Impact of Demographic Trends on Future Development Patterns and the Loss of Open Space in the California Mojave Desert

During the post-World War II era, the Mojave Desert Region of San Bernardino County, California, has experienced rapid levels of population growth. Over the past several decades, growth has accelerated, accompanied by significant shifts in ethnic composition, most notably from predominantly White non-Hispanic to Hispanic. This study explores the impacts of changing ethnicity on future development and the loss of open space by modeling ethnic propensities regarding family size and settlement preferences reflected by U.S. Census Bureau data. Demographic trends and land conversion data were obtained for seven Mojave Desert communities for the period between 1990 and 2001. Using a spatially explicit, logistic regression-based urban growth model, these data and trends were used to project community-specific future growth patterns from 2000 to 2020 under three future settlement scenarios: (1) an “historic” scenario reported in earlier research that uses a Mojave-wide average settlement density of 3.76 persons/ha; (2) an “existing” scenario based on community-specific settlement densities as of 2001; and (3) a “demographic futures” scenario based on community-specific settlement densities that explicitly model the Region’s changing ethnicity. Results found that under the demographic futures scenario, by 2020 roughly 53% of within-community open space would remain, under the existing scenario only 40% would remain, and under the historic scenario model the communities would have what amounts to a deficit of open space. Differences in the loss of open space across the scenarios demonstrate the importance of considering demographic trends that are reflective of the residential needs and preferences of projected future populations.     

Downscaling climate change scenarios in an urban land use change model

The objective of this paper is to describe the process through which climate change scenarios were downscaled in an urban land use model and the results of this experimentation. The land use models (Urban Growth Model [UGM] and the Land Cover Deltatron Model [LCDM]) utilized in the project are part of the SLEUTH program which uses a probabilistic cellular automata protocol. The land use change scenario experiments were developed for the 31-county New York Metropolitan Region (NYMR) of the US Mid-Atlantic Region. The Intergovernmental Panel on Climate Change (IPCC), regional greenhouse gas (GHG) emissions scenarios (Special Report on Emissions Scenarios (SRES) A2 and B2 scenarios) were used to define the narrative scenario conditions of future land use change. The specific research objectives of the land use modeling work involving the SLEUTH program were threefold: (1) Define the projected conversion probabilities and the amount of rural-to-urban land use change for the NYMR as derived by the UGM and LCDM for the years 2020 and 2050, as defined by the pattern of growth for the years 1960-1990; (2) Down-scale the IPCC SRES A2 and B2 scenarios as a narrative that could be translated into alternative growth projections; and, (3) Create two alternative future growth scenarios: A2 scenario which will be associated with more rapid land conversion than found in initial projections, and a B2 scenario which will be associated with a slower level of land conversion. The results of the modeling experiments successfully illustrate the spectrum of possible land use/land cover change scenarios for the years 2020 and 2050. The application of these results into the broader scale climate and health impact study is discussed, as is the general role of land use/land cover change models in climate change studies and associated environmental management strategies.     

Constructing land-use maps of the Netherlands in 2030

The National Environmental Assessment Agency of the RIVM in the Netherlands is obliged to report on future trends in the environment and nature every 4 years. The last report, Nature Outlook 2, evaluated the effects of four alternative socio-economic and demographic scenarios on nature and the landscape. Spatially detailed land-use maps are needed to assess effects on nature and landscape. The objective of the study presented here was how to create spatially detailed land-use maps of the Netherlands in 2030 using the Environment Explorer, a Cellular Automata-based land-use model to construct land-use maps from four scenarios. One of these is discussed in great detail to show how the maps were constructed from the various scenario elements, story lines and additional data and assumptions on national, regional and local land-use developments. It was the first time in the history of our outlooks that consistent, spatially detailed land-use maps of the Netherlands for 2030 were constructed from national economic and demographic scenarios. Each map represents a direct reflection of model input and assumptions. The maps do not show the most probable developments in the Netherlands but describe the possible change in land use if Dutch society were to develop according to one of the four scenarios. The large (societal) uncertainties are reflected in the total set of future land-use maps. The application of a land-use model such as the Environment Explorer ensures that all relevant aspects of a scenario, i.e. economic and demographic developments, zoning policies and urban growth, are integrated systematically into one consistent framework.     

