Greening trend in grassland of the Lhasa River Region on the Qinghai-Tibetan Plateau from 1982 to 2013

2016 ◽  
Vol 38 (6) ◽  
pp. 591 ◽  
Author(s):  
Han Luo ◽  
Ya Tang ◽  
Xuan Zhu ◽  
Baofeng Di ◽  
Yuhui Xu
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Western China ◽  
Upward Trend ◽  
Modis Ndvi ◽  
Significant Upward Trend ◽  
River Region ◽  
Normalised Difference Vegetation Index ◽  
Lhasa River ◽  
The Impact

Local residents of the Lhasa River Region (LRR) on the Qinghai-Tibetan Plateau in western China have noticed that the surrounding mountains have appeared conspicuously green since the 1980s. To verify these claims, we investigated trends of grassland activities in the LRR from 1982 to 2013 by using remotely sensed Normalised Difference Vegetation Index (NDVI) data, as a proxy for photosynthetic activity. Due to the limitation of available remote sensing data, we used long-term data with low resolution, GIMMS3 g NDVI, to explore the temporal changes between 1982 and 2012; we used moderate resolution data, MODIS NDVI, to investigate the spatial variations of trends between 2001 and 2013. In addition, we examined the relationship between grassland change and climate change. The results revealed a significant upward trend in the annual mean NDVI of the LRR from 1982 to 2012, corroborating the observations of the local people. The increasing trend was more pronounced during the period of 1982–1999 than during the period of 2000–2012. The seasonal NDVI also exhibited a significant upward trend in spring and summer from 1982 to 1999. From the higher resolution MODIS NDVI data analysis, during 2001–2013, the lower regression slope values were mainly distributed in the river valley (the area of lower elevation), whereas the higher values pixels were located in the northern LRR (the area of higher elevation). In addition, the annual NDVI correlated significantly with temperature and precipitation during the study period. Temperature is a more significant factor influencing grassland change than precipitation in spring and autumn. However, the precipitation with the time lag effect is more significantly correlated with NDVI during the growing season (from May to October). The results of this project will help to monitor regional vegetation changes, understand the impact of climate change, and better manage the economically, environmentally and culturally significant grasslands of the LRR.

scholarly journals Analysis of meteorological variations on wheat yield and its estimation using remotely sensed data. A case study of selected districts of Punjab Province, Pakistan (2001-14)

2017 ◽  
Vol 12 (3) ◽  
Author(s):  
Rafia Mumtaz ◽  
Shahbaz Baig ◽  
Iram Fatima
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Crop Yield ◽  
Vegetation Index ◽  
Wheat Yield ◽  
Least Square ◽  
Wheat Crop ◽  
Main Challenge ◽  
Normalised Difference Vegetation Index ◽  
The Impact

Land management for crop production is an essential human activity that supports life on Earth. The main challenge to be faced by the agriculture sector in coming years is to feed the rapidly growing population while maintaining the key resources such as soil fertility, efficient land use, and water. Climate change is also a critical factor that impacts agricultural production. Among others, a major effect of climate change is the potential alterations in the growth cycle of crops which would likely lead to a decline in the agricultural output. Due to the increasing demand for proper agricultural management, this study explores the effects of meteorological variation on wheat yield in Chakwal and Faisalabad districts of Punjab, Pakistan and used normalised difference vegetation index (NDVI) as a predictor for yield estimates. For NDVI data (2001-14), the NDVI product of Moderate Resolution Imaging spectrometer (MODIS) 16-day composites data has been used. The crop area mapping has been realised by classifying the satellite data into different land use/land covers using iterative self-organising (ISO) data clustering. The land cover for the wheat crop was mapped using a crop calendar. The relation of crop yield with NDVI and the impact of meteorological parameters on wheat growth and its yield has been analysed at various development stages. A strong correlation of rainfall and temperature was found with NDVI data, which determined NDVI as a strong predictor of yield estimation. The wheat yield estimates were obtained by linearly regressing the reported crop yield against the time series of MODIS NDVI profiles. The wheat NDVI profiles have shown a parabolic pattern across the growing season, therefore parabolic least square fit (LSF) has been applied prior to linear regression. The coefficients of determination (<em>R</em><sup>2</sup>) between the reported and estimated yield was found to be 0.88 and 0.73, respectively, for Chakwal and Faisalabad. This indicates that the method is capable of providing yield estimates with competitive accuracies prior to crop harvest, which can significantly aid the policy guidance and contributes to better and timely decisions.

scholarly journals Diagnosing the impacts of permafrost on catchment hydrology: field measurements and model experiments in a mountainous catchment in western China

2021 ◽  
Author(s):  
Hongkai Gao ◽  
Chuntan Han ◽  
Rensheng Chen ◽  
Zijing Feng ◽  
Kang Wang ◽  
...  
Keyword(s):  
Climate Change ◽  
Landscape Heterogeneity ◽  
Measurement Data ◽  
Field Measurements ◽  
Western China ◽  
Catchment Hydrology ◽  
Catchment Scale ◽  
Streamflow Response ◽  
The Impact ◽  
Permafrost Regions

