scholarly journals Quantitative Contributions of Climate Change and Human Activities to Vegetation Changes in the Upper White Nile River

2021 ◽  
Vol 13 (18) ◽  
pp. 3648
Author(s):  
Bo Ma ◽  
Shanshan Wang ◽  
Christophe Mupenzi ◽  
Haoran Li ◽  
Jianye Ma ◽  
...  
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Human Activities ◽  
Vegetation Change ◽  
Agricultural Land ◽  
Future Trend ◽  
Nile River ◽  
Vegetation Changes ◽  
The Future ◽  
White Nile

Vegetation changes in the Upper White Nile River (UWNR) are of great significance to the maintenance of local livelihoods, the survival of wildlife, and the protection of species habitats. Based on the GIMMS NDVI3g and MODIS normalized difference vegetation index (NDVI) data, the temporal and spatial characteristics of vegetation changes in the UWNR from 1982 to 2020 were analyzed by a Theil-Sen median trend analysis and Mann-Kendall test. The future trend of vegetation was analyzed by the Hurst exponential method. A partial correlation analysis was used to analyze the relationship of the vegetation and climate factors, and a residual trend analysis was used to quantify the influence of climate change and human activities on vegetation change. The results indicated that the average NDVI value (0.75) of the UWNR from 1982 to 2020 was relatively high. The average coefficient of variation for the NDVI was 0.059, and the vegetation change was relatively stable. The vegetation in the UWNR increased 0.013/10 year on average, but the vegetation degradation in some areas was serious and mainly classified as agricultural land. The results of a future trend analysis showed that the vegetation in the UWNR is mainly negatively sustainable, and 62.54% of the vegetation will degrade in the future. The NDVI of the UWNR was more affected by temperature than by precipitation, especially on agricultural land and forestland, which were more negatively affected by warming. Climate change and human activities have an impact on vegetation changes, but the spatial distributions of the effects differ. The relative impact of human activities on vegetation change accounted for 64.5%, which was higher than that of climate change (35.5%). Human activities, such as the large proportion of agriculture, rapid population growth and the rapid development of urbanization were the main driving forces. Establishing a cross-border drought joint early warning mechanism, strengthening basic agricultural research, and changing traditional agricultural farming patterns may be effective measures to address food security and climate change and improve vegetation in the UWNR.

scholarly journals Using Budyko-Type Equations for Separating the Impacts of Climate and Vegetation Change on Runoff in the Source Area of the Yellow River

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3418
Author(s):  
Dan Yan ◽  
Zhizhu Lai ◽  
Guangxing Ji
Keyword(s):  
Climate Change ◽  
Human Activities ◽  
Vegetation Change ◽  
Yellow River ◽  
Climatic Factors ◽  
Source Area ◽  
The Yellow River ◽  
Vegetation Changes ◽  
Potential Evaporation ◽  
Runoff Change

Assessing the contribution rates of climate change and human activities to the runoff change in the source area of the Yellow River can provide support for water management in the Yellow River Basin. This paper firstly uses a multiple linear regression method to evaluate the contribution rates of climate change and human activities to the vegetation change in the source area of the Yellow River. Next, the paper uses the Budyko hypothesis method to calculate the contribution rates of climatic factors (including precipitation, potential evaporation, and subsequent vegetation changes) and vegetation changes caused by human activities to the runoff change of the Tangnaihai Hydrometric Station. The results showed that: (1) the annual runoff and precipitation in the source area of the Yellow River have a downward trend, while the annual potential evaporation and NDVI (Normalized Difference Vegetation Index) show an increasing trend; (2) The contribution rates of climate change and human activities to the vegetation change in the source area of the Yellow River is 62.79% and 37.21%, respectively; (3) The runoff change became more and more sensitive to changes in climate and underlying surface characteristic parameters; (4) The contribution rates of climatic factors (including precipitation, potential evaporation, and subsequent vegetation changes) and vegetation changes caused by human activities to the runoff change at Tangnaihai Hydrological Station are 75.33% and 24.67%, respectively; (5) The impact of precipitation on runoff reduction is more substantial than that of potential evaporation.

