Standard Rain Gauge Research Articles

Evaluation of precipitation measurements using a standard rain gauge in relation to data from a precision lysimeter

Abstract The construction of modern lysimeters with a precise weighing system made it possible to achieve an unprecedented accuracy of precipitation measurement. This study compares two methods of measuring precipitation in the conditions of the humid continental climate of the Eastern Slovakian Lowland (Slovakia): measurement using a standard tipping-bucket rain gauge vs. precision weighable lysimeter. Data from the lysimeter were used as a reference measurement. The comparison period lasted four years (2019–2022). Only liquid rainfall was compared. The rain gauge was found to underestimate precipitation compared to the lysimeter. Cumulative precipitation for the entire monitored period captured by the rain gauge was 2.8% lower compared to lysimeter measurements. When comparing hourly and daily totals of precipitation and precipitation events, a very high degree of agreement was detected (r 2 > 0.99; RMSE from 0.22 to 0.51 mm h–1). A comparison based on precipitation intensity showed a decreasing trend in measurement accuracy with increasing precipitation intensity. This tendency has an exponential course. With increasing intensity of precipitation, increasing intensity of wind was also recorded. In order to correct measurement errors, simple correction method was proposed, which helped to partially eliminate the inaccuracies of the rain gauge measurement.

Developing a Formula to Estimate Precipitation at Ungauged Location and Analysis of Rainfall Pattern: Case Study for Rastra Bank Chowk, Pokhara, Nepal

Pokhara receives the second highest amount of rainfall in the country, according to Department of Hydrology and Meteorology. The rainfall distribution within this small region is random. The precipitation in Pokhara is measured from limited rain gauge stations. For understanding the spatial variation, it is necessary to access the daily rainfall data at the gauged as well as ungauged stations. In view of this problem, this study is aimed at developing the formula to estimate the rainfall value at an ungauged station, Rastrabank Chowk Pokhara using the calibration and validation method. For this purpose, the daily rainfall data of the sample station was measured using standard rain gauge for a period of four months from May 13, 2020 to September 15, 2020. The analysis of the spatial distribution and variation of daily rainfall at meteorological stations as well as sample station was done to select the data for the development of the formula. Calibration and validation of formula was performed for equal period using the statistical indices NSE, R2 and PBIAS. Calibration was performed using rainfall data of available meteorological stations of Pokhara in the first two consecutive months. From the numerous hit and trial procedures, the equation developed with rainfall data of Airport and Malepatan stations comprising of three constant values were obtained with the highest NSE and R2. PBIAS value was then calculated for maximum NSE and R2. In the next phase, validation of the equation for other two months (14 July- 15 September,2020) was performed to obtain maximum possible value of NSE and R2 and a smaller value of PBIAS. The equation was obtained with 0.980 NSE, 0.980 R2 and 6.437 % PBIAS value which indicated good agreement between observed and predicted rainfall value. Spatial rainfall pattern analysis using SURFER model demonstrated that there was a homogenous distribution of rainfall in Malepatan, Airport and sample stations. The temporal trend showed that the month July of 2020 had a higher amount of precipitation at Pokhara valley. From the HYSPLIT model, it was observed that the rainfall events in Pokhara valley was due to westerlies dominance. This study would provide the rainfall estimation techniques and hence would significantly contribute to meteorological investigations and water resource planning.

