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Performance Assessment of Satellite Precipitation Products over Nigeria: A compromise programming Approach

EARTH SYSTEMS AND ENVIRONMENT 2025年 1-22页

作者： Shiru, Mohammed Sanusi Chung, Eun-Sung Sa'adi, Zulfaqar Fed Univ Dutse Fac Sci Dept Environm Sci PMB 7156 Dutse Nigeria Seoul Natl Univ Sci & Technol Dept Civil Engn Seoul 01811 South Korea Univ Teknol Malaysia Res Inst Sustainable Environm Ctr Environm Sustainabil & Water Secur Johor Baharu 81310 Malaysia Univ Teknol Malaysia Fac Civil Engn Dept Water & Environm Engn Johor Baharu 81310 Malaysia

Satellite precipitation products (SPPs) remain a good alternative to gauge based data, where data can be scarce or not available at long term. However, they can be characterized by uncertainties which can emanate from complexities like sampling, algorithmic and instrumental errors;sensitivity to topography;land use and land cover, contrasts in surface temperature and emissivity and climate. Therefore, the choice of an SPP for climate and hydrological study is crucial to its outcome. This study assesses the performances of five SPPs namely, CHIRPS, CMORPH, MSWEP, PERSIANN - CDR and TAMSAT in reproducing the properties of observed precipitation for annual and seasonal periods. Five statistical metrics namely, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Modified Index of Agreement (MD), Cohen's Effect Size (D) and Skill Score (SS) were used. The scores from the metrics for each SPP were aggregated using compromise programming (CP) in order to determine the best performing SPP. In addition, Boxplot and Taylor diagram were used to assess the closeness of the SPPs to the observed precipitation at both seasonal and annual timescales. The study revealed that based on the statistical performances for the annual and seasonal periods at the different stations, TAMSAT ranked as the best performing SPP 104 times over MSWEP with 101, CHIRPS with 93, CMORPH with 26 and PERSIANN-CDR with only 1. However, TAMSAT was placed second to MSWEP after the aggregation of the statistical metrics using CP. The performances of the SPPs were affected by the climatic conditions with CHIRPS having the best performance at the Sahel & Sudan zone (SSZ), TAMSAT at the Guinea zone (GZ) and MSWEP at the Rainforest & Mangrove zone (RMZ) of the country for the annual evaluation. Performances also varies during the seasonal periods. PERSIANN-CDR has been found to perform poorly for the study area in this study.

关键词： compromise programming Performance Assessment Satellite Precipitation Product Statistical Metrics Nigeria

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Multi-Criteria Assessment of Gridded Rainfall Data Accuracy in Nigeria Using compromise programming

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EARTH SYSTEMS AND ENVIRONMENT 2025年 1-28页

作者： Salami, Afeez Alabi Olorunfemi, Jacob Funso Eludoyin, Adebayo Oluwole Univ Ilorin Dept Geog & Environm Management PMB 1515 Ilorin Kwara Nigeria Obafemi Awolowo Univ Dept Geog PMB 13 Ife Osun Nigeria

Precipitation monitoring is vital for regions like Nigeria, where rainfall variability significantly impacts key sectors, yet conventional rain gauge networks face limitations in spatial coverage. This study conducts a multi-criteria assessment of gridded rainfall data (GRD) accuracy in Nigeria using compromise programming (CP), evaluating eleven free-access gridded precipitation products (FGPPs) against ground observations across daily, monthly, seasonal, and annual scales. The evaluation employs statistical metrics, including Pearson Correlation Coefficient, Mean Error, Bias, Root-Mean-Square Error, and Nash-Sutcliffe Efficiency Coefficient. A multi-criteria evaluation framework using CP was applied to rank the FGPPs based on their reliability across varied temporal resolutions. The study highlights the most reliable datasets for Nigerian applications, enhancing data selection for resource management. This innovative approach ranks the FGPPs in a way that reflects their performance across temporal scales and highlights the most reliable products for Nigerian applications. FGPPs generally demonstrated positive correlations with ground observations, with Global Precipitation Climatology Centre (GPCC), Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT) African Rainfall Climatology And Time-series (TARCAT), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Climate Data Record (PERSIANN-CDR) performing well on daily assessments, while Climate Hazards InfraRed Precipitation with Station data (CHIRPS), GPCC, and Global Precipitation Climatology Project (GPCP) as top performers, with observed FGPPs performance varying across eco-climatic regions in Nigeria. Disparities in dataset accuracy highlight the need to select FGPPs adapted to specific temporal and regional conditions, enhancing the accuracy of climate studies and resource management in data-scarce regions.

