scholarly journals The Effect of Climate and Technological Uncertainty in Crop Yields on the Optimal Path of Global Land Use

2014 ◽  
Author(s):  
Yongyang Cai ◽  
Jevgenijs Steinbuks ◽  
Joshua Elliott ◽  
Thomas W. Hertel
Keyword(s):  
Land Use ◽  
Crop Yields ◽  
Optimal Path ◽  
Technological Uncertainty ◽  
Global Land

scholarly journals Landscape controls on riverine export of dissolved organic carbon from Great Britain

2021 ◽  
Author(s):  
Jennifer L. Williamson ◽  
Andrew Tye ◽  
Dan J. Lapworth ◽  
Don Monteith ◽  
Richard Sanders ◽  
...  
Keyword(s):  
Land Use ◽  
Great Britain ◽  
Population Density ◽  
Organic Carbon ◽  
Dissolved Organic Carbon ◽  
Forest Cover ◽  
River Systems ◽  
C Cycle ◽  
Global Land ◽  
Doc Export

AbstractThe dissolved organic carbon (DOC) export from land to ocean via rivers is a significant term in the global C cycle, and has been modified in many areas by human activity. DOC exports from large global rivers are fairly well quantified, but those from smaller river systems, including those draining oceanic regions, are generally under-represented in global syntheses. Given that these regions typically have high runoff and high peat cover, they may exert a disproportionate influence on the global land–ocean DOC export. Here we describe a comprehensive new assessment of the annual riverine DOC export to estuaries across the island of Great Britain (GB), which spans the latitude range 50–60° N with strong spatial gradients of topography, soils, rainfall, land use and population density. DOC yields (export per unit area) were positively related to and best predicted by rainfall, peat extent and forest cover, but relatively insensitive to population density or agricultural development. Based on an empirical relationship with land use and rainfall we estimate that the DOC export from the GB land area to the freshwater-seawater interface was 1.15 Tg C year−1 in 2017. The average yield for GB rivers is 5.04 g C m−2 year−1, higher than most of the world’s major rivers, including those of the humid tropics and Arctic, supporting the conclusion that under-representation of smaller river systems draining peat-rich areas could lead to under-estimation of the global land–ocean DOC export. The main anthropogenic factor influencing the spatial distribution of GB DOC exports appears to be upland conifer plantation forestry, which is estimated to have raised the overall DOC export by 0.168 Tg C year−1. This is equivalent to 15% of the estimated current rate of net CO2 uptake by British forests. With the UK and many other countries seeking to expand plantation forest cover for climate change mitigation, this ‘leak in the ecosystem’ should be incorporated in future assessments of the CO2 sequestration potential of forest planting strategies.

Conference and workshop on modelling global land use implications in the environmental assessment of biofuels

2008 ◽  
Vol 13 (3) ◽  
pp. 178-183 ◽  
Author(s):  
Jesper Kløverpris ◽  
Henrik Wenzel ◽  
Martin Banse ◽  
Llorenç Milà i Canals ◽  
Anette Reenberg
Keyword(s):  
Land Use ◽  
Environmental Assessment ◽  
Global Land

Response of global land evapotranspiration to climate change, elevated CO2, and land use change

2021 ◽  
Vol 311 ◽  
pp. 108663
Author(s):  
Jianyu Liu ◽  
Yuanyuan You ◽  
Jianfeng Li ◽  
Stephen Sitch ◽  
Xihui Gu ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Elevated Co2 ◽  
Global Land

Estimates of the Earth surface influence on the accuracy of numerical prediction of air temperature in Belarus using the WRF model

2021 ◽  
Vol 4 ◽  
pp. 50-68
Author(s):  
S.А. Lysenko ◽  
◽  
P.О. Zaiko ◽  
Keyword(s):  
Land Use ◽  
Air Temperature ◽  
Numerical Weather Prediction ◽  
Land Surface ◽  
Lead Time ◽  
Weather Prediction ◽  
Wrf Model ◽  
Surface Model ◽  
Numerical Weather ◽  
Global Land

The spatial structure of land use and biophysical characteristics of land surface (albedo, leaf index, and vegetation cover) are updated using the GLASS (Global Land Surface Satellite) and GLC2019 (Global Land Cover, 2019) modern satellite databases for mesoscale numerical weather prediction with the WRF model for the territory of Belarus. The series of WRF-based numerical experiments was performed to verify the influence of the updated characteristics on the forecast quality for some difficult to predict winter cases. The model was initialized by the GFS (Global Forecast System, NCEP) global numerical weather prediction model. It is shown that the use of high-resolution land use data in the WRF and the consideration of the new albedo and leaf index distribution over the territory of Belarus can reduce the root-mean-square error (RMSE) of short-range (to 48 hours) forecasts of surface air temperature by 16–33% as compared to the GFS. The RMSE of the temperature forecast for the weather stations in Belarus for a forecast lead time of 12, 24, 36, and 48 hours decreased on average by 0.40°С (19%), 0.35°С (10%), 0.68°С (23%), and 0.56°С (15%), respectively. The most significant decrease in RMSE of the numerical forecast of temperature (up to 2.1 °С) was obtained for the daytime (for a lead time of 12 and 36 hours), when positive feedbacks between albedo and temperature of the land surface are manifested most. Keywords: numerical weather prediction, WRF, digital land surface model, albedo, leaf area index, forecast model validation

Evaluation of global land use/land cover products for hydrologic simulation in the Upper Yom River Basin, Thailand

2020 ◽  
Vol 708 ◽  
pp. 135148 ◽  
Author(s):  
Chirayut Chirachawala ◽  
Sangam Shrestha ◽  
Mukand S. Babel ◽  
Salvatore G.P. Virdis ◽  
Supattana Wichakul
Keyword(s):  
Land Use ◽  
Land Cover ◽  
River Basin ◽  
Land Use Land Cover ◽  
Hydrologic Simulation ◽  
Global Land
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