Impact of Decentralization and Rail Network Extension on Future Traffic in the Bangkok Metropolitan Region

In many large cities in developing countries, investments in transportation infrastructure are insufficient for the growing population, resulting in chronic traffic congestion and overcrowding. The urban population of developing countries is expected to increase further toward the middle of this century, and urban planning and transportation policies that foresee future population changes and economic growth are necessary to make these cities more sustainable. Bangkok is one of the most congested metropolitan areas in the world, and transport projects such as the extension of the public transportation system are being implemented. However, due to the monocentric urban structure, both road and rail traffic is extremely congested during peak hours, which impedes some economic activities and personal interaction. In this study, we simulate the impact of urban and transportation measures in Bangkok from today to 2050. In addition to the expansion of the planned rail transit network, we evaluate the effects of a land use scenario in which sub-centers are established to develop a polycentric urban structure. The impact of alternative zoning and transportation policies and projects in Bangkok is discussed. Although this study is focused on Bangkok, the findings are assumed to be transferable to other large cities in developing countries.

Improving an Urban Cellular Automata Model Based on Auto-Calibrated and Trend-Adjusted Neighborhood

Accurately simulating urban expansion is of great significance for promoting sustainable urban development. The calculation of neighborhood effects is an important factor that affects the accuracy of urban expansion models. The purpose of this study is to improve the calculation of neighborhood effects in an urban expansion model, i.e., the land-use scenario dynamics-urban (LUSD-urban) model, by integrating the trend-adjusted neighborhood algorithm and the automatic rule detection procedure. Taking eight sample cities in China as examples, we evaluated the accuracies of the original model and the improved model. We found that the improved model can increase the accuracy of simulated urban expansion in terms of both the degree of spatial matching and the similarity of urban form. The increase of accuracy can be attributed to such integration comprehensively considers the effects of historical urban expansion trends and the influences of neighborhoods at different scales. Therefore, the improved model in this study can be widely used to simulate the process of urban expansion in different regions.

Simulation of Biocapacity and Spatial-Temporal Evolution Analysis of Loess Plateau in Northern Shaanxi Based on the CA–Markov Model

Biocapacity evaluation is an important part of sustainable development research, but quantitative and spatial evaluation and future scenario analysis still have model and methodological difficulties. Based on the high-resolution Globeland30 dataset, the authors analyzed the characteristics of land use/cover changes of the Loess Plateau in Northern Shaanxi from 2000 to 2020. Then, comprehensively considering the driving factors of social development, topography, climatic conditions, and spatial distance, the logistic regression method and the CA–Markov model were used to simulate the land use scenario in 2030. Finally, the biocapacity model was used to describe the spatial distribution and spatial-temporal evolution of the regional biocapacity in detail. The results showed the following: (1) Biocapacity was jointly restricted by land use types, yield factors, and equivalence factors. The high values were mainly distributed in the riparian areas of the central and eastern regions, the ridges and valleys of the central and western regions, and the farmland patches of the southern valleys; the median values were mainly distributed in the forest of the southern mountains; the low values were mainly distributed in the grassland and unused land in the hilly and gully areas of the central and northern regions. (2) The biocapacity of Loess Plateau in Northern Shaanxi increased by 9.98% from 2000 to 2010, and decreased by 4.14% from 2010 to 2020, and the total amount remained stable. It is predicted that by 2030, the regional biocapacity will continue to increase by 0.03%, reaching 16.52 × 106 gha.

An examination of extreme floods, effects on land-use change and seasonality in the Lower St. Johns River Basin, Florida using HSPF and statistical methods

As population growth and urbanization are steadily rising, the need for dependable flood estimation techniques is crucial. This study evaluates extreme flood events in select sub-basins of the Lower St. Johns River in Florida, USA. The study summarizes work of a recent thesis and combines that work with new research regarding the effect of urbanization on the natural hydrologic processes and flood magnitudes in the watershed. Additionally, the effects of varying seasonality into the hydrologic modeling procedure are also investigated. This research focuses on determining the 10-, 25-, 50-, and 100-year return frequency flood flows in Julington Creek, Ortega River, and Pablo Creek of the Lower St. Johns River Basin in Florida, USA. The major findings of this research indicate that by implementing a range of flood estimation methods one can better describe the inherent uncertainty with traditional estimates. Also, the research showed that varying seasonality in the hydrologic modeling procedure does not result in vast differences in the resulting flood estimates. However, various land-use scenarios may produce simulated flood flows of greater magnitude – especially when a more urbanized land-use scenario is modeled.

