Ridge–furrow rainfall harvesting system helps to improve stability, benefits and precipitation utilization efficiency of maize production in Loess Plateau region of China

2022 ◽  
Vol 261 ◽  
pp. 107360
Author(s):  
Guangzhou Chen ◽  
Peng Wu ◽  
Junying Wang ◽  
Peng Zhang ◽  
Zhikuan Jia
2021 ◽  
Author(s):  
Gaimei Liang ◽  
Baoliang Chi ◽  
Nana Li ◽  
Wenliang Chen ◽  
Wei Qin ◽  
...  

2011 ◽  
Vol 5 ◽  
pp. 307-313 ◽  
Author(s):  
ZHANG Guozhen ◽  
YANG Yuanchao ◽  
LIU Xiaodong ◽  
ZHAO Weina
Keyword(s):  

2016 ◽  
Vol 94 ◽  
pp. 427-436 ◽  
Author(s):  
Wei-Jie Yu ◽  
Ju-Ying Jiao ◽  
Dong-Li Wang ◽  
Ning Wang ◽  
Zhi-Jie Wang ◽  
...  

2018 ◽  
Vol 98 (3) ◽  
pp. 531-541
Author(s):  
Qingyin Zhang ◽  
Ming’an Shao

Change in land use causes changes in soil properties and soil fertility, with long-term effects on ecosystem and crop productivity. This study determined soil fertility along sequential conversion of cropland to grassland in China’s Loess Plateau. Soil samples were collected in 2015 at two sites in the semiarid region, following the conversion of cropland to grassland. Soil particle-size distribution, bulk density, pH, organic carbon (OC), total nitrogen (TN), total phosphorus (TP), available potassium, and available phosphorus were measured in this study. In addition, we analysed the changes of soil OC, TN, and TP, and evaluated soil fertility after the conversion from cropland to grassland. The establishment of grassland significantly increased soil OC, N, and P content, especially in the 0–10 cm soil layer. The highest change in soil OC, N, and P content occurred 6–10 yr after land conversion. The measured soil variables did not change significantly after 10 yr of land conversion. The overall increase in soil fertility after the land conversion was 13% at one site and 26% at the other site. The results suggested that establishing grassland could enhance soil fertility in the semiarid Loess Plateau region of China, and this enhancement is optimal 6–10 yr after the establishment of grassland.


Author(s):  
Hang Zhang ◽  
Hai Chen ◽  
Tianwei Geng ◽  
Di Liu ◽  
Qinqin Shi

Social-ecological production landscape resilience (SELPR) is a significant representation of the continuous supply capacity of landscape services. It is a quantitative assessment of the spatial-temporal evolution of SELPR under internal and external disturbances that provides a scientific basis for regional ecological environments and socio–economic development. Taking Mizhi County for the study of the Loess Plateau region, a three-dimensional (social system, ecosystem, and production system) SELPR evaluation framework was constructed. Data integration was performed using the watershed as the evaluation unit. This study quantitatively evaluated the spatial–temporal differentiation of the social–ecological production landscape (SELPs) subsystem’s resilience and the total SELPR in the study area and classified the areas from the three-system resilience combination level to achieve regional development trade-offs. The results were as follows: (1) In 2009–2018, the change in the social–ecological production landscapes pattern in Mizhi County showed a significant reduction in agricultural production landscapes, relatively stable social living landscapes, and an increase in ecological landscapes; (2) in 2009–2018, the SELPR increased by 12.38%. The spatial distribution of resilience was significantly different, showing a distribution pattern of high central and low surrounding areas; (3) the county’s watershed development zones were divided into five partitions: synergistic promotion areas, ecological restoration areas, social development areas, production optimization areas, and comprehensive remediation areas. The five types of zones have a certain agglomeration effect. In addition, the main obstacle factors affecting the SELPR of each zone are quite different. The key issues and development directions of different types of watersheds are also proposed in this paper.


CATENA ◽  
2014 ◽  
Vol 121 ◽  
pp. 22-30 ◽  
Author(s):  
Wen-Feng Tan ◽  
Rui Zhang ◽  
Hua Cao ◽  
Chuan-Qin Huang ◽  
Qin-Ke Yang ◽  
...  

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