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Research has shown that the climate in northwest China has turned to warm-wet in recent decades. Does this mean that the entire northwest of China has become wet in the last few decades? In the context of the climate transition in northwest China, this paper investigates whether the Bosten Lake Basin (BLB) located in southern Xinjiang has been dry or wet in the last 30 years. We used the Standardized Precipitation Evapotranspiration Index (SPEI) and Temperature Vegetation Drought Index (TVDI) to investigate these changes. The results show that although the dry-wet changes indicated by the SPEI and TVDI exhibited slight spatiotemporal differences, the entire BLB reflected a tendency to be dry. That is, the BLB has not become wet during the climate transition in northwest China, but is developing a trend toward aridification. The main conclusions of this study are as follows: (1) The SPEI indicated a drying trend in seasonal and interannual variations in plains; in mountains, except in spring and summer it has a drying trend, too. (2) The TVDI showed that although the drying trend in summer and winter was weaker than that in spring and autumn in the BLB, where some regions represented a significant tendency toward wetness owing to seasonal or annual changes, the entire study area has still become more dry. [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]

Climate variability and human activities are two main contributing attributions for runoff changes in the Yellow River, China. In the loess hilly-gully regions of the middle Yellow River, water shortage has been a serious problem, and this results in large-scale constructions of soil and water conservation (SWC) measures in the past decades in order to retain water for agricultural irrigation and industrial production. This disturbed the natural runoff characteristics. In this paper, we focused on a typical loess hilly-gully region (Wudinghe and Luhe River basins) and investigated the effects of SWC measures and climate variability on runoff during the period of 1961-2013, while the SWC measures were the main representative of human activities in this region. The nonparametric Mann-Kendall test was used to analyze the changes of annual precipitation, air temperature, potential evapotranspiration (PET), and runoff. The analysis revealed the decrease in precipitation, significant rise in temperature, and remarkable runoff reduction with a rate of more than 0.4 mm per year. It was found that runoff capacity in this region also decreased. Using the change point detection methods, the abrupt change point of annual runoff series was found at 1970, and thus, the study period was divided into the baseline period (1961-1970) and changed period (1971-2013). A conceptual framework based on four statistical runoff methods was used for attribution analysis of runoff decline in the Wudinghe and Luhe River basins (−37.3 and −56.4%, respectively). Results showed that runoff reduction can be explained by 85.2-90.3% (83.3-85.7%) with the SWC measures in the Wudinghe (Luhe) River basin while the remaining proportions were caused by climate variability. The findings suggested that the large-scale SWC measures demonstrated a dominant influence on runoff decline, and the change of precipitation extreme was also a promoting factor of the upward trending of SWC measures' contribution to runoff decline. This study enhances our understanding of runoff changes caused by SWC measures and climate variability in the typical semiarid region of Loess Plateau, China. [ABSTRACT FROM AUTHOR]

Threshold level method is well-known for drought identification with the advantage of its simplicity. However, there is no criterion for classification of drought classes in this method. Therefore, a K index based on threshold level method was proposed and verified to perform well in drought assessment in the Luanhe River basin, China. Meteorological data and remote sensing data were used to calculate the net primary productivity (NPP) of the basin by the CASA model. Results showed that the model had a good performance in comparison with the downloaded yearly remote sensing NPP and monthly PsnNet. The NPP in the basin tended to increase slowly during the year of 2000–2010, and the NPP in the downstream was generally larger than upstream. In three selected representative drought years, drought reduced NPP by about 15–25%, and during the growth season, drought may reduce NPP by about 4.6%, 2.7%, and 1.9% in July, August, and September, respectively, due to reduced precipitation. NPP on grasslands and agricultural land were more susceptible to drought than forests. The result of gray incidence analysis showed that the effects of drought on NPP had a certain delay with about 5 months. [ABSTRACT FROM AUTHOR]

A regional analysis of soil temperature (ST) is essential for improving our understanding of the soil thermal regime and its link with the atmosphere. This study attempts to assess trends in the Poyang Lake Basin (PLB) ST magnitude during 1960–2016 from station observations at multiple depths. The Mann–Kendall, Thiel-Sen, linear regression, and probability density statistics (PDF) are used for ST trend assessment with a significance level of 95%. The ST seasonal variability shows minimum values in winter (8℃) and maximum in the summer season (32 ℃). On an interannual scale, spring and winter seasons exhibited a significant increase in both land surface temperature (LST) (0.4℃, 0.4℃) and ST (0.3 °C, 0.15℃) magnitude than summer (LST − 0.1℃, ST 0.2℃) and autumn seasons (LST 0.3℃, ST 0.2℃). The northern basin exhibited a significant increase in LST, and ST magnitude, especially during the cold seasons (spring, winter) than the warm seasons. The maximum and minimum temperature trend and their diurnal difference infer an increase in the minimum temperature, especially during the summer, autumn, and winter seasons. The PDF further inferred that extreme cold events' frequency decreased, and a significant increase in extreme warm events is obvious in the recent decade. The increasing trend in soil temperature magnitude is more in the northern basin than the high-altitude southern basin. Large-scale global warming and regional water and energy cycle changes can be the leading factors of such a warming trend. [ABSTRACT FROM AUTHOR]

Using statistical methods and contingency table method, this paper evaluates the accuracy of 12 years (1998-2009) Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA) daily-accumulated precipitation products within a year, the dry season, and rain season for each of the five subbasins and for each grid point (0.25 × 0.25°) in the Lancang River basin by comparing the results with data from the 35 rain gauges. The results indicate that TMPA daily precipitation estimates tend to show an underestimation comparing to the rain gauge daily precipitations under any scenarios, especially for the middle stream in the dry season. The accuracy of TMPA-averaged precipitation deteriorates with the increase of elevation at both basin and grid scale, with upstream and downstream having the worst and best accuracy, respectively. A fair capability was shown when using daily TMPA accumulations to detect rain events at drizzle rain and this capability improves with the increase of elevation. However, the capability deteriorates when it is used to detect moderate rain and heavy rain events. The accuracy of TMPA precipitation estimate products is better in the rain season than in the dry season at all scenarios. Time difference and elevation are the main factors that have impact on the accuracy of TMPA daily-accumulated precipitation products. [ABSTRACT FROM AUTHOR]