Integrated urban water management modelling under climate change scenarios

The concept of integrated water management is uncommon in urban areas, unless there is a shortage of supply and severe conflicts among the users competing for limited water resources. Further, problem of water management in urban areas will aggravate due to uncertain climatic events. Therefore, an Integrated Urban Water Management Model considering Climate Change (IUWMCC) has been presented which is suitable for optimum allocation of water from multiple sources to satisfy the demands of different users under different climate change scenarios. Effect of climate change has been incorporated in non-linear mathematical model of resource allocation in term of climate change factors. These factors have been developed using runoff responses corresponding to base and future scenario of climate. Future scenarios have been simulated using stochastic weather generator (LARS-WG) for different IPCC climate change scenarios i.e. A1B, A2 and B1. Further, application of model has been demonstrated for a realistic water supply system of Ajmer urban fringe (India). Developed model is capable in developing adaptation strategies for optimum water resources planning and utilization in urban areas under different climate change scenarios.     

Forecasts of habitat loss and fragmentation due to urban growth are sensitive to source of input data

The conversion of natural habitat to urban settlements is a primary driver of biodiversity loss, and species' persistence is threatened by the extent, location, and spatial pattern of development. Urban growth models are widely used to anticipate future development and to inform conservation management, but the source of spatial input to these models may contribute to uncertainty in their predictions. We compared two sources of historic urban maps, used as input for model calibration, to determine how differences in definition and scale of urban extent affect the resulting spatial predictions from a widely used urban growth model for San Diego County, CA under three conservation scenarios. The results showed that rate, extent, and spatial pattern of predicted urban development, and associated habitat loss, may vary substantially depending on the source of input data, regardless of how much land is excluded from development. Although the datasets we compared both represented urban land, different types of land use/land cover included in the definition of urban land and different minimum mapping units contributed to the discrepancies. Varying temporal resolution of the input datasets also contributed to differences in projected rates of development. Differential predicted impacts to vegetation types illustrate how the choice of spatial input data may lead to different conclusions relative to conservation. Although the study cannot reveal whether one dataset is better than another, modelers should carefully consider that geographical reality can be represented differently, and should carefully choose the definition and scale of their data to fit their research objectives.     

Regression modeling of streamflow, baseflow, and runoff using geographic information systems

Regression models for predicting total streamflow (TSF), baseflow (TBF), and storm runoff (TRO) are needed for water resource planning and management. This study used 54 streams with >20 years of streamflow gaging station records during the period October 1971 to September 2001 in Pennsylvania and partitioned TSF into TBF and TRO. TBF was considered a surrogate of groundwater recharge for basins. Regression models for predicting basin-wide TSF, TBF, and TRO were developed under three scenarios that varied in regression variables used for model development. Regression variables representing basin geomorphological, geological, soil, and climatic characteristics were estimated using geographic information systems. All regression models for TSF, TBF, and TRO had R(2) values >0.94 and reasonable prediction errors. The two best TSF models developed under scenarios 1 and 2 had similar absolute prediction errors. The same was true for the two best TBF models. Therefore, any one of the two best TSF and TBF models could be used for respective flow prediction depending on variable availability. The TRO model developed under scenario 1 had smaller absolute prediction errors than that developed under scenario 2. Simplified Area-alone models developed under scenario 3 might be used when variables for using best models are not available, but had lower R(2) values and higher or more variable prediction errors than the best models.     

