scholarly journals Spatial-temporal Evolution of Vegetation Coverage and Analysis of it’s Future Trends in Wujiang River Basin

2018 ◽  
Vol 108 ◽  
pp. 042066 ◽  
Author(s):  
Jianyong Xiao ◽  
Xiaoyong Bai ◽  
Dequan Zhou ◽  
Qinghuan Qian ◽  
Cheng Zeng ◽  
...  
Keyword(s):  
River Basin ◽  
Temporal Evolution ◽  
Vegetation Coverage ◽  
Future Trends ◽  
Wujiang River ◽  
Evolution Of Vegetation

scholarly journals Temporal and Spatial Evolution of Vegetation Coverage in the Mianyuan River Basin Influenced by Strong Earthquake Disturbance

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Bin-rui Gan ◽  
Xing-guo Yang ◽  
Wen Zhang ◽  
Jia-wen Zhou
Keyword(s):  
River Basin ◽  
Vegetation Index ◽  
Active Fault ◽  
Recovery Period ◽  
Vegetation Coverage ◽  
Economic Losses ◽  
Terrestrial Vegetation ◽  
Variable Regions ◽  
2008 Wenchuan Earthquake ◽  
Evolution Of Vegetation

AbstractThe 2008 Wenchuan earthquake caused significant economic losses and degradation of regional ecosystems, including the terrestrial vegetation. Since the vegetation root system can enhance the soil’s anti-erosion capacity and therefore mitigate the occurrence of slope instabilities, it is beneficial to study the spatial and temporal evolution of vegetation for a long-term assessment of co-seismic secondary disasters. The Mianyuan River Basin, an uninhabited area passing through an active fault located in the earthquake-affected region, was selected as the study area. The Normal Difference Vegetation Index (NDVI) was calculated using remote sensing images from 1994 to 2017 to analyze the process of vegetation growth, loss, fluctuation and recovery. Statistical results suggest that the area in the middle and lower reaches, near the river network, and with a slope of 30 to 40 degrees were variable regions, showing more significant vegetation destruction during the earthquake and faster repair after the seismic event. Besides, vegetation near the fault was damaged more severely after the earthquake, but the active fault did not play an essential role in the vegetation recovery period. In the Mianyuan River Basin, vegetation experienced a volatility period (5 plus or minus one year) before entering the recovery period. In 8 to 9 years after the earthquake, the surficial vegetation could recover to the state before the earthquake.

scholarly journals Analysis of Runoff Variation Characteristics and Influencing Factors in the Wujiang River Basin in the Past 30 Years

2021 ◽  
Vol 19 (1) ◽  
pp. 372
Author(s):  
Wenxian Guo ◽  
Jianwen Hu ◽  
Hongxiang Wang
Keyword(s):  
River Basin ◽  
Kendall Test ◽  
Annual Runoff ◽  
Underlying Surface ◽  
Vegetation Coverage ◽  
Factors Affecting ◽  
Runoff Variation ◽  
Wujiang River ◽  
Variation Characteristics ◽  
Moderate Change

Changes in climate and the underlying surface are the main factors affecting runoff. Quantitative assessment of runoff characteristics, and determination of the climate and underlying surface contribution to changes in runoff are critical to water resources management and protection. Based on the runoff data from the Wulong Hydrological Station, combined with the Mann-Kendall test, Indicators of Hydrologic Alteration (IHA), Budyko hypothesis, and changes in climate and the underlying surface, this study comprehensively analyzed the runoff in the Wujiang River Basin (WRB). The results showed that: (1) The annual runoff of Wujiang River showed a downward trend, and an abrupt change occurred in 2005. (2) The overall hydrological change in WRB is 46%, reaching a moderate change. (3) The contribution rates of precipitation (P), potential evaporation (ET0), and underlying surface to runoff changes are 61.5%, 11.4%, and 26.9%, respectively. (4) After 2005, the WRB has become more arid, human activities have become more active, vegetation coverage has increased, and the built-up land has increased significantly.

Determinants and spatial-temporal evolution of vegetation coverage in the karst critical zone of South China

2018 ◽  
Vol 38 (24) ◽  
Author(s):  
肖建勇 XIAO Jianyong ◽  
王世杰 WANG Shijie ◽  
白晓永 BAI Xiaoyong ◽  
周德全 ZHOU Dequan ◽  
田义超 TIAN Yichao ◽  
...  
Keyword(s):  
South China ◽  
Temporal Evolution ◽  
Critical Zone ◽  
Vegetation Coverage ◽  
Evolution Of Vegetation

Spatial-Temporal Evolution of the Distribution Pattern of Neolithic Sites in Han River Basin, China

2018 ◽  
Vol 25 (1) ◽  
pp. 1-13
Author(s):  
Wenmin Qin ◽  
Lunche Wang ◽  
Aiwen Lin ◽  
Chao Yang ◽  
Hongji Zhu
Keyword(s):  
Distribution Pattern ◽  
River Basin ◽  
Temporal Evolution ◽  
Han River ◽  
Han River Basin

scholarly journals A Study on the Relationship between Land Use Change and Water Quality of the Mitidja Watershed in Algeria Based on GIS and RS

2020 ◽  
Vol 12 (9) ◽  
pp. 3510 ◽  
Author(s):  
Dechao Chen ◽  
Acef Elhadj ◽  
Hualian Xu ◽  
Xinliang Xu ◽  
Zhi Qiao
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Land Use Change ◽  
River Basin ◽  
Agricultural Land ◽  
Vegetation Coverage ◽  
Water Quality Control ◽  
Urban Settlement ◽  
The Relationship

