Remote sensing monitoring on regional crop water productivity in the Haihe River Basin

2013 ◽  
Vol 23 (6) ◽  
pp. 1080-1090 ◽  
Author(s):  
Fapeng Li ◽  
Chesheng Zhan ◽  
Zongxue Xu ◽  
Shanshan Jiang ◽  
Jun Xiong
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.


2019 ◽  
Vol 11 (6) ◽  
pp. 705 ◽  
Author(s):  
Poolad Karimi ◽  
Bhembe Bongani ◽  
Megan Blatchford ◽  
Charlotte de Fraiture

Remote sensing techniques have been shown, in several studies, to be an extremely effective tool for assessing the performance of irrigated areas at various scales and diverse climatic regions across the world. Open access, ready-made, global ET products were utilized in this first-ever-countrywide irrigation performance assessment study. The study aimed at identifying ‘bright spots’, the highest performing sugarcane growers, and ‘hot spots’, or low performing sugarcane growers. Four remote sensing-derived irrigation performance indicators were applied to over 302 sugarcane growers; equity, adequacy, reliability and crop water productivity. The growers were segmented according to: (i) land holding size or grower scale (ii) management regime, (iii) location of the irrigation schemes and (iv) irrigation method. Five growing seasons, from June 2005 to October 2009, were investigated. The results show while the equity of water distribution is high across all management regimes and locations, adequacy and reliability of water needs improvement in several locations. Given the fact that, in general, water supply was not constrained during the study period, the observed issues with adequacy and reliability of irrigation in some of the schemes were mostly due to poor scheme and farm level water management practices. Sugarcane crop water productivity showed the highest variation among all the indicators, with Estate managed schemes having the highest CWP at 1.57 kg/m3 and the individual growers recording the lowest CWP at 1.14 kg/m3, nearly 30% less. Similarly center pivot systems showed to have the highest CWP at 1.63 kg/m3, which was 30% higher than the CWP in furrow systems. This study showcases the applicability of publicly available global remote sensing products for assessing performance of the irrigated crops at the local level in several aspects.


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

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