中原经济区能源消费视角下的大气环境压力评估

研究以能源消费模式为切入点,分析中原经济区能源消费总量、消费结构和利用效率的现状水平,并分析能源消费引起的大气环境压力状况。基于经济发展速度调控及节能减排力度的不同,设置2020年三种能源消费情景,使用区域能源消费总量优化模型模拟预测不同情景下的能源消费总量,并分析不同情景下的大气环境压力。结果表明,快速发展和适度发展Ⅰ情景下,2020年区域能源消费总量将比2012年增加4.2×10~8tce和2.4×10~8tce,煤炭消费总量将增加3.1×10~8tce和1.2×10~8tce,大气污染物排放压力增加30%和50%;适度发展Ⅱ情景下,能源消费总量将增加0.2×10~8tce,煤炭消费总量将下降0.3×10~8tce,大气污染物排放压力将降低20%。因此,要实现经济发展稳步增长(年均增长率7.7%)和大气污染物排放总量削减10%目标,重中之重是实现煤炭消费总量"零增长"或"负增长",同时力争能源消费总量控制在5×10~8~6×10~8tce,凭借煤炭占比大幅下降(降至65%左右)最大限度发挥能源供给领域节能效应,依靠产业结构升级节能效应和技术节能拓展能源消费领域节能空间,将能效水平提高至0.6tce/万元以下。     

MINIMIZING THE IMPACT OF URBANIZATION ON LONG TERM RUNOFF1

Increasing concern about the problems caused by urban sprawl has encouraged development and implementation of smart growth approaches to land use management. One of the goals of smart growth is water resources protection, in particular minimizing the runoff impact of urbanization. To investigate the magnitude of the potential benefits of land use planning for water resources protection, possible runoff impacts of historical and projected urbanization were estimated for two watersheds in Indiana and Michigan using a long term hydrological impact analysis model. An optimization component allowed selection of land use change placements that minimize runoff increase. Optimizing land use change placement would have reduced runoff increase by as much as 4.9 percent from 1973 to 1997 in the Indiana study watershed. For nonsprawl and sprawl scenarios in the Michigan watershed for 1978 to 2040, optimizing land use change placement would have reduced runoff increase by 12.3 percent and 20.5 percent, respectively. The work presented here illustrates both an approach to assessing the magnitude of the impact of smart growth and the significant potential scale of smart growth in moderating runoff changes that result from urbanization. The results of this study have significant implications for urban planning.     

Runoff Simulation of the Headwaters of the Yellow River Using The SWAT Model With Three Snowmelt Algorithms1

Abstract: The Soil and Water Assessment Tool (SWAT) model combined with different snowmelt algorithms was evaluated for runoff simulation of an 114,345 km² mountainous river basin (the headwaters of the Yellow River), where snowmelt is a significant process. The three snowmelt algorithms incorporated into SWAT were as follows: (1) the temperature‐index, (2) the temperature‐index plus elevation band, and (3) the energy budget based SNOW17. The SNOW17 is more complex than the temperature‐based snowmelt algorithms, and requires more detailed meteorological and topographical inputs. In order to apply the SNOW17 in the SWAT framework, SWAT was modified to operate at the pixel scale rather than the normal Hydrologic Response Unit scale. The three snowmelt algorithms were evaluated under two parameter scenarios, the default and the calibrated parameters scenarios. Under the default parameters scenario, the parameter values were determined based on a review of the current literature. The purpose of this type of evaluation was to assess the applicability of SWAT in ungauged basins, where there is little observed data available for calibration. Under the calibrated parameters scenario, the parameters were calibrated using an automatic calibration program, the Shuffled Complex Evolution (SCE‐UA). The purpose of this type of evaluation was to assess the applicability of SWAT in gauged basins. Two time periods (1975‐1985 and 1986‐1990) of monthly runoff data were used in this study to evaluate the performance of SWAT with different snowmelt algorithms. Under the default parameters scenario, the SWAT model with complex energy budget based SNOW17 performed the best for both time periods. Under the calibrated parameters scenario, the parameters were calibrated using monthly runoff from 1975‐1985 and validated using monthly runoff from 1986‐1990. After parameter calibration, the performance of SWAT with the three snowmelt algorithms was improved from the default parameters scenario. Further, the SWAT model with temperature‐index plus elevation band performed as well as the SWAT model with SNOW17. The SWAT model with temperature‐index algorithm performed the poorest for both time periods under both scenarios. Therefore, it is suggested that the SNOW17 model be used for modeling ungauged basins; however, for gauged basins, the SNOW17 and simple temperature‐index plus elevation band models could provide almost equally good runoff simulation results.     

