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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. [ABSTRACT FROM AUTHOR]

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 "true" precipitation. The problem in previous studies was that the biases on precipitation data introduced by different precipitation measurement methods were not comprehensively compared and quantified with those obtained by lysimeters under different climatic conditions. The aim was to quantify measurement errors of standard precipitation gauges as compared to the lysimeter reference and to analyse 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 TERrestial Environmental Observatories (TERENO)-SOILCan lysimeter network. Gauge types included tipping bucket gauges (TBs), weighable gauges WGs), acoustical sensors (ASs), and optical laser disdrometers (LDs). The data were collected from 2015-2018 at three sites in Germany and compared with a temporal resolution of 1 hour for precipitation above a threshold of 0.1 mm h-1. 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) 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 measuring biases (-0.14 to -0.06 mm h- 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 measuring 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 climatic conditions. The results indicate that even with well-maintained and professionally operated stations, considerable precipitation measurement errors can occur, which generally lead to a loss of recorded precipitation amounts. Data from standard precipitation gauges therefore still represent potentially significant uncertainty factors. The results suggest that the application of relatively simple correction schemes, manual or automated data quality checks, instrument calibrations and/or adequate choice of observation periods can help improve the data quality of gauge-based measurements for water balance calculations, ecosystem modelling, water management, assessment of agricultural irrigation needs or radar-based precipitation analyses. [ABSTRACT FROM AUTHOR]

Copyright of Hydrogeology Journal is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of African Journal of Ecology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To characterize snow isotopic signatures, monitoring of snowmelt was carried out at two sites (Oukaimden and Ifni) in the Moroccan High Atlas Mountains. For the Oukaimden site, samples of snow were taken by two methods to compare sampling techniques: (1) coring with a polyvinyl chloride (PVC) tube and (2) passive capillary sampling (PCS) installed at the snow/soil interface. The analyses show variable isotope contents, ranging from −14.7 to −2.5 ‰ for oxygen-18 and from −116 to −28.2 ‰ for deuterium. The most depleted values are observed in March 2013 at high elevation (3229 m asl). The majority of snow core samples display fractionation by sublimation, whereas those collected by the PCS sampling method are close to the Global Meteoric Water Line. The isotopic signature is comparable for snow, surface water and groundwater samples, indicating that snowmelt plays an important role in recharging aquifers, lakes, and rivers on the southern and northern sides of the Atlas Mountains. Recharge by snowmelt allows the dilution of salinity in adjacent aquifers. Characterization of the stable isotopic composition of snow obtained from snow cores is limited in comparison with the PCS method, which provides realistic compositions of the melt water contribution to water resources in this semi-arid area. [ABSTRACT FROM AUTHOR]