Development of spatially explicit emission scenario from land-use change and biomass burning for the input data of climate projection

Abstract. In order to estimate a country-scale soil organic carbon (SOC) stock change in agricultural lands in Japan, while taking into account the effect of land-use changes, climate, different agricultural activities and the nature of soils, a spatially explicit model simulation system was developed using Rothamsted Carbon Model (RothC) with an integration of spatial and temporal inventories. Simulation was run from 1970 to 2008 with historical inventories. Simulated SOC stock was compared with observations in a nation-wide stationary monitoring program conducted during 1979–1998. Historical land-use change, characterized by a large decline in the area of paddy fields as well as a small but continuous decline in the area of orchards, occurred along with a relatively large increase in upland crop fields, unmanaged grasslands, and settlements (i.e. conversion of agricultural fields due to urbanization or abandoning). Results of the simulation on SOC stock change under varying land-use change indicated that land-use conversion from agricultural fields to settlements or other lands, as well as that from paddy fields to croplands have likely been an increasing source of CO2 emission, due to the reduction of organic carbon input to soils and the enhancement of SOC decomposition through transition of soil environment from anaerobic to aerobic conditions. The area-weighted mean concentrations of the simulated SOC stocks calculated for major soil groups under paddy fields and upland crop fields were comparable to those observed in the monitoring. Whereas in orchards, the simulated SOC stocks were underestimated. As the results of simulation indicated that SOC stock change under managed grasslands and settlements has been likely a major sink and source of CO2 emission at country-scale, respectively, validation of SOC stock change under these land-use types, which could not have been accomplished due to limited availability or a lack of measurement, remains a forthcoming challenge.

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Commercial and industrial land use change, job decentralization and growth controls: a spatially explicit analysis

Journal of Land Use Science ◽

10.1080/17474230903437162 ◽

2010 ◽

Vol 5 (1) ◽

pp. 45-66 ◽

Cited By ~ 9

Author(s):

Michail Fragkias ◽

Jacqueline Geoghegan

Keyword(s):

Land Use ◽

Land Use Change ◽

Spatially Explicit ◽

Industrial Land ◽

Industrial Land Use ◽

Explicit Analysis ◽

Growth Controls

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Deriving spatially explicit water uses from land use change modelling results in four river basins across Europe

The Science of The Total Environment ◽

10.1016/j.scitotenv.2018.02.051 ◽

2018 ◽

Vol 628-629 ◽

pp. 1079-1097 ◽

Cited By ~ 4

Author(s):

Verena Huber García ◽

Swen Meyer ◽

Kasper Kok ◽

Peter Verweij ◽

Ralf Ludwig

Keyword(s):

Land Use ◽

Land Use Change ◽

River Basins ◽

Spatially Explicit ◽

Explicit Water ◽

Water Uses

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Land Use Change from Biofuels Derived from Forest Residue: A Case of Washington State

Economics Research International ◽

10.1155/2013/836823 ◽

2013 ◽

Vol 2013 ◽

pp. 1-12 ◽

Cited By ~ 2

Author(s):

Daniel Brent ◽

Sergey Rabotyagov

Keyword(s):

Land Use ◽

Land Use Change ◽

The United States ◽

Washington State ◽

Spatially Explicit ◽

Biofuel Policy ◽

Indirect Land Use Change ◽

Forest Residue ◽

Net Returns ◽

Processing Plants

Biofuel policy in the United States is transitioning away from corn towards second-generation biofuels in part because of the debate over environmental damages from indirect land use change. We combine a spatially explicit parcel level model for land use change in Washington State with simulations for biofuel policy aimed at utilizing forest residue as feedstock. Using a spatially explicit model provides greater precision in measuring net returns to forestland and development and indicates which areas will be most impacted by biofuel policy. The effect of policy is simulated via scenarios of increasing net returns to forestry and of siting feedstock-processing plants. Our results suggest that forestland will increase from such a policy, leading to a net reduction in atmospheric carbon from indirect land use change. This is in contrast to the experience of corn ethanol where the change in carbon emissions is potentially positive and large in magnitude.

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SPATIALLY EXPLICIT HYDROLOGIC MODELING OF LAND USE CHANGE

JAWRA Journal of the American Water Resources Association ◽

10.1111/j.1752-1688.2002.tb01548.x ◽

2002 ◽

Vol 38 (1) ◽

pp. 241-252 ◽

Cited By ~ 32

Author(s):

Glenn E. Moglen ◽

R. Edward Beighley

Keyword(s):

Land Use ◽

Land Use Change ◽

Hydrologic Modeling ◽

Spatially Explicit

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An open and extensible framework for spatially explicit land use change modelling in R: the lulccR package (0.1.0)

Geoscientific Model Development Discussions ◽

10.5194/gmdd-8-3359-2015 ◽

2015 ◽

Vol 8 (4) ◽

pp. 3359-3402 ◽

Cited By ~ 2

Author(s):

