Tipping Bucket Rain Gauges Research Articles

Development of an Automatic Portable Calibrator for Tipping Bucket Rain Gauge (TBRG) Using a Load Cell and Simple Water Sensor

The tipping bucket rain gauge is an automatic rain gauge that can measure rain intensity in mm/hour. Accurate measurement of rain intensity requires calibration of the rain gauge to ensure traceability. Calibration of a tipping bucket rain gauge is related to the volume of water as a calibration medium and time so as to produce a discharge that can be converted into rain intensity. Technological developments can make tipping bucket rain gauge calibration automatic by utilizing an Arduino Mega2560 microcontroller, a load cell and a simple water sensor based on the LM393 comparator IC, and combined with a compact design printed using a three-dimensional printer so that it can be used for ex-situ calibration. The data produced by this tool can be downloaded via the application that was built and produces a file in Excel form.

Syphons in tipping bucket rain gauges: How do they affect rainfall intensity estimates derived from inter-tip times?

Tipping-bucket rain gauges (TBRGs) are widely used globally to record rainfall amounts over nominated accumulation durations such as 15-minute rainfall, hourly rainfall, and daily rainfall. To reduce the under-estimation of rainfall amounts that results from high rates of inflow to the tipping buckets in intense rainfall, small syphons are commonly installed between the rain-collecting funnel and the bucket mechanism. The syphon is designed to regulate the inflow, reducing the systematic error inherent in the basic TBRG mechanism.The inter-tip times (ITTs) of a TBRG are often used as a source of rainfall intensity data, since the ITTs provide the highest temporal resolution possible from such gauges. However, the influence of the syphon is generally neglected in this approach to intensity estimation. Experimental results are presented here from a high-quality TBRG fed with known rates of water inflow, simulating rain of various constant intensities. Tests were replicated with the syphon installed, and with it removed.Results confirm that the syphon significantly perturbs the sequence of ITTs, causing apparent fluctuations in intensity that do not in fact exist. At least two factors contribute to this. The first is the lack of correspondence between syphon and bucket volumes, such that more than one syphon operation may be needed to fill one bucket. The second factor is the continued inflow to the syphon during its emptying cycle. This lengthens the time required for the syphon to cycle, as well as worsening any mismatch between the amount of water discharged through the syphon to the tipping-bucket mechanism and the bucket capacity. In fact, there can be no fixed relationship between the syphon discharge volume and the capacity of a TBRG bucket. Therefore, one syphon emptying cycle can deliver more than the nominal 0.2 mm needed to trigger a tip event, such that the varying excess (dependent on the rainfall intensity) drains to the second bucket, which in turn tips earlier than would be expected. Consequently, even at constant intensity, the ITTs display increased variability, with widely-varying apparent intensities among successive ITTs. The variance among ITTs is shown always to be greater in data from a syphon-equipped TBRG than from a “straight-through” (no-syphon) gauge, such that the reliability of intensity data obtained from the ITTs of a syphon-equipped TBRG are reduced by the presence of the syphon.

In situ observations of rain rate and precipitation microphysics over the coastal area of South China: Perspectives for satellite validation

Abstract This study investigates precipitation observed by a set of collocated ground-based instruments in Zhuhai, a coastal city located at the southern tip of the Pearl River Delta of Guangdong Province in South China. Seven months of ground-based observations from a tipping-bucket rain gauge (RG), two laser disdrometers (PARSIVEL and PWS), and a vertically-pointing Doppler Micro Rain Radar-2 (MRR), spanning from December 2021 to July 2022, are statistically evaluated to provide a reliable reference for China’s spaceborne precipitation measurement mission. Rainfall measurement discrepancies are found between the instruments, though the collocated deployment mitigates uncertainties originating from spatial/temporal variabilities of precipitation. The RG underestimates hourly rain amounts at the observation site, opposite to previous studies, leading to 18.2% percent bias (Pbias) of hourly rain amounts when compared to the PARSIVEL. With the same measurement principle, the hourly-accumulated rain between the two laser disdrometers has a Pbias of 15.3%. Discrepancies between MRR and disdrometers are assumed to be due to different temporal/spatial resolution, instrument sensitivities and observation geometry, with a Pbias of mass-weighted mean diameter and normalized intercept parameter of gamma size distribution less than 9%. The vertical profiles of drop size distribution (DSD) derived from the MRR are further examined during extreme rainfalls in the East Asia monsoon season (May, June, and July). Attributed to the abundant moisture which favors the growth of raindrops, coalescence is identified as the predominant effective process and the raindrop mass-weighted mean diameter increases by 33.7% when falling from 2000 m to 600 m during the extreme precipitation event in May.