Adaptation potential of ecosystem-based management to climate change in the eastern Canadian boreal forest

Ecosystem-based management (EBM) of forests is gaining acceptance for its focus on the maintenance of the long-term integrity of ecosystem processes, but climate change challenges this view because of its impacts on these very processes. We have therefore evaluated the robustness of EBM to projected climate change, considering the role of climate on forest growth and fire regime in a boreal forest of eastern Canada. A climate sensitive growth index model was calibrated for three commercial species and used to project the evolution of merchantable volume for two climate scenarios (B1 and A2) under conventional and EBM strategies. Current burn rate and burn rates under future climate scenarios were also considered. Under the most extreme projected climate scenario, the periodic timber supply could be reduced by up to 79% through direct (growth reduction) and indirect (fire) effects. However, ecological indicators show that EBM is a more robust forest management strategy than conventional one demonstrating its adaptation potential to climate change at least in the short term.     

Mapping socio-economic scenarios of land cover change: a GIS method to enable ecosystem service modelling

We present a GIS method to interpret qualitatively expressed socio-economic scenarios in quantitative map-based terms. (i) We built scenarios using local stakeholders and experts to define how major land cover classes may change under different sets of drivers; (ii) we formalized these as spatially explicit rules, for example agriculture can only occur on certain soil types; (iii) we created a future land cover map which can then be used to model ecosystem services. We illustrate this for carbon storage in the Eastern Arc Mountains of Tanzania using two scenarios: the first based on sustainable development, the second based on 'business as usual' with continued forest-woodland degradation and poor protection of existing forest reserves. Between 2000 and 2025 4% of carbon stocks were lost under the first scenario compared to a loss of 41% of carbon stocks under the second scenario. Quantifying the impacts of differing future scenarios using the method we document here will be important if payments for ecosystem services are to be used to change policy in order to maintain critical ecosystem services.     

城镇体系规划中的生态与环境保护规划--以潮州市为例

目前城镇体系规划在各地区相应开展,但作为城镇体系规划重要内容之一的生态与环境保护规划却没有得到普遍重视,这与城市可持续发展战略是不相适应的.从城镇体系规划角度出发,简述了生态与环境保护规划的要求、内容及作用,并以潮州市为例,对生态与环境保护规划进行了探讨,为城镇的开发与可持续发展提供决策依据.     

设立国家高新区能否驱动城市绿色发展——基于双重差分法的经验数据

国家高新区是新时代中国落实创新驱动发展战略、实现经济高质量发展和绿色发展的重要制度安排。本研究以2008年之后设立了国家高新区的城市为实验组,以一直未设立国家高新区的城市为对照组,形成2003—2019年的231个城市的面板数据,采用多期双重差分法实证检验国家高新区的设立对城市绿色发展水平的驱动作用及其机制。研究发现,设立国家高新区能显著提升城市绿色发展水平,但提升效应有待进一步加强。其机制主要是国家高新区通过提高经济增长质量和资源节约利用水平,提升环境治理和生态保护水平,改善居民绿色行为和居住环境,进而提升城市的绿色生产指数、绿色生态指数和绿色生活指数。以上结论表明国家高新区可通过推动产业结构提档升级和节能减排来进一步增强绿色先行示范作用,引领城市绿色发展。     

Coupling of the Water Cycle with Patterns of Urban Growth in the Baltimore Metropolitan Region,United States