The wettest place in Sri Lanka

The average annual rainfall of Sri Lanka varies from 900 mm to 5,500 mm. A debate and misconception have continued on the “wettest place” or the rain gauge station that receives the highest rainfall in the country. Seven rain-gauge stations (seven locations) were selected considering the regions receiving with probable highest rainfall in Sri Lanka. The average annual total rainfall and average number of rainy days were analysed using daily rainfall data covering the most recent five years (2015 – 2019) to detect the rain gauge station receiving the highest rainfall. Among the locations considered, the newly established rain gauge station at the Welioya Estate (6.9288 N, 80.5582E, 1,258 m amsl) reported the highest rainfall, where the estate has received an average annual rainfall of 5,081 mm. Except during the South West Monsoon (SWM) season (May to September), the three rain-gauge stations located around Watawala Estate have recorded the lowest cumulative seasonal rainfall catch resulting in the same pattern of ranks in the average annual total rainfall. This study revealed that the Welioya Estate in Hatton receives the highest average annual rainfall in Sri Lanka. However, absence of standard rain-gauges installed in many locations in Sri Lanka to collect daily observations is a drawback in conducting detailed analysis rainfall across all agro-ecological regions in Sri Lanka.

Evaluation of precipitation measurements methods under field conditions during a summer season: A comparison of the standard rain gauge with a weighable lysimeter and a piezoelectric precipitation sensor

Current precipitation measurements are conducted largely by simple automatic rain gauges. Despite being error-prone and sometimes of questionable accuracy, the procedure is still widely used. In recent years new possibilities have emerged, which are based on different measuring principles. Although the application of alternative devices is increasing, its use in research is limited. In this study, precipitation measurements by different devices were compared, and systematic errors caused by individual characteristics were corrected. Data were collected by means of a monitoring network, which included a piezoelectric precipitation sensor mounted at 2.3 m, a standard tipping bucket at 1 m, and a weighable gravitation lysimeter at ground level. As measurements at ground level are considered as optimum, the records of the lysimeter were thereby determined as a reference. The results showed that precipitation measured by elevated rain gauges differed in total between −6.8% and +35% compared to rainfall measured by the lysimeter. The records correlated well, but the analyses indicated a strong influence of the precipitation intensity on the recorded amount of precipitation. The deviations between values of the rain gauges and those of the lysimeter increased with rainfall intensity. In general, the tipping bucket demonstrated negative error values and indicated an underestimation of precipitation compared to records at ground level, whereas the piezoelectric precipitation sensor showed an overestimation by highly positive error values. A subsequent precipitation correction through the linear scaling method improved significantly the raw data of the rain gauges.

Correlating pattern of river discharge with degree of urbanization in sub-catchments of River Asa in Ilorin, Nigeria

The study examined the hydrological response pattern of urbanized streams to landuse in sub-catchment areas of River Asa in Ilorin, Nigeria. Data for the study were collected directly from the field over a period of one hydrological year. Rainfall data were collected in each basin using a standard rain gauge of 20cm orifice while basin discharge was computed from a rating equation generated from stage readings on staff gauge mounted at the outlet of each of the study basin. Landuse map of the study area was prepared from satellite imagery obtained from Regional Centre for Training in Aerospace Survey (RECTAS), Obafemi Awolowo University, Ile-Ife. Result obtained indicates that runoff discharge in all the studied basins reflects closely the rainfall pattern with periods of peak discharge coinciding with periods of heavy rainfall. The study further reveals that basin landuse characteristics have profound influence on pattern of river discharge. Based on the result obtained, the study recommends a number of options to efficient basin management in the city. Keywords: Pattern, Discharge, Landuse, Urbanization, Sub-catchment

Spatial Characteristics of Rainfall at Sparsely Distributed Station Network over the High-Latitude Mountainous Regions in Eastern Siberia

To describe the spatial characteristics of rainfall at sparsely distributed measurement network over the high-latitude mountainous regions in eastern Siberia through ground-based observation, rainfall observations were performed using non-recording standard rain gauges. Such standard rain gauges have been used over the years to measure annual rainfall at six sites from the Suntar Khayata Range to Oymyakon and 12 sites along the Kolyma Highway from Magadan to Agayakan. Relational expressions of rainfall were obtained and observation data from these gauges clearly showed that the corrected rainfall in these areas depends on altitude, that the rainfall increased slightly with an increase in altitude, and that the increased ratio of rainfall due to altitude decreased with an increase in the distance from the nearby coast.

