Search

Global warming has caused severe regional water security risks, and from the theory of the hydrological cycle, the daily extreme temperature could also bring an impact on the streamflow volume, which could be even more important than the average temperature. Therefore, based on the level of the maximum or minimum temperature warming scenarios, a variety of meteorological datasets were selected to assess the asymmetric effect of increased daily extreme temperature on the streamflow from a multi-scale perspective by using the Variable Infiltration Capacity (VIC) model. Model simulations indicate that the streamflow experiences more significant changes in response to the maximum temperature than in response to the minimum temperature, and the relationships of streamflow with both the maximum and minimum temperatures show an upwards parabolic response function, but the response function varies with the type of warming. Additionally, the seasonal and monthly duration curves results show that the increases in both the maximum and minimum temperatures demonstrate a similar response that leads the proportion of the flood period streamflow to be increased (Tmin : 0.16–0.53%/°C; Tmax : 0.11–0.51%/°C). When the minimum temperature increases, the higher the original temperature in the region, the greater the proportion of the flood period streamflow increases. However, when the maximum temperature increases, the opposite effect occurs. • This paper included a numerical analysis of the sensitivity of streamflow to daily extreme temperature increases. • This paper discusses in detail the regional asymmetric effect of daily extreme temperature increase to streamflow. • A relatively complete picture of the hydrological processes caused by daily extreme temperature rise is presented. [ABSTRACT FROM AUTHOR]

Frequent drought disasters have significant impacts on socio-economic and ecosystems, and it is crucial to explore the propagation characteristics of drought for disaster prevention and mitigation. In this paper, based on 0.25° × 0.25° grid-point Meteorological hydrological and large-scale climate factor data, the start-to-start, peak-to-peak, and end-to-end drought propagation times, and the periods and rates of drought development and recovery were estimated for 11 regions in the Luanhe River Basin under stationary and non-stationary conditions. The Generalized Additive Model for Location, Scale and Shape (GAMLSS) framework was used to construct stationary and non-stationary models to capture the stationary and non-stationary drought characteristics respectively, and then the drought development and recovery patterns, and drought propagation times were assessed. The results showed that under the influence of climate factors, severe drought events occurred in most study areas, the duration of meteorological drought was prolonged by 0.1–0.6 months, and the peak intensity was increased by about 0.05. The severity of hydrological drought increased by 0.2–0.8, and the peak intensity decreased by 0.1–0.2. The rate of development and recovery of hydrological drought was accelerated by 0.1–0.2 per month. The propagation time of start-to-start was shortened by 0.2 months, and the propagation time of end-to-end was extended by 1–2 months. These mean that water resource control authorities need to propose responses to droughts more quickly. • The non-stationary drought indices considering climatic factors were constructed. • The drought propagation time was calculated from start to start, peak to peak, and end to end. • Quantification of the effects of climate change on drought propagation [ABSTRACT FROM AUTHOR]