S. Moulds ◽

W. Buytaert ◽

A. Mijic

Keyword(s):

Land Use ◽

Land Use Change ◽

Global Environmental Change ◽

Model Development ◽

Spatially Explicit ◽

Change Models ◽

R Programming Language ◽

Global Environmental ◽

R Programming ◽

Scientific Results

Abstract. Land use change has important consequences for biodiversity and the sustainability of ecosystem services, as well as for global environmental change. Spatially explicit land use change models improve our understanding of the processes driving change and make predictions about the quantity and location of future and past change. Here we present the lulccR package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of different models; (3) different aspects of the modelling procedure must be performed in different environments because existing applications usually only perform the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the widely used CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a dataset included with the package. It is envisaged that lulccR will enable future model development and comparison within an open environment.

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Combined effects of predicted climate and land use changes on future hydrological droughts in the Luanhe River basin, China

10.21203/rs.3.rs-162130/v1 ◽

2021 ◽

Author(s):

Xu Chen ◽

Ruiguang Han ◽

Yongjie Wang

Keyword(s):

Climate Change ◽

Land Use ◽

Land Use Change ◽

River Basin ◽

Emission Scenario ◽

Land Use Changes ◽

Model Parameters ◽

Baseline Scenario ◽

Luanhe River Basin ◽

Hydrological Droughts

Abstract Drought can be impacted by both climate change and land use change in different ways. Thus, in order to predict future drought conditions, hydrological simulations as an ideal means, can be used to account for both projected climate change and projected land use change. In this study, projected climate and land use changes were integrated with the SWAT (Soil and Water Assessment Tool) model to estimate the combined impact of climate and land use projections on hydrological droughts in the Luanhe River basin. We presented that the measured runoff and the remote sensing inversion of soil water content were simultaneously used to validate the model to ensure the reliability of model parameters. Following the calibration and validation, the SWAT model was forced with downscaled precipitation and temperature outputs from a suite of nine Global Climate Models (GCMs) based on the CMIP5, corresponding to three different representative concentration pathways (RCP 2.6, RCP 4.5 and 8.5) for three distinct time periods: 2011–2040, 2041–2070 and 2071–2100, referred to as early-century, mid-century and late-century, respectively, and the land use predicted by CA-Markov model in the same future periods. Hydrological droughts were quantified using the Standardized Runoff Index (SRI). Compared to the baseline scenario (1961–1990), mild drought occurred more frequently during the next three periods (except the 2080s under the RCP2.6 emission scenario). Under the RCP8.5 emission scenario, the probability of severe drought or above occurring in the 2080s increased, the duration prolonged and the severity increased. Under the RCP2.6 scenario, the upper central region of the Luanhe river in the 2020s and upper reaches of the Luanhe river in the 2080s, were more likely to suffer extreme drought events. And under the RCP8.5 scenario, the middle and lower Luanhe river in the 2080s, were more likely to suffer these conditions.

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New land use change scenarios for Brazil: refining global SSPs with a regional spatially-explicit allocation model

10.1101/2021.08.12.456156 ◽

2021 ◽

Author(s):

Francisco Gilney Silva Bezerra ◽

Celso Von Randow ◽

Talita Oliveira Assis ◽

Karine Rocha Aguiar Bezerra ◽

Graciela Tejada ◽

...

Keyword(s):

Land Use ◽

Land Use Change ◽

Forest Restoration ◽

Global Climate ◽

Global Analysis ◽

Spatially Explicit ◽

Surface Model ◽

Modeling Framework ◽

Allocation Model ◽

The Future

The future of land use and cover change in Brazil, in particular due to deforestation and forest restoration processes, is critical for the future of global climate and biodiversity, given the richness of its five biomes. These changes in Brazil depend on the interlink between global factors, due to its role as one of the main exporters of commodities in the world, and the national to local institutional, socioeconomic and biophysical contexts. Aiming to develop scenarios that consider the balance between global and local factors, a new set of land use change scenarios for Brazil were developed, aligned with the global structure Shared Socio-Economic Pathways (SSPs) and Representative Concentration Pathway (RCPs) developed by the global change research community. The narratives of the new scenarios align with SSP1/RCP 1.9, SSP2/RCP 4.5, and SSP3/RCP 7.0. The scenarios were developed combining the LuccME spatially explicit land change allocation modeling framework and the INLAND surface model to incorporate the climatic variables in water deficit. Based on detailed biophysical, socio-economic and institutional factors for each biome in Brazil, we have created spatially-explicit scenarios until 2050, considering the following classes: forest vegetation, grassland vegetation, planted pasture, agriculture, mosaic of small land uses, and forestry. The results aim at regionally detailing global models and could be used both regionally to support decision-making, but also to enrich global analysis.

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