Territorial planning,environmental issues and social appraisal: some general implications of ‘new’ assessment methodologies

The paper attempts to conceptualise a range of problems arising from project appraisals. The author presents some general considerations concerning the role of social appraisal in territorial planning, the theoretical weaknesses of cost‐benefit analysis in assessing the effects of projects on territorial resources and some questions relating to assessment methodologies and the welfare foundations of social appraisal within planning practices. The author moves away from evaluation as a technical process towards one which also incorporates ‘practical’ knowledge in a process of argumentation.     

THE LAW OF THE COLORADO RIVER: COPING WITH SEVERE SUSTAINED DROUGHT1

ABSTRACT: The waters of the Colorado River are divided among seven states according to a complex ‘Law of the River’ drawn from interstate compacts, international treaties, statutes, and regulations. The Law of the River creates certain priorities among the states and the Republic of Mexico, and in the event of a severe sustained drought, the Law of the River dictates the distribution of water and operation of the elaborate reservoir system. Earlier work indicated that there is remarkable resilience in the system for established uses of water in the Lower Basin of the Colorado River. This work shows, based on an application of the Law of the River using computer modeling of operations of facilities on the Colorado River, that there may be serious environmental consequences and related legal restraints on how the water is used in times of shortage and that the existing legal and institutional framework governing the Colorado River does not adequately address all the issues that would be raised in a severe sustained drought. Several possible legal options for dealing with drought in the context of the Law of the River are identified.     

SOCIAL IMPLICATIONS OF SEVERE SUSTAINED DROUGHT CASE STUDIES IN CALIFORNIA AND COLORADO1

ABSTRACT: Survey data collected in the San Joaquin Valley of southern California and the Grand Valley of western Colorado reveal that residents of both areas believe that a severe sustained drought is likely to occur within the next 20–25 years and that their communities would be seriously impacted by such an event. Although a severe sustained drought affecting the Colorado River Basin would cause major economic and social disruptions in these and other communities, residents express little support for water management alternatives that would require significant shifts in economic development activities or in water use and allocation patterns. In particular, residents of these areas express little support for strategies such as construction and growth moratoriums, mandatory water conservation programs, water transfers from low-to high-population areas, water marketing, or reallocations of water from agricultural to municipal/industrial uses. This rejection of water management strategies that would require a departure from “business as usual” with respect to water use and allocations severely restricts the capacity of these and similar communities to respond effectively should a severe sustained drought occur.     

MITIGATING IMPACTS OF A SEVERE SUSTAINED DROUGHT ON COLORADO RWER WATER RESOURCES1

ABSTRACT: We evaluated the effects of institutional responses developed for coping with a severe sustained drought (SSD) in the Colorado River Basin on selected system variables using a SSD inflow hydrology derived from the drought which occurred in the Colorado River basin from 1579–1616. Institutional responses considered are reverse equalization, salinity reduction, minimum flow requirements, and temporary suspension of the delivery obligation of the Colorado River Compact. Selected system variables (reservoir contents, streamflows, consumptive uses, salinity, and power generation) from scenarios incorporating the drought-coping responses were compared to those from Baseline conditions using the current operating criteria. The coping responses successfully mitigated some impacts of the SSD on consumptive uses in the Upper Basin with only slight impacts on consumptive uses in the Lower Basin, and successfully maintained specified minimum streamflows throughout the drought with no apparent effect on consumptive uses. The impacts of the coping responses on other system variables were not as clear cut. We also assessed the effects of the drought-coping responses to normal and wet hydrologic conditions to determine if they were overly conservative. The results show that the rules would have inconsequential effects on the system during normal and wet years.     

THE SOCIAL IMPACT OF RESERVOIR CONSTRUCTION IN THE URBAN FRINGE: A TEN-YEAR COMPARISON1

ABSTRACT This paper examines the social impact of reservoir construction on a rural community group located in the urban fringe of a major metropolitan area in central Ohio. The study data were collected at three intervals over a ten-year period (1970, 1974, 1980). Evaluation of resident opinions in the affected community revealed significant attitude differences over time for four of the five variables measured. The findings revealed that the study group desired more social stability but had accommodated the changes experienced to date. Responses to the attitude scales showed that the people in the study group were well integrated and were closely identified with each other at all three test periods. Attitudes toward the lake project were significantly more positive over time, and in 1980 the collective community group held a basically neutral attitude about the lake. The development agency was also perceived more positively over time.     

