Urban parks,value uplift and green gentrification: An application of the spatial hedonic model in the city of Brisbane

This paper explores the impact of urban parks on real estate prices making use of a hedonic price approach. Focusing on Brisbane, Australia, as a case study site, we use spatial hedonic models to analyse housing sales data across 15,000 sales transactions to investigate the effects of parks on nearby housing prices, paying attention to park typology and classification. Our findings indicate that recreational and sport parks are differently associated with price variations. The study also examines a specific and significant inner-city park currently undergoing a major redevelopment—namely Victoria Park. Our analysis of the Victoria Park site seeks to quantify the value uplift, that is, the future increase in property prices as a result of the transformation of the current private golf course in this location into a new publicly accessible parkland. This study’s property economics modelling analysis indicates the conversion of Victoria Park from a golf course to public parkland will increase property prices by an average of 3 % for properties located within 750 m of the park. The article concludes with a discussion of value capture opportunities that these findings present as well as challenges of green gentrification for this and similar urban renewal projects and possible policy responses.     

基于混合产流模式的黄土高原流域水沙过程耦合模拟

为深入理解黄土高原干旱半干旱地区复杂地貌条件下流域水沙运移规律。基于垂向混合产流机理和运动波方程，构建分布式流域水文模型，耦合流域土壤侵蚀和泥沙输移过程模拟模块，并考虑梯田对水沙过程的影响，建立适用于黄土高原的分布式流域水沙过程模型。选取黄土高原延河支流西川河流域多年实测场次洪水过程的径流泥沙资料，对模型进行率定和验证。径流模拟的纳什效率系数在0.56以上，平均值超过0.70,模拟次洪过程的峰形、峰值、峰现时间与实测过程具有较好的一致性；侵蚀产输沙模拟精度较低，其纳什效率系数均值率定期为0.79,但验证期仅为0.45,模拟结果整体趋势与实测值较一致，但输沙量模拟峰值比实测值偏低。模型可以较精确地模拟黄土高原流域洪水产汇流过程，但输沙量模拟值偏低，一方面由于产汇流模块的误差传递；另一方面，对重力侵蚀考虑不足。因此，未来模型将考虑滑坡、崩塌等重力侵蚀过程，提升模拟精度和效率，为流域水沙过程模拟与流域综合治理提供有效工具。     

Potential of retrofitted urban green infrastructure to reduce runoff - A model implementation with site-specific constraints at neighborhood scale

The urbanization has resulted in significant changes in the water balance. Urban Green Infrastructures (UGI) have become a promising method for reducing reoccurring floods whilst providing additional social and ecological benefits. However, there are several challenges to successfully implementing UGI in already developed areas, such as accounting for retrofitting UGI scenarios and pre-existing use of spaces. Accurate estimations of the potential of UGI in reducing flood-causing at the watershed scale are therefore important. This study investigates the influence of site-specific constraints on the effectiveness of UGI in reducing flood-causing runoff at the watershed scale. In particular, this study takes urban fabric characteristics in the development of UGI implementation strategies for different types of residential and industrial neighborhoods into account. Furthermore, it applies a hydrological simulation-based approach to estimate the runoff reduction potential of these strategies for a case study in the Metropolitan Area of San José, Costa Rica. The results indicate that UGI implementation potential depends on urban fabric characteristics and modelling different UGI implementation scenarios shows differing hydrological performance. In residential areas, either permeable pavement or infiltration trenches and street planters lead to the highest runoff reduction. In industrial areas, only permeable pavements lead to the highest runoff reduction. Overall, industrial areas enable more potential for UGI and reduce runoff generation. The findings of this study can guide the development of retrofitting UGI scenarios and upscaling strategies under heterogeneous settlement characteristics.     

Modelling soil erosion and sediment yield at a catchment scale: the case of Masinga catchment,Kenya

Development of improved soil erosion and sediment yield prediction technology is required to provide catchment stakeholders with the tools they need to evaluate the impact of various management strategies on soil loss and sediment yield in order to plan for the optimal use of the land. In this paper, a newly developed approach is presented to predict the sources of sediment reaching the stream network within Masinga, a large‐scale rural catchment in Kenya. The study applies the revised universal soil loss equation (RUSLE) and a developed hillslope sediment delivery distributed (HSDD) model embedded in a geographical information system (GIS). The HSDD model estimates the sediment delivery ratio (SDR) on a cell‐by‐cell basis using the concept of runoff travel time as a function of catchment characteristics. The model performance was verified by comparing predicted and measured plot runoff and sediment yield. The results show a fairly good relationship between predicted and measured sediment yield (R²=0·82). The predicted results show that the developed modelling approach can be used as a major tool to estimate spatial soil erosion and sediment yield at a catchment scale. Copyright © 2006 John Wiley & Sons, Ltd.