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Estimating gross primary production (GPP) and net primary production (NPP) are significant important in studying carbon cycles. Using models driven by multi-source and multi-scale data is a promising approach to estimate GPP and NPP at regional and global scales. With a focus on data that are openly accessible, this paper presents a GPP and NPP model driven by remotely sensed data and meteorological data with spatial resolutions varying from 30 m to 0.25 degree and temporal resolutions ranging from 3 hours to 1 month, by integrating remote sensing techniques and eco-physiological process theories. Our model is also designed as part of the Multi-source data Synergized Quantitative (MuSyQ) Remote Sensing Production System. In the presented MuSyQ-NPP algorithm, daily GPP for a 10-day period was calculated as a product of incident photosynthetically active radiation (PAR) and its fraction absorbed by vegetation (FPAR) using a light use efficiency (LUE) model. The autotrophic respiration (Ra) was determined using eco-physiological process theories and the daily NPP was obtained as the balance between GPP and Ra. To test its feasibility at regional scales, our model was performed in an arid and semi-arid region of Heihe River Basin, China to generate daily GPP and NPP during the growing season of 2012. The results indicated that both GPP and NPP exhibit clear spatial and temporal patterns in their distribution over Heihe River Basin during the growing season due to the temperature, water and solar influx conditions. After validated against ground-based measurements, MODIS GPP product (MOD17A2H) and results reported in recent literature, we found the MuSyQ-NPP algorithm could yield an RMSE of 2.973 gC m-2 d-1 and an R of 0.842 when compared with ground-based GPP while an RMSE of 8.010 gC m-2 d-1 and an R of 0.682 can be achieved for MODIS GPP, the estimated NPP values were also well within the range of previous literature, which proved the reliability of our modelling results. This research suggested that the utilization of multi-source data with various scales would help to the establishment of an appropriate model for calculating GPP and NPP at regional scales with relatively high spatial and temporal resolution. [ABSTRACT FROM AUTHOR]

As global warming produces dramatic climate changes, water management is facing increasingly serious challenges. Given to the process of climate change and its complex effects on watershed hydrology, this paper investigates the spatial and temporal variation characteristics of major climatic factors (i.e., precipitation and temperature) over the upper Yangtze River basin (UYRB), China. The statistical analyses are based on annual and seasonal scales during 1951–2020 with a recorded period of seven decades. The Mann–Kendall nonparametric test and R/S analysis are used to record the temporal trends (past and future) of climate variables; the Pettitt test, standard normal homogeneity test and Buishand test are used to detect the homogeneity in climate series. The sensitivities of the streamflow to climatic parameters are assessed at the watershed scale, especially considering the Three Gorges Dam's (TGD) effect on changing runoff. The results of the study indicate that the annual precipitation of 29 out of 34 series indicate homogeneity, while 31 out of 34 annual mean temperature series show heterogeneity, with jump points around 1997 in the mean temperature of 20 sites. Detectable changes in precipitation were not observed during 1951–2020; however, the temperature increased significantly in the whole basin on annual and seasonal scales, except for several stations in the eastern part. The magnitude of increase in air temperature in high altitudes (Tibet Plateau) is higher than that in low altitudes (Sichuan Plain) over the last seven decades, and future temperatures continue to sharply increase in high altitudes. The TGD plays an important role in explaining the seasonal variations in streamflow at Yichang station, with streamflow experiencing a sharp increase in winter and spring (dry season) and a decrease in summer and autumn (rainy season) compared to the pre-TGD period. The streamflow variation at an annual scale is mainly regulated by climate fluctuation (variation in precipitation). During the last seven decades, increasing air temperature and decreases in rainfall and runoff signify reduced water resources availability, and the climate tends to be warmer and drier over the basin. The sensitivity of the streamflow to watershed precipitation is higher than that to temperature, with variation in annual rainfall explaining 71% of annual runoff variability. [ABSTRACT FROM AUTHOR]

