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Abstract: Beijing’s mountainous areas have an important ecological significance because they are ecological conservation and water source protection areas of Beijing. The impact of precipitation on the vegetation coverage of Beijing’s mountainous areas is qualitatively analyzed using multi-temporal Landsat images obtained during the last 20 years. Firstly, the influence of external factors, such as phenology and relative radiometric correction, on the normalized difference vegetation index (NDVI) are removed by the normalization of remote sensing images for different periods. Then, the vegetation coverage is calculated using the method of the dimidiate pixel model. Finally, based on that, the relationship between precipitation in different seasons and change of vegetation coverage is discussed. The results indicate that the mean vegetation coverage has the same change trends with winter and summer precipitation, but an opposite change trend with spring precipitation. The paper provides a theoretical basis and data support for further research on driving models of natural vegetation restoration in Beijing’s mountainous areas. [Copyright &y& Elsevier]

Summary: Oxygen and hydrogen stable isotopes (δ 18O and δD) in precipitation collected in every event from 2007 to 2009 in Guangzhou, South China, are presented in this paper. The total correlation between δ 18O and δD is obtained as δD =(8.46±0.13) δ 18O+(15.0±0.9). More negative δ 18O and δD generally occur during summer and autumn, while less negative or even positive δ 18O and δD occur during winter and spring. Significant negative correlations between precipitation δ 18O and temperature, and between precipitation δ 18O and precipitation amount are observed. Regression line changes from year to year are likely due to changes in moisture sources for the precipitation. The moisture contributed by adjacent seas or local evaporation account for the main precipitation during winter and early spring, while summer monsoon brings huge amounts of moisture from remote seas associated with higher temperature and larger precipitation amounts. Seasonal variations of the precipitation D-excess provide more details for changes in moisture sources. Higher D-excess values during winter and early spring are estimated to correspond to a lesser proportion of remote moisture, while lower D-excess values during summer and autumn correspond to larger remote moisture transported by summer monsoons. This generally agrees with the results of model analysis on single isobaric backward trajectories for air parcels during specific time periods. Results of this study imply that precipitation δ 18O and δD, as well as some related paleoclimate proxies such as δ 18O in speleothem and tree ring, and δD in plant-derived organic compounds and tree ring, currently cannot indicate changes in temperature or precipitation amount separately, but should be comprehensive proxies for monsoon climate. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is a fundamental component of the hydrological cycle. It is also the main mode of irrigation and precipitation loss in cultivated lands. Accurate estimation of ET is therefore important for sustainable water resources management, including monitoring droughts and simulating crop production. Whereas precipitation and runoff are measured with reasonable accuracy, ET is difficult to quantify especially at the basin/regional scale. Remote sensing (RS) energy balance models are therefore the commonly preferred methods for estimating ET on large spatial scales. The ETWatch model is one such RS-based model that interactively links several standard RS-algorithms to estimate ET. Another promising alternative method for estimating ET is the terrestrial-based water balance approach. Observations of the Gravity Recovery and Climate Experiment (GRACE) allow sufficient closure of terrestrial water balance. In combination with measured precipitation and runoff data, GRACE data can be used to estimate ET. This paper compares ET estimated by the RS-based ETWatch model with that derived as a residual of the terrestrial-based water balance technique (GRACE plus measured precipitation data) for the approx. 319 000-km2 Hai River Basin (HRB) in North China. About 63 consecutive months of data, spanning December 2002 to February 2008, are used in the study. The amplitudes and phases of the RS-based ETWatch-estimated ET match favourably those of the terrestrial-based water balance technique. The average seasonal (12.7 mm) and annual (16.6 mm) RMSE is less than 10% of the estimated ET. This implies that the RS-based ETWatch model reliably estimates ET at large spatial scales. Time series plots show that the amplitudes of the hydrological components of precipitation, ET and total water storage change are highest in summer and lowest in winter. The GRACE-derived total water storage change shows overall storage loss in the basin. This method could be used not only to fine-tune RS-based ET models, but also to monitor basin/regional water storage change in real-time conditions. Citation Moiwo, J. P., Yang, Y., Yan, N. & Wu, B. (2011) Comparison of evapotranspiration estimated by ETWatch with that derived from combined GRACE and measured precipitation data in Hai River Basin, North China. Hydrol. Sci. J. 56(2), 249-267. [ABSTRACT FROM AUTHOR]