With increasing spatiotemporal resolution and accuracy, satellite-based precipitation estimations (SPEs) have become critical data sources for hydrological applications. Their global scale coverage and short latency perfectly fit the requirements of flood forecasting. However, the comprehensive evaluation of the latest generation of SPEs is an essential step before the confident use of these indirect precipitation estimators. Therefore, the latest releases of the Integrated MultisatellitE Retrievals for Global Precipitation Measurement (IMERG) Version 5 products, including the near-real-time "Early" run and "Later" run products (IMERG-E and IMERG-L, respectively), and the post-real-time "Final" run IMERG product (IMERG-F), are employed in this paper. Through the hydrometeorological assessment of these three IMERG products against dense gauge observations during the period from April 2014 to December 2015 over the Upper Huaihe River Basin (UHRB), the usability of IMERG products in hydrological application is explored via the Variable Infiltration Capacity model. The results indicate that, irrespective of a slight positive bias, the post-real-time IMERG-F product presents the best performance among the three IMERG products at both the grid scale and basin scale. Although all three IMERG products show remarkably high probability of detection (POD, approximately 0.82), the IMERG-E presents a relatively higher false alarm ratio (FAR = 0.37) in comparison with IMERG-L (FAR = 0.32) and IMERG-F (FAR = 0.31), which is primarily due to the significant overestimation in light rain events. In terms of hydrological simulations of streamflow, the dense gauge observations exhibit very good performance for both entire simulation period and flood events, as expected. IMERG-F demonstrates acceptable performance in entire simulation, while both IMERG-E and IMERG-L demonstrate poor performance. Given the clear overestimation in short-terms flooding and the notable underestimation in long-terms flooding, all three IMERG products should be used with caution in flood simulation over UHRB. Overall, this is a systematic assessment of IMERG products. We hope this study can provide useful guidelines for potential hydrologists of IMERG products and further IMERG algorithm development. Also, given the scope of on-going efforts to improve the IMERG products, we believe the subsequent versions of IMERG can be widely used in global or regional hydrological application, particularly in the field of flood forecasting. Unlabelled Image • The latest IMERG-E, IMERG-L, and IMERG-F are statistically and hydrologically evaluated over upper Huaihe River Basin. • IMERG-F presents the best performance, and IMERG-E demonstrate comparably statistical performance to IMERG-L. • IMERG-F demonstrates acceptable performance in daily hydrological simulation. • Both IMERG-E and IMERG-L demonstrate poor hydrological utility. • All three IMERG products should be used with caution in flood simulation over upper Huaihe River Basin. [ABSTRACT FROM AUTHOR]

Abstract: An automated approach to storm classification that relies on identifying storms from observed radar data and classifying them based on their shape, radar, and near-storm environmental parameters is described in this paper. Storms are identified and clustered within CONUS radar and environmental data using a combined watershed segmentation and k-means clustering technique. Storms were manually classified into short-lived convective cells, supercells, ordinary cells, or convective cells at two scales, using data from selected severe weather events between May 2008 and July 2009. Objects of composite reflectivity were identified and tracked using a clustering technique at two spatial scales, and attributes for every storm cluster were extracted based on radar and near-storm environment data from model analysis fields. Quinlan decision trees were trained on these individual attributes and implemented to nowcast storm types for both scales. It is shown in this paper that storms can be automatically identified and classified using a decision tree, and that these automatic classifications have different climatological properties, which are potentially useful for short-term forecasting. [Copyright &y& Elsevier]

Abstract Global Satellite Mapping of Precipitation (GSMaP) product is an important satellite precipitation product of Global Precipitation Measurement (GPM) mission, which provides an alternative means to ground-based rainfall estimates, in which case a rigorous product assessment was required before implementation. The objective of this paper is to evaluate and calibrate the errors of GSMaP_Gauge (GG) products, then SWAT model is chosen to evaluate its performance in hydrological simulation. It was found that the GG has a superior ability in detecting moderate rainfall events of 10–20 mm/d, while other magnitude accuracy needs to be strengthened. The Nash-Sutcliffe coefficient of efficiency (NS), coefficient of determination (R2) and the percent bias (PBIAS) were used to evaluate hydrological model performance in the daily scale, supporting the view that GG still allow considerable room for improvement. SWAT model driving by GG performed relatively poorly which is 0.77 ≤ R2 ≤ 0.84, 0.53 ≤ NS ≤ 0.64 and |PBIAS| < 9%, while the performance of corrected GG is relatively better that is 0.85 ≤ R2 ≤ 0.87, 0.70 ≤ NS ≤ 0.75 and |PBIAS| < 15%. Through the error's correction of GG, it brings a better performance of runoff simulation under SWAT modeling, leading to 11.94% and 6.1% maximum increase in NS and R2 respectively. Certain shortcomings are also noted that improvements to the relative runoff depth errors are limited or worse. But in general, GSMaP product has the potential to be an alternative data source for the research on hydrological simulation and water resources management in data-poor or ungauged basins. Highlights • GSMaP_Gauge has a superior ability in detecting moderate rainfall events of 10–20 mm/d. • GSMaP_Gauge-based model has the potential to describe well the runoff. Through correction of its errors, it brings the improvement of runoff simulation. • Certain shortcomings are that there are still large relative runoff depth errors, mainly reflected in the base flow. • The results can provide a deep insight to the GSMaP estimates'error features correction and potential utilization in water resources management. [ABSTRACT FROM AUTHOR]