A number of previous studies have contributed to a better understanding of the thermal impacts of dam-related reservoirs on stream temperature, but very few studies have focused on air temperature, especially at the catchment scale. In addition, due to the lack of quantitative analysis, the identification of the effects of water impoundment on regional air temperature is still lacking. We investigated the impacts of reservoirs on the regional air temperature changes before and after two large dam constructions in the lower Jinsha River located in southwest China, by using a 40 year record of reanalysis data at 90 m resolutions. Furthermore, the long short-term memory (LSTM) model was also employed to construct an impoundment effect on the temperature (IET) index. Research results indicate that compared to the pre-impoundment period (1980–2012), the variations in the air temperature at the catchment scale were reduced during the post-impoundment period (2013–2019). The annual maximum air temperature decreased by 0.4 °C relative to the natural regimes. In contrast, the cumulative effects of dam-related reservoirs increased the annual mean and minimum air temperature by 0.1 °C and 1.0 °C, respectively. Warming effects prevailed during the dry season and in the regions with high elevations, while cooling effects dominated within a 4 km buffer of the reservoirs. Therefore, this study offers important insights about the impacts of anthropogenic impoundments on air temperature changes, which could be useful for policymakers to have a more informed and profound understanding of local climate changes in dammed areas. [ABSTRACT FROM AUTHOR]

Assimilation of high-resolution geostationary satellite data is of great value for precise precipitation prediction in regional basins. The operational geostationary satellite imager carried by the Himawari-8 satellite, Advanced Himawari Imager (AHI), has two additional water vapor channels and four other channels compared with its predecessor, MTSAT-2. However, due to the uncertainty in surface parameters, AHI surface-sensitive channels are usually not assimilated over land, except for the three water vapor channels. Previous research showed that the brightness temperature of AHI channel 16 is much more sensitive to the lower-tropospheric temperature than to surface emissivity, which is similar to the three water vapor channels 8–10. As a follow-up work, this paper evaluates the effectiveness of assimilating brightness temperature observations over land from both the three AHI water vapor channels and channel 16 to improve watershed precipitation forecasting through both case analysis (in the Haihe River basin, China) and batch tests. It is found that assimilating AHI channel 16 can improve the upstream near-surface atmospheric temperature forecast, which in turn affects the development of downstream weather systems. The precipitation forecasting test results indicate that adding the terrestrial observations of channel 16 to the assimilation of AHI data can improve short-term precipitation forecasting in the basin. [ABSTRACT FROM AUTHOR]

Driven by ERA‐Interim reanalysis, two climate simulations are conducted from April to August for 20 years (1998–2017) during the East Asia summer monsoon with Model for Prediction Across Scale‐Atmosphere (MPAS‐A). The global variable‐resolution (MPAS‐VR) and regional (MPAS‐RCM) configurations are adopted under the same model framework with 92–25 km mesh refinement centered over Mainland China (MPAS‐A experiments hereafter). MPAS‐VR allows flexible interactions across scales. Constrained by the "reanalysis‐based" lateral boundary conditions (LBCs), MPAS‐RCM could well capture the evolution of large‐scale fields and becomes a proper reference for evaluating MPAS‐VR. The evaluations are conducted for precipitation, near‐surface air temperature, and circulation features against observed climate. Two MPAS‐A experiments present comparable results for the mean climatology and interannual variability except that MPAS‐VR presents wet biases along the tropical ocean and underestimation in the Yangtze–Huaihe River basin. Compared with MPAS‐VR, MPAS‐RCM presents better daily variations and rain belts' evolution, which demonstrates the crucial effects of the LBCs for the limited‐area model. The simulated circulation and moisture flux can explain most of the deviations. However, two MPAS‐A experiments show consistent results for the extreme precipitation frequency and the extreme indices over Mainland China. With the same dynamic core and model physics, those climate features are similarly resolved by the two simulations. Thus, the 92–25 km MPAS‐VR simulation is demonstrated as a promising tool for regional climate hindcast. Plain Language Summary: In this work, we conduct model experiments by two configurations during the East Asia summer monsoon using Model for Prediction Across Scale‐Atmosphere with refinement mesh centered over Mainland China. The global variable‐resolution configuration (MPAS‐VR hereafter) allows flexible interaction across global features to regional climate details. Constrained by the reanalysis (which blends simulated and observed results) around the boundary, the regional limited‐area configuration with the truncated mesh (MPAS‐RCM hereafter) is used for identifying the model's biases mostly related to its dynamic core and parameterization, which is a proper reference for MPAS‐VR. We evaluate the model's performances against the observed climate for the near‐surface air temperature and precipitation. Using MPAS‐RCM as the criterion, MPAS‐VR well captures the mean climatology, interannual variability, and extreme events, which demonstrates itself as a promising tool for regional climate details. The diverged circulation in the two experiments can explain most of the simulated biases. Extreme precipitation frequency and extreme indices over Mainland China suggest similar deficiencies in the two simulations due to a common model framework. Key Points: Dynamical downscaling is conducted by Model for Prediction Across Scale for Atmosphere (MPAS‐A) with a global variable‐resolution (MPAS‐VR) and truncated regional (MPAS‐RCM) configurationsTwo MPAS‐A experiments present comparable results with simulated circulation explaining most of their divergencesExtreme frequency and indices over Mainland China suggest similar deficiencies in the two simulations due to a common model framework [ABSTRACT FROM AUTHOR]