Abstract: Long-term changes to the Yellow River delta in China have received considerable attention not only because of the growing economic importance of the delta region but also because they provide a clear example of the dominant role played by anthropogenic effects upon a large dynamic river delta. This paper presents a detailed study on the morphological consequences of reduction in river sediment load and influence of human activities based on sediment load data at three gauging stations in the upper, middle and lower reaches of the Yellow River basin from 1950 to 2007. The results indicate that sediment loads at all three gauging stations display a gradually decreasing trend over the past 58years. The primary reason for this decrease is shown to be due to various human activities, including the construction of Longyangxia and Liujiaxia reservoirs in the upper reaches, water–soil conservation practices and the commissioning of Sanmenxia and Xiaolangdi reservoirs in the middle reaches. It is estimated that water–soil conservation practices which are a major factor to the decrease of sediment load at Huayuankou gauging station account for 40% of the total amount of reduction, sediment trapping by Sanmenxia and Xiaolangdi reservoirs account for 30% of the total amount of reduction and the 10% decrease is caused by human activities in the upper reaches. The remaining 20% decrease is attributed to precipitation decrease. The reduction of sediment load has directly impacted on the lower Yellow River and the delta region, causing alternate changes between siltation and scouring in the lower river channel along with an increased rate of erosion over the whole Yellow River delta. [Copyright &y& Elsevier]

Vegetation around the Daihai Lake, northern China, is very sensitive to climate changes. In this paper, pollen-based quantitative climate reconstructions using three methods [weighted averaging partial least squares method (WAPLS), modern analog technique (MAT), and pollen response surface method (PRS)] were conducted to obtain robust reconstructions of Holocene climate changes in the Daihai Lake area. The result obtained by the three methods all consistently show the annual precipitation to have been 50–100 mm lower in the early Holocene, 100–200 mm higher in the Mid-Holocene, and 50–100 mm lower again in the late Holocene than at present. The WAPLS and the MAT methods also show quasi-synchronous oscillations of the mean annual temperature (Ta); 1°–2°C lower in the Early Holocene and 1°–3°C higher in the Mid-Holocene than today. The time period from 6200 to 5100 cal yr BP was the wettest and the warmest interval, with an annual precipitation (Pa) greater than 550 mm and mean annual temperature Ta higher than 6.5°C. Several cold and dry events can be identified to occur about 8200, 6000, and 4400 cal yr BP, with an annual precipitation less than 400 mm and a mean annual temperature colder than 4.5°C, respectively. The mean temperature of the warmest month (Tw) as reconstructed using both WAPLS and MAT methods was relatively stable during the Holocene, fluctuating about ±2°C relative to the present level, but the PRS method suggests more varied Tw values in both amplitude and frequency. After 1500 cal yr BP, no consistent pattern can be observed from these three different analyses, probably because of the impact of intensified human disturbances on the natural vegetation. The fluctuations of annual precipitation (Pa) correspond to that observed in Dongge Cave in southern China. The differences might be linked to Indian monsoon and East Asia monsoon climates or caused by the different degree of dating precision, different temporal resolution, and different sensitive response of climate proxies to the climate variations. [ABSTRACT FROM AUTHOR]