This paper investigates the annual and seasonal precipitation variability at 20 stations over upper Indus River basin (UIRB) by using an innovative trend analysis (ITA) method, Mann-Kendall (MK) and Sen's slope estimator tests. Moreover, the annual precipitation time series is investigated for five precipitation intensities i.e. light, low, moderate, high and heavy; and on a seasonal scale for extreme values i.e. light and heavy precipitation intensities. Annual precipitation showed an increasing trend at four stations in the northeast region and a decreasing trend at two stations in the southeast region of UIRB. On a seasonal scale, the results showed that Garidopatta, Peshawar, Astore and Gupis stations are more sensitive to seasonal precipitation variabilities. Changes in heavy precipitation (> 90th percentile) are found more severe in winter and summer seasons in the northern regions suggesting a probable flooding aggravation. However, a reduction in flooding event observed during the spring season in the southern regions of the UIRB indicating a shift in the precipitation regime from south to north. The results of light precipitation (< 10th percentile) intensity showed that winter and spring seasons are more vulnerable to the occurrence of prolonged drought events. Moreover, ITA method has the advantage of detecting the sub-trends in the precipitation series because of its ability to present the results in graphical format. The results of this study could help to understand seasonal and annual precipitation variability over UIRB and will have imperative insinuations for further studies. [ABSTRACT FROM AUTHOR]

Small scale rainfall variability is a key factor driving runoff response in fast responding systems, such as mountainous, urban and arid catchments. In this paper, the spatial–temporal autocorrelation structure of convective rainfall is derived with extremely high resolutions (60 m, 1 min) using estimates from an X-Band weather radar recently installed in a semiarid-arid area. The 2-dimensional spatial autocorrelation of convective rainfall fields and the temporal autocorrelation of point-wise and distributed rainfall fields are examined. The autocorrelation structures are characterized by spatial anisotropy, correlation distances ~ 1.5–2.8 km and rarely exceeding 5 km, and time-correlation distances ~ 1.8–6.4 min and rarely exceeding 10 min. The observed spatial variability is expected to negatively affect estimates from rain gauges and microwave links rather than satellite and C-/S-Band radars; conversely, the temporal variability is expected to negatively affect remote sensing estimates rather than rain gauges. The presented results provide quantitative information for stochastic weather generators, cloud-resolving models, dryland hydrologic and agricultural models, and multi-sensor merging techniques. [ABSTRACT FROM AUTHOR]

The multi-scale convection activities are highly prone to induce the local severe rainstorms within Yangtze River Basin (YRB), and the orographic effect of the windward slope located within the Second-Step Terrain Region (SSTR) is widely confirmed to have significant roles in strengthening the multi-scale Eastward-Moving Southwest Vortex (EMSV) systems that belongs to a typical type of the convection activities, this paper is thereby focused on revealing the orographic effect of the windward slope on the multi-scale EMSV systems from a new perspective of Potential Vortex (PV) framework. Results show that the different synoptic circulations involved in the multi-scale EMSV systems can be effectively decomposed into the meso-scale balanced circulation and the local-scale perturbed circulation based on the Piecewise Potential Vortex Inversion (PPVI) technique. Then these different structure circulations demonstrate dissimilar modification under the topographical force of the windward slope within SSTR. The good agreements among the positive PV anomalies, the cyclonic perturbed circulation and the local heavy precipitation are explicitly discovered around the windward slope region, which suggests that the positive PV anomalies induced by the windward slope can reinforce the local precipitation via the regulation of the cyclonic perturbed circulation. Further investigation of the linkage between the windward slope and the positive PV anomalies reveals that the reinforcement of the latent heat release that is favorable for the genesis of the positive PV anomalies relies more on the strengthening of the updraft driven by the orographic lifting effect than the increase of the horizontal convergence of the low-level wind driven by the orographic blocking effect around the windward slope region. • The multi-scale structure circulation can be decomposed into the balanced circulation and the perturbed circulation based on the PPVI technique • The positive PV anomalies induced by the windward slope can reinforce the local precipitation via the cyclonic perturbed circulation • The reinforcement of the latent heat release that is favorable for the genesis of the positive PV anomalies mainly relies on the orographic lifting effect around the windward slope region. • This work broadens the application scope of the PPVI technique in the study of the multi-scale synoptic systems [ABSTRACT FROM AUTHOR]