High relative humidity (RH) and temperature extremes can occur simultaneously and persist for periods of time, resulting in serious harm to human health, especially in humid regions. Here, in the case of the Gan River Basin, we used air temperature and RH from the observed and ERA5 reanalysis datasets to construct the apparent temperature and investigate the characteristics of heat and cold waves. Heat waves showed the increasing trends from 1961 to 2018 (particularly from 1997 to 2018), whereas during the same period, cold waves showed the significant decreasing trends. In general, ERA5 reasonably reflected the spatiotemporal characteristics of heat and cold waves, and the ability to simulate cold waves was slightly greater than that of heat waves. The amplifying effect of high RH on heat waves was significantly greater than on cold waves. The increasing rates of heat waves in ERA5 at the mild, moderate, and severe grades were slightly greater than the observations. Cold waves at various grades showed significant downward trends, and the decreasing rates of cold waves in the observations were slightly greater than those in ERA5. Using an analysis of the return period (occurrence probability), traditional univariate risk assessment methods based on maximum or minimum temperature may substantially underestimate the risk of extreme events, such as the 2014 heat wave and the 1969 cold wave, because the effects of RH were ignored. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the uncertainty ranges of high flows under climate change in Jinhua River basin, eastern China. Four representative concentration pathways (RCPs), three global climate models (GCMs), 10 downscaling parameter sets and three hydrologic models are applied to simulate future discharges. Changes of annual maximum discharges are assessed for the baseline period (1961-1990) and future period (2011-2040). The uncertainties of annual maximum discharges are calculated for each uncertainty source and compared with different combinations of them. The minimum temperature will probably increase all year round in the future period and maximum temperature would increase in most cases. The changes of precipitation showed different directions by different models and emission scenarios. The annual maximum discharges would decrease for all RCPs. The order of uncertainty ranges of high flows due to different uncertainty sources from high to low is: hydrologic models, GCMs, parameter sets in the downscaling method and emission scenarios. It must be noted that the small uncertainty contribution from different emission scenarios is due to the study period when the differences in increase of radiative forcing and greenhouse gas concentration are less obvious between different RCPs compared to the second half of the 21st century. [ABSTRACT FROM AUTHOR]