Precipitation is considered a crucial component in the hydrological cycle and changes in its spatial pattern directly influence the water resources. We compare different interpolation techniques in predicting the spatial distribution pattern of precipitation in Chongqing. Six interpolation methods, i.e., Inverse Distance Weighting (IDW), Radial Basis Function (RBF), Diffusion Interpolation with Barrier (DIB), Kernel Interpolation with Barrier (KIB), Ordinary Kriging (OK) and Empirical Bayesian Kriging (EBK), were applied to estimate different rainfall patterns. Annual mean, rainy season and dry-season precipitation was calculated from the daily precipitation time series of 34 meteorological stations with a time span of 1991 to 2019, based on Leave-One-Out Cross-Validation (LOOCV), Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Symmetric Mean Absolute Percentage Error (SMAPE) and Nash–Sutcliffe Efficiency coefficient (NSE) as validation indexes of the applied models for calculating the error degree and accuracy. Correlation test and Spearman coefficient was performed on the estimated and observed values. A method combining Entropy Weight and Technique for Order Preference by Similarity to Ideal Solution (Entropy-Weighted TOPSIS) was introduced to rank the performance of six interpolation methods. The results indicate that interpolation technique performs better in estimating during periods of low precipitation (i.e., dry season, relative to rainy season and mean annual). The performance priorities of the six methods under the combined multiple precipitation distribution patterns are KIB > EBK > OK > RBF > DIB > IDW. Among them, KIB method has the highest accuracy which maps more accurate precipitation surfaces, with the disadvantage that estimation error is prone to outliers. EBK method is the second highest, and IDW method has the lowest accuracy with a high degree of error. This paper provides information for the application of interpolation methods in estimating rainfall spatial pattern and for water resource management of concerned regions. [ABSTRACT FROM AUTHOR]

The Oligocene marked the beginning of the present 'icehouse' epoch and witnessed the development and evolution of the Asian monsoon system (AMS). In this paper, the early Oligocene Ningming flora of Guangxi, southern China, is analysed to investigate the AMS based on climate proxies derived from Climate Leaf Analysis Multivariate Program (CLAMP). CLAMP results suggest that the prevailing climate experienced by the Ningming flora was humid subtropical with hot summers and warm winters. Although the record of precipitation seasonality is muted, it is about half as strong as that seen today in monsoon climates of South China, indicating a very weak monsoonal signal. Despite suggesting weak rainfall seasonality, the position of the Ningming flora in physiognomic space indicates that leaves exhibit monsoon-adapted morphologies, comparable to today's vegetation exposed to the Indonesia–Australia monsoon (I-AM) and the transitional monsoon area (influenced by the East Asia monsoon, South Asia monsoon and I-AM). Leaf architectural signatures reveal that the Ningming flora grew under a humid subtropical climate with subtle monsoon signatures. Although it is difficult to distinguish the different domains of the Asian monsoon under such a subtle monsoon influence, based on leaf signatures from southern Asia, it can be inferred that the Ningming Basin during the early Oligocene was exposed to a climate regime similar to that today influenced by the I-AM. In addition, the moist enthalpy method was applied to quantitatively reconstruct the paleoelevation of the Ningming Basin. This approach suggests a paleoelevation estimate of ~1.24–1.35 ± 0.52 km for the early Oligocene, suggesting that a drop in paleoelevation of the Ningming Basin took place after the early Oligocene (Rupelian). The CLAMP results suggest that the early Oligocene Ningming area was at a mid-altitude and experienced a humid subtropical climate with subtle monsoon signatures. • Leaves from the early Oligocene Ningming Basin were subjected to a CLAMP analysis. • The prevailing paleoclimate was humid subtropical with hot summers and warm winters. • Leaf physiognomic spectra shows an adaptation to monsoon climates. • The paleoclimate is similar to a climate regime today influenced by the I-AM. • The early Oligocene Ningming Basin was likely at a height of ~ 1.24–1.35 km. [ABSTRACT FROM AUTHOR]

