Abstract Analysis of hydrological impacts of land use change raises questions about whether, and how much, such impacts are misrepresented because of errors in river flow observations. In this paper, land use change impacts (represented by changes in watershed storage) and different ranges of discharge measurement error are compared to assess how errors in discharge measurement can potentially mask a land use change impact. Using a watershed from the Ethiopian highlands to exemplify this, we simulated five different levels of land use change impacts with five levels of watershed storage reductions (from 10% to 50% change) and the associated time series of runoff. Different levels of observation error were then introduced into these artificial time series. Comparison was made between every pair, i.e. a time series derived from a certain level of land use change (storage reduction) versus a time series corresponding to a given level of observation error, using a step-change t-test. Significant step-changes between pairs define the detectability of land use change impact. The analysis was made for the entire 30-year time series as well as for the most extreme annual weather conditions. The results showed that for the average year and wettest year, 75% or more error in observed discharge masks the maximum simulated land use change impact on hydrology. In dry years, a 50% error in discharge is enough to mask the same impact. Knowing (and improving) the level of data quality contributes to a better understanding of hydrological uncertainties and improves the precision in assessing land use change impacts. Both of these are essential elements in water resources development planning.

中文翻译：

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观测不确定性是否掩盖了土地利用变化对水文影响的信号？

摘要 土地利用变化的水文影响分析提出了这样的问题，即这种影响是否以及在多大程度上由于河流流量观测的错误而被歪曲。在本文中，土地利用变化影响（由流域蓄水量的变化表示）和不同范围的排放测量误差进行了比较，以评估排放测量中的误差如何潜在地掩盖土地利用变化的影响。使用埃塞俄比亚高地的一个流域来举例说明这一点，我们模拟了五个不同级别的土地利用变化影响，五个级别的流域蓄水量减少（从 10% 到 50% 的变化）和相关的径流时间序列。然后将不同水平的观测误差引入到这些人工时间序列中。每对之间进行比较，即 使用阶跃变化 t 检验，从特定水平的土地利用变化（存储减少）得出的时间序列与对应于给定观测误差水平的时间序列。对之间的显着阶跃变化定义了土地利用变化影响的可检测性。分析是针对整个 30 年时间序列以及最极端的年度天气条件进行的。结果表明，对于平均年份和最湿润年份，75%或更多的观测误差掩盖了模拟土地利用变化对水文的最大影响。在干旱年份，50% 的排放误差足以掩盖同样的影响。了解（并提高）数据质量水平有助于更好地了解水文不确定性，并提高评估土地利用变化影响的精度。