Hydrological processes depend directly on climate conditions [e.g., precipitation, potential evapotranspiration ( PE)] based on the water balance. This paper examines streamflow datasets at four hydrological stations and meteorological observations at 79 weather stations to reveal the streamflow changes and underlying drivers in four typical watersheds (Meigang, Saitang, Gaosha, and Xiashan) within Poyang Lake Basin from 1961 to 2000. Most of the less than 90th percentile of daily streamflow in each watershed increases significantly at different rates. As an important indicator of the seasonal changes in the streamflow, CT (the timing of the mass center of the streamflow) in each watershed shows a negligible change. The annual streamflow in each watershed increases at different rates, with a statistically significant trend (at the 5 % level) of 9.87 and 7.72 mm year, respectively, in Meigang and Gaosha watersheds. Given the existence of interactions between precipitation and PE, the original climate elasticity of streamflow can not reflect the relationship of streamflow with precipitation and PE effectively. We modify this method and find the modified climate elasticity to be more accurate and reasonable using the correlation analysis. The analyses from the modified climate elasticity in the four watersheds show that a 10 % increase (decrease) in precipitation will increase (decrease) the annual streamflow by 14.1-16.3 %, while a 10 % increase (decrease) in PE will decrease (increase) the annual streamflow by −10.2 to −2.1 %. In addition, the modified climate elasticity is applied to estimate the contribution of annual precipitation and PE to the increasing annual streamflow in each watershed over the past 40 years. Our result suggests that the percentage attribution of the increasing precipitation is more than 59 % and the decreasing in PE is less than 41 %, indicating that the increasing precipitation is the major driving factor for the annual streamflow increase for each watershed. [ABSTRACT FROM AUTHOR]

The Inner Mongolia grassland of China is representative of semi-arid grasslands in temperate zones. Studying land surface processes in this region will improve the understanding of regional climate formation and the feedback with global climate change. Satellite remote sensing provides an excellent opportunity to study land-atmosphere interactions at the regional scale. It is necessary to develop feasible and reasonable remote sensing-based methods to map surface energy fluxes for a specific study area. In this paper, previously published algorithms and empirical formulae were tested with Landsat 7 ETM+ data to derive the regional distributions of land surface reflectance, surface temperature, NDVI and land surface energy fluxes (net radiation, soil heat flux, sensible heat flux and latent heat flux) over the upper Xilin River watershed in Inner Mongolia, China. A new land use/land cover classification was developed and applied for regionalization analysis. Validation of remote sensing derived surface reflectance, surface temperature, net radiation and sensible heat flux with field measurements shows differences of about 13, 4, 1, and 28%, respectively. This study provides valuable guidance for further investigation of the whole watershed. [ABSTRACT FROM AUTHOR]

Taking the Taihu Lake Basin as an example, in this study, the characteristics of the rainfall factors in the study area were analyzed using daily rainfall data from 1955 to 2019. Three factors, i.e., the contribution rate of the rainfall in the flood season, the rainfall frequency, and the maximum daily rainfall, were selected to determine the optimal probability distribution function for each single factor. Furthermore, the root mean square error goodness-of-fit test was used to determine the optimal copula function for the three-dimensional joint probability distribution characteristics of the rainfall factors. The research results show that the three-dimensional copula joint probability method contains much more information than the results of the single variable probability calculation. The copula function can be used to analyze the multi-dimensional joint distribution of rainfall factors, which can fill the gap in research on multiple rainfall factors. [ABSTRACT FROM AUTHOR]

Climate system anomalies and intensified human disturbances have different impacts on the hydrological cycle at different scales, chiefly leading to prominent spatio-temporal heterogeneities in precipitation distributions. It is of great significance to accurately detect the non-stationary changes of precipitation. Focusing on the Inner Mongolia section of the Yellow River basin which is considered as the key ecological barrier in northern China, the best probabilistic model with time-varying moments was established to fit the wet-season precipitation series from 1988 to 2017 for 38 meteorological stations. Considering four three-parameter distributions, time was used as covariate to describe the linear or nonlinear change of each parameter, and model optimization was performed by Akaike Information Criterion. Combined with conventional methods including the Trend-Free Pre-Whitening Mann–Kendall trend test and Sen's slope estimator, the non-stationary behaviors of wet-season precipitation variability were quantitatively captured. Results showed that the generalized gamma distribution performed best in fitting the wet-season precipitation series in the study area, characterized with high skewness and heavy tails. The non-stationary characteristics of the wet-season precipitation were obvious in most areas during the past 30 years, especially in the central region. The non-stationarities of wet-season precipitation manifested in a downward trend in the mean value, an increase in dispersion degree and significant changes in distribution shape with time, consequently adding the uncertainty to wet-season precipitation process and raising the risk of extreme conditions. The findings of this study provide scientific references to water resources management, drought resistance, and disaster reduction. [ABSTRACT FROM AUTHOR]

Hydrological drought is a highly complex and extreme natural disaster, which has increased in deficit, areal extent, and frequency with the penetration of climate change impact. For better anticipating hydrological droughts, it is crucial to evaluate hydrological drought and its teleconnections with large-scale climate indices (LSCI) effectively. This study estimated the dynamics and patterns of hydrological drought in the near-real river networks by virtue of the standardized runoff index (SRI) based on VIC and large-scale routing model in the Xijiang River basin, and revealed their teleconnections with the climate indices. Results show that model simulation can reasonably reveal the hydrological drought evolutions in near-real river networks and effectively expose the drought downward spread along main channels. The drought spread distances in Hongshuihe and Yujiang Rivers are farther under the comprehensive influence of climate, topography, and watershed shape. Hydrological drought evolutions in the upper reaches are mainly manifested as three patterns, including S12 (simultaneous significant changes in drought intensity, concentration degree, and frequency), S7(simultaneous significant changes in drought intensity and frequency), and S1(single significant change in drought intensity). These drought dynamic patterns are majority affected by climate variation patterns M1 (warm and cold AMO), M3 (cold PDO), and M7 (warm AMO/AO). For decision-makers, this work is beneficial for understanding and anticipating hydrological droughts in the river networks, and further selecting management strategies for water resources. Highlights: The quantitative results of model simulation are reliable for drought evaluation. Drought concentration period delays and drought risk increases significantly. Dynamic evolutions of drought mainly manifest as three combinations patterns. Upstream drought is mainly affected by AMO, PDO, and AMO/AO. [ABSTRACT FROM AUTHOR]