• Dynamic yield prediction with the integral regression model at any time intervals. • Remote sensing-based TVDI replaces precipitation to represent the actual amount of water available to crops. • We couple the three types of factors (sunshine hours, temperature, and precipitation/TVDI) into a comprehensive factor for yield prediction. • The combination of sunshine hours, temperature, and TVDI has better dynamic yield prediction results. This paper describes integrating remote sensing and meteorological data for dynamic winter wheat yield prediction at fixed date intervals with an integral regression model. In most cases, both rainfall and irrigation supply the water needs of crops. We postulated that meteorological precipitation could not fully represent the actual amount of water available to crops, whereas the temperature vegetation dryness index (TVDI) can represent actual water, which monitors soil moisture. According to this, meteorological and remote-sensing data based on sunshine hours, temperature, and TVDI formed a light–temperature–water data combination, which are the three most fundamental and critical factors related to crop growth. The new data combination was used as the input variables of the integral regression model, which could predict the crop yield at a fixed date interval of any length. The dynamic results were then compared with that of the meteorology data combination (sunshine hours, temperature, and precipitation). We selected a total of seven county-level areas in semi-humid and arid regions in China. The proposed dynamic prediction approach achieved good results at the county level from March 21 to maturity at 16-day intervals with predicted R2 > 0.94 and root mean squared error range of 15.54–121.01 kg ha−1 between predicted and actual yield with leave-one-year-out cross-validation for each prediction date. The trend of dynamic prediction accuracy had a relatively stable state. In addition, TVDI contained more crop water information, and prediction results using TVDI and meteorology were generally superior to that using only meteorology for semi-humid and arid areas, with the best results for arid regions. Thus, integrating meteorology and TVDI could effectively dynamically predict yield at county level for most agroclimatic regions, and particularly for arid regions. The work has implications for dynamic yield prediction and improving prediction accuracy and can be extended to other areas. [ABSTRACT FROM AUTHOR]

Abstract: The purpose of the paper is to extract and make the best use of rainfall information contained in the Chinese historical archives of Qing Dynasty, and reconstruct the precipitation series during 1736–1911. The study followed the Yu-Fen-Cun (rainfall infiltration depth) observation method in Qing Dynasty, to conduct soil infiltration experiment under the natural rainfall conditions during 2004–2006. The related parameters, such as precipitation, intensity, initial soil moisture content and infiltration depth have been measured at 10 stations (east of 105°E, 30°–40°N) with representative climatic conditions and soil physical texture in the middle and lower reaches of the Yellow River and Yangtze-Huaihe River Valley. The statistical results indicate that precipitation is the primary influencing factor to infiltration depth and is positively correlated with the infiltration depth. Additionally, the effects of every factor on infiltration depth are significantly different between the middle and lower reaches of the Yellow River and Yangtze-Huaihe River Valley. Finally, the relationship equations of precipitation and infiltration depth are established for each site, most of which can pass over 60% of the variance explanations and provide quantitative models to reconstruct the precipitation series using Yu-Fen-Cun records in Qing Dynasty. [Copyright &y& Elsevier]

The large scale character of the interannual variation of precipitation and the urban effect on local annual precipitation anomaly are investigated in this paper based on the 1960-2000 annual precipitation observations at 20 stations in the Beijing region. The results show that: the annual precipitation in the Beijing region possesses the large scale variation character with the linear trend of -1. 197/10 yr, which corresponds to a total reduction of 27.82 mm in annual precipitation in the 41 years; the local annual precipitation anomalies (percent of the normal 1960-2000) show a positive center near the urban area, i. e. urban precipitation island (UPI), whose intensity increases with the linear trend of 0.6621% /10 yr, opposite to the interannual trend of large scale precipitation over the Beijing region; changes in the UPI are also associated with the intensity of synoptic processes of precipitation, and when the synoptic processes are strong (wet years), the intensity of UPI strengthens, while the synoptic processes are weak (dry years), and the UPI disappears in the Beijing region. [ABSTRACT FROM AUTHOR]

This paper presents a large data set on carbon isotope composition (δ13C) of modern soils which were collected under the main vegetation communities along an altitude of 1250–5500 m above sea level in the Qinghai-Tibetan Plateau. The δ13C values of 198 samples range from -28.6 to -15.1‰ versus PDB and exhibit a clean relation to different vegetation communities from forest (-25.9 ± 1.2‰) to shrub (-24.7 ± 1.4‰), steppe (-23.1 ± 1.3‰), alpine meadow (-23.6 ± 0.7‰), alpine desert steppe (-21.3 ± 1.6‰), and alpine desert (-18.9 ± 2.5‰). We attributed the observed variability in δ13C values to that the mean annual precipitation (MAP) and the mean annual temperature (MAT) are the main factors controlling the distribution of vegetation types in the Tibetan Plateau, which causes the change in carbon isotope composition of modern soils at any given altitude. The result of both linear and nonlinear regression analyses also confirms that MAP and MAT are the major factors affecting the δ13C values of surface soils. In the absence of favorable moisture and temperature conditions, low pCO2 alone is not sufficient to cause the distinct changes in carbon isotope composition of modern soils in the Tibetan Plateau. This study provides some fundamental information on the carbon isotope composition of terrestrial carbon pools and bears some practical significance for the use of carbon isotope data to document vegetation changes and environmental conditions of the high plateau in the past. [ABSTRACT FROM AUTHOR]

