Suchergebnisse

Due to the cumulative effects of rapid urbanization, population growth and climate change, many inland and coastal water bodies around the world are experiencing severe water pollution. To help make land-use and climate change adaptation policies more effective at a local scale, this study used a combination of participatory approaches and computer simulation modeling. This methodology (called the &ldquo ; Participatory Watershed Land-use Management&rdquo ; (PWLM) approach) consist of four major steps: (a) Scenario analysis, (b) impact assessment, (c) developing adaptation and mitigation measures and its integration in local government policies, and (d) improvement of land use plan. As a test case, we conducted PWLM in the Santa Rosa Sub-watershed of the Philippines, a rapidly urbanizing area outside Metro Manila. The scenario analysis step involved a participatory land-use mapping activity (to understand future likely land-use changes), as well as GCM precipitation and temperature data downscaling (to understand the local climate scenarios). For impact assessment, the Water Evaluation and Planning (WEAP) tool was used to simulate future river water quality (BOD and E. coli) under a Business as Usual (BAU) scenario and several alternative future scenarios considering different drivers and pressures (to 2030). Water samples from the Santa Rosa River in 2015 showed that BOD values ranged from 13 to 52 mg/L ; indicating that the river is already moderately to extremely polluted compared to desirable water quality (class B). In the future scenarios, we found that water quality will deteriorate further by 2030 under all scenarios. Population growth was found to have the highest impact on future water quality deterioration, while climate change had the lowest (although not negligible). After the impact assessment, different mitigation measures were suggested in a stakeholder consultation workshop, and of them (enhanced capacity of wastewater treatment plants (WWTPs), and increased sewerage connection rate) were adopted to generate a final scenario including countermeasures. The main benefit of the PWLM approach are its high level of stakeholder involvement (through co-generation of the research) and use of free (for developing countries) software and models, both of which contribute to an enhanced science-policy interface.

Parks and other public green spaces (hereafter "urban green spaces") provide many benefits to urban dwellers, but some residents receive few benefits due to a lack of urban green spaces nearby their home/workplace. Understanding spatial variations in urban green space accessibility is thus important for urban planning. As a case study, here we mapped urban green space accessibility in Japan's highly urbanized Tokyo and Kanagawa Prefectures using a Gravity Model (GM). As the inputs for the GM, we used georeferenced datasets of urban green spaces obtained from various sources, including national government (Ministry of Land, Transportation, Infrastructure, and Tourism; MLIT), a commercial map provider (ESRI Japan Corporation), and a crowdsourcing initiative (OpenStreetMap). These datasets all varied in terms of their spatial and thematic coverage, as could be seen in the urban green space accessibility maps generated using each individual dataset alone. To overcome the limitations of each individual dataset, we developed an integrated urban green space accessibility map using a maximum value operator. The proposed map integration approach is simple and can be applied for mapping spatial accessibility to other goods and services using heterogeneous geographic datasets.

Parks and other public green spaces (hereafter "urban green spaces") provide many benefits to urban dwellers, but some residents receive few benefits due to a lack of urban green spaces nearby their home/workplace. Understanding spatial variations in urban green space accessibility is thus important for urban planning. As a case study, here we mapped urban green space accessibility in Japan's highly urbanized Tokyo and Kanagawa Prefectures using a Gravity Model (GM). As the inputs for the GM, we used georeferenced datasets of urban green spaces obtained from various sources, including national government (Ministry of Land, Transportation, Infrastructure, and Tourism; MLIT), a commercial map provider (ESRI Japan Corporation), and a crowdsourcing initiative (OpenStreetMap). These datasets all varied in terms of their spatial and thematic coverage, as could be seen in the urban green space accessibility maps generated using each individual dataset alone. To overcome the limitations of each individual dataset, we developed an integrated urban green space accessibility map using a maximum value operator. The proposed map integration approach is simple and can be applied for mapping spatial accessibility to other goods and services using heterogeneous geographic datasets.

Just a few decades ago, Adyar River in India's city of Chennai was an important source of water for various uses. Due to local and global changes (e.g., population growth and climate change), its ecosystem and overall water quality, including its aesthetic value, has deteriorated, and the water has become unsuitable for commercial uses. Adverse impacts of excessive population and changing climate are expected to continue in the future. Thus, this study focused on predicting the future water quality of the Adyar river under "business as usual" (BAU) and "suitable with measures" scenarios. The water evaluation and planning (WEAP) simulation tool was used for this study. Water quality simulation along a 19 km stretch of the Adyar River, from downstream of the Chembarambakkam to Adyar (Bay of Bengal) was carried out. In this analysis, clear indication of further deterioration of Adyar water quality by 2030 under the BAU scenario was evidenced. This would be rendering the river unsuitable for many aquatic species. Due to both climate change (i.e., increased temperature and precipitation) and population growth, the WEAP model results indicated that by 2030, biochemical oxygen demand (BOD) and Escherichia coli concentrations will increase by 26.7% and 8.3%, respectively. On the other hand, under the scenario with measures being taken, which assumes that "all wastewater generated locally will be collected and treated in WWTP with a capacity of 886 million liter per day (MLD)," the river water quality is expected to significantly improve by 2030. Specifically, the model results showed largely reduced concentrations of BOD and E. coli, respectively, to the tune of 74.2% and 98.4% compared to the BAU scenario. However, even under the scenario with measures being taken, water quality remains a concern, especially in the downstream area, when compared with class B (fishable surface water quality desirable by the national government). These results indicate that the current management policies and near future water resources ...

© 2020 by the authors. Due to the cumulative effects of rapid urbanization, population growth and climate change, many inland and coastal water bodies around the world are experiencing severe water pollution. To help make land-use and climate change adaptation policies more effective at a local scale, this study used a combination of participatory approaches and computer simulationmodeling. Thismethodology (called the "ParticipatoryWatershed Land-use Management" (PWLM) approach) consist of four major steps: (a) Scenario analysis, (b) impact assessment, (c) developing adaptation and mitigation measures and its integration in local government policies, and (d) improvement of land use plan. As a test case, we conducted PWLM in the Santa Rosa Sub-watershed of the Philippines, a rapidly urbanizing area outside Metro Manila. The scenario analysis step involved a participatory land-use mapping activity (to understand future likely land-use changes), as well as GCM precipitation and temperature data downscaling (to understand the local climate scenarios). For impact assessment, the Water Evaluation and Planning (WEAP) tool was used to simulate future river water quality (BOD and E. coli) under a Business as Usual (BAU) scenario and several alternative future scenarios considering different drivers and pressures (to 2030). Water samples from the Santa Rosa River in 2015 showed that BOD values ranged from 13 to 52 mg/L; indicating that the river is already moderately to extremely polluted compared to desirable water quality (class B). In the future scenarios, we found that water quality will deteriorate further by 2030 under all scenarios. Population growth was found to have the highest impact on future water quality deterioration, while climate change had the lowest (although not negligible). After the impact assessment, different mitigation measures were suggested in a stakeholder consultation workshop, and of them (enhanced capacity of wastewater treatment plants (WWTPs), and increased sewerage connection rate) were adopted to generate a final scenario including countermeasures. The main benefit of the PWLM approach are its high level of stakeholder involvement (through co-generation of the research) and use of free (for developing countries) software and models, both of which contribute to an enhanced science-policy interface.