Precipitation is considered one of the most important forcing data in scientific investigations involving agriculture, water management, and climate variability. Knowledge of precipitation variation during rainy seasons is the key to the understanding of the precipitation variability under the effect of climate change. This study evaluated some rainy season features (e.g., onset, retreat, and rainy-season precipitation) over the Yellow River basin (YRB), China, and the influence of the El Niño-Southern Oscillation (ENSO). The multi-scale moving t-test was applied to capture the onset and retreat of rainy season. The possible linkage between ENSO-induced precipitation and monsoon and atmospheric circulation was also explored. From the analysis, four conclusions can be drawn: (1) Rainy season began the earliest (latest) and ended the latest (earliest) in the southern (northern) YRB, with rainy-season precipitation increasing from northwest to southeast. (2) Rainy-season precipitation showed strong correlation to SST in Niño regions. Precipitation can reach up to 20% above the average precipitation for decaying central Pacific warming (CPW) and down to 35% below the average precipitation for developing eastern Pacific warming (EPW) in most areas of the YRB. (3) Developing El Niño showed the strongest dry signals among developing ENSO and ENSO Modoki phases. Decaying El Niño and El Niño Modoki indicated overall increasing precipitation, with La Niña and La Niña Modoki during the corresponding period showing the opposite tendency. (4) Different performances of ENSO-induced precipitation attributed to the combined influence of the monsoon from the India Ocean and the atmospheric circulation in the Western North Pacific (WNP). Stronger anti-cyclone and monsoon are related to increasing rainy-season precipitation. These findings can improve the predictability of rainy season features and ENSO-induced precipitation. [ABSTRACT FROM AUTHOR]

According to the daily maximum and minimum temperature and the precipitation at 40 meteorological stations in the Daqing River Basin of China during 1980–2015, the spatial and temporal trends of extreme temperature and precipitation are analyzed. The trend strengths, stability, and magnitude are calculated for ten indices of temperature and eight indices of precipitation. The results show that trends of extreme temperature indices are significant, but extreme precipitation indices are insignificant. Through the extreme temperature indices, the cold indices of extreme temperature decrease steadily and the warm indices of extreme temperature rise steadily, indicating that the trends of temperature rising in the basin are obvious and stable. In addition, indices of the extreme precipitation indicate that the consecutive dry days (CDD) decrease, the heavy precipitation days (R20) and the consecutive wet days (CWD) increase, and the annual total precipitation (PRCPTOT) increases steadily. The results have certain scientific value for climate change and a series of impacts brought by climate change in the Daqing River Basin. [ABSTRACT FROM AUTHOR]

Based on the meteorological data of 60 stations above the Bengbu Sluice of Huaihe River from 1961 to 2015, Crop Water Deficit Index (CWDI) and Relative Moisture Index (M) were calculated. Taking winter wheat drought as the representative of agricultural drought, the temporal and spatial characteristics of winter wheat drought and meteorological drought during growth period were analyzed. The duration, severity and frequency of 30 major drought events were identified through the run theory, and the correlation between agricultural drought and meteorological drought was studied. The results showed that: (1) In terms of time, the proportion of agricultural drought in winter wheat growth period was higher than that of meteorological drought, and the years with the largest interannual difference occurred in the pre-winter growth period; (2) In terms of space, the winter wheat drought and meteorological drought in the whole growth period and each growth period were distributed by zonal mode structure, and the drought gradually increases from south to north. More than 75% of the drought of winter wheat occurs from over-wintering period to filling and mature period, while meteorological drought only occurred during over-wintering period; (3) Winter wheat drought was delayed compared with meteorological drought, and its intensity was greater than meteorological drought; (4) When the duration of meteorological drought reached 1.28 dekad or the drought severity reached 3.35, the drought of winter wheat will be triggered, and the frequency of the duration and severity return period of winter wheat drought was greater than that of meteorological drought. [ABSTRACT FROM AUTHOR]

In summer 2020, precipitation in many parts of China reached its maximum in the past 60 years, and southern China suffered from severe flooding, which was mainly due to the strong westward subtropical high, the enhanced east Asian summer monsoon, the development of meridional circulation, and the active cold vortex in the middle and high latitudes. We tried to apply a statistical bias correction method to improve the prediction of summer precipitation at 160 stations in China in 2020. In summer 2020, the precipitation anomaly percentages were above 40% in the Yellow River Basin and the Yangtze River Basin. Using the bias correction method, the main rain belt of the corrected summer precipitation was located in the Yangtze River's middle reaches and the Yellow River Basin, which is in line with the observations, but it does not catch the trend of more summer precipitation in the Huaihe River Basin. In addition, the corrected predicted results can basically catch the trend of dryness in South and Southwest China. Relative to the original model output, the abnormal correlation coefficient (ACC) between the corrected predictions, and the observations increased from − 0.02 to 0.30, and the prediction score (PS) increased from 67.8 to 77.4 for summer rainfall in 2020. Moreover, the bias correction method showed stable and considerable improvement for the prediction of summer precipitation in China from 2014 to 2019. Overall, this study demonstrates that the bias correction method can effectively improve the accuracy of the summer precipitation predicted results in China. [ABSTRACT FROM AUTHOR]