This paper presents some improvements of a probabilistic quantitative precipitation forecasting method based on analogues, formerly developed on small basins located in South-Eastern France. The scope is extended to large scale basins mainly influenced by frontal systems, considering a case study area related to the Saône river, a large basin in eastern France. For a given target situation, this method consists in searching for the most similar situations observed in a historical meteorological archive. Precipitation amounts observed during analogous situations are then collected to derive an empirical predictive distribution function, i.e. the probabilistic estimation of the precipitation amount expected for the target day. The former version of this forecasting method (Bontron, 2004) has been improved by introducing two innovative variables: temperature, that allows taking seasonal effects into account and vertical velocity, which enables a better characterization of the vertical atmospheric motion. The new algorithm is first applied in a perfect prognosis context (target situations come from a meteorological reanalysis) and then in an operational forecasting context (target situations come from weather forecasts) for a three years period. Results show that this approach yields useful forecasts, with a lower false alarm rate and improved performances from the present day D to day D + 2. [ABSTRACT FROM AUTHOR]

Thunderstorm cell-lightning activity is discussed in terms of analysing a thunderstorm's lightning frequency–equipotential temperature relationship. Thunderstorms were tracked using Doppler radars in five-minute time steps. Lightning is assigned to the nearest thunderstorm cell, it is characterised by lightning frequency data using LINET. Equipotential temperature is not directly estimated, instead the notion of air mass catchment is introduced to represent it. It is shown in this paper that the thunderstorm cell with maximum lightning frequency in the current time step is almost always the so-called leading storm cell. The lightning frequency activity of the non-leading storm cells is not significant. [ABSTRACT FROM AUTHOR]

This paper draws attention to highlight the spatial and temporal variability in precipitation lapse rate (PLR) and precipitation extreme indices (PEIs) through the mesoscale characterization of Teesta river catchment, which corresponds to north Sikkim eastern Himalayas. A PLR rate is an important variable for the snowmelt runoff models. In a mountainous region, the PLR could be varied from lower elevation parts to high elevation parts. In this study, a PLR was computed by accounting elevation differences, which varies from around 1500 m to 7000 m. A precipitation variability and extremity were analysed using multiple mathematical functions viz. quantile regression, spatial mean, spatial standard deviation, Mann–Kendall test and Sen's estimation. For this reason, a daily precipitation, in the historical (years 1980–2005) as measured/observed gridded points and projected experiments for the 21st century (years 2006–2100) simulated by CMIP5 ESM-2 M model (Coupled Model Intercomparison Project Phase 5 Earth System Model 2) employing three different radiative forcing scenarios (Representative Concentration Pathways), utilized for the research work. The outcomes of this study suggest that a PLR is significantly varied from lower elevation to high elevation parts. The PEI based analysis showed that the extreme high intensity events have been increased significantly, especially after 2040s. The PEI based observations also showed that the numbers of wet days are increased for all the RCPs. The quantile regression plots showed significant increments in the upper and lower quantiles of the various extreme indices. The Mann–Kendall test and Sen's estimation tests clearly indicated significant changing patterns in the frequency and intensity of the precipitation indices across all the sub-basins and RCP scenario in an intra-decadal time series domain. The RCP8.5 showed extremity of the projected outcomes. [ABSTRACT FROM AUTHOR]

