Optimal spatial allocation of water resources based on Pareto ant colony algorithm

The spatial allocation of water resources is optimised using the multi-objective functions and multi-constrained conditions of the Pareto ant colony algorithm (PACA). The objective function is the highest benefit to the economy, society and the environment, while the constraints include water supply, demand and quality. The PACA is improved by limiting local pheromone scope and dynamically updating global pheromone levels. Since both strategies guide the ant towards borders of high-pheromone concentration, the new approach enhances the global search capability and convergence speed. Programming, database management and interface tools are then integrated into geographic information systems (GIS) software. The study area is located in Zhenping County, Henan Province, China, and water resource data are obtained using remote sensing (RS) and GIS technology. The improved PACA is solved in the GIS environment. Optimal spatial allocation schemes are obtained for surface, ground and transferred water and the model yields optimal spatial benefit schemes of water resources, embracing economic, social and ecological benefits. The results of improved PACA are superior to those of other intelligent optimisation algorithms, including the ant colony algorithm, multi-objective genetic algorithm and back-propagation artificial neural network. Therefore, the integration of RS, GIS and PACA can effectively optimise the large-scale, multi-objective allocation of water resources. The model also enhances the global search capability, convergence speed and result precision, and can potentially solve other optimal spatial problems with multi-objective functions.     

Optimal spatial land-use allocation for limited development ecological zones based on the geographic information system and a genetic ant colony algorithm

Limited development ecological zones (LDEZs) are often located in poverty-stricken, ecologically vulnerable areas where ethnic minorities reside. Studies on optimal spatial land-use allocation in LDEZs can promote economic and intensive land use, improve soil quality, facilitate local socioeconomic development, and maintain environmental stability. In this study, we optimized spatial land-use allocations in an LDEZ using the geographic information system (GIS) and a genetic ant colony algorithm (GACA). The multi-objective function considers economic benefits and ecological green equivalents, and improves soil erosion. We developed the GACA by integrating a genetic algorithm (GA) with an ant colony algorithm (ACA). This avoids a large number of redundant iterations and the low efficiency of the GA, and the slow convergence speed of the ACA. The study area is located in Pengyang County, Ningxia, China, which is a typical LDEZ. The land-use data were interpreted from remote sensing (RS) images and GIS. We determined the optimal spatial land-use allocations in the LDEZ using the GACA in the GIS environment. We compared the original and optimal spatial schemes in terms of economic benefits, ecological green equivalents, and soil erosion. The results of the GACA were superior to the original allocation, the ACA, and the multi-objective genetic algorithm, in terms of the optimum, time, and robust performance indexes. We also present some suggestions for the reasonable development and protection of LDEZs.     

2000-2015年三江平原主要作物需水量征及影响因素分析

全生育期内作物需水量的研究是农业水资源有效利用和进行合理灌溉的重要依据。基于三江平原22个气象站点2000—2015年逐日气象观测资料及中国区域地面气象要素数据集,利用国际粮农组织 （FAO）Penman-Monteith模型和分段单值平均作物系数法,分别对三江平原水稻、玉米和大豆的作物需水量进行计算,分析作物需水量年际变化特征,采用通径分析法研究作物需水量的变化成因。结果表明：（1）三江平原16 a来年均参考作物蒸散量为537.4 mm,日均为 3.5 mm,呈波动减少趋势。（2）生长季内,水稻在分蘖期需水量最大,为177.1 mm,玉米在七叶期需水量最大,为99.7 mm,大豆在结荚期需水量最大,为96.1 mm;水稻、玉米和大豆的净灌溉需水量分别为195.4 mm、130.8 mm和72.2 mm,对灌溉的依赖程度水稻>玉米>大豆。（3）由通径分析结果可知,三江平原作物需水量的主要影响因素为净辐射、气温和日照时数。     

黑河干流水系水资源优化分配的多目标规划模型

流域水资源综合利用的优化分配是一个多目标决策问题。本文根据黑河干流水系的特点税流域内水资源分配利用的系统分析,详细介绍了黑河干流水系的多目标水资源分配规划模型,研制的模型考虑了水资源开发利用的国民经济发展和流域环境质量二方面的目标,按分区设计了工业、农业、林业、牧业(灌溉草场)、生态林草地和城镇、人畜生活用水等六个用水户,分别给出地表水和地下水二种配水量。通过二套数据计算,证明黑河干流水系多目标水资源分配规模模型可为流域合理开发利用水资源提供定量配水依据。     

A multi-type ant colony optimization (MACO) method for optimal land use allocation in large areas