The precipitation pattern in the Taihu Lake basin in East China has significantly changed over the last decades, perhaps due to intensive urbanization. However, there is limited understanding of the effect of large-scale expansion of city groups on the precipitation variability, which causes a challenge for flood control in the basin. Considering the process of urbanization, we investigated in this study the variability of precipitation in different urban zones and characteristic scales and explored the influence of urban development on the rain island effect in the basin. The basin was divided into three zones (old urban area, new urban area, and suburbs) considering different degrees of urbanization. Results indicated that precipitation change and its response to urbanization had spatial differences at various characteristic scales. Urbanization exhibited a significant "precipitation enhancement effect" at the characteristic scales including annual, flood season, summer, autumn, and winter but indicated a "precipitation reduction effect" in spring. Annual (flood season) precipitation in 1990–2013 increased by 30.04 mm (16.94 mm), due to urbanization, compared with that in the preceding period. The rate of contribution of urbanization to precipitation increase was 15.6%, 41.1%, and 14.4% in summer, autumn, and winter. The enhancement effect of short duration rainfall extremes in old urban area was also discernible, and that in new urban areas would enhance along with urban expansion, complicating urban flood and waterlogging control. More effective adaptation strategies should be implemented to handle the unfavorable situation. [ABSTRACT FROM AUTHOR]

Objective evaluation of the relationships among different types of droughts remains a challenging task due to the combined impacts of climate change and land surface modification caused by human activities. Based on the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) at the 3- and 6-month timescales, this study presents a systematic analysis of the relationships between the severity (S) and duration (D) of meteorological (MD) and hydrological droughts (HD) in the three catchments of the upper Huai River Basin in China. The relation between SPI and SRI is explored by the maximal information coefficient and the mutual entropy. The spatial propagation mechanism of MD is identified by the centroid trajectory, and the response of HD to MD is quantified by the model averaging method. The results indicate a drying (wetting) trend in the upstream (downstream) area, while the centroid trajectory of MD is found in the midstream area, but not associated with the large (or small) S and D simultaneously. There is a strong correlation (determination coefficient > 0.55) between SPI and SRI in all three subareas, particularly at the 6-month timescale. The increasing influences of human activities (e.g., regulation of water conservancy facilities) from upstream to downstream lead to a weaker correlation between SPI and SRI as well as a decreasing threshold of D for MD to trigger HD in downstream. By contrast, the drier climatic conditions are the main reason for the increasing threshold of S for MD to trigger HD from upstream to downstream. [ABSTRACT FROM AUTHOR]

High-precision areal rainfall is crucial for hydrometeorological coupled forecasts. The accuracy of quantitative precipitation estimates (QPE) is improved by merging radar-rain gauge data with an integration approach based on a statistical weight matrix in the Yishu River catchment, China. First, a local Z-R relationship (Z = 85R1.82) is reconstructed using a genetic optimization algorithm to minimize the error from different precipitation patterns and climate zones. Next, based on the local Z-R relationship, six methods of merging radar-rain gauge data are respectively adapted to improve the accuracy of QPE, as follows: mean field bias (MFB), Kalman filter (KLM), optimum interpolation (OPT), variation method (VAR), two-step calibration of KLM and OPT (KOP), and two-step calibration of KLM and VAR (KVR). The results indicate that QPE accuracy is clearly improved, and is in good agreement with rain gauge observations, after the six merging methods are applied. Among these methods, KOP performs the best, reducing the mean relative error from 55.2 to 15.1%. An innovative aspect of this work is the inclusion of an integrated ideology based on a statistical weight matrix, which further improves the accuracy of QPE by incorporating the advantages of each estimation mode. The results further show that the accuracy of QPE derived from the integration approach is higher than that obtained by any individual method; QPE values are similar to those obtained the automatic rain gauge network in both the spatial distribution and location of the intense precipitation centers, and better reflects the precipitation status over the ground surface. This approach could serve as a promising conventional method for QPE in the study region. [ABSTRACT FROM AUTHOR]

Drought has become one of the most serious meteorological disasters for agricultural production in many areas around the world, and the situation could be worse under the impact of climate change. To facilitate better adaptation planning, this study proposed a drought assessment framework integrating downscaling method, drought index, copula technique, and bivariate frequency analysis, and applied it to investigate the change of the drought characteristics and drought risks from the past to the future in Huang-Huai-Hai River basin (HRB), North China. Drought was firstly defined by standardized precipitation evapotranspiration index (SPEI) based on 1497 observed grid data from 1979 to 2004. Then, we constructed the joint distribution of drought duration and severity based on copulas to detect and quantify the drought risks. To address the effect of climate change, similar calculation process was applied to the future climate data, which was downscaled using delta change method from representative concentration pathway (RCP 8.5) of 12 general circulation models (GCMs). The study results suggested that, under climate change condition, most irrigation districts over HRB would generally experience lower frequency of drought events but with extended duration; some districts would have more serious drought, but majority would experience similar or even lower level of severity. In light of the mean joint occurrence probability, the irrigation district at the south part of Huai River basin would likely experience the highest increase of drought risks in near future (by 0.86%) and distant future (by 0.76%), while most of other districts over HRB would face low risk of serious drought risks. The obtained results offer useful information to agricultural managers or water resources authorities who are interested in the development of effective long-term adaptation strategies for drought management. [ABSTRACT FROM AUTHOR]

