An eco-environmental water demand based model for optimising water resources using hybrid genetic simulated annealing algorithms. Part I. Model development

We propose here an improved multi-objective optimisation model that considers eco-environmental water demand (EWD) for allocating water resources in a river basin over the long term. The model considers economic, social, and environmental objectives, and it improves on traditional optimisation methods by emphasizing not only the water demand of the artificial ecosystem but also that of the natural ecosystem. Water resource constraints are considered. The hybrid genetic simulated annealing algorithms (HGSAA) technique incorporates a genetic algorithm (GA) and a simulated annealing (SA) algorithm, which have strong local and global searching abilities, in order to solve the highly non-linear model and avoid local and pre-mature convergence. In the method, the water demands of users in the planning year serve as the basis for long-term optimisation using a forecasting procedure. In this study, the combined forecasting method based on the principle of optimal combination is built to forecast domestic and industrial water demands. The proposed model and method are subsequently used in a companion paper to optimise water allocation in the Haihe River basin in China [An eco-environmental water demand based model for optimising water resources using hybrid genetic simulated annealing algorithms. Part II. Model application and results 90 (8), 2612–2619].     

Automatic Calibration of Hydrologic Models With Multi‐Objective Evolutionary Algorithm and Pareto Optimization1

Abstract: In optimization problems with at least two conflicting objectives, a set of solutions rather than a unique one exists because of the trade‐offs between these objectives. A Pareto optimal solution set is achieved when a solution cannot be improved upon without degrading at least one of its objective criteria. This study investigated the application of multi‐objective evolutionary algorithm (MOEA) and Pareto ordering optimization in the automatic calibration of the Soil and Water Assessment Tool (SWAT), a process‐based, semi‐distributed, and continuous hydrologic model. The nondominated sorting genetic algorithm II (NSGA‐II), a fast and recent MOEA, and SWAT were called in FORTRAN from a parallel genetic algorithm library (PGAPACK) to determine the Pareto optimal set. A total of 139 parameter values were simultaneously and explicitly optimized in the calibration. The calibrated SWAT model simulated well the daily streamflow of the Calapooia watershed for a 3‐year period. The daily Nash‐Sutcliffe coefficients were 0.86 at calibration and 0.81 at validation. Automatic multi‐objective calibration of a complex watershed model was successfully implemented using Pareto ordering and MOEA. Future studies include simultaneous automatic calibration of water quality and quantity parameters and the application of Pareto optimization in decision and policy‐making problems related to conflicting objectives of economics and environmental quality.     

The Control of Land-Use Patterns for Stormwater Management at Multiple Spatial Scales

While most research about the relationship between land use and watershed hydrological output has focused primarily on land-use types and their impact on hydrological processes, the relationship between characteristics of land-use patterns (such as pattern fragmentation, connectivity, and coherence) and hydrological processes has not been well examined. Using historical stormwater data, this study evaluates the hydrological effects of different land-use scenarios in the Qing-shui watershed in Beijing, China, at a variety of spatial scales. This study demonstrates that planning and managing land-use patterns can significantly reduce runoff under different scales, particularly for small storm events. In contrast to other aspects of land-use structure characteristics, such as the shape complexity of land-use patches, fragmented level of the patches of land-use types appear as dominant drivers of runoff. The results of the study suggest that land-use pattern management should be an important component of Best Management Practices to reduce the impacts of urbanization on natural hydrological processes.     

Comparison of Two Spatial Optimization Techniques: A Framework to Solve Multiobjective Land Use Distribution Problems

Two spatial optimization approaches, developed from the opposing perspectives of ecological economics and landscape planning and aimed at the definition of new distributions of farming systems and of land use elements, are compared and integrated into a general framework. The first approach, applied to a small river catchment in southwestern France, uses SWAT (Soil and Water Assessment Tool) and a weighted goal programming model in combination with a geographical information system (GIS) for the determination of optimal farming system patterns, based on selected objective functions to minimize deviations from the goals of reducing nitrogen and maintaining income. The second approach, demonstrated in a suburban landscape near Leipzig, Germany, defines a GIS-based predictive habitat model for the search of unfragmented regions suitable for hare populations (Lepus europaeus), followed by compromise optimization with the aim of planning a new habitat structure distribution for the hare. The multifunctional problem is solved by the integration of the three landscape functions (“production of cereals,” “resistance to soil erosion by water,” and “landscape water retention”). Through the comparison, we propose a framework for the definition of optimal land use patterns based on optimization techniques. The framework includes the main aspects to solve land use distribution problems with the aim of finding the optimal or best land use decisions. It integrates indicators, goals of spatial developments and stakeholders, including weighting, and model tools for the prediction of objective functions and risk assessments. Methodological limits of the uncertainty of data and model outcomes are stressed. The framework clarifies the use of optimization techniques in spatial planning.     