scholarly journals Human disturbance caused stronger influences on global vegetation change than climate change

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7763
Author(s):  
Xianliang Zhang ◽  
Xuanrui Huang
Keyword(s):  
Climate Change ◽  
Human Disturbance ◽  
Human Activities ◽  
Vegetation Change ◽  
Vegetation Changes ◽  
Vegetation Distribution ◽  
Human Disturbances ◽  
The Past ◽  
Desert Regions ◽  
Global Vegetation

Global vegetation distribution has been influenced by human disturbance and climate change. The past vegetation changes were studied in numerous studies while few studies had addressed the relative contributions of human disturbance and climate change on vegetation change. To separate the influences of human disturbance and climate change on the vegetation changes, we compared the existing vegetation which indicates the vegetation distribution under human influences with the potential vegetation which reflects the vegetation distribution without human influences. The results showed that climate-induced vegetation changes only occurred in a few grid cells from the period 1982–1996 to the period 1997–2013. Human-induced vegetation changes occurred worldwide, except in the polar and desert regions. About 3% of total vegetation distribution was transformed by human activities from the period 1982–1996 to the period 1997–2013. Human disturbances caused stronger damage to global vegetation change than climate change. Our results indicated that the regions where vegetation experienced both human disturbance and climate change are eco-fragile regions.

scholarly journals The effects of ENSO, climate change and human activities on the water level of Lake Toba, Indonesia: a critical literature review

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hendri Irwandi ◽  
Mohammad Syamsu Rosid ◽  
Terry Mart
Keyword(s):  
Climate Change ◽  
Water Level ◽  
Human Activities ◽  
Southern Oscillation ◽  
Climatic Conditions ◽  
Water Levels ◽  
Dominant Factor ◽  
Climate Projections ◽  
Continuous Increase ◽  
The Future

AbstractThis research quantitatively and qualitatively analyzes the factors responsible for the water level variations in Lake Toba, North Sumatra Province, Indonesia. According to several studies carried out from 1993 to 2020, changes in the water level were associated with climate variability, climate change, and human activities. Furthermore, these studies stated that reduced rainfall during the rainy season due to the El Niño Southern Oscillation (ENSO) and the continuous increase in the maximum and average temperatures were some of the effects of climate change in the Lake Toba catchment area. Additionally, human interventions such as industrial activities, population growth, and damage to the surrounding environment of the Lake Toba watershed had significant impacts in terms of decreasing the water level. However, these studies were unable to determine the factor that had the most significant effect, although studies on other lakes worldwide have shown these factors are the main causes of fluctuations or decreases in water levels. A simulation study of Lake Toba's water balance showed the possibility of having a water surplus until the mid-twenty-first century. The input discharge was predicted to be greater than the output; therefore, Lake Toba could be optimized without affecting the future water level. However, the climate projections depicted a different situation, with scenarios predicting the possibility of extreme climate anomalies, demonstrating drier climatic conditions in the future. This review concludes that it is necessary to conduct an in-depth, comprehensive, and systematic study to identify the most dominant factor among the three that is causing the decrease in the Lake Toba water level and to describe the future projected water level.

scholarly journals Vegetation Changes and Their Response to Global Change Based on NDVI in the Koshi River Basin of Central Himalayas Since 2000

2020 ◽  
Vol 12 (16) ◽  
pp. 6644
Author(s):  
Xue Wu ◽  
Xiaomin Sun ◽  
Zhaofeng Wang ◽  
Yili Zhang ◽  
Qionghuan Liu ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Cover ◽  
River Basin ◽  
Human Activities ◽  
Vegetation Change ◽  
Precipitation Trend ◽  
Central Himalayas ◽  
Annual Minimum Temperature ◽  
Vegetation Activity ◽  
Koshi River Basin