The Tizinafu watershed is characterized by extremely scarce precipitation and low temperature, and snow and glacier melting which dominate the main water resource of this area. Thus, assessing the snowmelt water resource has great significance to local residents and ecological systems. Based on snowmelt runoff model (SRM) and Markov chain Monte Carlo (MCMC) simulation, four combinations of meteorological data consisting of two daily temperature data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the variable infiltration capacity (VIC) model and two daily precipitation data from Tropical Rainfall Measuring Mission (TRMM) and VIC, respectively, are evaluated for this ungauged basin in Bayesian uncertainty analysis. By comparing the performances of the four meteorological data combinations based on SRM (SRMMODIS + TRMM, SRMMODIS + VIC, SRMVIC + TRMM and SRMVIC + VIC, the former and latter subscripts denote temperature and precipitation data, respectively), results show that the four SRMs are both capable of reproducing the runoff process of the Tizinafu watershed on daily runoff simulation, and SRMVIC + VIC has the best performance. In addition, the impact of climate change on the water resources of the Tizinafu watershed is also evaluated in Bayesian uncertainty analysis, and four climate change scenarios under the condition of Representative Concentration Pathway 8.5 of CMIP5 projection are considered. The results demonstrate that the mean annual runoff prediction of the 2090s increased by 17.2%, 20.2%, 24.1%, and 16.2% compared to that of base year for the four scenarios, respectively. In addition, with the increase of the cryosphere area, snow cover area will have an increasing impact on the mean annual runoff of the study area in the 2090s. The runoff components of snowpack melt and new snow are both sensitive to the cryosphere area, while the runoff component of rainfall is not sensitive to the cryosphere area. [ABSTRACT FROM AUTHOR]

Drought projection is of critical significance for designing long-term drought adaptation strategies to cope with changing climate. This study presents an application of multi-class models for characterizing future droughts in the Yellow River basin (YRB). Using meteorological observations and simulations of three CMIP5 climatic models as input into VIC hydrologic model, the standardized Palmer drought index-based joint drought index (SPDI-JDI) is calculated to investigate spatiotemporal patterns and possible changes of future drought in the YRB, through an approach of bivariate modeling and analysis. It is concluded that moderate drought will be alleviated with decreased duration and severity, but extreme drought risk is likely to increase for future climate scenarios (2021–2050) relative to baseline period (1961–2000). From the perspective of bivariate analyses, the concurrence probability of drought events with extreme duration and severity might rise in the future, while increasing variability and heterogeneity of duration, severity and bivariate joint/concurrent return period would also increase the stochastic occurrence of extreme drought over time and space. These findings can provide insights into projection of climate change impacts on drought trends for the next 30 years, and help to preparations for strict control of socio-economic water consumption as well as eco-environmental protection and restoration in the YRB. [ABSTRACT FROM AUTHOR]

Better investigation of extreme precipitation in large river basins is important for hydro-meteorological research and water resources management. Based on daily precipitation data from 17 national meteorological stations in Nenjiang River Basin (NRB) during 1959–2011, spatial-temporal characteristics and trends of seven extreme precipitation indices were analyzed in this study using Mann-Kendall non-parametric test and the ensemble empirical mode decomposition (EEMD) method. We found that almost all selected extreme precipitation indices declined in regionally averaged values, except maximum 5-day precipitation amount (Rx5day). Both extreme precipitation indices and their trends demonstrated spatial varieties. Generally, lower basin obtained less extreme precipitation and tended to be drier. But the amount and intensity of extreme precipitation in upper basin, where are more humid, are rising. Extreme precipitation indices presented apparent non-linear process with periodic oscillations of 1.63–1.94a for IMF1 to 25–31a for IMF4. The findings of this study are useful for the management of water resources in NRB, as well as provide reference information for precipitation evolution under climate change in other regions. [ABSTRACT FROM AUTHOR]

Droughts are regional phenomena that dynamic varied along the time; however, the spatiotemporal dynamic processes of drought were usually ignored in the drought identification methods. To better understand the space-time structure of drought, a space-time continuum drought identification method was used to identify drought intensity, duration, and area in Huai River basin, and their multiple dependences were modeled by copulas. The Intensity-Area-Frequency (IAF) curves were used to model the regional variation of drought in this study. Without identified space-time structure of drought, the construction of IAF curves is usually focusing on the decreasing drought intensity with increasing areal extent. However, stronger drought intensity was found to be followed by larger areal extent when considering the space-time structure of drought, and a copula-based method was introduced to better constructive IAF curves. Conditional probabilities of several drought characteristics taking extreme values were further analyzed. Compared to probabilities estimated by univariate frequency analysis, results indicate that occurrence frequency of drought was underestimated when neglecting any natural characteristic of drought, and underestimation was more serious for the more extreme situations of drought. Furthermore, owing to stronger dependences of drought characteristics from short-term to long-term, more serious underestimations of occurrence frequency of drought were found for the drought from short-term to long-term when neglecting any natural characteristic of drought. [ABSTRACT FROM AUTHOR]

It is critical to assess drought risk probability based on a really spatio-temporal continuum identification and characterization method, which is of great importance for drought resistance, planning, and management of water resource as well as agricultural production. Therefore, the major motivation of this study is to identify and characterize hydrological drought events in a three-dimensional framework and further assess the potential drought risk probability in a multivariate framework in the Luanhe River basin during 1961–2011. The study adopts a really spatio-temporal continuum identification method to characterize drought, and copula functions for multivariate risk probability assessment of hydrological drought. First, the Soil and Water Assessment Tool (SWAT) model is used to simulate the watershed runoff and the cubic spline interpolation method is used to obtain the gridded data sets. Second, the Standardized Runoff Index (SRI) and the three-dimensional identification method are employed to identify hydrological drought. Third, according to three drought parameters of drought severity (S), duration (D), and affect area (A), the marginal distribution, bivariate, and trivariate joint distribution are constructed, and the optimal ones are selected based on different evaluation methods of goodness-of-fit. Fourth, based on the derived marginal and joint distributions, drought risk probability is fully assessed. Results indicate that: (1) SWAT model is a reliable tool to simulate the watershed hydrologic processes; (2) the three-dimensional identification method used in this study is robust and efficient; (3) the optimal marginal distributions for S, D, and A are GEV, GEV, and lognormal distribution; the optimal bivariate copula function for S-D, S-A, and D-A are Joe, Gumbel, and Joe copula; and the optimal trivariate copula function for S-D-A is Nested Gumbel copula; (4) return periods of the first five most serious drought events are 80, 75, 46, 45, and 40 years, respectively; (5) to completely characterize the spatio-temporal variability of hydrological drought, it is necessary to completely consider the three characteristic variables of S, D, and A. [ABSTRACT FROM AUTHOR]