Optimizing land use allocation is a challenging task, as it involves multiple stakeholders with conflicting objectives. In addition, the solution space of the optimization grows exponentially as the size of the region and the resolution increase. This article presents a new ant colony optimization algorithm by incorporating multiple types of ants for solving complex multiple land use allocation problems. A spatial exchange mechanism is used to deal with competition between different types of land use allocation. This multi-type ant colony optimization optimal multiple land allocation (MACO-MLA) model was successfully applied to a case study in Panyu, Guangdong, China, a large region with an area of 1,454,285 cells. The proposed model took only about 25 minutes to find near-optimal solution in terms of overall suitability, compactness, and cost. Comparison indicates that MACO-MLA can yield better performances than the simulated annealing (SA) and the genetic algorithm (GA) methods. It is found that MACO-MLA has an improvement of the total utility value over SA and GA methods by 4.5% and 1.3%, respectively. The computation time of this proposed model amounts to only 2.6% and 12.3%, respectively, of that of the SA and GA methods. The experiments have demonstrated that the proposed model was an efficient and effective optimization technique for generating optimal land use patterns.     

人工牧草需水量的模拟计算及其有效性检验

 较高精度的模拟计算作物需水量对制定节水高效灌溉制度、灌溉排水规划和水资源合理配置至关重要。目前模拟计算作物需水量的主要方法有FAO-56双作物系数法、双涌源能量守恒模型、根系层水量平衡模型和SWAP模型。任何方法计算的作物需水量用于生产实践时,都应进行模拟结果的有效性检验。基于灌溉试验数据,应用联合国粮农组织推荐的FAO-56双作物系数法模拟计算了人工牧草——披碱草、冰草的需水量。并采用拟合相关图法、回归分析法和残差估计误差指示法对需水量模拟值进行了有效性检验。拟合相关图法给出统计相关趋势,属定性检验; 回归分析法和残差估计误差指示法给出了模拟值与实测值间的拟合优度和残差估计误差的范围,属定量检验。这种定性定量相结合的方法客观的检验了需水量模拟值与实测值的一致性,经有效性检验后的需水量模拟值可用于生产实践。     

民勤咸水灌溉及SWAP模型模拟研究

 采用0.8 g·L-1和5 g·L-1浓度咸水对民勤传统作物黄河蜜进行咸水灌溉试验。通过野外试验和实验室分析,评价了咸水灌溉对土壤性质和作物产量的影响,校正了SWAP模型并对相关因子进行了模拟分析。研究结果显示,尽管基于当地种植经验的灌水量与基于潜在蒸发蒸腾量（ET0）及根据田间持水量计算的需水量有一定差异,但灌溉水质和灌水量与田间产量具有较好的一致性;0.8 g·L-1处理的水利用效率高于5 g·L-1处理,湿润年的水利用效率高于干旱年;模拟结果显示,SWAP模型对不同试验处理和不同气候条件下的土壤性质和作物产量模拟效果较好。由此得出结论,在民勤可以利用SWAP模型模拟不同环境条件下的土壤水分状况及作物产量,为农田耕作提供理论支撑。     

山西省中部五大盆地主要作物农田热量、水量盈亏分析

本文根据晋中五大盆地的热量、水量实测数据和当地的实际情况,分析计算了不同耕作制度下主要作物农田热量盈亏量和无灌溉条件下的水量盈亏量。为充分合理利用水热资源,发展农业生产,提供科学依据。     

基于多目标分析的石羊河流域水资源优化配置研究

 在论述区域水资源可持续利用与水资源承载能力关系的前提下,运用多目标多阶段分析法,建立了石羊河流域水资源优化配置模型,并计算了2010年、2020年的水资源最佳分配量。结果表明,水资源配置常遇到许多不确定性或模糊性问题,需要不确定型或模糊模型予以解决。开发建立多层次、多用户的面向对象的交互式模拟与优化耦合模型,可以解决水资源配置的许多实际问题。     

A comparison of scenario-based hybrid bilevel and multi-objective location-allocation models for earthquake emergency shelters: a case study in the central area of Beijing,China

The accurate location and allocation of disaster emergency shelters are key components of effective urban planning and emergency management. Various models have been developed to solve the location-allocation problem, but gaps remain with regard to model realism and associated applicability. For the available location and allocation models of earthquake emergency shelters, uncertainty with respect to earthquake hazard, population exposure, rate of damage to buildings and the effects of evacuee behavior are often neglected or oversimplified. Moreover, modifying the models can be an alternative means of improving the solution quality when the optimization algorithm has difficulty coping with a complex, high-dimensional problem. This article develops a scenario-based hybrid bilevel model that addresses the concerns related to high-dimensional complexity and provides a higher degree of realism by incorporating the uncertainties of population dynamics and earthquake damage scenarios into location-allocation problems for earthquake emergency shelters. A modified particle swarm optimization algorithm combined with a simulated annealing algorithm was applied to derive solutions using the hybrid bilevel model and a conventional multi-objective model, and the solutions obtained using the two models were then compared. The novel features of the study include the hybrid bilevel model that considers the dynamic number of evacuees and its implementation for earthquake emergency shelter location and allocation. The results show that the solutions significantly differ between daytime and nighttime. When applied to the multi-objective model, the optimization algorithm is time consuming and may only find the local optima and provide suboptimal solutions in the considered scenarios with more evacuees. By contrast, the hybrid bilevel model shows more desirable performance because it significantly reduces the dimensionality of the location-allocation problem based on a two-step-to-reach approach. The proposed hybrid bilevel model is proven to be useful for optimal shelter allocation, and the presented results can be used as a reference for balancing the interests of the government and residents during the planning of shelters in Beijing.     