APPLICATION OF GREY MODEL AND ARTIFICIAL NEURAL NETWORKS TO FLOOD FORECASTING1

The main focus of this study was to compare the Grey model and several artificial neural network (ANN) models for real time flood forecasting, including a comparison of the models for various lead times (ranging from one to six hours). For hydrological applications, the Grey model has the advantage that it can easily be used in forecasting without assuming that forecast storm events exhibit the same stochastic characteristics as the storm events themselves. The major advantage of an ANN in rainfall‐runoff modeling is that there is no requirement for any prior assumptions regarding the processes involved. The Grey model and three ANN models were applied to a 2,509 km² watershed in the Republic of Korea to compare the results for real time flood forecasting with from one to six hours of lead time. The fifth‐order Grey model and the ANN models with the optimal network architectures, represented by ANN1004 (34 input nodes, 21 hidden nodes, and 1 output node), ANN1010 (40 input nodes, 25 hidden nodes, and 1 output node), and ANN1004T (14 input nodes, 21 hidden nodes, and 1 output node), were adopted to evaluate the effects of time lags and differences between area mean and point rainfall. The Grey model and the ANN models, which provided reliable forecasts with one to six hours of lead time, were calibrated and their datasets validated. The results showed that the Grey model and the ANN1010 model achieved the highest level of performance in forecasting runoff for one to six lead hours. The ANN model architectures (ANN1004 and ANN1010) that used point rainfall data performed better than the model that used mean rainfall data (ANN1004T) in the real time forecasting. The selected models thus appear to be a useful tool for flood forecasting in Korea.     

环境保护及可持续发展需要加强现代化档案工作

新世纪可持续发展思想成为主流,中国处于社会转型时期,在西部大开发、环境保护、城市建设等许多领域,环境档案具有不可替代的重要功能。但是目前的环境档案工作还亟待强化高科技化、法制化和提高人才素质,特别需要强化档案的资源开发观念。     

基于神经网络的温度预测

室内温度与诸多影响因素之间的非线性、复杂性等关系 ,给建模、预测带来了难度 ,引入了人工神经网络 ;利用人工神经网络的非线性、并行计算和自学习特性进行建模 ,实现了对温度模拟     

提高交通安全——实现智能汽车的研究

主要介绍了通过智能汽车的研究 ,提高城市交通安全的必要性 ;综述了发达国家关于智能汽车研究的现状与趋势 ,并通过国外智能汽车发展的趋势 ;进一步论证智能汽车的研究是汽车工业发展的方向 ,也是提高交通安全的重要手段之一。此外 ,论文提出利用模式识别技术的智能汽车的结构框架 ;指出神经网络方法应用与模式识别技术结合的优势。最后 ,论文在阐述我国需要发展智能汽车的同时 ,提出应结合中国国情相应研究相关理论 ,为今后的实施奠定基础的近期目标 ,并提出展望     

SOIL SALINITY PREDICTION USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: This study explores the applicability of Artificial Neural Networks (ANNs) for predicting salt build‐up in the crop root zone. ANN models were developed with salinity data from field lysimeters subirrigated with brackish water. Different ANN architectures were explored by varying the number of processing elements (PEs) (from 1 to 30) for replicate data from a 0.4 m water table, 0.8 m water table, and both 0.4 and 0.8 m water table lysimeters. Different ANN models were developed by using individual replicate treatment values as well as the mean value for each treatment. For replicate data, the models with twenty, seven, and six PEs were found to be the best for the water tables at 0.4 m, 0.8 m and both water tables combined, respectively. The correlation coefficients between observed salinity and ANN predicted salinity of the test data with these models were 0.89, 0.91, and 0.89, respectively. The performance of the ANNs developed using mean salinity values of the replicates was found to be similar to those with replicate data. Not only was there agreement between observed and ANN predicted salinity values, the results clearly indicated the potential use of ANN models for predicting salt build‐up in soil profile at a specific site.