Validation of TRMM and FEWS Satellite Rainfall Estimates with Rain Gauge Measurement over Ashanti Region, Ghana

Satellite rainfall estimates have predominantly been used for climate impact studies due to poor rain gauge network in sub-Saharan Africa. However, there are limited microscale studies within the sub-region that have assessed the performance of these satellite products, which is the focus of the present study. This paper therefore considers validation of Tropical Rainfall Measuring Mission (TRMM) and Famine Early Warning System (FEWS) satellite estimates with rain gauge measurements over Ashanti region of Ghana. First, a consistency assessment of the two gauge data products, the Automatic Rain Gauge (ARG) and Ghana Meteorological Agency (GMet) Standard Rain Gauge (SRG) measurements, was performed. This showed a very good agreement with correlation coefficient of 0.99. Secondly, satellite rainfall products from TRMM and FEWS were validated with the two gauge measurements. Validation results showed good agreement with correlation coefficients of 0.6 and 0.7 for TRMM and FEWS with SRG, and 0.87 and 0.86 for TRMM and FEWS with ARG respectively. Probability Of Detection (POD) and Volumetric Hit Index (VHI) were found to be greater than 0.9. Volumetric Critical Success Index (VCSI) was 0.9 and 0.8 for TRMM and FEWS respectively with low False Alarm Ratio (FAR) and insignificant Volumetric Miss Index (VMI). In general, relatively low biases and RMSE values were observed. The biases were less than 1.3 and 0.8 for TRMM and FEWS-RFE respectively. These indicate high rainfall detection capabilities of both satellite products. In addition, both TRMM and FEWS were able to capture the onset, peak and cessation of the rainy season, as well as the dry spells. Although TRMM and FEWS sometimes under/overestimated rainfall, they have the potential to be used for agricultural and other hydro-climatic impact studies over the region. The Dynamic-Aerosol-Cloud-Chemistry Interactions in West Africa (DACCIWA) project will provide an improved spatial gauge network database over the study area to enhance future validation and other climate impact studies.

Actual evapotranspiration and precipitation measured by lysimeters: a comparison with eddy covariance and tipping bucket

Abstract. This study compares actual evapotranspiration (ETa) measurements by a set of six weighable lysimeters, ETa estimates obtained with the eddy covariance (EC) method, and evapotranspiration calculated with the full-form Penman–Monteith equation (ETPM) for the Rollesbroich site in the Eifel (western Germany). The comparison of ETa measured by EC (including correction of the energy balance deficit) and by lysimeters is rarely reported in the literature and allows more insight into the performance of both methods. An evaluation of ETa for the two methods for the year 2012 shows a good agreement with a total difference of 3.8% (19 mm) between the ETa estimates. The highest agreement and smallest relative differences (< 8%) on a monthly basis between both methods are found in summer. ETa was close to ETPM, indicating that ET was energy limited and not limited by water availability. ETa differences between lysimeter and EC were mainly related to differences in grass height caused by harvest and the EC footprint. The lysimeter data were also used to estimate precipitation amounts in combination with a filter algorithm for the high-precision lysimeters recently introduced by Peters et al. (2014). The estimated precipitation amounts from the lysimeter data differ significantly from precipitation amounts recorded with a standard rain gauge at the Rollesbroich test site. For the complete year 2012 the lysimeter records show a 16 % higher precipitation amount than the tipping bucket. After a correction of the tipping bucket measurements by the method of Richter (1995) this amount was reduced to 3%. With the help of an on-site camera the precipitation measurements of the lysimeters were analyzed in more detail. It was found that the lysimeters record more precipitation than the tipping bucket, in part related to the detection of rime and dew, which contribute 17% to the yearly difference between both methods. In addition, fog and drizzle explain an additional 5.5% of the total difference. Larger differences are also recorded for snow and sleet situations. During snowfall, the tipping bucket device underestimated precipitation severely, and these situations contributed also 7.9% to the total difference. However, 36% of the total yearly difference was associated with snow cover without apparent snowfall, and under these conditions snow bridges and snow drift seem to explain the strong overestimation of precipitation by the lysimeter. The remaining precipitation difference (about 33%) could not be explained and did not show a clear relation to wind speed. The variation of the individual lysimeters devices compared to the lysimeter mean are small, showing variations up to 3% for precipitation and 8% for evapotranspiration.