Exploring changes in Ecuadorian land use for food production and their effects on natural resources

A model is used for the dynamic and spatially explicit exploration of near future agricultural land-use changes. In a case study for Ecuador, different plausible scenarios are formulated, taking into account possible developments in national food demand until the year 2010. The protection of nature parks and restrictions due to land degradation are evaluated with respect to their possible spatial impacts on the land-use change dynamics within the country. Under the assumptions of the demand scenarios, agricultural land-use expands significantly, resulting in more use of land in existing agricultural areas and frontier-type expansion into relatively undisturbed natural areas. The patterns of change depend on the increase in demand, competition between land-use types, changes in driving factors of land use, and the area and characteristics of land that is excluded from agricultural use. The modelled land-use dynamics are related to their possible impacts on the natural resource base, specifically soil fertility. The results indicate potential negative effects of land-use changes on the soil nutrient balance and biodiversity. It is argued that spatial and temporal quantification of land-use dynamics at the landscape level can support research and policies aimed at understanding the driving factors of land-use change and the behaviour of complex agro-ecosystems under changing conditions at different scales. In this way, issues dealing with sustainable food production and the management of the natural resource base can be addressed in a more integrated and quantitative manner.     

合肥市近19年来土地利用格局的时空变化分析

利用Landsat TM、ETM 、CBERS—2资源卫星数据,采用基于知识型光谱特性的增强与人机交互解译相结合的方法,提取了合肥市1987年、2000年和2006年土地利用类型的专题信息。利用GIS空间分析技术和数理统计方法,分析了合肥市近19年来的土地利用变化特征。结果表明:①在整个阶段—耕地减少了23.38%,建设用地增加了61.26%;城镇用地新增速度最快,且新增速率远大于转移速率,属高速扩张型;②区内最"敏感"的类型是交通用地,其新增速率在两个阶段分别达到1.64和1.62,远高于其它的类型;④从城市扩展的方向上看,合肥城市的发展主要以西南部、南部和东部为主,西南部最为明显;城市已经形成以老城区为核心,向东、北、西南三翼伸展,形成"南进—东拓—西缓—北抑"的空间发展布局。     

Modeling Change-Pattern-Value Dynamics on Land Use: An Integrated GIS and Artificial Neural Networks Approach

The use of spatial methods to detect and characterize changes in land use has been attracting increasing attention from researchers. The objectives of this article were to formulate the dynamics of land use on the temporal and spatial dimensions from the perspectives of the Change-Pattern-Value (CPV) and driving mechanism, based on multitemporal remote sensing data and socioeconomic data. The Artificial Neural Networks were used to identify the factors driving changes in land use. The Pearl River Delta Region of southeast China, which was experiencing rapid economic growth and widespread land conversion, has been selected as the study region. The results show that from 1985 to 2000 in the study region (1) the most prominent characteristics of change in land use were the expansion of the urban land at the expense of farmland, forests, and grasslands, (2) the land-use pattern was being optimized during this period, (3) in an analysis of value, built-up land can yield a return of more than 30 times that of farmland, water area, and forests lands, and (4) rapid economic development, growth in population, and the development of an infrastructure were major driving factors behind ecological land loss and the nonecological land expansion.     