Vegetation forms a main component of the terrestrial biosphere owing to its crucial role in land cover and climate change, which has been of wide concern for experts and scholars. In this study, we used MODIS (moderate-resolution imaging spectroradiometer) NDVI (Normalized Difference Vegetation Index) data, land cover data, meteorological data, and DEM (Digital Elevation Model) data to do vegetation change and its relationship with climate change. First, we investigated the spatio-temporal patterns and variations of vegetation activity in the Koshi River Basin (KRB) in the central Himalayas from 2000 to 2018. Then, we combined NDVI change with climate factors using the linear method to examine their relationship, after that we used the literature review method to explore the influence of human activities to vegetation change. At the regional scale, the NDVIGS (Growth season NDVI) significantly increased in the KRB in 2000–2018, with significant greening over croplands in KRB in India. Further, the croplands and forest in the KRB in Nepal were mainly influenced by human interference. For example, improvements in agricultural fertilization and irrigation facilities as well as the success of the community forestry program in the KRB in Nepal increased the NDVIGS of the local forest. Climate also had a certain impact on the increase in NDVIGS. A significant negative correlation was observed between NDVIGS trend and the annual minimum temperature trend (TMN) in the KRB in India, but an insignificant positive correlation was noted between it and the total annual precipitation trend (PRE). NDVIGS significantly decreased over a small area, mainly around Kathmandu, due to urbanization. Increases in NDVIGS in the KRB have thus been mainly affected by human activities, and climate change has helped increase it to a certain extent.

Projecting future vegetation change for northeast China using CMIP6

2020 ◽  
Author(s):  
Wei Yuan ◽  
Shuang-ye Wu ◽  
Shugui Hou
Keyword(s):  
Climate Change ◽  
Vegetation Change ◽  
Management Strategies ◽  
Future Climate ◽  
Future Climate Change ◽  
Vegetation Changes ◽  
Emission Scenarios ◽  
Climate Data ◽  
Climate Conditions ◽  
Temperature And Precipitation

<p>This study aims to establish future vegetation changes in the east and central of northern China (ECNC), an ecologically sensitive region in the transition zonal from humid monsoonal to arid continental climate. The region has experienced significant greening in the past several decades. However, few studies exist on how vegetation will change with future climate change, and great uncertainties exist due to complex, and often spatially non-stationary, relationships between vegetation and climate. In this study, we first used historical NDVI and climate data to model this spatially variable relationship with Geographically Weighted Logit Regression. We found that temperature and precipitation could explain, on average, 43% of NDVI variance, and they could be used to model NDVI fairly well. We then establish future climate change using the output of 11 CMIP6 models for the medium (SSP245) and high (SSP585) emission scenarios for the mid-century (2041-2070) and late-century (2071-2100). The results show that for this region, both temperature and precipitation will increase under both scenarios. By late-century under SSP585, precipitation is projected to increase by 25.12% and temperature is projected to increase 5.87<sup>o</sup>C in ECNC. Finally, we used future climate conditions as input for the regression models to project future vegetation (indicated by NDVI). We found that NDVI will increase under climate change. By mid-century, the average NDVI in ECNC will increase by 0.024 and 0.021 under SSP245 and SSP585. By late-century, it will increase by 0.016 and 0.006 under SSP245 and SSP585 respectively. Although NDVI is projected to increase, the magnitude of increase is likely to diminish with higher emission scenarios, possibly due to the benefit of precipitation increase being gradually encroached by the detrimental effects of temperature increase. Moreover, despite the overall NDVI increase, the area likely to suffer vegetation degradation will also expands, particularly in the western part of ECNC. With higher emissions and later into the century, region with low NDVI is likely to shift and/or expand north-forward. Our results could provide important information on possible vegetation changes, which could help to develop effective management strategies to ensure ecological and economic sustainability in the future.</p>

scholarly journals Quantifying Influences of Natural and Anthropogenic Factors on Vegetation Changes Based on Geodetector: A Case Study in the Poyang Lake Basin, China

