Multi-scenario simulation of land use/land cover change and water yield evaluation coupled with the GMOP-PLUS-InVEST model: A case study of the Nansi Lake Basin in China
“…For example, Qiang Huang et al focus on the hollowing out of rural settlements and try to explore a layout that reduces the loss of agricultural land, protects the ecological environment, and improves the conditions of agricultural production and the living standards of rural villagers 51 . Yingchun Liu et al focus on how to promote Watershed protection and land use layout optimization in Southwest Lake Basin, China 52 . Figure 6 Situational simulation of Tongling’s land.…”
Optimizing the spatial layout of the national territory is crucial for realizing the transformation and development of resource-oriented cities in the context of high-quality development in the new period. This paper takes Tongling City as a case study, based on the analysis of the historical development foundation, then uses the SD-FLUS comprehensive model to carry out a systematic analysis of the transformation in five dimensions of economy, society, population, science and technology, resources and environment, and discusses the optimization of spatial pattern under the contextual simulation. The conclusions are as follows: ① The hierarchical framework of “system-indicator-element” is not only internally interconnected, but also inextricably linked with the relationship between the various categories of the land use system. ② Decrease of cropland, forest, water, grassland, and barren decreases from the economic development, social progress, and comprehensive development, and there is a small increase in the area under the scenario of resource and environmental protection, and the direction of the change of the impervious is in the opposite direction. ③ Cultivated land is retained in situ and concentrated to a small extent, forested land is reduced to a small extent while the status quo is maintained, and the Yangtze River water system will be retained and protected to a large extent, but part of the waters of Zongyang County will give way to the expansion of construction land under the development objectives of the new county. Building land will be expanded and extended to the northeast in the original site area, while the southwest corner of the original county center will be expanded to some extent in Zongyang County to promote the county’s economic development.
“…For example, Qiang Huang et al focus on the hollowing out of rural settlements and try to explore a layout that reduces the loss of agricultural land, protects the ecological environment, and improves the conditions of agricultural production and the living standards of rural villagers 51 . Yingchun Liu et al focus on how to promote Watershed protection and land use layout optimization in Southwest Lake Basin, China 52 . Figure 6 Situational simulation of Tongling’s land.…”
Optimizing the spatial layout of the national territory is crucial for realizing the transformation and development of resource-oriented cities in the context of high-quality development in the new period. This paper takes Tongling City as a case study, based on the analysis of the historical development foundation, then uses the SD-FLUS comprehensive model to carry out a systematic analysis of the transformation in five dimensions of economy, society, population, science and technology, resources and environment, and discusses the optimization of spatial pattern under the contextual simulation. The conclusions are as follows: ① The hierarchical framework of “system-indicator-element” is not only internally interconnected, but also inextricably linked with the relationship between the various categories of the land use system. ② Decrease of cropland, forest, water, grassland, and barren decreases from the economic development, social progress, and comprehensive development, and there is a small increase in the area under the scenario of resource and environmental protection, and the direction of the change of the impervious is in the opposite direction. ③ Cultivated land is retained in situ and concentrated to a small extent, forested land is reduced to a small extent while the status quo is maintained, and the Yangtze River water system will be retained and protected to a large extent, but part of the waters of Zongyang County will give way to the expansion of construction land under the development objectives of the new county. Building land will be expanded and extended to the northeast in the original site area, while the southwest corner of the original county center will be expanded to some extent in Zongyang County to promote the county’s economic development.
“…The selection of the three scenarios in this study was based on the future development plan outlined in the "Development Plan for the Urban Agglomeration on the North Slope of Tianshan Mountain", which carried a degree of subjectivity [74]. Consequently, the three scenarios chosen for prediction represent extreme ends of the spectrum: business-as-vvusual development, the pursuit of maximization of environmental benefits under the constraints of the development plan, and the maximization of economic growth.…”
The serious problem of soil erosion not only has a profound impact on people’s lives but also results in a series of ecological and environmental challenges. To determine the impact of changes in land use type on soil erosion in the urban agglomeration on the northern slopes of the Tianshan Mountains, this study commences by employing the InVEST-SDR (integrated valuation of ecosystem services and tradeoffs–sediment delivery ratio) model to calculate soil erosion levels spanning from 2000 to 2020. Subsequently, it forecasts land use and land cover (LULC) conditions for the year 2030 under three scenarios: Q1 (natural development), Q2 (ecological protection), and Q3 (economic priority). This projection is accomplished through the integration of a coupled Markov chain and multi-objective planning model (MOP) alongside patch-generating land use simulation (PLUS) models. Ultimately, based on these outcomes, the study predicts soil erosion levels for the year 2030. There has been a consistent decline in soil erosion from 2000 to 2020 with high-intensity erosion concentrated in the Tianshan Mountain region. Grasslands, glaciers, and permafrost are identified as the most erosion-prone land types in the study area, with forests exhibiting the highest capacity for soil retention. Converting from grassland and barren land to forest within the same area results in a substantial reduction in soil erosion, specifically by 27.3% and 46.3%, respectively. Furthermore, the transformation from barren land to grassland also leads to a noteworthy 19% decrease in soil erosion. Over the past two decades, the study area has witnessed a significant decline in the area of grasslands, with a notable shift towards barren and impervious surfaces due to economic development and mining activities. The three predicted scenarios depict significant expansion towards barren land, grassland, and impervious area, respectively. Soil erosion decreases under different shared socio-economic pathway (SSP) scenarios relative to 2020. There is an increase in soil erosion in the Q1 scenario and in the Q3 scenario, whereas the amount of soil erosion in the Q2 scenario exhibits a continued decrease when only the effect of land change on soil erosion is considered. Persistently rapid economic development can exacerbate soil erosion problems, underscoring the need to find a balance between economic growth and ecological conservation. As economic expansion slows down, greater emphasis should be placed on environmental protection to maintain ecological stability.
“…This model develops the LEAS module and CARS module on the basis of the Markov module's land use demand quantity prediction. This model can not only screen suitable driving factors [25], but also set multi-scenario simulation predictions [26][27][28].…”
With regard to the aims of achieving the “Dual Carbon” goal and addressing the significant greenhouse gas emissions caused by urban expansion, there has been a growing emphasis on spatial research and the prediction of urban carbon emissions. This article examines land use data from 2000 to 2020 and combines Grid and the PLUS model to predict carbon emissions in 2030 through a multi-scenario simulation. The research findings indicate the following: (1) Between 2000 and 2020, construction land increased by 95.83%, with carbon emissions also increasing. (2) By 2030, for the NDS (natural development scenario), carbon emissions are expected to peak at 6012.87 × 104 t. Regarding the ratio obtained through the EDS (economic development scenario), construction land is projected to grow to 3990.72 km2, with expected emissions of 6863.29 × 104 t. For the LCS (low-carbon scenario), the “carbon peak” is expected to be reached before 2030. (3) The intensity of carbon emissions decreases as the city size increases. (4) The shift of the center of carbon emission intensity and the center of construction land all indicate movement towards the southeast. Studying the trends of regional land use change and the patterns of land use carbon emissions is beneficial for optimizing the land use structure, thereby enabling us to achieve low-carbon emission reductions and sustainable urban development.
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