Abstract. Increased attention directed at permafrost hydrology has been prompted by climate change. In spite of an increasing number of field measurements and modeling studies, the impacts of permafrost on hydrological processes at the catchment scale are still unclear. Permafrost hydrology models at the catchment scale were mostly developed based on a “bottom-up” approach, hence by aggregating prior knowledge at the spot/field scales. In this study, we followed a “top-down” approach to learn from field measurement data to understand permafrost hydrology at the catchment scale. In particular, we used a stepwise model development approach to examine the impact of permafrost on streamflow response in the Hulu catchment in western China. We started from a simple lumped model (FLEX-L), and step-wisely included additional complexity by accounting for topography (i.e. FLEX-D) and landscape heterogeneity (i.e. FLEX-Topo). The final FLEX-Topo model, was then analyzed using a dynamic identifiability analysis (DYNIA) to investigate parameters’ temporal variation. By enabling temporal dynamics on several parameters, we diagnosed the physical relationships between parameter variation and permafrost impacts. We found that in the Hulu catchment: 1) the improvement associated to the model modifications suggest that topography and landscape heterogeneity are dominant controls on catchment response; 2) baseflow recession in permafrost regions is the result of a linear reservoir, and slower than non-permafrost regions; 3) parameters variation infers seasonally non-stationary precipitation-runoff relationships in permafrost catchment; 4) permafrost impacts on streamflow response mostly at the beginning of the melting season; 5) allowing the temporal variations of frozen soil related parameters, i.e. the unsaturated storage capacity and the splitter of fast and slow streamflow, improved model performance. Our findings provide new insights on the impact of permafrost on catchment hydrology in vast mountain regions of western China. More generally, they help to understand the effect of climate change on permafrost hydrology.

scholarly journals The Warming Tibetan Plateau improves winter air quality in the Sichuan Basin, China

2020 ◽  
Author(s):  
Shuyu Zhao ◽  
Tian Feng ◽  
Xuexi Tie ◽  
Zebin Wang
Keyword(s):  
Climate Change ◽  
Air Pollution ◽  
Air Quality ◽  
Tibetan Plateau ◽  
Sichuan Basin ◽  
The Tibetan Plateau ◽  
Aerosol Formation ◽  
Warming Rate ◽  
The Sichuan Basin ◽  
The Impact

Abstract. Impacts of global climate change on the occurrence and development of air pollution have attracted more attentions. This study investigates impacts of the warming Tibetan Plateau on air quality in the Sichuan Basin. Meteorological observations and ERA-interim reanalysis data reveal that the Tibetan Plateau has been rapidly warming during the last 40 years (1979–2017), particularly in winter when the warming rate is approximately twice as much as the annual warming rate. Since 2013, the winter temperature over the plateau has even risen by 2 °C. Here, we use the WRF-CHEM model to assess the impact of the 2 °C warming on air quality in the Sichuan Basin. The model results show that the 2 °C warming causes an increase in the Planetary Boundary Layer (PBL) height and a decrease in the relative humidity (RH) in the basin. The elevated PBL height strengthens vertical diffusion of PM2.5, while the decreased RH significantly reduces secondary aerosol formation. Overall, PM2.5 concentration is reduced by 17.5 % (~ 25.1 μg m−3), of which the reduction in primary and secondary aerosols is 5.4 μg m−3 and 19.7 μg m−3, respectively. These results reveal that the recent warming plateau has improved air quality in the basin, to some certain extent, mitigating the air pollution therein. Nevertheless, climate system is particularly complicated, and more studies are needed to demonstrate the impact of climate change on air quality in the downstream regions as the plateau is likely to continue warming.

Decoupling the effect of the forest pest damage from the effects of meteorology using space-borne remote sensing and modelling

2021 ◽  
Author(s):  
Hrvoje Marjanovic ◽  
Aniko Kern
Keyword(s):  
Climate Change ◽  
Greenhouse Gas Emission ◽  
Carbon Sink ◽  
Meteorological Data ◽  
Environmental Data ◽  
Forest Pest ◽  
Modis Ndvi ◽  
Pest Damage ◽  
Lace Bug ◽  
The Impact