2021 ◽  
Vol 13 (24) ◽  
pp. 5081
Author(s):  
Yiming Wang ◽  
Zengxin Zhang ◽  
Xi Chen
Keyword(s):  
Land Use ◽  
Human Activities ◽  
Vegetation Change ◽  
Poyang Lake ◽  
Anthropogenic Factors ◽  
Lake Basin ◽  
Vegetation Changes ◽  
Vegetation Growth ◽  
Poyang Lake Basin ◽  
Natural And Anthropogenic Factors

Understanding the driving mechanism of vegetation changes is essential for vegetation restoration and management. Vegetation coverage in the Poyang Lake basin (PYLB) has changed dramatically under the context of climate change and human activities in recent decades. It remains challenging to quantify the relative contribution of natural and anthropogenic factors to vegetation change due to their complicated interaction effects. In this study, we selected the Normalized Difference Vegetation Index (NDVI) as an indicator of vegetation growth and used trend analysis and the Mann-Kendall test to analyze its spatiotemporal change in the PYLB from 2000 to 2020. Then we applied the Geodetector model, a novel spatial analysis method, to quantify the effects of natural and anthropogenic factors on vegetation change. The results showed that most regions of the basin were experiencing vegetation restoration and the overall average NDVI value in the basin increased from 0.756 to 0.809 with an upward yearly trend of +0.0026. Land-use type exerted the greatest influence on vegetation change, followed by slope, elevation, and soil types. Except for conversions to construction land, most types of land use conversion induced an increase in NDVI in the basin. The influence of one factor on vegetation NDVI was always enhanced when interacting with another. The interaction effect of land use types and population density was the largest, which could explain 45.6% of the vegetation change, indicating that human activities dominated vegetation change in the PYLB. Moreover, we determined the ranges or types of factors most suitable for vegetation growth, which can be helpful for decision-makers to optimize the implementation of ecological projects in the PYLB in the future. The results of this study could improve the understanding of the driving mechanisms of vegetation change and provide a valuable reference for ecological restoration in subtropical humid regions.

scholarly journals Detecting Vegetation Change in the Pearl River Delta Region Based on Time Series Segmentation and Residual Trend Analysis (TSS-RESTREND) and MODIS NDVI

2020 ◽  
Vol 12 (24) ◽  
pp. 4049
Author(s):  
Zhu Ruan ◽  
Yaoqiu Kuang ◽  
Yeyu He ◽  
Wei Zhen ◽  
Song Ding
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Pearl River Delta ◽  
Vegetation Change ◽  
Vegetation Changes ◽  
Pearl River Delta Region ◽  
Modis Ndvi ◽  
Time Series Segmentation ◽  
The Pearl River ◽  
The City

Time Series Segmentation and Residual Trend analysis (TSS-RESTREND) can detect an abrupt change that was undetected by Residual Trend analysis (RESTREND), but it is usually combined with the Global Inventory for Mapping and Modeling Studies (GIMMS) Normalized Difference Vegetation Index (NDVI), which cannot detect detailed vegetation changes in small areas. Hence, we used Time Series Segmentation and Residual Trend analysis (TSS-RESTREND) and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI (MOD-TR) to analyze the vegetation dynamic of the Pearl River Delta region (PRD) in this study. To choose the most suitable MODIS NDVI from MOD13Q1 (250 m), MOD13A1 (500 m), and MOD13A2 (1 km), whole and local comparison of results of the break year and MOD-TR were used. Meanwhile, a comparison of vegetation change at the city-scale was also implemented. Moreover, to reduce insignificant trend pixels in TSS-RESTREND, a combination method of TSS-RESTREND and RESTREND (CTSS-RESTREND) was proposed. We found that: (1) MOD13Q1 and MOD13A1 two NDVI were suitable for combination with TSS-RESTREND to detect vegetation change in PRD, but MOD13Q1 was a better choice when considering the accuracy of local detailed vegetation change; (2) CTSS-RESTREND could detect more pixels with a significant change (i.e., significant increase and significant decrease) than those of TSS-RESTREND and RESTREND. Also, its effectiveness could be verified by Landsat data; (3) at the city-scale, the CTSS-RESTREND detected that only vegetation decreases in Shenzhen, Foshan, Dongguan, and Zhongshan were higher than vegetation increases, but, significant vegetation changes (i.e., decreases and increases) were mainly concentrated in Huizhou, Jiangmen, Zhaoqing, and Guangzhou.