Application of a Three-Dimensional Water Quality Model as a Decision Support Tool for the Management of Land-Use Changes in the Catchment of an Oligotrophic Lake

While expansion of agricultural land area and intensification of agricultural practices through irrigation and fertilizer use can bring many benefits to communities, intensifying land use also causes more contaminants, such as nutrients and pesticides, to enter rivers, lakes, and groundwater. For lakes such as Benmore in the Waitaki catchment, South Island, New Zealand, an area which is currently undergoing agricultural intensification, this could potentially lead to marked degradation of water clarity as well as effects on ecological, recreational, commercial, and tourism values. We undertook a modeling study to demonstrate science-based options for consideration of agricultural intensification in the catchment of Lake Benmore. Based on model simulations of a range of potential future nutrient loadings, it is clear that different areas within Lake Benmore may respond differently to increased nutrient loadings. A western arm (Ahuriri) could be most severely affected by land-use changes and associated increases in nutrient loadings. Lake-wide annual averages of an eutrophication indicator, the trophic level index (TLI) were derived from simulated chlorophyll a, total nitrogen, and total phosphorus concentrations. Results suggest that the lake will shift from oligotrophic (TLI = 2–3) to eutrophic (TLI = 4–5) as external loadings are increased eightfold over current baseline loads, corresponding to the potential land-use intensification in the catchment. This study provides a basis for use of model results in a decision-making process by outlining the environmental consequences of a series of land-use management options, and quantifying nutrient load limits needed to achieve defined trophic state objectives.     

COMPARATIVE STUDY OF OPTIMIZATION TECHNIQUES FOR IRRIGATION PROJECT PLANNING1

ABSTRACT: This study presents three optimization techniques for on‐farm irrigation scheduling in irrigation project planning: namely the genetic algorithm, simulated annealing and iterative improvement methods. The three techniques are applied to planning a 394.6 ha irrigation project in the town of Delta, Utah, for optimizing economic profits, simulating water demand, and estimating the crop area percentages with specific water supply and planted area constraints. The comparative optimization results for the 394.6 ha irrigated project from the genetic algorithm, simulated annealing, and iterative improvement methods are as follows: (1) the seasonal maximum net benefits are $113,826, $111,494, and $105,444 per season, respectively; and (2) the seasonal water demands are 3.03*10³ m³, 3.0*10³ m³, and 2.92*10³ m³ per season, respectively. This study also determined the most suitable four parameters of the genetic algorithm method for the Delta irrigated project to be: (1) the number of generations equals 800, (2) population size equals 50, (3) probability of crossover equals 0.6, and (4) probability of mutation equals 0.02. Meanwhile, the most suitable three parameters of simulated annealing method for the Delta irrigated project are: (1) initial temperature equals 1,000, (2) number of moves equal 90, and (3) cooling rate equals 0.95.     

Modeling the spatial dynamics of regional land use: the CLUE-S model

Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution. The model structure is based on systems theory to allow the integrated analysis of land-use change in relation to socio-economic and biophysical driving factors. The model explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability. Stability is incorporated by a set of variables that define the relative elasticity of the actual land-use type to conversion. The user can specify these settings based on expert knowledge or survey data. Two applications of the model in the Philippines and Malaysia are used to illustrate the functioning of the model and its validation.     

基于Kriging模型的载人航天某装置结构优化设计研究

对于处在振动环境中的载人航天某装置复杂结构,设计过程中存在最小化质量、同时最大化一阶整体振动频率的多目标优化问题,可以利用多目标遗传算法(NSGA-II)求解得到Pareto最优解集,但利用NSGA-II进行求解计算量大,对于复杂结构更甚。为了节省计算时间,提出基于Kriging代理模型的复杂结构多目标优化设计方法,首先通过拉丁超立方采样获得样本点,然后通过样本点创建Kriging模型,最后利用多目标遗传算法求解代理模型得到Pareto最优解集,方便设计师从中选择最优解,优化结果表明本文所述方法合理有效。     

农村工业化进程中的土地资源优化配置研究——以浙江永康市为例

在阐述农村工业化与土地资源优化配置关系问题的基础上，以浙江永康市为例，对当前我国农村工业化过程中土地资源优化配置问题进行了研究。研究表明，永康目前处于工业化中期阶段，工业用地扩张趋势明显，但同时也存在用地结构布局不甚合理、集约利用程度较低以及环境影响等问题。解决这些问题可通过切实保护耕地，合理安排建设用地规模与布局，提高土地集约利用率和控制环境污染等有效途径。     