关键词： compromise programming Gridded Rainfall Data Multi-Criteria Evaluation Nigeria Climate Monitoring Precipitation Accuracy

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compromise programming: Non-interactive calibration of utility-based metrics

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2015年第2期244卷 519-524页

作者： Kanellopoulos, A. Gerdessen, J. C. Claassen, G. D. H. Wageningen Univ Operat Res & Logist Grp NL-6706 KN Wageningen Netherlands TI Food & Nutr NL-6709 PA Wageningen Netherlands

Utility functions have been used widely to support multi-objective decision-making. Expansion of a general additive utility function around the ideal results in a composite linear-quadratic metric of a compromise programming problem. Determining the unknown parameters of the composite linear-quadratic metric requires substantial interaction with the decision maker who might not always be available or capable to participate in such a process. We propose a non-interactive method that uses information on observed attribute levels to obtain the unknown parameters of the composite linear-quadratic metric and enables forecasting and scenario analysis. The method is illustrated with a small scale numerical example. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Utility optimization Goal programming compromise programming Preferential weights Model calibration

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compromise programming: A utility-based linear-quadratic composite metric from the trade-off between achievement and balanced (non-corner) solutions

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2007年第3期182卷 1369-1382页

作者： Ballestero, Enrique Univ Politecn Valencia Alcoy Sch Escuela Politecn Super Alcoy Alicante 03801 Spain

In this paper, compromise programming (CP) is viewed as the maximization of the decision maker's additive utility function (whose arguments are the criteria under consideration) subject to an efficient frontier of criteria and the non-negativity constraints in a deterministic context. This is equivalent to minimizing the difference ('distance') between utility at the ideal point and utility at a frontier point on the criteria map, a meaningful statement as minimizing distances to the utopia is the ethos of compromise programming. By Taylor expansion of utility around the ideal point, the distance to the utopia becomes the weighted sum of linear and quadratic CP distances, which gives us the composite metric. While the linear terms pursue achievement, the quadratic ones pursue balanced (non-corner) solutions. Because some decision makers fear imbalance while others prefer large achievements even to the detriment of balance, the paper defines an aversion to imbalance ratio, so that the composite linear-quadratic metric should conform to this ratio depending on the decision maker's preferences and attitudes. As the problem of selecting an appropriate metric is an ongoing issue in CP, the paper is a contribution to theory and practice. For the sole purpose of suggesting industrial applications, an example is developed. (c) 2006 Elsevier B.V. All rights reserved.

关键词： multiple criteria analysis compromise programming metrics utility theory corner solutions

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compromise programming with Tchebycheff norm for discrete stochastic orders

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ANNALS OF OPERATIONS RESEARCH 2013年第1期211卷 433-446页

作者： Sitarz, Sebastian Univ Silesia Inst Math PL-40007 Katowice Poland

This paper presents a method of decision making with returns in the form of discrete random variables. The proposed method is based on two approaches: stochastic orders and compromise programming used in multi-objective programming. Stochastic orders are represented by stochastic dominance and inverse stochastic dominance. compromise programming uses the augmented Tchebycheff norm. This norm, in special cases, takes form of the Kantorovich and Kolmogorov probability metrics. Moreover, in the paper we show applications of the presented methodology in the following problems: projects selections, decision tree and choosing a lottery.

关键词： Multi-objective programming compromise programming Tchebycheff norm Stochastic dominance

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compromise programming Based Model for Augmenting Food Production with Minimum Water Allocation in a Watershed: a Case Study in the Indian Himalayas

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WATER RESOURCES MANAGEMENT 2014年第15期28卷 5247-5265页

作者： Dogra, Pradeep Sharda, V. N. Ojasvi, P. R. Prasher, Shiv O. Patel, R. M. Cent Soil & Water Conservat Res & Training Inst 218 Kaulagarh Rd Dehra Dun 248195 Uttar Pradesh India Agr Scientists Recruitment Board New Delhi 110012 India McGill Univ Dept Bioresource Engn Montreal PQ H9X 3V9 Canada

A compromise programming based model has been developed for maximizing food production with minimum allocation of available water at watershed scale after meeting human, livestock and environmental needs under different scenarios. Agricultural water allocation in conjunction with available land resources under a set of constraints has been examined. The formulated model has the potential to analyze the implications of water availability on agricultural water allocation plans, and consequently food production. A case study in Indian Himalayan region, where despite abundant availability of water, rainfed agriculture is mostly practiced by majority of farmers with a primary objective of self-sufficiency in food production, well demonstrates the applicability of the developed model. Three distinct scenarios affecting water availability were considered. Analysis of imposition of fixed mandatory outflows of 20 to 70 % (as per water source) for satisfying environmental needs with present production mix revealed water scarcity within the study watershed ranging from 4 to 66 % across various quarters of an year, which necessitates optimum utilization of rainfed fallow land by allocating it to high value crops ginger and lentil (6 to 32 times more than existing allocation) on one hand, and drastic reduction (76 to 100 %) of area under all irrigated crops (except onion with 4-6 times increase) on the other, to achieve the conflicting objectives. The compromise plans also suggested increase (by 14 % in environmental watershed scenario) or decrease (by 29 % in degraded watershed scenario) in size of livestock population as per scenario based water availability. Overall, the compromise plans were successful in achieving a high percentage (> 93 %) of ideal values of the objective functions, which were 155 to 170 % of existing food production and 71 to 85 % of existing water utilization across the scenarios. The proposed optimization model has the potential for application in ident