Data Construction and Spatiotemporal Trend Attribution of Runoff over the African Continent (1981–2016)

2021 ◽  
Author(s):  
Fidele Karamage ◽  
Yongwei Liu ◽  
Yuanbo Liu
Keyword(s):  
Climate Change ◽  
Statistical Methods ◽  
Human Activities ◽  
Water Resource Management ◽  
Agricultural Land ◽  
Curve Number ◽  
Discharge Data ◽  
Resource Managers ◽  
Runoff Change ◽  
Natural Resource Managers

AbstractThe availability of streamflow records in Africa has been declining since the 1980s due to malfunctioning gauging stations and data collection failures. Africa also has insufficient hydrological information owing to the allocation of few resources to research efforts. Unreliable runoff datasets and large uncertainties in runoff trends due to climate change patterns and human activities are major challenges to water resource management in Africa. Therefore, this study aimed to improve runoff estimates and to assess runoff trend responses to climate change and human activities in Africa during 1981–2016. Using statistical methods, monthly gridded runoff datasets were generated for the period of 1981–2016 from a modified runoff curve number method calibrated with river discharge data from 535 gauging stations. According to the cross-validation results, the constructed runoff datasets comprised the Nash and Sutcliffe coefficients ranging from 0.5 to 1, coefficients of determination ranging from 0.5 to 1 and percent biases between ±25% for a large number of stations up to 73%, 80% and 91% of the 535 gauged catchments used as references. Analysis of runoff trend responses to climate change and human activities revealed that land cover change contributed more (72%) to the observed net runoff change (0.30%•a−1) than continental climate changes (28%). These contributions were results of cropland expansion rate of 0.46%•a−1 and a precipitation increase of 0.07%•a−1. The performance and simplicity of the statistical methods used in this study could be useful for improving runoff estimations in other regions with limited streamflow data data. The results of the current study could be important to natural resource managers and decision makers in terms of raising awareness of climate change adaptation strategies and agricultural land-use policies in Africa.

Trend Analysis of Climate Change in Chittagong Station in Bangladesh

2015 ◽  
Vol 47 ◽  
pp. 42-53
Author(s):  
Mallika Roy ◽  
Bablo Biswas ◽  
Sanjib Ghosh
Keyword(s):  
Climate Change ◽  
Linear Relationship ◽  
Trend Analysis ◽  
Correlation Coefficient ◽  
Human Activities ◽  
Correlation Coefficients ◽  
P Value ◽  
Annual Average ◽  
Agriculture Industry ◽  
Average Rainfall

The amount of rainfall received over an area is an important factor in assessing availability of water to meet various demands for agriculture, industry, irrigation, generation of hydroelectricity and other human activities. Over the study period of recent 30 years, trend values of monsoon average rainfall in Chittagong have increased. This paper has measured the correlation coefficients between rainfall and time for Chittagong, where correlation coefficient for Chittagong is positive. In order to check the strength of linear relationship between rainfall and time, P-value has been measured. Due to various factors of Chittagong region of Bangladesh, there is a growing need to study the rainfall, temperature and humidity pattern. This study was checked annual average rainfall of 30 years, temperature of 60 years and humidity of 28 years for this region. It is hoped that this research may be of help to the concerned organizations and experts working on increasing climate variation in Chittagong.

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