Judging Rainfall Intensity from Inter-Tip Times: Comparing ‘Straight-Through’ and Syphon-Equipped Tipping-Bucket Rain Gauge Performance

The inter-tip times (ITTs) of tipping-bucket rain gauges (TBRGs) potentially provide the highest-resolution intensity data that can be acquired from this type of gauge. At an intensity of 100 mm h−1, a typical gauge with a sensitivity of 0.2 mm of rainfall would be expected to tip every 7.2 s. However, TBRGs are often equipped with syphons to reduce the dynamic calibration error that results from continued (and unmeasured) inflow to a bucket as it tips. This increases the accuracy of rainfall depth recording, but the time to fill and empty the syphon can reduce the ability of a TBRG to respond to (and for the ITTs to reflect) short-term intensity fluctuations. This ability is already limited by the discretisation arising from the filling and emptying of the buckets themselves. Laboratory tests with controlled water inflow rates were performed using two high-quality TBRGs, one a ‘straight-through’ design and the other syphon-equipped. These confirmed that at all intensities at which the syphon operates, a regular sequence of fixed-duration ITTs (such as the 7.2 s mentioned above) does not occur. Rather, the ITTs are perturbed by the syphon cycling. The gauges were also co-located in the field and linked to carefully synchronised event data loggers. Data collected during several rainfall events revealed differences in the ITTs and again confirm that the ITT sequence of a syphon-equipped TBRG exhibits artefacts related to syphon operation that are not present in the ‘straight-through’ data. These artefacts can result in ITT differences of many minutes, depending on the rainfall intensity and are problematic for the use of ITTs to estimate intensity. Peaks and troughs in the intensity profile also differed between the two gauges. It is recommended that in the application of TBRGs for studies where short-term intensity data are required, ‘straight-through’ gauges should be used, and syphon-equipped gauges should be avoided.

Development of Experimental Low-Cost Rain Gauges and their Evaluation During a High Intensity Storm Event

The measurement of rainfall via ground sensors is fundamental in a variety of hydrological applications, including rainfall-runoff simulations, basin water balance and flood forecasting. The tipping bucket rain gauge (TBR) constitutes the most common type of automatic gauge for the measurement of rainfall intensity. The objective of this work is the development of low-cost and reliable rain gauges, including their data logger, which could be installed at remote, rural areas, in order to supplement with rainfall data the limited or non-existing network of hydrological stations. To achieve this target, two experimental TBRs with diameters of 20 cm (RG20) and 28 cm (RG28) were developed. Electronic boards Arduino UNO and Raspberry Pi were used for their data logger. The measurements of RG20 and RG28 were compared with those of a high quality rain gauge ARG100 and a daily non-recording rain gauge. The cyclone Daniel on 06-09-2023 caused an intermittent storm event in the city of Athens, Greece, which was measured by all three TBRs for purposes of evaluation. The results showed that the variations between ARG100 and RG28 were lower than 6%, while the variations between ARG100 and RG20 were about 10% during a few time intervals of high rainfall intensity. The return period of the storm event were estimated at 43, 59 and 45 years for rainfall durations of 10, 20 and 30 min, respectively.

Integration of data acquisition system for rainfall measurement on IoT-based tipping bucket rain gauge

Rainfall is an important parameter in determining weather conditions. Rainfall data can be used for various purposes, such as for consideration in planning a civil building. If rainfall cannot be measured properly, it will result in an inaccurate design. In actual conditions, rain gauges are usually placed in locations far from power sources. However, to obtain data in digital form, a power source is required. In obtaining digital data, electronic components and monitoring systems are needed which require a power source and an internet connection to send measurement data to the website. The rainfall gauge used in this study is of the tipping bucket type. In the rain gauge used, there is a magnetic switch that functions to calculate the tip that occurs when it rains so that the rainfall value is obtained. The rainfall gauge used in this study has an accuracy of 97.85%. This tool is equipped with an IoT-based monitoring system, namely using a website. Based on the results of the tests that have been carried out, and the range of rainfall per 5 minutes that can be measured is 0 mm-74,5 mm, the range of rainfall per 1 hour that can be measured is 0 mm-894 mm, and the range of rainfall per 1 day that can be measured is 0 mm-21456 mm. In receiving data from the rainfall gauge used in this study, the Arduino Mega microcontroller and the GSM 808 module were used to send data reading the rainfall gauge to the website. On the website display, you can see the rainfall that is happening, and you can see a graph of rainfall. There is a report menu that can be used to download rainfall data per 5 minutes, per 1 hour, and per 1 day with the date selection feature of the rainfall data you want to download. Downloaded rainfall data is in the form of an Excel file.

Comparative study of rainfall measurement by optical disdrometer, tipping-bucket rain gauge, and weighing precipitation gauge

AbstractIn this study, the rainfall measurement characteristics of an optical particle size velocity (Parsivel) disdrometer, tipping-bucket rain gauge (TBG), and Pluvio weighing precipitation gauge (WPG) were analyzed and compared. Correlation analysis was performed between the 10-min and 1-h rainfall data observed with the Parsivel, TBG, and Pluvio from 2010 to 2019 at the Cloud Physics Observation Site which is located in northeast area of South Korea (N37.6869, E128.7586). At higher rainfall intensities, the Parsivel observed more rainfall; however, the TBG lost more rainfall during observation. The correlation between the Pluvio and Parsivel data was higher than that between the TBG and Parsivel data. Additionally, the Pluvio showed reduced loss in the rainfall observation than that by the TBG. The correlation between the Pluvio and TBG data was the highest, and the coefficient of determination increased by a maximum of 42.08% for 1-h rainfall compared to that for 10-min rainfall. Therefore, the Pluvio can generate relatively accurate rainfall data for water resource utilization.

