STOCHASTIC MODELING OF MONTHLY AND DAILY RAINFALL SEQUENCES1

ABSTRACT: A monthly model and two daily models (I and II) are presented for the purpose of generating monthly and daily rainfall sequences in the Quae Yai river basin in Thailand. Performance of the models are evaluated by comparing the statistical parameters of the generated sequences with those from historical data. For monthly generation, Thomas-Fiering model worked satisfactorily in spite of the monthly correlations being weak, if any. Daily Model I, which assumes no persistence between daily rainfall amounts within the wet spells, could not preserve some important parameters regardless of the simplicity in model construction. Application of multi-state transition probability matrix model gave good results, although the user has to modify some parameters looking at the performance of the model for each historical record.     

A CODED ALGORITHM FOR CAPACITY EXPANSION OF A WATER QUALITY MANAGEMENT SYSTEM1

ABSTRACT: This paper describes a mathematical model, an algorithm and a computer program that were specially developed to study the problem of a water quality management system undergoing a rapidly increasing environmental stress. The model output will determine the locations, sizes and the timing of construction of new treatment plants plus an overall treatment plant operating policy so that environmental standards are maintained at a minimum cost. The model, as formulated, is a 0-1 mixed integer programming problem which is solved by decomposing it into a capital budgeting problem (solved by Little's branch and bound algorithm) and an operational policy problem (solved by linear programming). The coded algorithm (in FORTRAN 10) has been tested with a semi-realistic example.     

AN OPTIMIZATION MODEL FOR EFFICIENT MANAGEMENT OF URBAN WATER RESOURCES1

ABSTRACT: A mathematical programming model is proposed to determine economically efficient urban water resource allocation and pricing policy by maximizing the sum of the consumer and producer surplus. The optimization of this nonlinear problem is accomplished by the use of linear programming algorithm. The feasibility of using recycled water for municipal purposes is examined in a planning context. The impact of higher water quality discharge standards on pricing and allocation of water is analyzed and the attractiveness of water reuse option is demonstrated.     

A NONLINEAR MULTILEVEL MODEL FOR REGIONAL WATER RESOURCES PLANNING1

ABSTRACT: A nonlinear multilevel transportation model is developed to study large-scale allocations in a water resources system. The model uses a modified transportation matrix formulated with nonlinear cost functions as the basic subregional model and the goal coordination method for multilevel decomposition and optimization of the overall regional system. The model is applied to projected water requirements for Salt Lake County in 1985. Sources of water supply - surface water, ground water, import water, and reuse of reclaimed wastewater on a restricted basis - are available to satisfy water requirements for municipal, industrial, and agricultural sectors in four subregions. The conjugate gradient projection method is used to optimize the first level subregional models having cost functions of the form of C = aX^b, and the second level problem is solved using the conjugate gradient method.     

基于随机模拟的地下水污染物最优水力截获量

水力截获技术是净化或抑制地下水污染最为广泛使用的一种方法，而该技术实施过程中，如何确定最优水力截获量是其需要重点解决的关键问题.本文针对传统确定性方法计算最优水力截获量不合理的问题，从水文地质参数的随机性出发，应用基于随机理论的蒙特卡罗方法，通过实例来研究渗透系数的空间变异性对地下水污染物水力截获系统的影响，并寻求估算最优水力截获量的新方法.通过研究表明：基于确定性方法计算出最优水力截获量为110m³/d时恰好能完全截获污染区的污染物；应用随机模拟研究含水层渗透系数的空间变异性对水力截获系统的影响，发现当以传统确定性方法所计算的最优水力截获量（110m³/d）抽水时，并不能总是完全截获地下水污染物，其面临的稳定平均风险率高达24%；充分考虑了含水层渗透系数空间变异的Monte Carlo方法较以往传统确定性方法更为可靠，为此本文提出利用随机方法从截获系统可接受风险角度确定最优截获量的新思路.     

Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.     

危险品运输网络优化设计研究综述

为分析当今反恐新形势下的危险品运输网络优化设计问题的研究现状,系统总结国内外关于一般场景和恐怖袭击威胁2种情况下危险品运输网络优化设计研究的主要模型和方法,梳理两者现有的研究内容,并讨论其共性及恐怖袭击威胁情景下的研究的新特点。结果发现:目前关于解决危险品运输网络优化设计问题模型的鲁棒性研究较为缺乏,尤其是模型在更为复杂和不确定性更强的恐怖袭击情景中适用性不强;危险品运输的鲁棒优化模型即使在突发事件条件下,也可以使决策者能够作出相对满意的决策;鲁棒性危险品运输网络能够规避风险扰动,可用来防止在恐怖袭击中因危险品车辆爆炸等造成更大的危害。     

地铁运营突发事件应急响应模式的马尔科夫链分析

为研究城市轨道交通网络化运营线路的风险传导规律和耦合关系,构建基于随机Petri网的同构马尔科夫链模型。通过模型分析突发事件应急响应模式中线路之间的相互影响,以及各线路启动突发事件应急响应模式对整个系统稳态的影响。结果表明,用该模型可从数学上研究城市轨道交通运营线路之间的传导规律和耦合关系,找出影响整个应急指挥系统效率的关键因素,最终提高地铁应对突发事件的能力。     

Livelihoods,conflict and aid programming: is the evidence base good enough?

In conflict‐affected situations, aid‐funded livelihood interventions are often tasked with a dual imperative: to generate material welfare benefits and to contribute to peacebuilding outcomes. There may be some logic to such a transformative agenda, but does the reality square with the rhetoric? Through a review of the effectiveness of a range of livelihood promotion interventions—from job creation to microfinance—this paper finds that high quality empirical evidence is hard to come by in conflict‐affected situations. Many evaluations appear to conflate outputs with impacts and numerous studies fail to include adequate information on their methodologies and datasets, making it difficult to appraise the reliability of their conclusions. Given the primary purpose of this literature—to provide policy guidance on effective ways to promote livelihoods—this silence is particularly concerning. As such, there is a strong case to be made for a restrained and nuanced handling of such interventions in conflict‐affected settings.     

Aggregating high-priority landscape areas to the parcel level: an easement implementation tool

Landscape characteristics and parcel ownership information are often collected on different spatial scales leading to difficulties in implementing land use plans at the parcel level. This study provides a method for aggregating highly resolute landscape planning information to the parcel level. Our parcel prioritization model directly incorporates a Land Trust's conservation goals in the form of a compromise programming model. We then demonstrate the use of our approach for implementation decisions, including parcel selection under a budget constraint and the estimation of a total conservation budget necessary to meet specific conservation goals. We found that these cost constraints significantly alter the composition of the 'best' parcels for conservation and can also provide guidance for implementation. The model's results were integral to a local Land Trust's ability to further define and achieve their goals.