Projecting future changes of streamflow in the Jinsha River Basin (JRB) is important for the planning and management of the west route of South-to-North Water Transfer Project (SNWTP). This paper presented an analysis of the implications of CMIP5 climate models on the future streamflow in the JRB, using SWAT model. Results show that: (1) In the JRB, a 10% precipitation decrease might result in a streamflow increase of 15 to 18% and a 1 °C increase in temperature might results in a 2 to 5% decrease in streamflow; (2) GFDL-ESM2M and NORESM1-M showed considerable skill in representing the observed precipitation and temperature, which can be chosen to analyze the changes in streamflow in the future; (3) The precipitation and temperature were projected to increase by 0.8 to 5.0% and 1.31 to 1.87 °C. The streamflow was projected to decrease by 4.1 to 14.3% in the upper JRB. It was excepted to change by −4.6 to 8.1% in the middle and lower JRB (MLJRB). The changes of low streamflow in the MLJRB were −5.8 to 7.4%. Therefore, the potential impact of climate on streamflow will have little effect on the planning and management of the west route of SNWTP. [ABSTRACT FROM AUTHOR]

In-depth understanding and accurate simulation of hydrological processes are of great significance for sustainable development and management of water resources. The study focused on a semi-arid catchment, the upper Tang River catchment in northern China, and investigated the performance of the RCCC-WBM model based on the detection results of trend, mutation, and periodicity. Results show that (1) as a result of climate change and intensive human activities, the observed runoff series after TFPW (trend-free pre-whiting) pretreatment presented a significant downward trend with the mutation point in 1996; (2) the abrupt change of air temperature series was also in 1996 with a significant rising trend, while the annual precipitation series exhibited an insignificant declining trend with no obvious mutation during 1973–2014; (3) the precipitation and runoff series had periodic variations roughly 7a multiples with the periodic oscillation strongest around 14a, while the air temperature series showed only one dominant period of 28a; (4) the RCCC-WBM model performed well in discharge simulation before the mutation year but gradually lost its stability after 1996, which was mainly affected by anthropogenic activities. It is essential to accurately identify the characteristics of hydrological elements and improve the applicability of hydrological models in the changing environment in future studies. [ABSTRACT FROM AUTHOR]

A regional Climate‐Weather Research and Forecasting (CWRF) model with a 30‐km horizontal resolution was applied to simulate the East Asian summer monsoon (EASM) and climate in China from 1980 to 2016. As compared with observations and reanalysis data, the model can reasonably reproduce the spatial distributions of the climatological mean atmospheric circulation and water vapour transport in East Asia, as well as the seasonal advance and retreat of EASM and rain bands. The correlation coefficient between the EASM circulation index in the simulation and reanalysis is.97. The model can well represent the geographic distributions of summer mean temperature and precipitation over most of China. However, model biases still exist, in particular the skill in the Yangtze–Huaihe River basin is relatively low. The simulated climatological mean temperature and precipitation deviations from observations may be related to the model's systematic circulation biases, with a thicker lower troposphere (i.e., higher temperature between 500 and 1,000 hPa) over most of China (except for the south and southwest) and a thinner one over the coastal oceans in summertime. Compared with the reanalysis, the model overestimates the land‐ocean thermal contrast, which causes the South Asian High shifted to the north and east, as well as the subtropical high and tropical convective activity located further north and persisted longer. Consequently, more water vapour transports northward, leading to more precipitation over North China–Northeast China and less precipitation over the Yangtze and Huaihe River basin. Therefore, the enhanced land‐ocean thermal contrast may be a major factor for the stronger EASM in the model, and corresponding precipitation and temperature biases in China. This analysis provides important information for further improving model performance in EASM simulation. [ABSTRACT FROM AUTHOR]

In this study, three representative concentration pathways (RCPs) and 15 general circulation models of the Coupled Model Intercomparison Project Phase 5 were used to assess the behaviour of precipitation (P) and surface air temperature (SAT) over part of the Songhua River Basin. The Water Evaluation and Planning (WEAP) model linked with SAT and P was used for monthly simulation of streamflow to assess the influence of land use/land cover and climate change on the streamflow. The results suggest that, under RCP2.6, RCP4.5 and RCP8.5, the SAT over the study area may increase in the 21st century by 1.12, 2.44 and 5.82°C, respectively. Moreover, by the middle of the 21st century, streamflow in the basin may have decreased by 19%. The decrease in streamflow may be due to changed land use conditions and water withdrawal, having critical implications for management and future planning of water resources in the basin. [ABSTRACT FROM AUTHOR]

