Long-term precipitation change by hourly data in Haihe River Basin during 1961–2004

2011 ◽  
Vol 54 (10) ◽  
pp. 1576-1585 ◽  
Author(s):  
ShuiQing Yin ◽  
Ge Gao ◽  
WeiJing Li ◽  
DeLiang Chen ◽  
LiSheng Hao
2018 ◽  
Vol 11 (1) ◽  
pp. 241-257 ◽  
Author(s):  
Sicheng Wan ◽  
Jianyun Zhang ◽  
Guoqing Wang ◽  
Lu Zhang ◽  
Lei Cheng ◽  
...  

Abstract Investigating long-term streamflow changes pattern and its response to climate and human factors is of crucial significance to understand the hydrological cycle under a changing environment. Caijiazhuang catchment located within Haihe River basin, north China was selected as the study area. To detect the trend and changes in streamflow, Mann–Kendall test was used. Elasticity and hydrological simulation methods were applied to assess the relative contribution of climate change and human activities on streamflow variability under three periods (baseline (1958–1977), impact I (1978–1997), and impact II (1998–2012)). The long-term hydro-climatic variables experienced substantial changes during the whole study period, and 1977 was the breaking year of streamflow change. Attribution analysis using the two methods showed consistent results: for impact I, climate change impacts explained 65% and 68% of streamflow reduction; however for impact II, it only represented 49% and 56% of streamflow reduction. This result indicated that human activities were intensifying over time. Various types of human activities presented significant effects on streamflow regimes including volumes and hydrographs. The findings of this paper could provide better insights of hydrological evolution and would thus assist water managers in sustainably managing and providing water use strategies under a changing environment.


2019 ◽  
Vol 11 (24) ◽  
pp. 3050
Author(s):  
Yulong Zhong ◽  
Wei Feng ◽  
Vincent Humphrey ◽  
Min Zhong

Terrestrial water storage (TWS) can be influenced by both climate change and anthropogenic activities. While the Gravity Recovery and Climate Experiment (GRACE) satellites have provided a global view on long-term trends in TWS, our ability to disentangle human impacts from natural climate variability remains limited. Here we present a quantitative method to isolate these two contributions with reconstructed climate-driven TWS anomalies (TWSA) based on long-term precipitation data. Using the Haihe River Basin (HRB) as a case study, we find a higher human-induced water depletion rate (−12.87 ± 1.07 mm/yr) compared to the original negative trend observed by GRACE alone for the period of 2003–2013, accounting for a positive climate-driven TWSA trend (+4.31 ± 0.72 mm/yr). We show that previous approaches (e.g., relying on land surface models) provide lower estimates of the climate-driven trend, and thus likely underestimated the human-induced trend. The isolation method presented in this study will help to interpret observed long-term TWS changes and assess regional anthropogenic impacts on water resources.


2014 ◽  
Vol 6 (2) ◽  
pp. 341-351 ◽  
Author(s):  
Chun Chang ◽  
Ping Feng ◽  
Fawen Li ◽  
Yunming Gao

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.


Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1798
Author(s):  
Xu Wu ◽  
Su Li ◽  
Bin Liu ◽  
Dan Xu

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.


2018 ◽  
Vol 36 (1) ◽  
pp. 79-92
Author(s):  
Fuqiang Yang ◽  
Li Dan ◽  
Jing Peng ◽  
Xiujing Yang ◽  
Yueyue Li ◽  
...  

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