Assessing Land-Use Impacts on Natural Resources

/ Much information is available on changes that occur in natural resources from both spatially-explicit data on environmental conditions and models of the interactions of these conditions and resources with human activities. The strategy for assessing land-use impacts on natural resources developed in this paper provides a framework for using relevant data and models to address questions of how management practices can promote both use and protection of resources. This assessment strategy integrates spatially explicit environmental data using geographic information systems (GIS) with computer models that simulate changes in land cover in response to land-use impacts. The computer models also simulate susceptibility of species to changes in habitat suitability and landscape patterns. The approach is applied to management of limestone barrens on the Oak Ridge Reservation in East Tennessee. Potential limestone barrens habitats are identified by overlaying appropriate soils, geology, slope, and land-use/land-cover conditions. Their validity is tested against known sites containing rare species that occur in these habitats. The location of habitats at risk in the aftermath of human activities is determined by using an available area model that identifies the size and proximity of sites that particular types of species can no longer use as habitat. The resulting risk map can be used in land management planning. The approach uses readily available in situ and remotely sensed data and is applicable to a wide range of locations and land-use scenarios. This approach can be refined based on needs identified by land managers and on the sensitivity of the results to the resolution of available resource information.KEY WORDS: Land management; Assessment; Habitat characterization; Limestone barrens; Ecological modeling; Geographic information systems     

SIMULATED ANNEALING WITH MEMORY AND DIRECTIONAL SEARCH FOR GROUND WATER REMEDIATION DESIGN1

ABSTRACT: Review of recent literature indicates an emergence in the use of combinatorial methods such as simulated annealing in ground water management during the past nine to ten years. While previous studies demonstrated the feasibility of using these methods, a general finding was that computational processing requirements were inordinately high relative to gradient‐based methods. An enhanced annealing algorithm was developed and used to demonstrate the potential for greatly improving the computational efficiency of simulated annealing as an optimization method for ground water management applications. The algorithm incorporates “directional search” and “memory” capabilities. Selecting search directions based on better understanding of the current neighborhood of the configuration space was shown to improve algorithm performance. Also, “memory” concepts derived from the Tabu Search Method show particular promise for improving the rate and quality of convergence. Performance of the enhanced annealing method was evaluated and the resultant management method was demonstrated using an example from the literature.     

ESTIMATING NONPOINT SOURCE POLLUTION LOADS WITH A GIS SCREENING MODEL1

ABSTRACT: The St. Johns River Water Management District (SJR-WMD) is using a Geographic Information System (GIS) screening model to estimate annual nonpoint source pollution loads to surface waters and determine nonpoint source pollution problem areas within the SJRWMD. The model is a significant improvement over current practice because it is contained entirely within the district's GIS software, resulting in greater flexibility and efficiency, and useful visualization capabilities. Model inputs consist of five spatial data layers, runoff coefficients, mean runoff concentrations, and stormwater treatment efficiencies. The spatial data layers are: existing land use, future land use, soils, rainfall, and hydrologic boundaries. These data layers are processed using the analytical capabilities of a cell-based GIS. Model output consists of seven spatial data layers: runoff, total nitrogen, total phosphorous, suspended solids, biochemical oxygen demand, lead, and zinc. Model output can be examined visually or summarized numerically by drainage basin. Results are reported for only one of the SJRWMD's ten major drainage basins, the lower St. Johns River basin. The model was created to serve a major planning effort at the SJRWMD; results are being actively used to address nonpoint source pollution problems.     

Private land management for biodiversity conservation

As human influences fragment native communities and ecosystems, remaining land must be better managed to conserve many elements of biodiversity. Much of this land is privately held, yet traditional private land-use management practices often further diminish biodiversity by promoting favored or edge-adapted species. Today, private land stewards are increasingly aware of and concerned about biodiversity, but little guidance exists for them to make land-use decisions incorporating principles and knowledge from conservation biology. Consequently, most management strategies are highly subjective. This article addresses that problem by introducing current conservation wisdom to management and use of private lands. The result is a model program for developing land management plans, with the goal of maintaining viable populations and natural distributions of native species and communities from a landscape perspective. The program establishes a protocol for classifying sites according to the importance of their species, communities, and other elements to global and regional biodiversity. These site classifications are based on the management objectives necessary to maintain important elements. Once managers classify a site, the program provides management standards, general stewardship principles, examples of land management strategies, and basic monitoring and evaluation procedures.     