Toward the camera rain gauge

AbstractWe propose a novel technique based on the quantitative detection of rain intensity from images, i.e., from pictures taken in rainy conditions. The method is fully analytical and based on the fundamentals of camera optics. A rigorous statistical framing of the technique allows one to obtain the rain rate estimates in terms of expected values and associated uncertainty. We show that the method can be profitably applied to real rain events, and we obtain promising results with errors of the order of . A precise quantification of the method's accuracy will require a more systematic and long‐term comparison with benchmark measures. The significant step forward with respect to standard rain gauges resides in the possibility to retrieve measures at very high temporal resolution (e.g., 30 measures per minute) at a very low cost. Perspective applications include the possibility to dramatically increase the spatial density of rain observations by exporting the technique to crowdsourced pictures of rain acquired with cameras and smartphones.

바람의 영향을 고려한 지상강우의 보정방법 연구

The purpose of this paper is to obtain reliable rainfall data for runoff simulation and other hydrological analysis by the calibration of gauge rainfall. The calibrated gauge rainfall could be close to the actual value with rainfall on the ground. In order to analyze the wind effect of ground rain gauge, we selected the rain gauge sites with and without a windshield and standard rain gauge data from Chupungryeong weather station installed by standard of WMO. Simple linear regression model and artificial neural networks were used for the calibration of rainfalls, and we verified the reliability of the calibrated rainfalls through the runoff analysis using . Rainfall calibrated by linear regression is higher amount of rainfall in 5%~18% than actual rainfall, and the wind remarkably affects the rainfall amount in the range of wind speed of 1.6~3.3m/s. It is hard to apply the linear regression model over 5.5m/s wind speed, because there is an insufficient wind speed data over 5.5m/s and there are also some outliers. On the other hand, rainfall calibrated by neural networks is estimated lower rainfall amount in 10~20% than actual rainfall. The results of the statistical evaluations are that neural networks model is more suitable for relatively big standard deviation and average rainfall. However, the linear regression model shows more suitable for extreme values. For getting more reliable rainfall data, we may need to select the suitable model for rainfall calibration. We expect the reliable hydrologic analysis could be performed by applying the calibration method suggested in this research.

Observation of the nitrogen deposition in the lower Liaohe River Plain, Northeast China and assessing its ecological risk

Little information about the nitrogen (N) deposition in the lower Liaohe River Plain (LRP) of Northeast China was available. A continuous 5-year observation (from 2004 to 2008) was conducted to determine the nitrogen deposition in precipitation collected by a standard rain gage, and then we assessed its ecological consequences. The mean inorganic nitrogen concentrations were 1.82 mg N L −1 for NH 4 +–N and 0.89 mg N L −1 for NO 3 −–N. On an annual basis, the averaged amounts of N deposition were 14.5 kg N ha −1 year −1, which were much lower than that of hotspots in China. However, the amount of deposited N should still be taken account into the N fertilizer management of the agroecosystems. Compared with the critical loads (CL) of N deposition, the deposited N would likely threaten the natural ecosystems in LRP. The N concentrations in rainwater and the amount of N deposition showed a clear seasonal pattern, and precipitation played an important role in regulating the N concentration. Furthermore, the seasonal fluctuation of NH 4 +/NO 3 − ratio reflected that the deposited N originated from both fertilizer application and fossil fuel combustion, and environmental factor (soil temperature, lightning and sunshine) might also contribute to the seasonal cycles of NH 4 +/NO 3 − ratio. The high annual NH 4 +/NO 3 − ratio (2.05) compared with the more developed region suggested that N deposition in this region was mostly affected by agricultural activities rather than industrial activities.