Framework for Accounting Reference Levels for REDD+ in Tropical Forests: Case Study from Xishuangbanna, China

The United Nations’ expanded program for Reducing Emissions from Deforestation and Forest Degradation (REDD+) aims to mobilize capital from developed countries in order to reduce emissions from these sources while enhancing the removal of greenhouse gases (GHGs) by forests. To achieve this goal, an agreement between the Parties on reference levels (RLs) is critical. RLs have profound implications for the effectiveness of the program, its cost efficiency, and the distribution of REDD+ financing among countries. In this paper, we introduce a methodological framework for setting RLs for REDD+ applications in tropical forests in Xishuangbanna, China, by coupling the Good Practice Guidance on Land Use, Land Use Change, and Forestry of the Intergovernmental Panel on Climate Change and land use scenario modeling. We used two methods to verify the accuracy for the reliability of land classification. Firstly the accuracy reached 84.43%, 85.35%, and 82.68% in 1990, 2000, and 2010, respectively, based on high spatial resolution image by building a hybrid matrix. Then especially, the 2010 Globeland30 data was used as the standard to verify the forest land accuracy and the extraction accuracy reached 86.92% and 83.66% for area and location, respectively. Based on the historical land use maps, we identified that rubber plantations are the main contributor to forest loss in the region. Furthermore, in the business-as-usual scenario for the RLs, Xishuangbanna will lose 158,535 ha (158,535 × 104 m2) of forest area in next 20 years, resulting in approximately 0.23 million t (0.23 × 109 kg) CO2e emissions per year. Our framework can potentially increase the effectiveness of the REDD+ program in Xishuangbanna by accounting for a wider range of forest-controlled GHGs.

Adequacy assessment of an urban drainage system considering future land use and climate change scenario

Dhaka, the capital of Bangladesh, has been experiencing severe water-logging and urban flooding in the last few decades. In this paper, we estimate the peak storm runoff of Hatirjheel-Begunbari canal – the largest drainage system of the city – under different operational, land use and climate scenarios (2013, 2025 and 2040). Our method includes digital elevation model (DEM) reconditioning, watershed delineation, and development of future land use scenario. We apply HEC-RAS to check the adequacy of Begunbari canal cross-sections to carry peak runoff for the scenarios considered here. The Hatirjheel-Begunbari system is found to drain stormwater from ∼25% area of the city. Within the system, built-up areas are increasing linearly by 0.8 Km2/year, whereas water-body and wetlands are decreasing exponentially, which might increase the runoff coefficient by 11% in 2040 relative to 2013. Climate-induced change in rainfall intensity along with land-use change show three times higher runoff in 2040 than in 2013. Around 58% of canal cross-sections appear to be overflown at both banks while carrying a 5-year return period peak runoff under the 2013 scenario. For future scenarios, all sections seem to cause an overflow, which is alarming.

Evaluating the Impacts of Future Urban Expansion on Surface Runoff in an Alpine Basin by Coupling the LUSD-Urban and SCS-CN Models

Effective evaluations of the future urban expansion impacts (UEI) on surface runoff in alpine basins are full of challenges due to the lack of reliable methods. Our objective was to provide a new approach by coupling the Land Use Scenario Dynamics-urban (LUSD-urban) and Soil Conservation Service-Curve Number (SCS-CN) models to estimate the future UEI on surface runoff. Taking the Qinghaihu-Huangshui basin (QHB) in the Tibetan Plateau, China, as an example, we first applied the SCS-CN model to quantify the surface runoff in 2000 and 2018 and analyzed the changes in surface runoff. Next, we applied the LUSD-urban model to simulate urban expansion under five localized shared socioeconomic pathways (SSPs) from 2018 to 2050. Finally, we assessed the UEI on surface runoff in the QHB from 2018 to 2050. We found that coupling the LUSD-urban and SCS-CN models could effectually evaluate the future UEI on surface runoff. Compared with the combination of the Future Land Use Simulation (FLUS) and SCS-CN models, our method reduced the absolute evaluation errors from 3.40% and 11.78% to 0.18% and 4.23%, respectively. In addition, the results showed that future urban expansion will have severe impacts on surface runoff in the valley region. For example, as a result of urban expansion, the surface runoff in the Huangzhong, Xining, and Datong catchments will increase by 4.90–9.01%, 4.25–7.36%, and 2.33–3.95%, respectively. Therefore, we believe that the coupled model can be utilized to evaluate the future UEI on surface runoff in alpine basins. In addition, the local government should pay attention to flood risk prevention, especially in the valley region, and adopt reasonable urban planning with soft and hard adaptation measures to promote the sustainable development of alpine basins under rapid urban expansion.

Flood-reduction scenario based on land use in Kedurus river basin using SWAT hydrology model

The rapid growth population phenomenon has causes excessive land demand for residential and economic activity. Moreover, the rapid urbanization also increases the contribution of land constrains. Land conversion from conservation to cultivation uses affects the surface runoff volume that leads to flooding. According to these problems, it is necessary to take steps to control flood in Kedurus Watershed. One of the proper urban development concept is the Water Sensitive City (WSC). The protection against flood in WSC can be accomplished with the land use arrangement that can reduces the surface runoff. The aim of this research is to determine the proper land use scenario to reduce floods in Kedurus Watershed. In order to reach this aim, the writer uses sensitivity analysis to identify the proper land use scenario to be applied in the watershed and SWAT to select the best scenario. The efforts to reduce flood through the land use scenario (scenario 2) could reduce the flood volume by 44,320.32 m3 or 8.11% of the total volume of flood in the area. The average reduction of flood volume in each sub basins is 12,92% and the highest number of reduction is 65,67% (sub basin 22).