Tobias Schnepper, Jannis Groh, Horst H. Gerke, Barbara Reichert, Thomas Pütz
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The aim was to quantify measurement errors in standard precipitation gauges as compared to the lysimeter reference and to analyze the effect of precipitation correction algorithms on the gauge data quality. Both correction methods rely on empirical constants to account for known external influences on the measurements, following a generic and a site-specific approach. Reference precipitation data were obtained from high-precision weighable lysimeters of the TERrestrial ENvironmental Observatories (TERENO)-SOILCan lysimeter network. Gauge types included tipping bucket gauges (TBs), weighable gauges (WGs), acoustic sensors (ASs) and optical laser disdrometers (LDs). From 2015-2018, data were collected at three locations in Germany, and 1 h aggregated values for precipitation above a threshold of 0.1 mm h−1 were compared. The results show that all investigated measurement methods underestimated the precipitation amounts relative to the lysimeter references for long-term precipitation totals with catch ratios (CRs) of between 33 %–92 %. Data from ASs had overall biases of −0.25 to −0.07 mm h−1, while data from WGs and LDs showed the lowest measurement bias (−0.14 to −0.06 mm h−1 and −0.01 to −0.02 mm h−1). Two TBs showed systematic deviations with biases of −0.69 to −0.61 mm h−1, while other TBs were in the previously reported range with biases of −0.2 mm h−1. The site-specific and generic correction schemes reduced the hourly measurement bias by 0.13 and 0.08 mm h−1 for the TBs and by 0.09 and 0.07 mm h−1 for the WGs and increased long-term CRs by 14 % and 9 % and by 10 % and 11 %, respectively. It could be shown that the lysimeter reference operated with minor uncertainties in long-term measurements under different site and weather conditions. The results indicate that considerable precipitation measurement errors can occur even at well-maintained and professionally operated stations equipped with standard precipitation gauges. This generally leads to an underestimation of the actual precipitation amounts. The results suggest that the application of relatively simple correction schemes, manual or automated data quality checks, instrument calibrations, and/or an adequate choice of observation period can help improve the data quality of gauge-based measurements for water balance calculations, ecosystem modeling, water management, assessment of agricultural irrigation needs, or radar-based precipitation analyses.","PeriodicalId":13143,"journal":{"name":"Hydrology and Earth System Sciences","volume":"21 1","pages":"0"},"PeriodicalIF":5.7000,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation of precipitation measurement methods using data from a precision lysimeter network\",\"authors\":\"Tobias Schnepper, Jannis Groh, Horst H. Gerke, Barbara Reichert, Thomas Pütz\",\"doi\":\"10.5194/hess-27-3265-2023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. Accurate precipitation data are essential for assessing the water balance of ecosystems. Methods for point precipitation determination are influenced by wind, precipitation type and intensity and/or technical issues. High-precision weighable lysimeters provide precipitation measurements at ground level that are less affected by wind disturbances and are assumed to be relatively close to actual precipitation. The problem in previous studies was that the biases in precipitation data introduced by different precipitation measurement methods were not comprehensively compared with and quantified on the basis of those obtained by lysimeters in different regions in Germany. The aim was to quantify measurement errors in standard precipitation gauges as compared to the lysimeter reference and to analyze the effect of precipitation correction algorithms on the gauge data quality. Both correction methods rely on empirical constants to account for known external influences on the measurements, following a generic and a site-specific approach. Reference precipitation data were obtained from high-precision weighable lysimeters of the TERrestrial ENvironmental Observatories (TERENO)-SOILCan lysimeter network. Gauge types included tipping bucket gauges (TBs), weighable gauges (WGs), acoustic sensors (ASs) and optical laser disdrometers (LDs). From 2015-2018, data were collected at three locations in Germany, and 1 h aggregated values for precipitation above a threshold of 0.1 mm h−1 were compared. The results show that all investigated measurement methods underestimated the precipitation amounts relative to the lysimeter references for long-term precipitation totals with catch ratios (CRs) of between 33 %–92 %. Data from ASs had overall biases of −0.25 to −0.07 mm h−1, while data from WGs and LDs showed the lowest measurement bias (−0.14 to −0.06 mm h−1 and −0.01 to −0.02 mm h−1). Two TBs showed systematic deviations with biases of −0.69 to −0.61 mm h−1, while other TBs were in the previously reported range with biases of −0.2 mm h−1. The site-specific and generic correction schemes reduced the hourly measurement bias by 0.13 and 0.08 mm h−1 for the TBs and by 0.09 and 0.07 mm h−1 for the WGs and increased long-term CRs by 14 % and 9 % and by 10 % and 11 %, respectively. It could be shown that the lysimeter reference operated with minor uncertainties in long-term measurements under different site and weather conditions. The results indicate that considerable precipitation measurement errors can occur even at well-maintained and professionally operated stations equipped with standard precipitation gauges. This generally leads to an underestimation of the actual precipitation amounts. 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引用次数: 0