Influence of the Sampling Period on the Deposition Time Series of Major Ions in Bulk Precipitation

The influence of a change from daily to weekly sampling of bulk precipitation on the obtained deposition values was studied with parallel sampling for 8 months at the station of Virolahti in 2004. Due to dry deposition, the deposition values of the whole period were found to be 5–70% higher from weekly sampling than from daily sampling, the biggest difference being for K+, Ca2+, Mg+ and Na+. The collection efficiencies of the summer sampler and the winter sampler compared to the standard rain gauge were studied from daily sampling in 1991–2003 and weekly sampling in 2004–2008. The performance was best in summer and in winter with rain samples (median value 85–88%), while the median value for daily snow samples was 72%. In winter, the total sum of precipitation collected in the daily sampler and the weekly sampler was 78% and 69%, respectively. The deficit in the weekly sampler in winter was concluded to be due to evaporation, while from the summer sampler no evaporation seemed to occur. Use of the precipitation amount measured by the standard rain gauge when calculating annual precipitation-weighted mean values gave higher mean concentrations than the use of the precipitation measured by the deposition sampler itself, the biggest difference of 8–11% being in the sea-salt ions Cl−, Mg+ and Na+. It was concluded that the concentration and deposition values measured by daily and weekly bulk sampling are incompatible, and should not be combined into the same time series.

Using Surface Tension Measurements To Understand How Pollution Can Influence Cloud Formation, Fog, and Precipitation

In remote locations, atmospheric aerosols are predominately composed of sulfates. However, in some polluted locations, as much as 50% of the aerosol mass can be composed of organic compounds. These organic molecules reduce the surface tension of aqueous droplets in the atmosphere leading to changes in several important atmospheric parameters, including the conditions required for cloud formation, cloud droplet number concentrations, and local precipitation patterns. To assess how much certain individual compounds contribute to changes in surface tension, laboratory measurements are made on a series of dicarboxylic acids, representative of the organic compounds found in the atmosphere. In this experiment, students first measure the surface tension of solutions containing oxalic, succinic, glutaric, and adipic acid to assess how much these can reduce the surface tension of water as a function of organic concentration. Second, using a low-cost, easy-to-build fog collector and a standard rain gauge, the students collect real-world samples and measure their surface tension. Trends in surface tension behavior of the real-world precipitation samples are compared to the solutions of known compounds, and atmospheric implications are discussed.

Atmospheric nitrogen deposition in south-east Scotland: Quantification of the organic nitrogen fraction in wet, dry and bulk deposition

Water soluble organic nitrogen (WSON) compounds are ubiquitous in precipitation and in the planetary boundary layer, and therefore are a potential source of bioavailable reactive nitrogen. This paper examines weekly rain data over a period of 22 months from June 2005 to March 2007 collected in 2 types of rain collector (bulk deposition and “dry + wet” deposition) located in a semi-rural area 15 km southwest of Edinburgh, UK (N55°51′44″, W3°12′19″). Bulk deposition collectors are denoted in this paper as “standard rain gauges”, and they are the design used in the UK national network for monitoring precipitation composition. “Dry + wet” deposition collectors are flushing rain gauges and they are equipped with a rain detector (conductivity array), a spray nozzle, a 2-way valve and two independent bottles to collect funnel washings (dry deposition) and true wet deposition. On average, for the 27 weekly samples with 3 valid replicates for the 2 types of collectors, dissolved organic nitrogen (DON) represented 23% of the total dissolved nitrogen (TDN) in bulk deposition. Dry deposition of particles and gas on the funnel surface, rather than rain, contributed over half of all N-containing species (inorganic and organic). Some discrepancies were found between bulk rain gauges and flushing rain gauges, for deposition of both TDN and DON, suggesting biological conversion and loss of inorganic N in the flushing samplers.

