

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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]

Parametric and non-parametric approaches for rainfall generation have been widely used in hydrological simulation. Both approaches, however, show inherent limitations for representing precipitation extremes. Hence, a stochastic generator able to represent all the range of precipitation amounts is desired. This paper presents a mixed stochastic generator designed for this purpose: the low to moderate rainfall amounts are modeled by the non-parametric approach, avoiding the adjustment of theoretical probability density functions to this range of precipitation and, the extreme rainfall amounts are modeled by the parametric approach, employing the upper-bounded 4-parameter log-normal (LN4) distribution function, with the upper bound estimated under a Bayesian framework, having the at-site probable maximum precipitation (PMP) as a reference value. The mixed generator was used for simulating a 10,000-year long series in the Pará river catchment, in the Brazilian state of Minas Gerais. Results showed that mean daily rainfall, the correspondent standard deviation, coefficient of skewness, number of wet days, and mean monthly and annual rainfall are adequately reproduced. Furthermore, by combining in a logical structure of analysis a prior distribution describing the uncertainties about the PMP estimates and the rainfall data, one can expect more reliable estimates of rare and extreme quantiles and their related uncertainties. [ABSTRACT FROM AUTHOR]

Regional evaporation has increased in many parts of the world in the last decades, but the drivers of these increases are widely debated. Part of the difficulty lies in the scarcity of high-quality long-term data on evaporation. In this paper, we analyze changes in catchment evaporation estimated from the water balances of 156 catchments in Austria over the period 1977-2014 and attribute them to changes in atmospheric demand and available energy, vegetation, and precipitation as possible drivers. Trend analyses suggest that evaporation has significantly increased in 60% of the catchments (p ≥ 0:05) with an average increase of 29±14mmyr-1 decade-1 (±standard deviation) or 4:9±2:3%decade-1. Pan evaporation based on 24 stations has, on average, increased by 29±5mmyr-1 decade-1 or 6:0±1:0%decade-1. Reference evaporation over the 156 catchments estimated by the Penman-Monteith equation has increased by 18±5mmyr-1 decade-1 or 2:8± 0:7%decade-1. Of these, 2.1% are due to increased global radiation and 0.5% due to increased air temperature according to the Penman-Monteith equation. A satellite-based vegetation index (NDVI) has increased by 0:02±0:01 decade-1 or 3:1±1:1%decade-1. Estimates of reference evaporation accounting for changes in stomata resistance due to changes in the NDVI indicate that the increase in vegetation activity has led to a similar increase in reference evaporation as changes in the climate parameters. A regression between trends in evaporation and precipitation yields a sensitivity of a 0:22±0:05mmyr-2 increase in evaporation to a 1mmyr-2 increase in precipitation. A synthesis of the data analyses suggests that 43±15%of the observed increase in catchment evaporation may be directly attributed to increased atmospheric demand and available energy, 34±14% to increased vegetation activity, and 24±5% to increases in precipitation. [ABSTRACT FROM AUTHOR]

The West Caucasus is the only Russian region where disastrous floods cause a great number of victims regularly. Developing the automated monitoring networks in the Kuban River Basin and Krasnodar Krai has improved the quality of hydrological information over the last years; however, its use for flood forecasting has to be more effective. The paper presents methods of short-term flood forecasting for West Caucasian rivers with rain floods prevalence during the warm season. They are based on applying the Flood Cycle Model (FCM), which has been tested for the first time in the region (the case study of the Tuapse, Psekups, and Pshish rivers). The presented forecasting methods, whose quality completely conforms to the criteria of the Russian Hydrometeorological Service, can enhance the existing hydrological forecasting systems. To further develop the flood forecasting methods for the West Caucasian rivers using physically based models, it is critically important to increase the precipitation measuring network density within the mountain parts of watersheds. [ABSTRACT FROM AUTHOR]

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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]