Located in a transition zone between the northern and southern climates in China, the Huai River Basin is prone to extreme events such as drought and flood. Based on the daily precipitation data at 134 stations between 1961 and 2013, this paper analyzed the spatial and temporal patterns of the dry and wet conditions in the Huai River Basin through the statistical analysis of the rainfall stations' annual and seasonal standard precipitation index (SPI) series. Annual SPI series exhibited a decreasing trend at 86 stations and an increasing trend at the remaining stations. None of the increasing trend was significant, while the decreasing trend was significant at two stations at 5% significance level (α = 0.05) and one station at 10% level. Seasonal-wise, there has been a prevailing trend of drying in spring and autumn, and wetting in summer and winter. The trends in the spring and summer SPI series have been mostly insignificant, while those in autumn and winter, significant (α = 0.10) at over 30 stations. The Pettitt test results indicated that the significant transitions (α = 0.10) in the autumn and winter SPI series mostly occurred in the middle to late 1980s. Comparison of the average number of dry and wet years between the two sub-periods of 1961–1984 and 1990–2013 suggested a significant increase (α = 0.05) in the average number of severely wet years across much of the basin. Overall, significant changes have already occurred in the dry and wet conditions of the Huai River Basin, which could have profound impacts on the food and water safety situation of the region. [ABSTRACT FROM AUTHOR]

This paper evaluates changes in precipitation in the upper the Euphrates–Tigris basin enclosing the whole area of Southeastern Anatolian Project (GAP), which is the largest investment for regional development in the history of Turkey and the fourth largest irrigation project in the world. For this purpose, the analyses are based on new data sequences formed by summing up monthly precipitation of 19 stations in the study area at seven different time scales. The Mann–Kendal (MK) and Theil–Sen Slope estimator (TSE) statistics to detect the direction and magnitude of an available monotonic trend in any given data, respectively, were used for the statistical analysis of the new data sequences. Besides, the sequential version of Mann–Kendal rank test (SVMK) to detect the approximate starting point of a trend was also applied the data set of the stations with significant monotonic trend. The monotonic trend was detected at 63% of the stations (12 of 19 stations) for the different time scales at 5% significance level. The stations with positive and negative or insignificant precipitation trends were scattered in the different parts of the basin. The significant trends were found in six stations with respect to the critical value (± 2.33) from the standard normal distribution for one-sided hypothesis at 1% significance level. The TSE results for 12 stations with monotonic trend at different time scales varied from − 2.36 mm to 2.51 mm per year. Of the six stations, the maximum decrease (− 72.5%) and increase (166.9%) in the percent change (PC) were determined in Agri and Bitlis stations, respectively. The approximate starting points of upward and downward trend for Kilis, Sirnak, Agri, Elazig, Bitlis and Siirt stations were at about 1980, 1979, 1987, 1986, 1984 and 1965 with respect to the SVMK test, respectively. According to the results obtained from the previous studies, the river basin is affected by the North Atlantic Oscillation (NAO) and global warming. Therefore, it is very likely that the NAO and global warming have been contributing to changes in precipitation of the river basin. [ABSTRACT FROM AUTHOR]

This paper presents the spatial variation of the annual maximum daily rainfall (AMDR) in more than 900 catchments of England and Wales over the last century with respect to different spatial features including geographic location, elevation, size, orientation and shape of catchments. A spatial pattern extraction and recognition (SPER) toolbox is employed to extract the spatial features of catchments where the AMDR is modelled by a well-tested Generalized Extreme Value (GEV) distribution. The results show that the GEV parameters μ and σ exhibit similar patterns and are usually larger with higher elevations. Increasing catchment size can decrease parameters due to areal averaging, however, in the middle-sized transition regions of the rainfall variation, e.g., east Wales, the trend reverses. For areas at higher elevation, parameters are greater in the west-northwest-oriented catchments while parameters in west-northwest or east-northeast-oriented catchments at lower elevation are similar or smaller than those with a north-south orientation. An elongated shape catchment usually has smaller parameters than a rounded-shape one. These findings reveal the heterogeneity of extreme rainfall distribution in space with respect to different spatial characteristics of catchments even under the same climate, which lays a basis for further catchment-based analysis concerning the relationship between hydrological response and geomorphic properties. • Century-long annual max daily rainfall (AMDR) over 900 catchments in England & Wales. • The spatial variation of the catchment orientated AMDR was investigated. • Determination of AMDR highly affected by location alongside size, orientation & shape. [ABSTRACT FROM AUTHOR]

