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Evaluation of Statistical and Rainfall-Runoff Models for Predicting Historical Daily Streamflow Time Series in the Des Moines and Iowa River Watersheds.

机译：评估Des moines和Iowa River流域历史每日流量时间序列的统计和降雨 - 径流模型。

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Daily records of streamflow are essential to understanding hydrologic systems and managing the interactions between human and natural systems. Many watersheds and locations lack streamgages to provide accurate and reliable records of daily streamflow. In such ungaged watersheds, statistical tools and rainfall-runoff models are used to estimate daily streamflow. Previous work compared 19 different techniques for predicting daily streamflow records in the southeastern United States. Here, five of the better-performing methods are compared in a different hydroclimatic region of the United States, in Iowa.

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Farmer, W. H.; Knight, R. R.; Eash, D. A.; Hutchinson, K. J.; Linhart, S. M.;
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年度 2015
页码 1-46
总页数 46
原文格式 PDF
正文语种 eng
中图分类工业技术;
关键词
Rainfall; Runoff; Streamflow; Watersheds; Hydrology; Drainage; Streamgage; Natural resources management; Hydroclimatic regions; Precipitation; Prediction in Ungaged Basins (PUBs);

机译：降雨;径流;溪流;流域;水文;排水;中庸;自然资源管理;水文气候区;降水;未开垦水域预测（pUBs）;

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专利

1. A Comparative Evaluation of Short-Term Streamflow Forecasting Using Time Series Analysis and Rainfall-Runoff Models in eWater Source [J] . Dushmanta Dutta, Wendy D. Welsh, Jai Vaze, Water Resources Management . 2012,第15期

机译：基于时间序列分析和降雨径流模型的水源短期流量预测比较评价
2. Evaluation of stochastic and artificial intelligence models in modeling and predicting of river daily flow time series [J] . Aghelpour Pouya, Varshavian Vahid Stochastic environmental research and risk assessment . 2020,第1期

机译：随机和人工智能模型在河流日流量时间序列建模和预测中的评估
3. Estimating daily time series of streamflow using hydrological model calibrated based on satellite observations of river water surface width: Toward real world applications [J] . Wenchao Sun, Hiroshi Ishidaira, Satish Bastola, Environmental research . 2015,第may期

机译：使用基于卫星对河水表面宽度的观测值进行校准的水文模型估算河流流量的每日时间序列：面向现实世界的应用
4. Ozone Treatment of Des Moines River Water in Ottumwa, Iowa [C] . L.J.Bollyky, B.Meerman, V.Robinson Ozone world congress . 1987

机译：臭氧处理衣阿华州奥图姆瓦的得梅因河水
5. Statistical Modeling of Carbon Dioxide and Cluster Analysis of Time Dependent Information: Lag Target Time Series Clustering, Multi-Factor Time Series Clustering, and Multi-Level Time Series Clustering [D] . Kim, Doo Young. 2016

机译：二氧化碳的统计建模和时间相关信息的聚类分析：滞后目标时间序列聚类，多因素时间序列聚类和多级时间序列聚类
6. Comparison of gridded precipitation datasets for rainfall-runoff and inundation modeling in the Mekong River Basin [O] . Sophal Try, Shigenobu Tanaka, Kenji Tanaka, 2020

机译：湄公河流域覆盖径流和淹没建模的网格降水数据集比较
7. Evaluation of statistical and rainfall-runoff models for predicting historical daily streamflow time series in the Des Moines and Iowa River watersheds [O] . William H. Farmer, Rodney R. Knight, David A. Eash, 2015

机译：评估统计和降雨 - 径流模型，用于预测DES MOINES和爱荷华河流域中的历史日报流程时间序列
8. Comparison Between Two Statistically Based Methods, and Two Physically Based Models Developed to Compute Daily Mean Streamflow at Ungaged Locations in the Cedar River Basin, Iowa. [R] . Linhart, S. M., Nania, J. F., Christiansen, D. E., 2013

机译：两种基于统计的方法和两种基于物理的模型的比较，这两种模型是为了计算爱荷华州锡达河流域未开垦地点的每日平均流量而开发的。

Evaluation of Statistical and Rainfall-Runoff Models for Predicting Historical Daily Streamflow Time Series in the Des Moines and Iowa River Watersheds.

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