We analyse the control of hydroclimatic factors on suspended sediment concentration (SSC) in Alpine catchments by differentiating among the potential contributions of erosion and suspended sediment transport driven by erosive rainfall, defined as liquid precipitation over snow-free surfaces, ice melt from glacierized areas, and snowmelt on hillslopes. We account for the potential impact of hydropower by intercepting sediment fluxes originated in areas diverted to hydropower reservoirs, and by considering the contribution of hydropower releases to SSC. We obtain the hydroclimatic variables from daily gridded datasets of precipitation and temperature, implementing a degree-day model to simulate spatially distributed snow accumulation and snow--ice melt. We estimate hydropower releases by a conceptual approach with a unique virtual reservoir regulated on the basis of a target-volume function, representing normal reservoir operating conditions throughout a hydrological year. An Iterative Input Selection algorithm is used to identify the variables with the highest predictive power for SSC, their explained variance, and characteristic time lags. On this basis, we develop a hydroclimatic multivariate rating curve (HMRC) which accounts for the contributions of the most relevant hydroclimatic input variables mentioned above. We calibrate the HMRC with a gradient-based nonlinear optimization method and we compare its performance with a traditional discharge-based rating curve.We apply the approach in the upper Rhône Basin, a large Swiss Alpine catchment heavily regulated by hydropower. Our results show that the three hydroclimatic processes -- erosive rainfall, ice melt, and snowmelt -- are significant predictors of mean daily SSC, while hydropower release does not have a significant explanatory power for SSC. The characteristic time lags of the hydroclimatic variables correspond to the typical flow concentration times of the basin. Despite not including discharge, the HMRC performs better than the traditional rating curve in reproducing SSC seasonality, especially during validation at the daily scale. While erosive rainfall determines the daily variability of SSC and extremes, ice melt generates the highest SSC per unit of runoff and represents the largest contribution to total suspended sediment yield. Finally, we show that the HMRC is capable of simulating climate-driven changes in fine sediment dynamics in Alpine catchments. In fact, HMRC can reproduce the changes in SSC in the past 40 years in the Rhône Basin connected to air temperature rise, even though the simulated changes are more gradual than those observed. The approach presented in this paper, based on the analysis of the hydroclimatic control of suspended sediment concentration, allows the exploration of climate-driven changes in fine sediment dynamics in Alpine catchments. The approach can be applied to any Alpine catchment with a pluvio-glacio-nival hydrological regime and adequate hydroclimatic datasets. [ABSTRACT FROM AUTHOR]

In the last decades, an increase in the number of extreme precipitation events has been observed, which leads to increasing risks for flash floods and landslides. Thereby, conventional gauging stations are indispensable for monitoring and prediction. However, they are expensive in construction, management, and maintenance. Thus, density of observation networks is rather low, leading to insufficient spatio-temporal resolution to capture hydrological extreme events that occur with short response times especially in small-scale catchments. Smaller creeks and rivers require permanent observation, as well, to allow for a better understanding of the underlying processes and to enhance forecasting reliability. Today's smartphones with inbuilt cameras, positioning sensors and powerful processing units may serve as wide-spread measurement devices for event-based water gauging during floods. With the aid of volunteered geographic information (VGI), the hydrological network of water gauges can be highly densified in its spatial and temporal domain even for currently unobserved catchments. Furthermore, stationary low-cost solutions based on Raspberry Pi imaging systems are versatile for permanent monitoring of hydrological parameters. Both complementary systems, i.e. smartphone and Raspberry Pi camera, share the same methodology to extract water levels automatically, which is explained in the paper in detail. The annotation of 3D reference data by 2D image measurements is addressed depending on camera setup and river section to be monitored. Accuracies for water stage measurements are in range of several millimetres up to few centimetres. [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 this paper, the intensity, area and duration of future droughts in China are analyzed using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The SPI and SPEI are used to evaluate the simulation ability of drought characteristics with the regional climate model COSMO-CLM (CCLM). The projected intensity and duration of future drought events are analyzed for the period 2016-2050 under three different respective concentration pathways (RCPs). The simulated and projected drought events are analyzed by applying the intensity-area-duration method. The results show that CCLM has a robust capability to simulate the average drought characteristics, while some regional disparities are not well captured, mainly the simulation of more drought events of shorter duration in Northwest China. For the future period 2016-2050, more intense dryness conditions are projected for China. An increase in evapotranspiration is found all over China, while a reduction in precipitation is apparent in the southern river basins. The increase in evapotranspiration plays an important role in the changes of future droughts over the northern river basins and southern river basins. Under RCP2.6, drought events of longer duration and with higher frequency are projected for the southwest and southeast of China. Under RCP4.5 and RCP8.5, a continuing tendency to more dry conditions is projected along a dryness band stretching from the southwest to the northeast of China. More frequent drought events of longer duration are projected in the southwestern river basins. For all future droughts, larger extents are projected, especially for events with long-term duration. The projected long-term drought events will occur more often and more severe than during the baseline period, and their central locations will likely shift towards Southeast China. The results of this study can be used to initiate and strengthen drought adaptation measures at regional and local scale, especially in the south of China. [ABSTRACT FROM AUTHOR]