Abstract: We propose an extended study of recent flood-triggering storms and resulting hydrological responses for catchments in the Pyrenean foothills up to the Aude region. For hydrometeorological sciences, it appears relevant to characterize flash floods and the storm that triggered them over various temporal and spatial scales. There are very few studies of extreme storm-caused floods in the literature covering the Mediterranean and highlighting, for example, the quickness and seasonality of this natural phenomenon. The present analysis is based on statistics that clarify the dependence between the spatial and temporal distributions of rainfall at catchment scale, catchment morphology and runoff response. Given the specific space and time scales of rainfall cell development, we show that the combined use of radar and a rain gauge network appears pertinent. Rainfall depth and intensity are found to be lower for catchments in the Pyrenean foothills than for the nearby Corbières or Montagne Noire regions. We highlight various hydrological behaviours and show that an increase in initial soil saturation tends to foster quicker catchment flood response times, of around 3 to 10h. The hydrometeorological data set characterized in this paper constitutes a wealth of information to constrain a physics-based distributed model for regionalization purposes in the case of flash floods. Moreover, the use of diagnostic indices for rainfall distribution over catchment drainage networks highlights a unimodal trend in spatial temporal storm distributions for the entire flood dataset. Finally, it appears that floods in mountainous Pyrenean catchments are generally triggered by rainfall near the catchment outlet, where the topography is lower. [Copyright &y& Elsevier]

This paper explored the projected changes in precipitation, maximum temperature (T max), and minimum temperature (T min) over the Yangtze River Basin (YRB) based on 23 Global climate models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6). The Empirical Quantile Mapping (EQM) approach was firstly applied to correct the biases in the GCMs. Next, the future changes were investigated by analyzing the multi-model ensemble (MME) of the bias-corrected dataset during 2025–2044 (near-term), 2045–2064 (mid-term), and 2081–2100 (long-term) periods, with reference to the baseline period 1995–2014, under three integrated scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) of the Shared Socioeconomic Pathways (SSPs) and the Representative Concentration Pathways (RCPs). Results show that: (1) the biases in CMIP6 GCMs can be effectively corrected by EQM, and the MME performs better than individual models for each climatic variable. (2) Precipitation over the YRB from 2025 to 2100 is projected to increase at the rate of 9.66 mm/decade, 13.45 mm/decade, and 21.01 mm/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, the annual precipitation is projected to increase by 10.41%, 10.66% and 15.80%, under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (3) T max (T min) over the YRB is projected to increase by 0.09 (0.07) °C/decade, 0.29 (0.27) °C/decade, and 0.66 (0.64) °C/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, T max (T min) averaged over the YRB is projected to increase by 1.75 (1.50) °C, 2.72 (2.54) °C and 5.04 (4.85) °C under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (4) Uncertainties in the projected precipitation and temperature over the YRB were reduced based on MME. But further researches, such as selecting the superior models with respect to the regional climate of the YRB from the CMIP6 and using the ensemble methods that assign weight based on the performance of each model, are still needed to provide more reliable climate projections. • Projected changes were explored by 23 CMIP6 GCMs under the three SSP-RCP scenarios. • Biases in the GCMs were corrected by Empirical Quantile Mapping (EQM) method. • Multi-model ensemble (MME) was used to reduce the uncertainties. [ABSTRACT FROM AUTHOR]