Spatial variability in precipitation within the Hilton Experimental Site, Shropshire, UK (1982–2006)

AbstractAccurate precipitation measurements are essential for many hydrological and hydrogeological management strategies. Precipitation at the Hilton Experimental Site has been regularly measured since 1982. This paper summarises 157 rain gauge years of precipitation data, recorded between 1982 and 2006, using 11 rain gauges on the 0·5 hectare site. Precipitation varied markedly within the site. Precipitation totals were notably different between two adjacent rain gauges, the mean difference being 0·3% of the total. Variations in mean annual precipitation within the site were ⩽8%. Spatial variations in wind turbulence appeared to be the main factor influencing intra‐site variability. Precipitation totals varied with gauge exposure, with surface level gauges receiving ⩽5·9% more precipitation than standard rain gauges, the difference being less lower down the slope. On a steep (∼15° ) slope, basal sections had 2·5–7·9% more precipitation. Upper gauges received less, probably due to turbulence as increased exposure on the top of the slope resulted in precipitation being carried over the gauge orifice. Results confirm that due attention must be given to the inherent variability of precipitation amounts when calculating precipitation inputs. Copyright © 2008 John Wiley & Sons, Ltd.

Understanding winter sodium deposition in Taranaki, New Zealand

Research conducted in a limited number of regions has identified that Na deposition rate (kg Na/ha) is strongly influenced by 4 main factors: distance from coast, rainfall, wind speed, and wind direction. Despite the potential importance of Na deposition to the productivity of dairy farms, no comprehensive research has been conducted in Taranaki, New Zealand. Na, K, Ca, and Mg concentrations were determined in weekly rainwater samples collected in standard rain gauges erected at 15 sites, along 4 transects around Taranaki, between May and September 2006. Recorded Na concentrations ranged between 0.40 and 38 mg/L. High Na concentrations were associated with low rainfall volumes and proximity to the coast first receiving the prevailing wind, which was, during this period, the southern Taranaki coast. Na deposition ranged between 0.04 and 25 kg/ha.week. Equations were derived to predict the average Na concentration in rainwater and Na deposition in Taranaki for the 2006 winter period. The most influential factor explaining the variation in average Na concentration was the distance of the collector from the southern coast. Na and Mg depositions were highly correlated (R2 = 0.93; P < 0.01; n = 155), whereas correlations of Na with K or Ca were not as strong (R2 = 0.49 and 0.61, respectively). Measured Na deposition rates exceed those predicted by algorithms used in current nutrient budgeting software and could be used to improve this nutrient management software.

Radar and Rain Gauge Analysis of the Extreme Rainfall during Hurricane Danny’s (1997) Landfall

Abstract As a minimal hurricane, Danny moved over Mobile Bay around 0900 UTC 19 July 1997 and became stationary by midmorning, while situated within a synoptic col. Danny then evolved into an asymmetric storm with an intensely convective rainband that produced torrential rainfall through 1200 UTC 20 July 1997. Danny’s center remained <100 km from the National Weather Service (NWS) Weather Surveillance Radar-1988 Doppler (WSR-88D) in Mobile, Alabama, for over 48 h, allowing long-term surveillance of the storm’s inner core. This event marked the first time the tropical Z–R relationship was employed on an operational WSR-88D system during tropical cyclone landfall. A radar-estimated maximum rainfall accumulation of 1097 mm (43.2 in.) was analyzed over southwestern Mobile Bay. A NWS cooperative rain gauge located on Dauphin Island, Alabama, measured 896 mm (35.28 in.). An adjacent standard rain gauge measured the highest rainfall amount of 932 mm (36.71 in.). This paper investigates the spatial and temporal distribution and potential magnitude of Danny’s torrential rainfall episode over coastal Alabama. It is shown that both gauges and radar seriously underestimated event rainfall. An estimate is given for what could have been the true event rainfall amount. In the case of the radar, the WSR-88D Algorithm Testing and Display System is used to obtain a better estimate of rainfall using higher dBZ caps than the operational 50 dBZ. In the case of the tipping-bucket rain gauge, wind and mechanical error estimates were applied in order to quantify rainfall underestimation.