Regional municipal water plans typically do not recognize complex coupling patterns or that increased withdrawals in one location can result in changes in water availability in others. We investigated the interaction between urban growth and water availability in the Baltimore metropolitan region where urban growth has occurred beyond the reaches of municipal water systems into areas that rely on wells in low‐productivity Piedmont aquifers. We used the urban growth model SLEUTH and the hydrologic model ParFlow.CLM to evaluate this interaction with urban growth scenarios in 2007 and 2030. We found decreasing groundwater availability outside of the municipal water service area. Within the municipal service area we found zones of increasing storage resulting from increased urban growth, where reduced vegetation cover dominated the effect of urbanization on the hydrologic cycle. We also found areas of decreasing storage, where expanding impervious surfaces played a larger role. Although the magnitude of urban growth and change in water availability for the simulation period were generally small, there was considerable spatial heterogeneity of changes in subsurface storage. This suggests that there are locally concentrated areas of groundwater sensitivity to urban growth where water shortages could occur or where drying up of headwater streams would be more likely. The simulation approach presented here could be used to identify early warning indicators of future risk.     

Collaborative Modeling to Evaluate Water Management Scenarios in the Rio Grande Basin

This article describes the collaborative modeling process and the resulting water resources planning model developed to evaluate water management scenarios in the transboundary Rio Grande basin. The Rio Grande is a severely water stressed basin that faces numerous management challenges as it crosses numerous jurisdictional boundaries. A collaborative process was undertaken to identify and model water management scenarios to improve water supply for stakeholders, the environment, and international obligations of water delivery from Mexico to the United States. A transparent and open process of data collection, model building, and scenario development was completed by a project steering committee composed of university, nongovernmental, and governmental experts from both countries. The outcome of the process was a planning model described in this article, with data and operations that were agreed on by water planning officials in each country. Water management scenarios were created from stakeholder input and were modeled and evaluated for effectiveness with the planning model.     

Towards a Symbiosis: Urban Development and Environmental Quality in the Taipei Metropolitan Region

Environmental quality in urban areas has become an increasingly important topic in Taiwan. Previous research involving the interrelationshipsbetween urban development and environmental quality have rarely emphasized the symbiosis between urban areas and the natural environment. In recent years, the discipline of ecological economics has applied ecological energetic analysis to evaluate the contribution of the natural environment to an urban system. In addition, system simulation also plays a prominent role in assessing the dynamic interrelations between humans, economics and ecological systems. On the basis of an ecological economics perspective, this paper establishes indices of environmental quality and develops an ecological system model to simulate the interrelationshipsbetween urban developmentand environmentalquality of the Taipei metropolitan region. Furthermore, this paper not only proposes future development alternatives and strategies, but also initiates scenarios of the Taipei metropolitan region for policy simulation. According to those results, future development in the Taipei metropolitan region should adjust the interface and mechanism between man and nature for sustainable development.     

城市污水全量循环方法学研究

城市的快速发展对水资源、水环境的压力不断增大,城市生活污水排放量逐年增长。为节约水资源,改善水环境,将城市污水深度处理后回用于工业、市政等方面,设置不同情景对城市污水全量循环方法学开展研究,以实现城市污水不外排。     

秦皇岛市“创模”对策研究及效益分析

介绍了秦皇岛市创建国家环境保护模范城市的意义,重点阐述了完成创模任务的主要对策,包括:构建以旅游业为中心、特色产业互融互促的现代产业体系;加快城乡一体化建设;提升城镇发展质量和水平;加强重大基础设施建设;积极推广清洁能源,深入开展工程节能;积极推进循环经济发展等。秦皇岛市创建国家环境保护模范城市,将会在环境、经济和社会三方面产生明显的综合效益。     

沿海滩涂生态型围垦指标体系研究

随着近几年滩涂围垦工程的进行,为了协调围垦开发与生态环境保护之间的矛盾,生态型围垦的理念应运而生。本文对"生态型围垦"的内涵进行了深入辨析,提出了沿海滩涂生态型围垦概念模型,针对围垦工程规划前期、工程实施和运行管理3个阶段的特点,从管理、环境和生态3个方面提出相应指标,初步构架了生态型围垦指标体系,为沿海滩涂围垦的可持续及匡围区域生态环境管理提供技术支撑。