&lt;p&gt;The EU&amp;#8217;s climate change mitigation plans of 55% reduction in greenhouse gas emission by 2030 and reaching climate-neutrality by 2050 rely significantly on maintaining and increasing the carbon sink in European forests. In addition to direct consequences of climate change and ageing forests, this sink is becoming threatened by the new invasive forest pests which can decrease forest productivity. The Oak lace bug (Corythucha arcuata, Say 1832), native to North America, is a new invasive species rapidly spreading since 2012 from the east to the west of Europe. The oak lace bug (OLB) after establishment in an area shows no signs of retreating and negatively affects the tree photosynthetic capacity by feeding on leaf sap. The consequences of such new and persistent pest, which are not imminently life-threatening to trees but are long-lasting, have yet to be determined.&lt;/p&gt;&lt;p&gt;In our study, we used remotely sensed MODIS NDVI (MOD09Q1), gridded meteorological data (FORESEE), soil water content (ERA5 Land), available national forest management and land cover data to develop methods for detecting the presence and the assessment of the impact of the OLB. The study was focused on the modelling tools to decouple the effects caused by the environmental variables from the pest damage on the measured NDVI. To this different NDVI models were created based on the Least Absolute Shrinkage and Selection Operator (LASSO) technique and the most influential periods, to support accurate forest pest detection. We investigated forests containing oak trees in the transboundary area of Hungary and Croatia. The results show that the LASSO technique is a promising tool in NDVI modelling using meteorological and environmental data. The performance of the models based on the Most Influential Periods (MIP) of the different variables showed just slightly worse results, although their application is more intuitive. In the case of the OLB, the damage assessment results with the LASSO and MIP methods showed that the pest-caused NDVI decrease in pure oak stands during the late August to early September period can be as much as -14.5% and -15.6%, respectively.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Asknowledgments:&lt;/p&gt;&lt;p&gt;The research has been supported by the Croatian Science Foundation project MODFLUX (HRZZ IP-2019-04-6325), by the Hungarian Scientific Research Fund (OTKA FK-128709) and by the J&amp;#225;nos Bolyai Research Scholarship of the Hungarian Academy of Sciences.&lt;/p&gt;

The impact of climate change on runoff in the southeastern Tibetan Plateau

2013 ◽  
Vol 505 ◽  
pp. 188-201 ◽  
Author(s):  
Fapeng Li ◽  
Yongqiang Zhang ◽  
Zongxue Xu ◽  
Jin Teng ◽  
Changming Liu ◽  
...  
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Impact Of Climate Change ◽  
Southeastern Tibetan Plateau ◽  
The Impact

scholarly journals Study of the variation trend, abrupt behavior and relationship between climate and planting structure in a cold region of China: a case study of Heilongjiang Province

2017 ◽  
Vol 8 (3) ◽  
pp. 510-523 ◽  
Author(s):  
Wei Pei ◽  
Qiang Fu ◽  
Dong Liu ◽  
Tianxiao Li ◽  
Kun Cheng ◽  
...  
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Heilongjiang Province ◽  
Upward Trend ◽  
Cold Regions ◽  
Variation Trend ◽  
Significant Upward Trend ◽  
Abrupt Changes ◽  
The Relationship

Climate change has changed planting structure greatly in cold regions. Studies are needed that understand the relationship between climate change and agriculture in cold regions and to serve as references for studies of the impact of climate change on agriculture in similar areas. This paper uses Heilongjiang Province as a case study; seven test methods and mutual information were used to analyse the variation trend, abrupt changes and relationship between climate and planting structure. The following was concluded. (1) The precipitation trend was not significant; temperature showed a significant upward trend, the minimum temperature showed the sharpest increase. (2) The proportion of area planted in rice and maize showed a significant upward trend. The trend of rice was the most pronounced, the trend of wheat significantly decreased. (3) Abrupt changes in temperature occurred in the 1980s; abrupt changes in wheat were concentrated at the end of the 1990s. (4) The relationship between temperature and planting structure was stronger than that of precipitation, and the relationship between minimum temperature and planting structure was stronger than that of maximum temperature. The results show that temperature variables, especially minimum temperature, are the main factors affecting the change in planting structure in cold regions.

scholarly journals Quantifying Changes in Plant Species Diversity in a Savanna Ecosystem Through Observed and Remotely Sensed Data

2020 ◽  
Vol 12 (6) ◽  
pp. 2345
Author(s):  
Lazarus Chapungu ◽  
Luxon Nhamo ◽  
Roberto Cazzolla Gatti ◽  
Munyaradzi Chitakira
Keyword(s):  
Climate Change ◽  
Species Diversity ◽  
Plant Species ◽  
Vegetation Index ◽  
Shannon Index ◽  
Plant Species Diversity ◽  
Impact Of Climate Change ◽  
Normalised Difference Vegetation Index ◽  
The Impact ◽  
Index Of Diversity

This study examined the impact of climate change on plant species diversity of a savanna ecosystem, through an assessment of climatic trends over a period of forty years (1974–2014) using Masvingo Province, Zimbabwe, as a case study. The normalised difference vegetation index (NDVI) was used as a proxy for plant species diversity to cover for the absence of long-term historical plant diversity data. Observed precipitation and temperature data collected over the review period were compared with the trends in NDVI to understand the impact of climate change on plant species diversity over time. The nonaligned block sampling design was used as the sampling framework, from which 198 sampling plots were identified. Data sources included satellite images, field measurements, and direct observations. Temperature and precipitation had significant (p < 0.05) trends over the period under study. However, the trend for seasonal total precipitation was not significant but declining. Significant correlations (p < 0.001) were identified between various climate variables and the Shannon index of diversity. NDVI was also significantly correlated to the Shannon index of diversity. The declining trend of plant species in savanna ecosystems is directly linked to the decreasing precipitation and increasing temperatures.

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