Investigation of the nonlinear hydrologic response to precipitation forcing in physically based land surface modeling

This paper is concerned with the effect of precipitation forcing on land surface hydrological variables predicted by a physically based land surface scheme. The aspects considered are the differences in precipitation input across varying sensor measurements and temporal scales of aggregation. Precipitation accumulations at 1-, 2-, 3-, and 6-h time scales are derived on the basis of standard 5-min rain gauge rainfall measurements, hourly rain gauge calibrated WSR-88D radar rainfall estimates, and passive microwave calibrated half-hourly satellite infrared rain retrievals. The spatial resolution of the rainfall estimates is fixed to 1° grid boxes. The off-line community land model (CLM) is used to simulate land surface parameters on the basis of external meteorological forcing parameters. The study region and data consist of two vegetation-distinct (high and low vegetation cover) sites in Oklahoma. The data used include one warm season (May–August 2002) of in situ meteorological data from the Oklahoma Mesonet. The CLM is forced with the three different rainfall input datasets for varying temporal scales (1–6 h). Relative difference statistics in terms of rainfall and land surface parameters are presented between the two remote sensing rain retrievals and the gauge rainfall measurements used as reference. Results show that the hydrological response is nonlinear and strongly dependent on the error characteristics of the retrieval (e.g., more temporal correlated rainfall error results in higher error propagation in land surface parameters). We also investigate the temporal lag correlation of the error in rainfall with the error in the various land surface hydrological variables. Time resolution is shown to have an effect on the error statistics of the hydrologic variables. Coarse time resolutions are associated with errors of lower variance and higher correlation.

0.01 mm 급 우량계 개발에 관한 연구

A new method of automatic recording raingauge is developed to measure rainfall with 0.01mm resolution. This use two different signals to measure rainfall more accurately compare than other raingauges. One is weight of the tipping bucket with rainfall amount and the other is pulse from tipping bucket reverse. New method applied 1 mm tipping bucket mechanism and install loadcell under tipping bucket mechanism for measuring rainfall weight. Loadcell measure weight of rainfall until 1 mm with 0.01 mm resolution and more than 1 mm than bucket reverse and pulse signal generate, after that loadcell measure weight again. The validation of new instrument was examined in the room 65 mm/hour rainfall rate total 53 mm range. There is below than 1 % error of absolute rainfall amount and 0.01 mm resolution. The field test of instrument was carried out by comparing its measured values with values recorded by weight type and standard type on June 1 2003 at Terrestrial Environmental Research Center at Tsukuba University in Tsukuba of Japan, when it has recorded total amount of 40.58 mm rainfall by standard raingauge and new raingauge recorded 41.032 mm. Same rainfall intensity pattern observed in field observation with weight type raingauge. Rainfall intensity between weight type and Lee-A type raingauge reached 0.9947 correlation in 3 minute average.

THE IRRIGAGE: A NON?EVAPORATING IN?FIELD PRECIPITATION GAGE

Construction details and measurement data associated with a non-evaporating, in-field precipitation gage (theIrriGage) are presented. IrriGages are fabricated using standard pieces of PVC pipe and fittings. A plastic bottle is used tostore collected water and is attached to the bottom of the collection barrel. Collected water is only exposed to the atmospherethrough the collection barrel via a 9.5-mm drain hole. Evaporative losses from IrriGages were compared to losses from otherprecipitation collection devices in an in-field device evaporation study during the 2001 summer. During the study period,air temperatures often exceeded 38.C and daily grass-reference evapotranspiration rates exceed 8 mm/day. Evaporationlosses from IrriGages were negligible over several weeklong measurement periods, while substantial evaporation losses wereassociated with standard rain gages and other collection devices.