摘要
摘要准确的降水数据是评价生态系统水分平衡的基础。确定点降水的方法受风、降水类型和强度和/或技术问题的影响。高精度可称重的降水计提供地面降水测量,受风干扰的影响较小,并且假定相对接近实际降水。以往研究存在的问题是,不同降水测量方法引入的降水数据偏差没有在德国不同地区溶渗仪获得的降水数据的基础上进行全面的比较和量化。目的是量化标准降水计与参考渗湿计的测量误差,并分析降水校正算法对测量数据质量的影响。这两种校正方法都依赖于经验常数来解释已知的外部对测量的影响,遵循通用和特定地点的方法。参考降水数据由TERENO -SOILCan网络的高精度可称重渗湿仪获得。量具类型包括翻斗量具(TBs)、可称重量具(WGs)、声学传感器(ASs)和光学激光测差仪(ld)。2015-2018年,在德国的三个地点收集了数据,并比较了超过0.1 mm h−1阈值的1 h累积值。结果表明,所有研究的测量方法相对于长期降水总量的蒸渗计参考资料都低估了降水量,其捕获比在33% ~ 92%之间。来自as的数据总体偏差为- 0.25至- 0.07 mm h - 1,而来自WGs和ld的数据显示最小的测量偏差(- 0.14至- 0.06 mm h - 1和- 0.01至- 0.02 mm h - 1)。两个TBs显示出系统偏差,偏差为−0.69至−0.61 mm h−1,而其他TBs在先前报道的范围内,偏差为−0.2 mm h−1。位点特异性和一般校正方案分别使TBs的每小时测量偏差降低了0.13和0.08 mm h - 1, WGs的每小时测量偏差降低了0.09和0.07 mm h - 1,长期cr分别提高了14%和9%,10%和11%。可以看出,在不同地点和天气条件下的长期测量中,渗湿计基准的不确定度较小。结果表明,即使在配备标准降水计的维护良好和专业操作的台站,也会出现相当大的降水测量误差。这通常会导致对实际降水量的低估。结果表明,采用相对简单的校正方案、手动或自动数据质量检查、仪器校准和/或适当选择观测周期,有助于提高基于量具的水平衡计算、生态系统建模、水资源管理、农业灌溉需求评估或基于雷达的降水分析的数据质量。
Evaluation of precipitation measurement methods using data from a precision lysimeter network
Abstract. Accurate precipitation data are essential for assessing the water balance of ecosystems. Methods for point precipitation determination are influenced by wind, precipitation type and intensity and/or technical issues. High-precision weighable lysimeters provide precipitation measurements at ground level that are less affected by wind disturbances and are assumed to be relatively close to actual precipitation. The problem in previous studies was that the biases in precipitation data introduced by different precipitation measurement methods were not comprehensively compared with and quantified on the basis of those obtained by lysimeters in different regions in Germany. The aim was to quantify measurement errors in standard precipitation gauges as compared to the lysimeter reference and to analyze the effect of precipitation correction algorithms on the gauge data quality. Both correction methods rely on empirical constants to account for known external influences on the measurements, following a generic and a site-specific approach. Reference precipitation data were obtained from high-precision weighable lysimeters of the TERrestrial ENvironmental Observatories (TERENO)-SOILCan lysimeter network. Gauge types included tipping bucket gauges (TBs), weighable gauges (WGs), acoustic sensors (ASs) and optical laser disdrometers (LDs). From 2015-2018, data were collected at three locations in Germany, and 1 h aggregated values for precipitation above a threshold of 0.1 mm h−1 were compared. The results show that all investigated measurement methods underestimated the precipitation amounts relative to the lysimeter references for long-term precipitation totals with catch ratios (CRs) of between 33 %–92 %. Data from ASs had overall biases of −0.25 to −0.07 mm h−1, while data from WGs and LDs showed the lowest measurement bias (−0.14 to −0.06 mm h−1 and −0.01 to −0.02 mm h−1). Two TBs showed systematic deviations with biases of −0.69 to −0.61 mm h−1, while other TBs were in the previously reported range with biases of −0.2 mm h−1. The site-specific and generic correction schemes reduced the hourly measurement bias by 0.13 and 0.08 mm h−1 for the TBs and by 0.09 and 0.07 mm h−1 for the WGs and increased long-term CRs by 14 % and 9 % and by 10 % and 11 %, respectively. It could be shown that the lysimeter reference operated with minor uncertainties in long-term measurements under different site and weather conditions. The results indicate that considerable precipitation measurement errors can occur even at well-maintained and professionally operated stations equipped with standard precipitation gauges. This generally leads to an underestimation of the actual precipitation amounts. The results suggest that the application of relatively simple correction schemes, manual or automated data quality checks, instrument calibrations, and/or an adequate choice of observation period can help improve the data quality of gauge-based measurements for water balance calculations, ecosystem modeling, water management, assessment of agricultural irrigation needs, or radar-based precipitation analyses.
期刊介绍:
Hydrology and Earth System Sciences (HESS) is a not-for-profit international two-stage open-access journal for the publication of original research in hydrology. HESS encourages and supports fundamental and applied research that advances the understanding of hydrological systems, their role in providing water for ecosystems and society, and the role of the water cycle in the functioning of the Earth system. A multi-disciplinary approach is encouraged that broadens the hydrological perspective and the advancement of hydrological science through integration with other cognate sciences and cross-fertilization across disciplinary boundaries.