Multi-criteria, multi-objective and uncertainty analysis for agro-energy spatial modelling

The worldwide increase in the use of biomass as a Renewable Energy Source raises the issue of introducing crops dedicated to energy production into rural landscapes. The purpose of this paper is to set-up a GIS based multi-criteria approach to assess a range of possibilities for perennial energy crops conversion. The presented method was implemented at the regional level in the Yorkshire and the Humber Region in Northern UK. The first phase of the study aims to set-up a land capability model for the specific purpose of assessing the potential of different typologies of perennial energy crops, on the basis of specific pedo-climatic and topographic factors. The model output illustrates a range of potentials for energy crop conversion that can be explored in the given landscape. In the second phase a uncertainty analysis of the land capability model was performed through a simulation approach in order to interpret the influence of assumptions and uncertainty on input data and model parameters. The last phase of the study allows allocating the energy crop conversion area according to specific environmental constraints, nature protection targets, food production priorities and land capability values. The land allocation output gives a rather restrictive energy crop penetration scenario, where more than half of the conversion area is allocated to cropping systems with low land degradation potential. This scenario represents a preliminary regional analysis of the energy crop potential in terms of theoretically available conversion areas. The final results also show that the areas with highest environmental risks correspond to the areas with both the lowest suitability for energy crop cultivation and the highest model uncertainty.     

Using simulated annealing for resource allocation

Many resource allocation issues, such as land use- or irrigation planning, require input from extensive spatial databases and involve complex decisionmaking problems. Spatial decision support systems (SDSS) are designed to make these issues more transparent and to support the design and evaluation of resource allocation alternatives. Recent developments in this field focus on the design of allocation plans that utilise mathematical optimisation techniques. These techniques, often referred to as multi-criteria decision-making (MCDM) techniques, run into numerical problems when faced with the high dimensionality encountered in spatial applications. In this paper we demonstrate how simulated annealing, a heuristic algorithm, can be used to solve high-dimensional non-linear optimisation problems for multi-site land use allocation (MLUA) problems. The optimisation model both minimises development costs and maximises spatial compactness of the land use. Compactness is achieved by adding a non-linear neighbourhood objective to the objective function. The method is successfully applied to a case study in Galicia, Spain, using an SDSS for supporting the restoration of a former mining area with new land use.     

松嫩平原西部典型农田需水规律研究

采用联合国粮农组织最新推荐的模型方法(FAO56),利用近10年的日气象资料对松嫩平原西部玉米、大豆、高粱等作物近10年的农田逐日需水量进行了系统研究。得出了本区不同作物的需水规律,并根据当地的有效降雨量,获得了不同作物不同时段的水分亏缺规律,为节水灌溉和提高作物产量提供科学依据。     

中国地表潜在蒸散发敏感性的时空变化特征分析

潜在蒸散发是农田灌溉管理、作物需水量估算、稀缺资料地区水量平衡等研究中的重要参量,分析其对气象因子的敏感性有助于农业水资源优化配置和气候变化对水资源的影响研究.根据中国1960-2007年的653个气象台站的常规气象观测资料.采用优化太阳辐射计算的Penman-Monteith潜在蒸散发计算方法,分析了中国10大流域片...     

塔里木河上游地区土壤水盐变化与作物的关系

本文利用塔里木河上游灌区阿克苏水平衡站的有关试验观测资料，对绿洲农田地下水，土壤中水和盐的运动及植物耐盐性进行了对比分析，总结了土壤水盐运动的某些规律。．     

卫宁平原包气带水分运移特征研究

降雨、灌溉入渗和潜水蒸发在卫宁平原地下水循环中有重要的作用。为了准确评价卫宁平原地下水垂向入渗补给量和蒸发量,通过设立中卫、中宁两个包气带原位试验点,观测期为2013年6月~2013年11月和2014年4月~2014年10月,获取了两个试验点不同埋深处的土壤水负压、温度、岩性及水分运移参数,并采用定位通量法计算试验点的地表蒸散发、入渗量和潜水面蒸发、入渗量。结果显示：在包气带岩性相同、灌溉期相同（7~10月）、总灌溉量相近条件下,作物的灌溉模式决定了灌溉对潜水的补给强度：玉米少次大量（150 mm·次^-1）灌溉对潜水的补给量为373.65 mm,远远大于茄子多次小量（50 mm·次^-1）的灌溉模式下的152.3 mm;而在包气带岩性相同、种植作物相同、灌溉模式不变的前提下,同时期潜水面净补给强度相近：中宁试验点2013年7~10月份潜水面净通量为32.88 mm,2014年同期为57.42 mm。在降雨情况或灌溉量较小（50 mm）的情况下,植被的生长会阻碍水分在包气带中的下渗;在灌溉量较大（100 mm和150 mm）的情况下,植被的生长会促进包气带水分的下渗。     