Abstract: Recent research efforts have been geared towards developing high-resolution rainfall products from satellites for hydrological applications. A necessary step in assessing the potential and utility of these products is to quantify the uncertainty associated with them at validation scales appropriate for hydrological applications. The main objective of this paper is to evaluate the accuracy of the widely-known PERSIANN-CCS high-resolution (hourly, 0.04°×0.04°) satellite rainfall products against high-quality NEXRAD radar rainfall observations in the Little Washita watershed. Our results reveal that (1) PERSIANN-CCS shows high skills in reproducing the patterns of inter-annual rainfall variability on a monthly basis; (2) both at the hourly and storm scales, the performance statistics of PERSIANN-CCS exhibit large spread, suggesting that the quality of PERSIANN-CCS product is almost unique for each hour and storm; and (3) significant improvement in performance statistics is obtained as PERSIANN-CCS products are averaged to longer sub-daily time scales. The implications of our results are: (1) PERSIANN-CCS could be used with high confidence for inter-annual rainfall variability studies; (2) PERSIANN-CCS products need to be accompanied by corresponding hourly error estimates in order to provide meaningful error estimates for hydrological applications; and (3) research is needed to characterize the tradeoff between the quality of rainfall input and the space-time resolution of hydrological modeling, as a function of watershed size and hydrologic model complexity level. [Copyright &y& Elsevier]

Abstract: This paper presents the results of a study of a watershed experiencing the pressures of land-use change resulting from urban development. The study was undertaken to facilitate an understanding of the water balance of the watershed by developing and implementing watershed procedures that are to be addressed in a watershed plan. There were three components to the research: firstly, observation of the effects of spatially distributed rainfall measurements and their effect on modelling were assessed. Secondly, the model was then calibrated by observing how differing techniques can discretize both the landscape (e.g. land-use and soil type) and incoming precipitation. Finally, a modelling methodology was developed to integrate a Geographic Information System and a hydrologic model (e.g. Storm Water Management Model) in a water balance analysis on a watershed basis. Results show that, under certain conditions, kriging spatially distributed rainfall values can help predict rainfall at ungauged (virtual) sites. Discretization of a watershed was found to affect the differences between measured and generated runoff volumes; however, this can be refined with calibration. It was seen that a strong correlation between measured and predicted rainfall values did not always guarantee a strong relationship between measured and generated runoff Recommendations include the use of a longer time series of rainfall, streamflow and predicted rainfall to observe temporal variations, and the need to assess the differences in modelled rainfall values generated by various surface interpolation methods (e.g. Inverse Distance Weighting and other kriging options) currently available in GIS packages. [Copyright &y& Elsevier]

In this paper, future drought characteristics (frequency, duration and intensity) over China are analysed by using four climate models from CMIP6 under the seven SSP-RCP (shared socioeconomic pathway-representative concentration pathway) scenarios (SSP119, SSP126, SSP434, SSP245, SSP460, SSP370, and SSP585) for three defined periods of 2021–2040 (near-term), 2041–2060 (mid-term) and 2081–2100 (long-term). The corresponding four climate models output from CMIP5 are also used to conduct a comparison analysis between CMIP5 and CMIP6 to address the improvements added to CMIP6 in terms of drought identification. The drought characteristics are identified by applying the standardized precipitation-evapotranspiration index (SPEI) at a 12-month timescale and run theory. The results show that CMIP6 has a robust capability to capture historical (1986–2005) drought characteristics. For the future period of 2021–2040, the decrease in precipitation and increase in potential evapotranspiration will lead to continuous dry conditions in the upper and middle Yangtze River basin and eastern Pearl River basin. Relative to the reference period, drought events will be more frequent and severe with longer durations in the Northwest River basins and middle Yangtze River basin. Furthermore, higher emissions signify a greater increase in drought frequency and intensity in the long-term period. Except for the SSP585 scenario, the lower emission scenario corresponds to the higher drought duration soon and in the mid-21st century (2021–2060). This finding is regarded as a "strange phenomenon", which cannot be detected by the previous CMIP5-based emission scenarios (RCP2.6, RCP4.5 and the unlikely pathway RCP8.5). Therefore, additional "possible future"-based scenarios (SSP119, SSP126, SSP434, SSP245, SSP460, and SSP370) should be included in extreme climate studies, especially for the near future and mid-21st century. Notably, compared with CMIP5, the reduced biases in drought characteristics are more likely associated with improvements in the representation of physical processes in climate models from CMIP6. The results of this study could provide a basis for the development of drought adaptation measures over China. • Latest CMIP6 climate models and seven SSP-RCP scenarios are used to analyze the possible changes in droughts over China. • More robust projections will be presented by CMIP6 than CMIP5, due to the better representations in physical processes. • The higher emission signifies shorter drought duration, lower precipitation and PET in mid-21st century over China. [ABSTRACT FROM AUTHOR]