The influence of initial state variables on flood forecasting accuracy by using conceptual hydrological models is analyzed in this paper and a novel flood forecasting method based on correction of initial state variables is proposed. The new method is abbreviated as ISVC (Initial State Variable Correction). The ISVC takes the residual between the measured and forecasted flows during the initial period of the flood event as the objective function, and it uses a particle swarm optimization algorithm to correct the initial state variables, which are then used to drive the flood forecasting model. The historical flood events of 11 watersheds in south China are forecasted and verified, and important issues concerning the ISVC application are then discussed. The study results show that the ISVC is effective and applicable in flood forecasting tasks. It can significantly improve the flood forecasting accuracy in most cases. [ABSTRACT FROM AUTHOR]

The purpose of the paper is to provide some calculations on the current water balance for the Vistula Lagoon, which is exceptionally valuable in terms of biology and hydrology. It is located along the southern coast of the Baltic Sea in both Poland and Russia. In the era of marked climate change, but first and foremost the plans of the Polish side of the cross-cutting of the Vistula Spit, there has been a need to update the balance data of the Vistula Lagoon. In the near future, they may be an excellent comparative material to changes in the proportions of individual water circulation components in the Vistula Lagoon and changes in its entire ecosystem, caused by the implementation of the project. In the literature on the subject, balance sheet data from 50 years ago are used (these data were compiled in the initial part of the study), hence the concept of attempting to update them has appeared. Due to the lack of data from the Russian part of the catchment area, the main emphasis in the work was put on the completion and modernization of the components of the balance sheet of the Polish catchment. A novelty at work is the refinement of the potamical inflow to the Vistula Lagoon with small but numerous streams flowing from the Elbląg Upland, as well as the inflow forced by polder discharges. Climate water balance data are shown based on data available from IMGW in Warsaw and include monthly precipitation totals for the period 1996-2010 obtained at six gauging sites located near the Vistula Lagoon. Evaporation was calculated using Tichomirov's formula. River water influx was determined based on data available in Kruk (2011), data from IMGW (Pasaka River) and data from papers Bogdanowicz (2007, 2009) and documents associated with the Program for biological passages in rivers in Warminsko-Mazurskie Province (2007). Raw data were also obtained from the Office of Water Management in the city of Elblgg for the period 2006-2011. These data covered water flow moving from the polders. Groundwater influx was estimated using values provided by Silicz (1975). The volume of seawater influx was estimated using the data provided by Silicz (1975) and Chubarenko and Chubarenko (2002). The study confirms that water exchange in coastal lagoons is quite complex due to the presence of several different sources of recharge and several different places where water is lost. The complexity of water cycle is enhanced by a complex hydrographic system of lagoon catchments and a complicated system of water exchange with the sea. The total water volume involved in circulation in the Vistula Lagoon is estimated to be 24,225 mln m³ per year. The largest part of the water received by a coastal lagoon comes from the sea. In this case, it is about 77% (18,130 mln m³ per year). In addition, an array of catchment sources yields about 21% of the studied lagoon's water. Its catchment provides an additional 4,974 mln m³ of water. The Pregolya River produces 55% of the catchment influx. The volume of water forcibly produced by area polders is so small that it does not produce an observable effect on the water balance in the Lagoon (about 0.04% of total influx). The precipitation constitutes 2.3% of the power supply source of the Vistula Lagoon. On the other hand, the Strait of Baltiysk constitutes the main outflow pathway for water exiting the Vistula Lagoon - close to 98% of all outflow (23,694 mln m³). The remaining 2% is lost due to evaporation. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the influence of sub-daily precipitation time steps on model performance and hydrological components by applying the Green and Ampt infiltration method using the Soil and Water Assessment Tool (SWAT). Precipitation was measured at a resolution of 0.1 mm and aggregated to 5-, 15-, 30-, and 60-min time steps. Daily discharge data over a 10-year period were used to calibrate and validate the model. Following a global sensitivity analysis, relevant parameters were optimized through an automatic calibration procedure using SWAT- CUP for each time step. Daily performance statistics were almost equal among all four time steps ( NSE ≈ 0.47). Discharge mainly consisted of groundwater flow (55%) and tile flow (42%), in reasonable proportions for the investigated catchment. In conclusion, model outputs were almost identical, showing simulations responded nearly independently of the chosen precipitation time step. This held true for (1) the selection of sensitive parameters, (2) performance statistics, (3) the shape of the hydrographs, and (4) flow components. However, a scenario analysis revealed that the precipitation time step becomes important when saturated hydraulic conductivities are low and curve numbers are high. The study suggests that there is no need in using precipitation time steps <1 h for lowland catchments dominated by soils with a low surface runoff potential if daily flow values are being considered. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series. [ABSTRACT FROM AUTHOR]