Optimal operation model of a single reservoir with drought duration explicitly concerned

In this paper, a new model for a single reservoir operation optimization is proposed. The proposed model can design the optimal operation policy of a reservoir with explicit consideration of drought duration. The authors model this problem by formulating a single-stage loss function as a function of both the reservoir release and drought duration. Thereby the expected loss per period which is calculated based on the above extended single-stage loss function is minimized in infinite time horizon on the basis of Markov decision process (MDP) theory. The reliability indices are estimated as expected loss per period for specified extended loss functions. Finally, the features of the proposed model are illustrated through numerical analysis.     

河套灌区井渠联合运用优化灌溉模型

针对河套灌区的地面水与地下水联合运用问题,提出了井渠结合优化灌溉模型,以最佳种植模式和最优工程运行策略,达到控制地下水位、防治土壤盐碱化、获得农作物稳产高产的目的.模型有调蓄地面水源、土壤贮水层、地下含水层的能力.优化计算成果与266.7hm2试验示范区的实际运行结果相吻合,节水、节能、增产及控制地下水位、改良盐碱地等效果十分显著,这对发展节水型灌溉农业具有重要的现实意义.     

THE MEDIUM-RANGE NUMERICAL WEATHER PREDICTION OPERATION SYSTEM IN THE CHINA NATIONAL METEOROLOGICAL CENTER

It is not only meteorological problems for the medium-range numerical weather prediction(NWP) research to be in operation,but also engineering and technological problems.Here we gener-ally described the results of research,engineering construction,operation information and testing,inthe course of set-up of medium-range NWP operation system in the China National MeteorologicalCenter.     

地下水资源系统多目标管理模型与模糊带权二次规划方法

本文以济南地下水资源系统保泉供水管理课题为例,分析研究地下水资源系统多目标管理问题。首先建立起地下水资源系统多目标管理模型;然后利用模糊数学理论和权重概念,提出一种求解多目标决策问题的模糊带权二次规划方法,此方法可以同时解决互为竞争、互为矛盾的各目标之间的不可公度性和主次性问题。实际计算表明,所建立的模型和提出的方法具有较强的实用性和通用性。     

能源基地晋陕蒙接壤地区地质环境质量定量研究

本文基于地质环境是由诸多因素有机组合而成,其质量也是各因素质量的复杂组合,是一种模糊现象,难以精确评价,但又存在明显差异的认识,采用模糊数学理论,即以环境地质亚区为单元,考虑多因素的综合影响。采用数量化的动态聚类法,对晋陕蒙接壤地区地质环境质量进行了评价:包括自然条件下地质环境质量评价和煤炭、水资源开发后地质环境质量的相对变化评价。     

Flood-type trend analysis for alpine catchments

ABSTRACT

In many places, magnitudes and frequencies of floods are expected to increase due to climate change. To understand these changes better, trend analyses of historical data are helpful. However, traditional trend analyses do not address issues related to shifts in the relative contributions of rainfall versus snowmelt floods, or in the frequency of a particular flood type. We present a novel approach for quantifying such trends in time series of floods using a fuzzy decision tree for event classification and applied it to maximal annual and seasonal floods in 27 alpine catchments for the period 1980–2014. Trends in flood types were studied with Sen’s slope and double mass curves. Our results reveal a decreasing number of rain-on-snow and an increasing number of short rainfall events in all catchments, with flash floods increasing in smaller catchments. Overall, the results demonstrate the value of incorporating a fuzzy flood-type classification into flood trend analyses.     

An experiment on reservoir representation schemes to improve hydrologic prediction: coupling the national water model with the HEC-ResSim

ABSTRACT

This study experiments with reservoir representation schemes to improve the ability to model active water management in the National Water Model (NWM). For this purpose, we developed an integrated water management model, NWM-ResSim, by coupling the NWM with HEC-ResSim, and two reservoir representation schemes are tested: simulation of reservoir operations and retrieval of scheduled operations. The experiments focus on a pilot reservoir domain in the Russian River basin – Lake Mendocino, California – and its contributing watershed. The evaluation results suggest that the NWM-ResSim improves the simulation performance of reservoir outflow from this managed reservoir over the NWM default level pool routing scheme. The degree of this improvement depends on the suitability of the operation guidance; the reservoir operations simulation scheme could have acceptable errors for the purposes of water resources management, but not for flood operations. Results of the retrieval scheme of scheduled operations demonstrated better performance for sub-daily flood operations.     

Knowledge-Driven and Data-Driven Fuzzy Models for Predictive Mineral Potential Mapping

In this paper, we describe new fuzzy models for predictive mineral potential mapping: (1) a knowledge-driven fuzzy model that uses a logistic membership function for deriving fuzzy membership values of input evidential maps and (2) a data-driven model, which uses a piecewise linear function based on quantified spatial associations between a set of evidential evidence features and a set of known mineral deposits for deriving fuzzy membership values of input evidential maps. We also describe a graphical defuzzification procedure for the interpretation of output fuzzy favorability maps. The models are demonstrated for mapping base metal deposit potential in an area in the south-central part of the Aravalli metallogenic province in the state of Rajasthan, western India. The data-driven and knowledge-driven models described in this paper predict potentially mineralized zones, which occupy less than 10% of the study area and contain at least 83% of the model and validation base metal deposits. A cross-validation of the favorability map derived from using one of the models with the favorability map derived from using the other model indicates a remarkable similarity in their results. Both models therefore are useful for predicting favorable zones to guide further exploration work.     

Effects of variable attribute weights on landform classification

This paper focuses on the attribute weight issue and advocates use of modi?able attribute weights in terrain‐based environmental analysis and classi?cation. A question was asked: ‘How much will the result of a terrain‐based environmental analysis be affected if the weights of used terrain attributes are changed?’ The literature on landform classi?cation and the fuzzy k‐means method was reviewed in particular to help clarify the background and importance of this weight assignment issue. As an example, the effects of modifying attribute weights were evaluated for fuzzy k‐means landform classi?cation in a case study area. A total of 102 classi?cations were compared with each other and with a soil map, and comparison methods were speci?cally designed to evaluate the differences between these classi?cations. The results show that fuzzy k‐means landform classi?cation is sensitive to weight adjustments of adopted terrain attributes. The sensitivity is particularly high when the attribute weights started to be tuned away from the standard (i.e. uniform) weight of one. Better matching between landform classi?cation and a soil map may be produced when attribute weights are tuned. In all, we advocate the widespread adoption of an exploratory attitude in assigning attribute weights for environmental analysis and classi?cation. Copyright © 2006 John Wiley & Sons, Ltd.