Many catchments in northern Algeria, including the coastal Mitidja Basin in the north central part of the country have been negatively affected by the deterioration of water quality in recent years. This study aims to discover the relationship between land use change and its impact on water quality in the coastal Mitidja river basin. Based on the data of land use and water quality in 2000, 2010 and 2017, the relationship between land use change and surface water quality index in the Mitidja Watershed was discussed through GIS and statistical analysis. The results show that the physical and chemical properties of the Mitidja river basin have obvious spatial heterogeneity. The water quality of upstream was better than that of downstream. There was a significant spatial relationship between the eight water quality indicators and three land use types, including urban residential land, agricultural land and vegetation. In most cases, settlements and agricultural land are the dominant factors leading to river pollution, and higher vegetation coverage helps to improve water quality. The regression model revealed that percentage of urban settlement area was a predictor for NH4-N, BOD5, COD, SS, PO4-P, DO and pH, while vegetation was a predictor for NO3-N. The analysis also showed that during this period, urban settlement areas increased sharply, which has a significant impact on water quality variables. Agricultural land only had a significant positive correlation with PO4-P. The results provide an effective way to evaluate river water quality, control water pollution and land use management by landscape pattern.

scholarly journals Copula-Based Abrupt Variations Detection in the Relationship of Seasonal Vegetation-Climate in the Jing River Basin, China

2019 ◽  
Vol 11 (13) ◽  
pp. 1628 ◽  
Author(s):  
Jing Zhao ◽  
Shengzhi Huang ◽  
Qiang Huang ◽  
Hao Wang ◽  
Guoyong Leng ◽  
...  
Keyword(s):  
River Basin ◽  
Human Activities ◽  
Urban Areas ◽  
Large Scale ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Potential Evapotranspiration ◽  
Change Points ◽  
Vegetation Coverage ◽  
The Relationship

Understanding the changing relationships between vegetation coverage and precipitation/temperature (P/T) and then exploring their potential drivers are highly necessary for ecosystem management under the backdrop of a changing environment. The Jing River Basin (JRB), a typical eco-environmentally vulnerable region of the Loess Plateau, was chosen to identify abrupt variations of the relationships between seasonal Normalized Difference Vegetation Index (NDVI) and P/T through a copula-based method. By considering the climatic/large-scale atmospheric circulation patterns and human activities, the potential causes of the non-stationarity of the relationship between NDVI and P/T were revealed. Results indicated that (1) the copula-based framework introduced in this study is more reasonable and reliable than the traditional double-mass curves method in detecting change points of vegetation and climate relationships; (2) generally, no significant change points were identified during 1982–2010 at the 95% confidence level, implying the overall stationary relationship still exists, while the relationships between spring NDVI and P/T, autumn NDVI and P have slightly changed; (3) teleconnection factors (including Arctic Oscillation (AO), Pacific Decadal Oscillation (PDO), Niño 3.4, and sunspots) have a more significant influence on the relationship between seasonal NDVI and P/T than local climatic factors (including potential evapotranspiration and soil moisture); (4) negative human activities (expansion of farmland and urban areas) and positive human activities (“Grain For Green” program) were also potential factors affecting the relationship between NDVI and P/T. This study provides a new and reliable insight into detecting the non-stationarity of the relationship between NDVI and P/T, which will be beneficial for further revealing the connection between the atmosphere and ecosystems.

scholarly journals Analysis of the Changes in the Water Yield Coefficient over the Past 50 Years in the Huang-Huai-Hai River Basin, China

2018 ◽  
Vol 2018 ◽  
pp. 1-20 ◽  
Author(s):  
Xiaoqing Shi ◽  
Tianling Qin ◽  
Denghua Yan ◽  
Ruochen Sun ◽  
Shuang Cao ◽  
...  
Keyword(s):  
Land Use ◽  
River Basin ◽  
Vegetation Index ◽  
Yellow River ◽  
Rate Of Change ◽  
Vegetation Coverage ◽  
Water Yield ◽  
Yield Coefficient ◽  
Positive Trend ◽  
Land Use Types

This study analysed the temporal and spatial changes in the water yield coefficient (WYC), which represents the ratio of the gross amount of water resources to precipitation. Factors such as precipitation, rainstorm days, rainless days, vegetation cover change, and land use/cover change were considered to determine the causes of these changes. The results led to the following conclusions: (1) The average annual WYC of the Huang-Huai-Hai River Basin is between 0.03 and 0.58, with an average value of 0.17, which is smaller than the national average WYC of 0.4. (2) Temporally, the WYC varied slightly, with the western part showing a negative trend and the eastern part showing a positive trend. The WYC is positively correlated with precipitation, rainstorm days, and the normalized difference vegetation index (NDVI) and negatively correlated with rainless days. However, a slower change in NDVI produced a faster change in WYC. In areas with land use types exhibiting a large evapotranspiration decrease, the rate of change in the WYC increased. (3) Spatially, the distribution is fairly regular, exhibiting a gradual increase from the northern part of the Yellow River Basin (WYC < 0.1) to the surrounding areas. When the WYC is correlated with precipitation, rainstorm days, rainless days, and NDVI, the R2 values of the linear fitting results are 0.98, 0.91, 0.96, and 0.73, respectively. The WYC is positively correlated with precipitation, rainstorm days, and vegetation coverage and negatively correlated with rainless days, but the correlation coefficient is greatly influenced by the precipitation characteristics and land use types. In areas featuring high proportions of land use types associated with high evapotranspiration, the average WYC is low.

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