COMPARATIVE EVALUATION OF LAND COVER DATA SOURCES FOR EROSION PREDICTION1

ABSTRACT: A fundamental problem in protecting surface drinking water supplies is the identification of sites highly susceptible to soil erosion and other forms of nonpoint source (NPS) pollution. The New York City Department of Environmental Protection is trying to identify erodible sites as part of a program aimed at avoiding costly filtration. New York City's 2,000 square mile watershed system is well suited for analysis with geographic information systems (GIS); an increasingly important tool to determine the spatial distribution of sensitive NPS pollution areas. This study used a GIS to compare three land cover sources for input into the Modified Universal Soil Loss Equation (MUSLE), a model estimating soil loss from rangeland and forests, for a tributary watershed within New York City's water supply system. Sources included both conventional data (aerial photography) and Landsat data (MSS and TM images). Although land cover classifications varied significantly across these sources, location-specific and aggregate watershed predictions of the MUSLE were very similar. We conclude that using Landsat TM imagery with a hybrid classification algorithm provides a rapid, objective means of developing large area land cover databases for use in the MUSLE, thus presenting an attractive alternative to photo interpretation.     

Land-Cover Change Trajectories in Northern Ghana

Land-cover change trajectories are an emergent property of complex human–environment systems such as the land-use system. An understanding of the factors responsible for land change trajectories is fundamental for land-use planning and the development of land-related policies. The aims of this study were to characterize and identify the spatial determinants of agricultural land-cover change trajectories in northern Ghana. Land-cover change trajectories were defined using land-cover maps prepared from Landsat Thematic Mapper dataset acquired in 1984, 1992, and 1999. Binary logistic regression was used to model the probability of observing the trajectories as a function of spatially explicit biophysical and socioeconomic independent variables. Population densities generally increased along the continuum of land-use intensity, whereas distance from market and roads generally decreased along this continuum. Apparently, roads and market serve as incentives for settlement and agricultural land use. An increase in population density is an important spatial determinant only for trajectories where the dominant change process is agricultural extensification. A major response to population growth is an increase in cultivation frequency around the main market. Agricultural intensification is highly sensitive to accessibility by roads. The increase in land-use intensity is also associated with low soil quality. These results suggest the need for policies to restore soil fertility for agricultural sustainability. The models also provide a means for identifying functional relationships for in-depth analyses of land-use change in Ghana.     

An Optimization Method for Estimating Constituent Mean Concentrations in Base Flow‐Dominated Flow

Pollutant coefficients have been widely used to assess runoff nonpoint source pollution from individual land uses (e.g., agricultural, residential) of a watershed. Pollutant coefficients, known as event mean concentrations (EMCs), were developed by the U.S. Environmental Protection Agency's Nationwide Urban Runoff Program (NURP) to serve as a national measure for characterizing pollutant loading in a receiving water body. The term “baseflow pollutant coefficient (BPC)” is used in this study as a surrogate for EMC to describe mean concentration of pollutants in base flow‐dominated flow. A method for characterizing base flow quantity and quality for different land uses was explored using inverse modeling with two optimization techniques (a least square method and a genetic algorithm [GA] optimization), land use information, and streamflow quantity and quality data. The inverse model was formulated as a constrained minimization problem and demonstrated with data for 15 watersheds in Indiana. Results showed that estimated pollutant coefficients are comparable to the published literature. This indicates that the proposed method has the potential to effectively estimate constituent mean concentrations for pollutant load determination in gauged and ungauged watersheds, albeit more analysis with larger and more robust datasets is desirable to further refine and validate the accuracy of the approach.     

PROBLEMS AND METHODS INVOLVED IN RELATING LAND USE TO GROUND-WATER QUALITY1

ABSTRACT: Efforts to relate shallow ground-water quality to the land use near a well lead to several statistical difficulties. These include potential uncertainty in land-use categorical data due to misclassification, data closure, distributional skewing, and spatial autocorrelation. Methods of addressing these problems are, respectively, the establishment of limits on minimum buffer radius, the estimation of contrasts, rank-based tests of association, and sub-sampling to prevent buffer overlap. Relations between the presence of purgeable organic compounds in ground water and land use are used to illustrate these problems and methods.