The objective of this paper is to investigate the projected regional responses of univariate and bivariate behaviors of extreme precipitation to climate change over the upper-middle Huaihe River Basin. Based on twelve GCM outputs under historical, RCP4.5 and the observations at 32 rainfall stations, the equidistant cumulative distribution function matching method (EDCDFm) was utilized to bias correct daily precipitation during the historical (1961–2005) and future (2021–2080) periods. Four precipitation indices combinations were introduced based on eight precipitation indices to characterize the regional-scale changes of precipitation events, which designate the duration, intensity and amount of heavy and weak precipitation in a year. Their dependence structures were captured by Copulas. Kendall return period (KRP) were applied to discuss hazard scenarios and we quantified the spatial variability of KRPs under different marginal values. The results indicated that projected precipitation characteristics including the average intensity, the amount of annual precipitation, the intensity and amount of extreme precipitation together with annual extremes displayed increasing trends, while the changes of consecutive wet and dry days did not present pronounced trends. Decreased KRPs in the vast majority of the territory manifested that the frequency of simultaneous floods and droughts in a year as well as that of extreme heavy precipitation events would augment. Obvious spatial heterogeneity of the changes of KRP was partly attributed to the topography difference, especially the coastal areas along the main stream of the Huaihe River. Consequently, there will be a higher risk of water resources-related issues in this region for upcoming decades. • Significant decreases will occur in the intensity and amount of heavy precipitation for upcoming decades. • Change rates of precipitation indices combinations illustrate obvious spatial heterogeneity. • The frequency of simultaneous floods and droughts in a year and that of extreme heavy precipitation events will augment. [ABSTRACT FROM AUTHOR]

The wide application of satellite-based and reanalysis-based precipitation data has greatly promoted hydrometeorological research in areas where precipitation observations are scarce. However, the suitability of such precipitation products needs to be carefully evaluated before applications in certain basins because their inherited errors vary with different climate zones, seasonal cycles and land surface conditions; in addition, precipitation products have not been evaluated in the Xihe River basin, China. In this paper, two representative satellite-based precipitation products (Tropical Rainfall Measuring Mission (TRMM) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (CDR)) and two reanalysis-based precipitation products (China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) and National Centers for Environmental Prediction - Climate Forecast System Reanalysis (CFSR)) were selected for evaluation and corrected against gauge-observed data (OBS). Furthermore, the performances of precipitation products in hydrological simulations were also assessed using the SWAT model calibrated with OBS forcing and not with individual precipitation products. The results show that satellite-based precipitation has a higher quality than reanalysis-based precipitation. The CFSR and CDR overestimate precipitation (the overestimation of CDR precipitation is mainly concentrated in the precipitation intensity range of 1 mm/d to 5 mm/d), while the TRMM and CMADS underestimate precipitation in the Xihe River basin. The TRMM precipitation performs best during the wet season, while the CDR precipitation performed best during the dry season. After bias correction, the quality of TRMM precipitation improves significantly. The Nash-Sutcliffe coefficient (NS) (the percent bias (|PBIAS|)) increases (decreases) by 0.61 (77.27%) and 0.7 (39.15%) under the two different correction scenarios during 2009–2015. Overall, the above original precipitation products cannot be used as supplements to the OBS in the Xihe River basin unless they are corrected by the OBS. • Four precipitation products (TRMM, CDR, CMADS and CFSR) were selected for evaluation and corrected against OBS. • The hydrological simulation results show that satellite-based precipitation performs better than reanalysis precipitation. • TRMM performs best during the wet season, while CDR performes best during the dry season. [ABSTRACT FROM AUTHOR]