Xinjiang is located in an arid and semi-arid climate region in China, but Xinjiang Ili river valley is more humid, with higher precipitation intensity and precipitation, which is closely related to the role of the Tianshan Mountains. In this paper, through the NCRP 1° × 1° reanalysis data and the conventional observation data of the Ili River Valley in Xinjiang, the terrain sensitivity experiment conducted by the WRF model is used to analyze the short-term extreme precipitation event of the Ili River Valley from 18–19 of May 2017, to reveal the influence of Tianshan Mountains on the extreme precipitation event of the Ili River Valley. The results show that: (1) The reduction or removal of the terrain will cause a wide range of wind field changes, weaken the vertical upward movement of the windward slope, and the accumulation of water vapor before the windward slope will also be reduced; a large-scale change of the terrain will also affect the direction of water vapor transportation. These effects together lead to a decrease or increase in regional precipitation. (2) "Fuzzy" (smooth) terrain will affect the precipitation simulated by changing the local vertical movement and water vapor transport, which shows that the WRF model's accurate description of the terrain structure characteristics of mountainous areas is beneficial to accurately simulate the precipitation process on the windward slope area. [ABSTRACT FROM AUTHOR]

To clarify the precipitation and evolution law of the Laves phase in China low-activation martensitic (CLAM) steel during long-term aging at high temperature, this paper carried out an aging treatment of CLAM steel at 550 °C for up to 30,000 h. The segregation behavior of alloy elements and the precipitation amount and average size of the Laves phase were quantitatively characterized by transmission electron microscopy (TEM) and scanning electron microscopy (SEM), and the precipitation and coarsening behavior of the Laves phase were obtained. The results show that the Laves phase begins to precipitate within 5000 h after aging and mainly depends on M23C6 carbides to nucleate and grow at the grain boundary and subgrain boundary. During the aging process, the average size of the Laves phase grows continuously. After more than 25,000 h, the growth rate of the Laves phase decreases. After 30,000 h of aging, the average size reaches 439.9 nm, and the maximum size exceeds 800 nm. The area fraction of the Laves phase increases continuously during the 20,000 h aging process and tends to be stable after aging for 20,000 h. The area fraction is approximately 1.85%. [ABSTRACT FROM AUTHOR]

The influence of urbanization on regional precipitation is one of the most important issues in hydrology. This paper selected the North Haihe Basin as the study area and explored the connection between summer precipitation and urbanization index (URBI) based on satellite precipitation and nighttime lights datasets. A moving spatial percentage anomaly method (MSP) was used to signify the local induced enhancement of precipitation (LIEP). Local indicators of spatial association (LISA) clustering for LIEP and URBI based on Bivariate Moran's I coupled with digital elevation model (DEM) segmentation was used to separate the impacts caused by urbanization and terrain uplifting, and thus, the regions of interest (ROI) where the urban induced enhancement of precipitation (UIEP) plays a dominant role were located. A geographically weighted regression (GWR) model was used to reveal the spatial variation of the sensitivity of UIEP to URBI within the ROI. Pearson correlation and cross-wavelet analyses (XWT) were adopted to investigate the teleconnection between UIEP and climate anomalies, using Niño3.4 and SOI as indices. The results indicated that: (1) Urbanization effects on precipitation spatial variation in the upstream mountainous area would be hidden away by topographic factors. (2) From the perspective of the basin, the highest urbanization level areas have the Lowest LIEP, while the suburban areas have the highest LIEP, and the rural areas are in the middle. (3) The UIEP and the URBI are generally negatively correlated within ROI. (4) UIEP versus Niño3.4 and SOI both show a significant common high-power period at a time scale of 2 years. This work can help comprehensively understand the hydrological response to urbanization. [ABSTRACT FROM AUTHOR]

