[Objective] The research aimed to study the application of ordinal set pair analysis in the annual precipitation prediction of Liao River basin.[Method] The ordinal theory was introduced into the set pair analysis mod...[Objective] The research aimed to study the application of ordinal set pair analysis in the annual precipitation prediction of Liao River basin.[Method] The ordinal theory was introduced into the set pair analysis modeling,and the prediction model of set pair analysis was improved.A kind of rainfall prediction model based on the ordinal set pair analysis (OSPA) was put forward.The time sequence of annual rainfall in the hydrological rainfall station of Liao River basin during 1956-2006 was the research objective.The annual rainfall during 1998-2006 was predicted by the model,and the error analysis was given.[Result] In the relative errors of predicted results by ordinal set pair analysis,there were six relative errors within 5%,which occupied 66.7% of the total prediction number.One relative error was during 5%-10%,which occupied 11.1% of the total prediction number.Two relative errors were during 10%-15%,which occupied 22.2% of the total prediction number.All the relative errors were less than 20%,which met the precision requirement of annual rainfall prediction in Forecast Specification of Hydrological Information.[Conclusion] The rainfall prediction based on the ordinal set pair analysis model had high precision,and the prediction result was ideal.It was suitable for the annual rainfall prediction.展开更多
Previous studies on river health evaluation mainly focused on characterizations at a river-corridor scale and ignored the complex interactions between the river ecosystem and other components of the river basin.Based ...Previous studies on river health evaluation mainly focused on characterizations at a river-corridor scale and ignored the complex interactions between the river ecosystem and other components of the river basin.Based on the consideration of the interactions among rivers,associated river basin and habitats,an assessment framework with multi-scale indicators was developed.An index system divided among these three scales to characterize the health of river ecosystems in China’s Liao River Basin was established.Set pair analysis was applied to integrate the multi-scale indicators and determine the health classes.The evaluation results indicated that the rivers in the western and eastern zones of the Liao River were classified as sick,and rivers in the main stream of the Liao and Huntai rivers were classified as unhealthy.An excessive level of disturbances,such as large pollution loads and dense construction of water conservation projects within the river basin,were the main causes of the river health deterioration.展开更多
基金Supported by National Eleventh Five-year Water Special Item(2009ZX07208-010-T004)High-level Talent Introduction Plan Item, North China University of Water Resources and Electric Power(200926)+2 种基金Natural Science Research of Henan Education Department(2009A570002)Young Core Teacher Plan Item in Henan Province(2009GGJ3-061)Graduate Education Innovation Plan Foundation,North China University of Water Resources and Electric Power(YK2010-12)
文摘[Objective] The research aimed to study the application of ordinal set pair analysis in the annual precipitation prediction of Liao River basin.[Method] The ordinal theory was introduced into the set pair analysis modeling,and the prediction model of set pair analysis was improved.A kind of rainfall prediction model based on the ordinal set pair analysis (OSPA) was put forward.The time sequence of annual rainfall in the hydrological rainfall station of Liao River basin during 1956-2006 was the research objective.The annual rainfall during 1998-2006 was predicted by the model,and the error analysis was given.[Result] In the relative errors of predicted results by ordinal set pair analysis,there were six relative errors within 5%,which occupied 66.7% of the total prediction number.One relative error was during 5%-10%,which occupied 11.1% of the total prediction number.Two relative errors were during 10%-15%,which occupied 22.2% of the total prediction number.All the relative errors were less than 20%,which met the precision requirement of annual rainfall prediction in Forecast Specification of Hydrological Information.[Conclusion] The rainfall prediction based on the ordinal set pair analysis model had high precision,and the prediction result was ideal.It was suitable for the annual rainfall prediction.
基金This research was supported by the National Natural Science Foundation of China(Grant Nos.50979006 and 50939001)National Water Pollution Control Technology Major Projects(Grant No.2008ZX07526-001 and 2008ZX07209-009).
文摘Previous studies on river health evaluation mainly focused on characterizations at a river-corridor scale and ignored the complex interactions between the river ecosystem and other components of the river basin.Based on the consideration of the interactions among rivers,associated river basin and habitats,an assessment framework with multi-scale indicators was developed.An index system divided among these three scales to characterize the health of river ecosystems in China’s Liao River Basin was established.Set pair analysis was applied to integrate the multi-scale indicators and determine the health classes.The evaluation results indicated that the rivers in the western and eastern zones of the Liao River were classified as sick,and rivers in the main stream of the Liao and Huntai rivers were classified as unhealthy.An excessive level of disturbances,such as large pollution loads and dense construction of water conservation projects within the river basin,were the main causes of the river health deterioration.