Studying the shifts of vegetation phenology and the response of vegetation phenology to climate change helps to understand the dynamics of future ecosystems. However, since previous studies mostly focused on temperate ecosystems, much less is known about the biogeographic phenological shifts in sub-tropical regions, which have abundant biodiversity. The Yangtze River Basin (YRB) is located in the subtropical region of China and has abundant natural resources, a large population, and rapid economic development. Studying the variation characteristics of phenology and its responses to recent climate changes in YRB are important for understanding the impact of regional climate on subtropical ecosystems. In this study, we extracted the phenological parameters using Global Inventory Modeling and Mapping Studies (GIMMS) data to investigate the spatial and temporal variations of vegetation phenology across YRB during 1982–2015 and to examine how vegetation phenology responds to climate within different ecological zones. The results revealed that the start of growing season (SOS) was significantly advanced by 0.2 days/year (p < 0.01). However, there has been no significant trend in the end of growing season (EOS) throughout the whole study area for the past 34 years. The spatial pattern of the phenology metrics showed a high spatial heterogeneity: the SOS in the central YRB was earlier than that in other regions; the EOS in the southeast YRB was later than that in any other regions. Meanwhile, the SOS had a higher correlation with temperature than with precipitation. In particular, the spring temperature had a strong impact on the SOS and the effects of winter temperatures cannot be ignored. Although there were no significant correlations between the EOS and precipitation/temperature, it is interesting to note that when examining the interactions between phonological parameters, the EOS was positively correlated with the SOS. Furthermore, the pre-season temperature had a lag effect on the SOS, but no significant lag effect was observed for the EOS in YRB. In all, the present study can enhance our understanding of phenology dynamics and its relationship with climate in YRB and provide a useful reference to put forward a corresponding ecological protection policy. [ABSTRACT FROM AUTHOR]

This study examined hydrological and meteorological changes in China's Nenjiang River Basin. Taking account of the physical processes in hydrology and meteorology revealed by the hydrological elements, we selected typical periods and sites for analysis on temperature (1951–2004), precipitation, and runoff data (1955–2005). Through some methods including improved cumulative curve method, the Sen slope estimation method, Mann-Kendall non-parametric test analysis, the Pettitt mutation point test and Spearman rank correlation test, and the spatiotemporal characteristics of hydrological and meteorological elements were evaluated. An innovative concept of the "centroid of precipitation" was proposed to analyze the spatial evolution tendency of precipitation. The results are concluded as follows: (1) the temperature began to show a rising trend during the 1960s and 1970s in Nenjiang River Basin in the twentieth century. The temperature had risen significantly by the 1990s. Furthermore, the temperature increased significantly at the coldest place and in the coldest month. (2) There was no significant trend change in the annual precipitation in the Nenjiang River Basin. However, monthly precipitation before the flood season (April) and after the flood season (October) exhibited a significant upward trend. The centroid of precipitation was concentrated in a compact spatial distribution in the main flood season but was dispersed relatively in the other months. (3) River runoff showed a downward trend year by year and exhibited a mutation in 1979. The spatial variation in runoff showed that the fluctuation of downstream runoff was greater than that in the upper reaches of the basin and that the runoff from the upstream to the downstream reaches gradually decreased. According to the M-K mutation point test, the Pettitt mutation point test, and the improved cumulative curve method, a mutation in annual runoff sequence occurred in 1979. These findings will be helpful for understanding evolution of hydrological changes and will be supportive for local water managers to deal with changing climate. [ABSTRACT FROM AUTHOR]

Monthly rainfall in the Heihe River Basin (HRB) was simulated by the dynamical downscaling model (DDM) and statistical downscaling model (SDM). The rainy-season rainfall in the HRB obtained by SDM and DDM was compared with the observed datasets (OBS) over the period of 2003-2012. The results showed the following: (1) Both methods reasonably reproduced the spatial pattern of rainy-season rainfall in the HRB with a high-level skill. Rainfall simulated by DDM was better than that by SDM in the upstream, with biases of −12.09 and −13.59 %, respectively; rainfall simulated by SDM was better than that by DDM in the midstream, with biases of 3.91 and −23.22 %, respectively; there was little difference between the rainfall simulated by SDM and DDM in the downstream, with biases of −10.89 and −9.50 %, respectively. (2) Both methods reasonably reproduced monthly rainfall in rainy season in different subregions. Rainfall simulated by DDM was better than that by SDM in May and July in the upstream, whereas rainfall simulated by SDM was closer to OBS except August in the midstream and except August and September in the downstream. (3) For multi-year mean rainy-season rainfall in different stations, there was a little difference between the rainfall simulated by DDM and SDM in Tuole station in the upstream, with biases of −13.16 and −12.40 %, respectively; rainfall in Zhangye station simulated by SDM was overestimated with bias of 14.02 %, and rainfall simulated by DDM was underestimated with bias of −14.60 %; rainfall in Dingxin station simulated by DDM was reproduced better than that by SDM, with biases of −19.34 and −32.75 %, respectively. [ABSTRACT FROM AUTHOR]

The change structures of precipitation and precipitation intensity and rainy days are analyzed for the Pearl River Basin (from 1959 to 2009) on the basis of a suite of 24 climatic indices derived from daily precipitation data at 62 meteorological stations with the help of the Mann-Kendall test. Contributions of seasonal precipitation and precipitation intensity class to the annual precipitation are also examined using the inverse distance weighted method. The following four conclusions can be drawn: (1) although the average annual precipitation of the entire basin does not show obvious variation, the number of annual rainy days has decreased significantly in 98.3 % of the stations. These two factors result in an obvious increase in precipitation intensity at 64.5 % of the stations. (2) No clear change trend has been found for seasonal precipitation over the entire area; however, the number of rainy days in each season has decreased significantly. In particular, the number of rainy days in the entire year and in the fall season has decreased in 98.3 and 100 % of the stations, respectively. (3) Although the number of rainy days in drizzle has decreased in 83.9 % of the stations, the number of rainy days where heavy rain and extremely heavy rain occurred increased in nearly 75.8 and 82.3 % of the stations, respectively. (4) The number of rainy days in fall and winter contributes more to the change in the number of annual rainy days than the number of rainy days in spring and summer. Heavy rain and extremely heavy rain contribute more to the change in total annual precipitation than drizzle; however, they contribute less to the change in the number of annual rainy days than drizzle. The findings in this study can provide important information for formulating water resource and eco-environment management strategies in the Pearl River Basin to policymakers and stakeholders. [ABSTRACT FROM AUTHOR]