基于水利益共享的跨境流域水资源多目标分配研究——以澜沧江-湄公河为例

以水利益共享代替分水的理念有利于充分发挥水资源效益和减少区域矛盾冲突,但由于缺乏具体可实施的分配模式一直停留在设想阶段。基于水利益共享理念,建立跨境流域水资源多目标分配指标体系,并结合澜沧江-湄公河流域跨境水资源利用现状及需求,提出澜沧江-湄公河流域跨境水资源多目标分配模型。为基于水利益共享的跨境水资源多目标分配提供了具有充分可操作性的指标体系和分配模型,有助于推进跨境流域水利益共享的实施,实现区域双边或多边在水资源利用上的共赢和发展目标。     

秸秆覆盖下的夏玉米蒸散、水分利用效率和作物系数的变化

农业用水占华北水资源的70%以上,提高农业用水的效率对华北水资源安全具有重要意义。在节水农业研究中,利用农艺节水提高农田水分利用效率是节水农业的重要组成部分,其中减少农田无效棵间蒸发耗水和优化供水制度是主要的农艺节水措施。夏玉米是华北太行山山前平原的主要作物之一,一般在冬小麦收获前的5～7天套种在其中,以延长夏玉米的生育期。随着联合收割机的广泛应用,冬小麦收获后的秸秆直接覆盖夏玉米,对夏玉米的农田蒸散特别是苗期的蒸散产生影响;夏玉米生长在6～9月的雨季,一般年份降水能够满足夏玉米的需水要求,但夏季降水的分布变异较大,再加上近6年来的夏季干旱,使灌水对夏玉米的高产至关重要。为了提高夏玉米的农田水分利用效率,本研究的目的是建立秸秆覆盖下的夏玉米优化供水制度和研究秸秆覆盖对减少棵间无效耗水的影响及秸秆覆盖下的夏玉米作物系数的变化,为制定秸秆覆盖下的夏玉米优化供水制度提供依据。2年的实验结果显示,秸秆覆盖下的夏玉米产量在8000kg/ha,总蒸散量在390mm,水分利用效率在2.2kg/m3。干旱年份,夏玉米在灌四水的条件下产量最高,再增加灌水量,产量减少。水分利用效率随着灌水量的增加有所递减。     

Optimal land use allocation of urban fringe in Guangzhou

In response to the strong drive for social and economic development, local governments have implemented urban master plans, providing measures and timeframes to address the continuous demand for land and to alleviate urban problems. In this paper, a multi-objective model was constructed to discuss the problem, including economic benefits and ecological effectiveness, in terms of land use optimization. A genetic algorithm was then adopted to solve the model, and a performance evaluation and sensitivity analysis were conducted using Pareto optimality. Results showed that a set of tradeoffs could be acquired by the allocation of land use. In addition, the Pareto solutions proved the model to be efficient; for example, a limit of 13,500 ha of urban area conformed to plan recommendations. The reduction in crop land, orchard land, grassland, and unused land provided further efficiencies. These results implied that further potential regional land resources remain and that the urban master plan is able to support sustainable local development in the years to come, as well as verified that it is feasible to use land use allocation multi-objective modeling and genetic algorithms.     

广州市城市边缘区土地利用优化配置(英文)

In response to the strong drive for social and economic development, local governments have implemented urban master plans, providing measures and timeframes to address the continuous demand for land and to alleviate urban problems. In this paper, a multi-objective model was constructed to discuss the problem, including economic benefits and ecological effectiveness, in terms of land use optimization. A genetic algorithm was then adopted to solve the model, and a performance evaluation and sensitivity analysis were conducted using Pareto optimality. Results showed that a set of tradeoffs could be acquired by the allocation of land use. In addition, the Pareto solutions proved the model to be efficient; for example, a limit of 13,500 ha of urban area conformed to plan recommendations. The reduction in crop land, orchard land, grassland, and unused land provided further efficiencies. These results implied that further potential regional land resources remain and that the urban master plan is able to support sustainable local development in the years to come, as well as verified that it is feasible to use land use allocation multi-objective modeling and genetic algorithms.