In this paper, the diurnal variations of various clouds are analyzed using hourly cloud observations at weather stations in China from 1985 to 2011. In combination with merged hourly precipitation data, the relationship between the diurnal variations of clouds and precipitation in the summers from 2008 to 2011 are studied. The results show that the occurrence frequencies of total cloud and various cloud types exhibit significant diurnal variations. The diurnal variations of the occurrence frequencies of altocumulus and stratocumulus show a bimodal pattern, with peaks appearing in the early morning and late afternoon. The early morning peaks of altocumulus and stratocumulus appear earlier in the summer than in the other seasons, while the late afternoon maxima show an opposite trend. The occurrence frequency of nimbostratus peaks in the morning between 07 and 12 LST (local solar time), and the peak value lags 2 to 3 h from west to east along the Yangtze River valley; meanwhile, the diurnal variation shows no clear differences caused by changes in the latitude or seasons. Cumulus shows an afternoon (14 LST) maximum, while cumulonimbus peaks in the late afternoon during 16–20 LST, and both of them present a great diurnal range. Cirrus usually reaches its peak at 17–18 LST, and it differs by 1 to 2 h with a change in the latitude. The results of the study first show that the diurnal variations of precipitation among different regions are dominated by different clouds. The upper reaches of the Yangtze River valley present a midnight precipitation maximum that is mainly dominated by cumulonimbus. For the middle reaches of the Yangtze River valley impacted by nimbostratus, the precipitation peaks in the early morning. In South and Northeast China, the precipitation peaks in the afternoon and is determined by the diurnal variations of convective clouds. In the region between the Yangtze River valley and Yellow River valley, the precipitation peaks in the early morning and afternoon; the early morning peak is mainly determined by stratiform clouds, while the afternoon peak is closely related to convective clouds. [ABSTRACT FROM AUTHOR]

The use of remote sensing to monitor surface water bodies has gradually matured. Long-term serial water change analysis and floods monitoring are currently research hotspots of remote sensing hydrology. However, these studies are also faced with some problems, such as coarse temporal or spatial resolution of some remote sensing data. In general, flood monitoring requires high temporal resolution, and small-scale surface water extraction requires high spatial resolution. The machine learning method has been proven to be effective against long-term serial surface water extraction, such as random forests (RFs). MODIS data are well suited for large-scale surface water dynamic analysis and flood monitoring because of its short return cycle and medium spatial resolution. In this paper, the Yangtze River Basin (YRB) in China was selected as the study area, and two MODIS products (MOD09A1 and MOD13Q1) and RF method were used to extract the surface water from 2000 to 2016. Considering the disadvantages of temporal or spatial resolution of these two MODIS products, this study also presents a data fusion method to combine them and get higher spatiotemporal resolution water results. Finally, 762 surface water maps from 2000 to 2016 are obtained, whose temporal and spatial resolution is every eight days and 250 m, respectively. In addition, water extent variation is analyzed and compared to observed precipitation data. The main conclusions are as follows: (1) this constructed approach for long-term serial surface water extraction based on the RF classifier is feasible, and a good fusion method is used to obtain the surface water body with higher spatiotemporal resolution; (2) the maximum area of the surface water extent is 48.53 × 103 km2, and seasonal and permanent water areas are 20.51 × 103 km2 and 28.01 × 103 km2, respectively; (3) surface water area is increasing in the YRB, such that seasonal water area decreased by 3450 km2, and the permanent water area increased by 3565 km2 in 2001–2015; (4) precipitation is the main factor causing variation in the surface water bodies, and they both show an increasing trend in 2000–2016. As such, the approach is worth referring to other remote sensing applications, and these products are very both valuable for water resource management and flood monitoring in the study area. [ABSTRACT FROM AUTHOR]