As the largest component of the global water cycle, precipitation plays a critical role in determining available water in the terrestrial ecosystems. Numerous precipitation products have been generated during the last decades, but they differ substantially in terms of their spatial and temporal variations. In this study, we compared seven precipitation products covering ten major river basins of China from 1980 to 2007 and found large differences among the products. Overall, the Global Precipitation Climatology Center (GPCC) product shows the highest correlation with rain gauge measurements and lowest estimation errors over the ten basins. The performances of other products also clearly differ over the ten basins, and the maximum estimates were 1.27 ± 0.21 times the minimum estimates in terms of interannual variability in precipitation. Based on the seven products, we generated a new precipitation dataset using the Bayesian model averaging method. Compared with all the individual products, the new dataset indicates the decreased root mean square error and increased coefficient of correlation. In the statistical analysis of the weight for each of the products, the GPCC product contributed the maximum weight among almost all river basins. Both the ERA-Interim and MERRA products contributed the minimum weights, being less than 10 %. Our results highlight the need to investigate and improve the performance of precipitation products when evaluating the regional water balance. [ABSTRACT FROM AUTHOR]

Meteorological trend analysis is a useful tool for understanding climate change and can provide useful information on the possibility of future change. Lake Dianchi is the sixth largest freshwater body in China with serious eutrophication. Algal blooms outbreak was proven to be closely associated with some climatic factors in Lake Dianchi. It is therefore essential to explore the trends of climatic time series to understand the mechanism of climate change on lake eutrophication. We proposed an integrated method of Mann-Kendall (MK) test, seasonal-trend decomposition using locally weighted regression (LOESS) (STL), and regime shift index (RSI) to decompose the trend analysis and identify the stable and abrupt changes of some climate variables from 1951 to 2009. The variables include mean air temperature (Tm), maximum air temperatures (Tmax), minimum air temperatures (Tmin), precipitation (Prec), average relative humidity (Hum), and average wind speed (Wind). The results showed that (a) annual Tm, Tmax, and Tmin have a significant increasing trend with the increasing rates of 0.26, 0.15and 0.43 °C per decade, respectively; (b) annual precipitation has an insignificant decreasing trend with the decreasing rate of 3.17 mm per decade; (c) annual Hum has a significant decreasing trend in all seasons; and (d) there are two turning points for temperature rise around 1980 and 1995 and two abrupt change periods for precipitation with the extreme points appearing in 1963 and 1976. Temperature rise and precipitation decline in summer and autumn as well as wind speed decrease after the 1990s may be an important reason for algal blooms outbreak in Lake Dianchi. This study was expected to provide foundation and reference for regional water resource management. [ABSTRACT FROM AUTHOR]

Under global climate change, the change in temperature has greatly affected the hydrological processes and water resource security in the source region of the Yellow River, which is located in the Qinghai-Tibet Plateau and serves as a major source of domestic and agricultural water supply in the watershed. Multiple spatiotemporal analysis methods, including the S-mode empirical orthogonal function analysis, the inverse distance weighted interpolation, the weighted moving average method, and the Mann-Kendall test method were used to comprehensively analyze the temperatures of 14 meteorological stations at yearly and seasonal scales from 1961 to 2010. The results indicated that (1) general trends of temperature change have been rising, with an especially significant warming trend since the late 1990s; (2) in the last five decades, temperature trends in the study area underwent three stages, namely a cool stage (approximately 1961-1980), a fluctuating stage (approximately 1981-1997), and a warm stage (approximately 1998-2010); and (3) due to the combined effects of monsoons and geographic features, the source region could be divided into three zones according to the annual temperature variations: a low-value zone centered on Henan station in the northeastern edge; a high-value zone situated in the central, southern, and western area; and a transitional zone between the two zones mentioned above. This study is helpful for understanding temperature trends under climate change and can provide a basis for ecological protection. [ABSTRACT FROM AUTHOR]

This study analyzed the inter- and inner-annual variations of discharge regimes in the upper and mid reaches of the Heihe River basin. These variations then correlated with temperature and precipitation variations in the area. The differences between the runoff regimes at the upper and mid reaches were compared, and the human impacts on discharge variations in the Heihe River were discussed. The results indicate that in the upper reaches, the long-term trends and periods of discharge and precipitation correlate well. In the mid reaches, the discharge and temperature trends correlate well, and the short discharge and precipitation periods correlate well. Precipitation increases would generate more runoff in both the upper and mid reaches, but the effects of temperature increases on discharge are different in the upper and mid reaches. Temperature increases would enhance the glacial ablation processes and increase runoff in the upper reaches. However, temperature increases would increase the evaporation and decrease runoff in the mid reaches. After the 1980s, higher temperature enhanced snow and glacial melt, and increasing precipitation increased the discharge in the upper reaches. Although increasing precipitation increased some discharge, great human activities caused a notable discharge decrease in the 1990s in the mid reaches, especially during the spring to autumn when large amounts of water resources were used for irrigation. In summary, both precipitation and temperature impact the availability of water resources in the study area, and active and effective adaptation strategies should be developed to improve the efficiency of water resource exploration and to prevent the desertification processes in the arid Heihe River basin. [ABSTRACT FROM AUTHOR]