关键词： compromise programming Foodproduction Land-useplanning Waterallocation Watershed management

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Using compromise programming for macroeconomic policy making in a general equilibrium framework:: theory and application to the Spanish economy

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2008年第7期59卷 875-883页

作者： Andre, F. J. Cardenete Flores, Manuel Alejandro Romero, C. Univ Pablo Olavide Dept Econ Seville 41013 Spain Univ Politecn Madrid Madrid Spain

This paper aims to show how compromise programming, linked with some results connecting this approach with classic utility optimization, can become a useful analytical tool for designing and assessing macroeconomic policies. The functioning of the method is illustrated through an application to the Spanish economy. In this way, starting from a Computable General Equilibrium Model, a frontier of growth-inflation combinations is determined. After that, several Pareto-efficient policies that represent compromises between economic growth and inflation rate are established and interpreted in economic terms.

关键词： compromise programming economics computable general equilibrium model optimization multi-objective

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FUZZY MULTIPLE OBJECTIVE programming AND compromise programming WITH PARETO-OPTIMUM

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FUZZY SETS AND SYSTEMS 1993年第3期53卷 275-288页

作者： LEE, ES LI, RJ Department of Industrial Engineering Kansas State University Manhattan KS 66506-5105 USA

A fuzzy multiple objective decision making approach is proposed based on the desirable features of compromise programming and the fuzzy set theory. The proposed two-phase approach guarantees both nondominated and balanced solutions for solving both the crisp and the fuzzy multiple objective decision making problems. Furthermore, it is shown that the original compromise programming does not guarantee nondominated solutions if the distance parameter is assumed to be infinite and the resulting programming problem's solution is not unique.

关键词： FUZZY MULTIOBJECTIVE programming compromise programming PARETO-OPTIMUM

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Solving the bi-objective capacitated p-median problem with multilevel capacities using compromise programming and VNS

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2020年第1期27卷 361-380页

作者： Irawan, Chandra Ade Imran, Arif Luis, Martino Univ Nottingham Ningbo China Business Sch China Nottingham Univ Ningbo Zhejiang Peoples R China Inst Teknol Nas Dept Ind Engn Bandung 40124 Indonesia Univ Utara Malaysia Othman Yeop Abdullah Grad Sch Business Sintok Malaysia

A bi-objective optimisation using a compromise programming (CP) approach is proposed for the capacitated p-median problem (CPMP) in the presence of the fixed cost of opening facility and several possible capacities that can be used by potential facilities. As the sum of distances between customers and their facilities and the total fixed cost for opening facilities are important aspects, the model is proposed to deal with those conflicting objectives. We develop a mathematical model using integer linear programming (ILP) to determine the optimal location of open facilities with their optimal capacity. Two approaches are designed to deal with the bi-objective CPMP, namely CP with an exact method and with a variable neighbourhood search (VNS) based matheuristic. New sets of generated instances are used to evaluate the performance of the proposed approaches. The computational experiments show that the proposed approaches produce interesting results.

关键词： capacitated p-median problem bi-objective compromise programming VNS

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On the relation between compromise programming and Ordered Weighted Averaging operator

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INFORMATION SCIENCES 2010年第11期180卷 2239-2248页

作者： Zarghami, Mahdi Szidarovszky, Ferenc Univ Tabriz Fac Civil Engn Tabriz 51664 Iran Univ Arizona Dept Syst & Ind Engn Tucson AZ 85721 USA

This paper will demonstrate a strong relationship between the compromise programming (CP) method and the Ordered Weighted Averaging (OWA) operator. We will mathematically prove that the application of the CP method reflects the pessimistic view of the Decision Maker (DM), if the distance from the ideal point is minimized. It will however present an optimistic DM, if the distance from the nadir is maximized. The OWA operator may cover all of the optimistic, neutral and pessimistic views. A practical relationship will be developed between the power value of the CP method and the optimism degree of the DM based on fuzzy quantifiers. The theoretical results will be illustrated by a real case study of a water resources management problem. (C) 2010 Elsevier Inc. All rights reserved.

关键词： Information fusion Ordered Weighted Averaging Multi-criteria decision making compromise programming Optimism degree

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