The long-term mean air temperature has increased with continued greenhouse-gas emissions in the past decades in the Wei River Basin (WRB) (China), with little understanding of the changes in extreme temperatures. In this study, the change characteristics of both maximum (Tmax) and minimum (Tmin) temperatures at daily, monthly, and annual scales were fully examined, and their relations with the Arctic Oscillation (AO) were also explored. The modified Mann-Kendall trend test method (MMK) and heuristic segmentation method were employed to detect the trends and change points of the Tmax and Tmin at multiple scales, respectively. Subsequently, the cross wavelet transform was adopted to reveal the correlations between Tmax/Tmin and AO. Results indicated: (1) both monthly and annual Tmax and Tmin showed significantly increasing trends, whilst at daily scale they generally exhibited no obvious trends; (2) change points were found in monthly, seasonal, and annual Tmax and Tmin, implying that the stationarity of Tmax and Tmin series in the WRB has been ineffective; (3) AO had strong impacts on Tmax and Tmin changes in the WRB. Our results highlight the asymmetric response of Tmax and Tmin at the monthly, seasonal, and annual scales, which has great implications for ecosystem functions and agricultural production. [ABSTRACT FROM AUTHOR]

Simulation of surface air temperature over China from a set of regional climate model (RCM) climate change experiments are analyzed with the focus on bias and change signal of the RCM and driving general circulation models (GCMs). The set consists of 4 simulations by the RCM of RegCM4 driven by 4 different GCMs for the period of 1979–2099 under the mid-range RCP4.5 (representative concentration pathway) scenario. Results show that for present day conditions, the RCM provides with more spatial details of the distribution and in general reduces the biases of GCM, in particular in DJF (December–January–February) and over areas with complex topography. Bias patterns show some correlation between the RCM and driving GCM in DJF but not in JJA (June–July–August). In JJA, the biases in RCM simulations show similar pattern and low sensitivity to the driving GCM, which can be attributed to the large effect of internal model physics in the season. For change signals, dominant forcings from the driving GCM are evident in the RCM simulations as shown by the magnitude, large scale spatial distribution, as well as interannual variation of the changes. The added value of RCM projection is characterized by the finer spatial detail in sub-regional (river basins) and local scale. In DJF, profound warming over the Tibetan Plateau is simulated by RCM but not GCMs. In general no clear relationships are found between the model bias and change signal, either for the driving GCMs or nested RCM. [ABSTRACT FROM AUTHOR]

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

In this study, the intensity, area, and duration of droughts in China are analyzed using the Standardized Precipitation Index (SPI). The SPI was calculated on monthly data for 530 meteorological stations in China for the period 1960-2013. The time series were analyzed for ten major hydrological regions of China, respectively. The relationships between the intensity and the area of droughts for a specific duration were analyzed by the intensity-area-duration method. The results show that areas with a significant trend in dryness can be found in a band reaching from the southwest to the northeast of China, while areas with significant trends in wetness are especially detected in the northern river basins in recent decades. In addition, for recent years (2000-2013), most of the ten major hydrological regions show opposite trends in the SPI when compared to the whole study period (1960-2013) except for the central and southwestern parts of China. This dryness/wetness trends are related to the intensity and duration of drought events, which have been stronger and lasted longer in the detected dryness band except for some northern river basins. A regional shift of drought centers is found from the northwest to the southeast within Central China. Moreover, a decreasing trend in drought area is observed, which might be related to the regional changes in precipitation pattern associated with the atmosphere-ocean interaction. Changes in the SST of the Tropical Pacific and the Tropical Indian Ocean may have resulted in frequent severe drought events of small areal extent in the central and southwestern parts of China. For the study period, the most severe droughts that covered large areas mainly occurred in the north and west of China during the mid-to-late twentieth century. However, in the early twenty-first century, the most severe droughts were located in the southwest of China covering areas less than 0.7 million km. Conclusively, drought areas show a decreasing tendency, while more intense droughts of longer duration have been experienced, especially in the south of China, in the last decades. [ABSTRACT FROM AUTHOR]

