Evaluation of the WRF physics ensemble using a multivariable integrated evaluation approach over the Haihe river basin in northern China

2021 ◽  
Author(s):  
Danqiong Dai ◽  
Liang Chen ◽  
Zhuguo Ma ◽  
Zhongfeng Xu
Keyword(s):  
River Basin ◽  
Northern China ◽  
Haihe River Basin ◽  
Haihe River ◽  
Evaluation Approach ◽  
Physics Ensemble ◽  
The Haihe River Basin

Attribution for decreasing streamflow of the Haihe River basin, northern China: Climate variability or human activities?

2012 ◽  
Vol 460-461 ◽  
pp. 117-129 ◽  
Author(s):  
Zhenxin Bao ◽  
Jianyun Zhang ◽  
Guoqing Wang ◽  
Guobin Fu ◽  
Ruimin He ◽  
...  
Keyword(s):  
Climate Variability ◽  
River Basin ◽  
Human Activities ◽  
Northern China ◽  
Haihe River Basin ◽  
Haihe River ◽  
The Haihe River Basin

scholarly journals Quantitative Assessment of Soil Physical Quality in Northern China Based on S-theory

2015 ◽  
Vol 39 (5) ◽  
pp. 1311-1321 ◽  
Author(s):  
Dejun Yang ◽  
Zhengfu Bian ◽  
Kefeng Zhang ◽  
Jibing Xiong ◽  
Shaogang Lei
Keyword(s):  
Bulk Density ◽  
River Basin ◽  
Quantitative Assessment ◽  
Clay Content ◽  
Northern China ◽  
Haihe River Basin ◽  
Haihe River ◽  
Physical Quality ◽  
Soil Physical Quality ◽  
The Haihe River Basin

ABSTRACT Quantitative assessment of soil physical quality is of great importance for eco-environmental pollution and soil quality studies. In this paper, based on the S-theory, data from 16 collection sites in the Haihe River Basin in northern China were used, and the effects of soil particle size distribution and bulk density on three important indices of theS-theory were investigated on a regional scale. The relationships between unsaturated hydraulic conductivityKi at the inflection point and S values (S/hi) were also studied using two different types of fitting equations. The results showed that the polynomial equation was better than the linear equation for describing the relationships between -log Ki and -logS, and -log Kiand -log (S/hi)2; and clay content was the most important factor affecting the soil physical quality index (S). The variation in the S index according to soil clay content was able to be fitted using a double-linear-line approach, with decrease in the S index being much faster for clay content less than 20 %. In contrast, the bulk density index was found to be less important than clay content. The average S index was 0.077, indicating that soil physical quality in the Haihe River Basin was good.

Long-term variation of water vapor content and precipitation in the Haihe river basin

2014 ◽  
Vol 6 (2) ◽  
pp. 341-351 ◽  
Author(s):  
Chun Chang ◽  
Ping Feng ◽  
Fawen Li ◽  
Yunming Gao
Keyword(s):  
Water Vapor ◽  
River Basin ◽  
Reanalysis Data ◽  
Water Vapor Content ◽  
Haihe River Basin ◽  
Haihe River ◽  
Annual Water ◽  
Environmental Prediction ◽  
High Consistency ◽  
The Haihe River Basin

Based on the Haihe river basin National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis data from 1948 to 2010 and the precipitation data of 53 hydrological stations during 1957–2010, this study analyzed the variation of water vapor content and precipitation, and investigated the correlation between them using several statistical methods. The results showed that the annual water vapor content decreased drastically from 1948 to 2010. It was comparatively high from the late 1940s to the late 1960s and depreciated from the early 1970s. From the southeast to the northwest of the Haihe river basin, there was a decrease in water vapor content. For vertical distribution, water vapor content from the ground to 700 hPa pressure level accounted for 72.9% of the whole atmospheric layer, which indicated that the water vapor of the Haihe river basin was mainly in the air close to the ground. The precipitation in the Haihe river basin during 1957–2010 decreased very slightly. According to the correlation analysis, the precipitation and water vapor content changes showed statistically positive correlation, in addition, their break points were both in the 1970s. Furthermore, the high consistency between the precipitation efficiency and precipitation demonstrates that water vapor content is one of the important factors in the formation of precipitation.

scholarly journals Spatial and Temporal Variation Characteristics of Snowfall in the Haihe River Basin from 1960 to 2016

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1798
Author(s):  
Xu Wu ◽  
Su Li ◽  
Bin Liu ◽  
Dan Xu
Keyword(s):  
Temporal Variation ◽  
River Basin ◽  
Spatial And Temporal Variation ◽  
Haihe River Basin ◽  
Temperature Threshold ◽  
Threshold Method ◽  
Exponential Equation ◽  
Haihe River ◽  
The Haihe River Basin ◽  
Different Levels

The spatio-temporal variation of precipitation under global warming had been a research hotspot. Snowfall is an important part of precipitation, and its variabilities and trends in different regions have received great attention. In this paper, the Haihe River Basin is used as a case, and we employ the K-means clustering method to divide the basin into four sub-regions. The double temperature threshold method in the form of the exponential equation is used in this study to identify precipitation phase states, based on daily temperature, snowfall, and precipitation data from 43 meteorological stations in and around the Haihe River Basin from 1960 to 1979. Then, daily snowfall data from 1960 to 2016 are established, and the spatial and temporal variation of snowfall in the Haihe River Basin are analyzed according to the snowfall levels as determined by the national meteorological department. The results evalueted in four different zones show that (1) the snowfall at each meteorological station can be effectively estimated at an annual scale through the exponential equation, for which the correlation coefficient of each division is above 0.95, and the relative error is within 5%. (2) Except for the average snowfall and light snowfall, the snowfall and snowfall days of moderate snow, heavy snow, and snowstorm in each division are in the order of Zones III > IV > I > II. (3) The snowfall and the number of snowfall days at different levels both show a decreasing trend, except for the increasing trend of snowfall in Zone I. (4) The interannual variation trend in the snowfall at the different levels are not obvious, except for Zone III, which shows a significant decreasing trend.

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