地表径流
口译(哲学)
水文学(农业)
样品(材料)
考试(生物学)
水文模型
环境科学
统计
计算机科学
地质学
数学
岩土工程
气候学
生物
生态学
古生物学
化学
色谱法
程序设计语言
作者
Aymen Ben Jaafar,Zoubeïda Bargaoui
标识
DOI:10.1061/(asce)he.1943-5584.0001868
摘要
Rainfall-runoff conceptual models are used largely for river discharge prediction, for waterworks design, and as support for water quality assessment. The generalized split-sample test (GSST) recently was recommended to analyze rainfall-runoff models’ performance. Moreover, it was found that parameter transfer may be conditioned to the precipitation conditions of the donor and receiver periods. This study focused on the generalized split-sample test results, and analyzed them in terms of the information gain between rainfall and runoff series. This issue was not considered before in GSST interpretation. Six small to moderate-sized basins (50–500 km2) in northern Tunisia were studied using the daily bucket with a bottom hole (BBH) model and the GSST calibration-validation approach. The mean absolute error and the Nash–Sutcliffe efficiency (NSE) were adopted to quantify model performance. The analysis suggests that the mean information gain (MIG) may be an indicator of the explored hydrological conditions of the assessment periods. In addition, results show that validation periods characterized by high MIG improved robustness, displaying low standard deviation of monthly NSE and enhanced accuracy, as shown by mean monthly NSE. The study of the effects of underlying physiographic factors suggests that the transfer from period to period is likely to be more robust for moderate-size basins than for small basins and that basin steepness tends to decrease the robustness of the transfer.
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