With global climate changes intensifying, the hydrological response to climate changes has attracted more attention. It is beneficial not only for hydrology and ecology but also for water resource planning and management to understand the impact of climate change on runoff. In addition, there are large spatial variations in climate type and geographic characteristics across China. To gain a better understanding of the spatial variation of the response of runoff to changes in climatic factors and to detect the dominant climatic factors driving changes in annual runoff, we chose the climate elasticity method proposed by Yang and Yang (2011). It is shown that, in most catchments of China, increasing air temperature and relative humidity have negative impacts on runoff, while declining net radiation and wind speed have positive impacts on runoff, which slow the overall decline in runoff. The dominant climatic factors driving annual runoff are precipitation in most parts of China, net radiation mainly in some catchments of southern China, air temperature and wind speed mainly in some catchments in northern China. [ABSTRACT FROM AUTHOR]

In a case study in Tao River Basin, China, we derived a high spatial-resolution regional distribution of evapotranspiration (ET) using the single crop coefficient method and Budyko equation. We then further analyzed the spatio-temporal characteristics of this diverse eco-hydrological basin from 2001-2010. The results suggest that the single crop coefficient method based on leaf area index captures better spatial and temporal dynamics of the regional ET than did the Budyko Equation method. The rising temperature was the main reason for the increasing ET in the Tao River Basin during 2001-2010. Areas with high ET efficiency were distributed mainly in the areas where the vegetation coverage was high, and a lower runoff coefficient responded. The estimated spatial patterns of ET allowed an improved understanding of the eco-hydrological processes within the Tao River Basin and the method used might be generalized as a reference for future regional-scale eco-hydrological research. [ABSTRACT FROM AUTHOR]

A warmer climate may lead to less precipitation falling as snow in cold seasons. Such a switch in the state of precipitation not only alters temporal distribution of intra-annual runoff but also tends to yield less total annual runoff. Long-term water balance for 282 catchments across China is investigated, showing that a decreasing snow ratio reduces annual runoff for a given total precipitation. Within the Budyko framework, we develop an equation to quantify the relationship between snow ratio and annual runoff from a water-energy balance viewpoint. Based on the proposed equation, attribution of runoff change during the past several decades and possible runoff change induced by projected snow ratio change using climate experiment outputs archived in the Coupled Model Intercomparison Project Phase 5 (CMIP5) are analyzed. Results indicate that annual runoff in northwestern mountainous and northern high-latitude areas are sensitive to snow ratio change. The proposed model is applicable to other catchments easily and quantitatively for analyzing the effects of possible change in snow ratio on available water resources and evaluating the vulnerability of catchments to climate change. [ABSTRACT FROM AUTHOR]

Air temperature is one of the most essential variables in understanding global warming as well as variations of climate, hydrology, and eco-systems. However, current products and assimilation approaches alone can provide temperature data with high resolution, high spatio-temporal continuity, and high accuracy simultaneously (refer to 3H data). To explore this kind of potential, we proposed an integrated temperature downscaling framework by fusing multiple remotely sent, model-based, and in-situ datasets, which was inspired by point-surface data fusion and deep learning. First, all of the predictor variables were processed to maintain spatial seamlessness and temporal continuity. Then, a deep belief neural network was applied to downscale temperature with a spatial resolution of 1 km. To further enhance the model performance, calibration techniques were adopted by integrating station-based data. The results of the validation over the Yangtze River Basin indicated that the average Pearson correlation coefficient, RMSE, and MAE of downscaled temperature achieved 0.983, 1.96 °C, and 1.57 °C, respectively. After calibration, the RMSE and MAE were further decreased by ~20%. In general, the results and comparative analysis confirmed the effectiveness of the framework for generating 3H temperature datasets, which would be valuable for earth science studies. [ABSTRACT FROM AUTHOR]