Much attention has recently been focused on the effects that climate variability and human activities have had on runoff. In this study, data from the Kaidu River Basin in the arid region of northwest China were analyzed to investigate changes in annual runoff during the period of 1960-2009. The nonparametric Mann-Kendall test and the Mann-Kendall-Sneyers test were used to identify trend and step change point in the annual runoff. It was found that the basin had a significant increasing trend in annual runoff. Step change point in annual runoff was identified in the basin, which occurred in the year around 1993 dividing the long-term runoff series into a natural period (1960-1993) and a human-induced period (1994-2009). Then, the hydrologic sensitivity analysis method was employed to evaluate the effects of climate variability and human activities on mean annual runoff for the human-induced period based on precipitation and potential evapotranspiration. In 1994-2009, climate variability was the main factor that increased runoff with contribution of 90.5 %, while the increasing percentage due to human activities only accounted for 9.5 %, showing that runoff in the Kaidu River Basin is more sensitive to climate variability than human activities. This study quantitatively distinguishes the effects between climate variability and human activities on runoff, which can do duty for a reference for regional water resources assessment and management. [ABSTRACT FROM AUTHOR]

Multifractal analysis can provide parameters associated with different scales of rainfall, which may be useful for setting up parsimonious downscaling models of rainfall, or for revealing climate-specific properties. Time series of rain rate with 1-min resolution collected from ten stations over a monsoon watershed in eastern China were used to study the multifractal properties. The power spectra estimated by fast Fourier transform (FFT) and discrete Haar wavelet transform (DWT) showed three scaling regimes: the sub-hourly scaling regime with β ≈ 1.2, the scaling regime from 1 h to 1 day with β close to 0.6, and the low-frequency spectra plateau with β ≈ 0.1. From the hyperbolic tails of exceeding probability distributions, the estimated values of parameter q are in 2-2.5, which were consistent with the critical order of K( q) curves. The statistical moments display two main scaling regimes: the high-frequency regime from 3 min to 5 days and the scaling regime beyond 5 days. The scales of 5-10 days seem a transitional regime. The reason that the regimes, revealed by the power spectra, disagree with the statistical moments may be that both FFT and DWT power spectra have limited abilities of analyzing low-frequency scaling but are sensitive to the properties in high-frequency scales. The H values estimated for the regime of sub-hourly scales are larger than 0.4, and the values for the regime 1 h-1 day are close to 0.1. For the low-frequency scales beyond 1 day, negative H is obtained by DWT power spectra. The parameters of universal multifractal models were also estimated. The values of α for the scaling range of 1 min-5 days are 0.486 ± 0.047, and for the low-frequency scaling range, its values are 0.808 ± 0.323. For the high- and low-frequency scaling ranges, the values of C are 0.5 and 0.169, respectively, which is different from the values for daily rainfall series collected at the same rain gages. [ABSTRACT FROM AUTHOR]

The multifractal behavior of daily rainfall was investigated for a watershed in Eastern China to better understand the temporal structure of rainfall under monsoonal climate. In this study, over periods of up to 46 years, daily rainfall recorded in 1962 to 2007 at 10 meteorological stations in the administrative area of Lin-Yi City in Shandong province were analyzed with focus on features of power spectra, standard statistical moments, and exceedance probability tails of these daily rainfall time series. Spectral analysis and study of the moments of the rainfall intensity showed that a scaling range from 1 day to 1 year is present. Empirical moment scaling functions of the rainfall intensity calculated for different moments of order suggested that the values of universal multifractal parameters α and C for all stations were approximated to 0.7 and 0.37, respectively. Comparing with the parameters estimated in other literatures, our results showed higher values for α but lower values for C in general, which suggested that the rainfall series in the study watershed influenced by the East-Asia monsoon climate have similarities to that in France, but are spikier and smoother than that in the semi-arid region in Portugal. The parameter H values were estimated as vary from −0.18 to −0.22, which is similar to the result obtained by Tessier et al. (J Geophys Res-Atmos 101:26427-26440, ). [ABSTRACT FROM AUTHOR]

We examined climate variability at two timescales for northern Xinjiang, China: one is of the past 500 years using dendrochronology data and the other is of the past 50 years using meteorological station data. The regression models built from the 50-year period were used to reconstruct the climate of the 500-year period. The results indicate that climate underwent many alternating warm-cold and wet-dry periods in the past 500 years. For the 50-year period, we applied the Mann-Kendall jump test to data from 48 meteorological stations to identify possible transition points of temperature and precipitation. For this period, we also analyzed the impacts of latitude, altitude, slope aspect, and human activities on climate variability, aiming to recognize major factors that influence regional climate variability. The results show a warming and wetting trend in the recent 50 years in northern Xinjiang. We determined that natural pattern variability is dominant in the long-term climate variability in the region, but human impacts are non-negligible in the past 50 years. Regional climate variability may be associated with or driven by latitude, altitude, ecosystems, topography, and human activities. The study provides an empirical evidence of the unique regional characteristics of inland river basin in an arid area over the global climate change background. [ABSTRACT FROM AUTHOR]

The spatial and temporal variability of winter extreme low-temperature events and summer extreme high-temperature events was investigated using daily air temperature series (1960–2004) from 66 sites in the Yellow River basin, China, with the help of Mann–Kendall trend test method. In this study an extreme temperature event is defined by exceeding or falling below various threshold values of daily maximum and daily minimum air temperature: 90th percentile, 95th percentile for the high-temperature events; 10th percentile and 5th percentile for the low-temperature events. The analysis results indicate that: 1) significant upward trend of frequency and intensity of the high-temperature events is found in the stations in the west and north part of the Yellow River basin, but trends in most stations in the middle and lower Yellow River basin are not significant at >95% confidence level; 2) almost the whole Yellow River basin is dominated by the significant downward trend of frequency of the cold events. Stations featured by the increasing winter minimum temperature are also more than those featured by changing summer maximum temperature; and 3) annual warming trend in the Yellow River basin mainly results from the increase in winter minimum temperature. Significant warming in the upper reach of the Yellow River will be likely to threaten the availability of the water resource in the whole basin, which should draw certain concerns from local policy-makers and water resource management agency in the region. [ABSTRACT FROM AUTHOR]