Potential evapotranspiration (ET0) is an essential component of the hydrological cycle, and quantitative estimation of the influence of meteorological factors on ET0 can provide a scientific basis for studying the impact mechanisms of climate change. In the present research, the Penman–Monteith method was used to calculate ET0. The Mann–Kendall statistical test with the inverse distance weighting were used to analyze the spatiotemporal characteristics of the sensitivity coefficients and contribution rates of meteorological factors to ET0 to identify the mechanisms underlying changing ET0 rates. The results showed that the average ET0 for the Yanhe River Basin, China from 1978–2017 was 935.92 mm. Save for a single location (Ganquan), ET0 increased over the study period. Generally, the sensitivity coefficients of air temperature (0.08), wind speed at 2 m (0.19), and solar radiation (0.42) were positive, while that of relative humidity was negative (−0.41), although significant spatiotemporal differences were observed. Increasing air temperature and solar radiation contributed 1.09% and 0.55% of the observed rising ET0 rates, respectively; whereas decreasing wind speed contributed −0.63%, and relative humidity accounted for −0.85%. Therefore, it was concluded that the decrease of relative humidity did not cause the observed ET0 increase in the basin. The predominant factor driving increasing ET0 was rising air temperatures, but this too varied significantly by location and time (intra- and interannually). Decreasing wind speed at Ganquan Station decreased ET0 by −9.16%, and was the primary factor underlying the observed, local "evaporation paradox". Generally, increase in ET0 was driven by air temperature, wind speed and solar radiation, whereas decrease was derived from relative humidity. [ABSTRACT FROM AUTHOR]

Characterized by increasing surface air temperature, global warming has altered the hydrological cycle at global and regional scales. In order to adapt water resources management under the context of global warming, attribution analysis on regional differentiation of water resources in the Yangtze River basin (YRB) was conducted in this study. Meteoro-hydrological variations across the basin were examined for the period 1960–2013, and then a statistic-based method was applied in quantifying the contributions of climate variability and human activities on annual runoff variations in different tributary sub-basins in the YRB. Our observation indicates that both the annual increasing rate and the inter-annual fluctuations of temperature in China and in the YRB were higher than that of the global average since the turn of the century. Climate change analysis indicates that the YRB experienced a hot-wet period during 1994–2002 and a hot-dry period during 2003–2013, since the step change of temperature in 1993. Contributions of climate change and human activities on runoff variations varied spatially in the basin. With reference to the baseline period of 1960–1993, the contribution of climate change played a dominant role in most regions of the basin, especially in those upstream sub-basins. The effect of human activities in the basin was quite complicated, not only its regional differentiation, but also its contribution were opposite during the hot-wet period and the hot-dry period in some sub-basins. The result of this study is helpful in understanding the impacts of climate change and human activities on water resources variation in both temporal and spatial scales. [ABSTRACT FROM AUTHOR]

Understanding historical trends in temperature, precipitation, and runoff is important but incomplete for developing adaptive measures to climate change to sustain fragile ecosystems in cold and arid regions, including the Balagaer River watershed on the Mongolian Plateau of northeast China. The objective of this study was to detect such trends in this watershed from 1959 to 2017. The detection was accomplished using a Mann-Kendall sudden change approach at annual and seasonal time scales. The results indicated that the abrupt changes in temperature preceded that in either runoff or precipitation; these abrupt changes occurred between 1970 and 2004. Significant (α = 0.05) warming trends were found at the minimum temperatures in spring (0.041 °C a−1), summer (0.037 °C a−1), fall (0.027 °C a−1), and winter (0.031 °C a−1). In contrast, significant decreasing trends were found in the precipitation (−1.27 mm a−1) and runoff (−0.069 mm a−1) in the summer. Marginally increasing trends were found in the precipitation in spring (0.18 mm a−1) and fall (0.032 mm a−1), whereas an insignificant decreasing trend was found in the runoffs in these two seasons. Both precipitation and runoff in the wet season exhibited a significant decreasing trend, whereas in the dry season, they exhibited a marginally increasing trend. Sudden changes in spring runoff and sudden rises in temperature are the main causes of sudden changes in basin rainfall. [ABSTRACT FROM AUTHOR]