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.

Adjustment of 1 min rain gauge time series using co-located drop size distribution and wind speed measurements

Abstract. A procedure to adjust rainfall intensity (RI) measurements to account for the wind-induced measurement bias of traditional catching-type gauges is proposed and demonstrated with an application to a suitable case study. The objective is to demonstrate that adjustment curves derived from numerical simulations and disdrometer measurements allow for a posteriori correction of rainfall time series based on the wind velocity measurements alone. To quantify the impact of wind on long-term records, 1 min RI measurements from a cylindrical tipping-bucket rain gauge installed at the Hong Kong Observatory are adjusted. Catch ratios derived from the instrument's aerodynamic behaviour under varying wind speed and drop size combinations are obtained by fitting computational fluid-dynamic simulation results already available in the literature. Co-located high-resolution wind speed measurements from a cup and vane sensor and drop size distribution measurements from an optical video disdrometer (the 2DVD or two-dimensional video disdrometer) are used to infer the collection efficiency of the gauge as a function of wind speed and RI alone and to adjust raw data from a 4-year dataset (2018–2021) of 1 min RI measurements. Due to the specific local climatology, where strong wind is often associated with intense precipitation, 80 % of the dataset adjustments are limited to 4 % of the observed RI values. This, however, results in a significant amount of available freshwater resources that would be missing from the calculated hydrological and water management budget of the region should the adjustments be neglected. This work raises the need to quantify the impact of the wind-induced bias at other sites where disdrometer data support a characterisation of the relationship between the drop size distribution and the measured RI. Depending on the local rain and wind climatology, the correction may account for a significant portion of the annual rainfall amount.

Acoustic signal-based indigenous real-time rainfall monitoring system for sustainable environment

The rainfall weather station employs a tipping bucket rain gauge, which serves as a specialized instrument for the meticulous assessment and documentation of various rainwater parameters. The implementation of a tipping bucket rain gauge for rainfall monitoring bears significant implications for both societal productivity as well as improvement of human life. A noteworthy example can be the constructive influence of rainwater over the sustainable agricultural irrigation practices, wherein the precise monitoring of rainfall through a tipping bucket rain gauge enables the formulation of tedious irrigation strategies. The rainfall monitoring if often handle using rain gauge which majorly faces two challenges named as mechanical devices failure and high installation and maintenance cost. Considering the challenges, we propose the fully automated rain gauge (RG) based on the principle of sound and its properties for rainfall monitoring. The working prototype is part of our work whose primary task is to collect the rainfall acoustic value and store it in the cloud. Our mechanism is to use the acoustic property of rain data to categorize rainfall intensity. We perform blind signal separation on the received signal (acoustic signal recorded with the help of microphone sensor) and feed the separated signal to a recurrent convolution neural network (RCNN). The source separation of the collected acoustic signals is primarily being done using independent component analysis and principal components analysis. The proposed solution can be able to make the classification of rain intensity with more than 80% accuracy. In addition to this, the developed method provides the sustainable solution to the challenges with the low-cost and application-specific acceptable threshold criteria and supplement rain measurement techniques.

Monitoring spore washoff during a biological contamination incident response using automated stormwater samplers and sensors to predict contamination movement

This study examined the washoff of Bacillus globigii (Bg) spores from concrete, asphalt, and grass surfaces by stormwater. Bg is a nonpathogenic surrogate for Bacillus anthracis, which is a biological select agent. Areas (2.74 m × 7.62 m) of concrete, grass, and asphalt were inoculated twice at the field site during the study. Spore concentrations were measured in runoff water after seven rainfall events (1.2–65.4 mm) and complimentary watershed data were collected for soil moisture, depth of water in collection troughs, and rainfall using custom-built telemetry units. An average surface loading of 107.79 Bg spores/m2 resulted in peak spore concentrations in runoff water of 102, 260, and 4.1 CFU/mL from asphalt, concrete, and grass surfaces, respectively. Spore concentrations in the stormwater runoff were greatly reduced by the third rain event after both inoculations, but still detectable in some samples. When initial rainfall events occurred longer after the initial inoculation, the spore concentrations (both peak and average) in the runoff were diminished. The study also compared rainfall data from 4 tipping bucket rain gauges and a laser disdrometer and found they performed similarly for values of total rainfall accumulation while the laser disdrometer provided additional information (total storm kinetic energy) useful in comparing the seven different rain events. The soil moisture probes are recommended for assistance in predicting when to sample sites with intermittent runoff. Sampling trough level readings were critical to understanding the dilution factor of the storm event and the age of the sample collected. Collectively the spore and watershed data are useful for emergency responders faced with remediation decisions after a biological agent incident as the results provide insight into what equipment to deploy and that spores may persist in runoff water at quantifiable levels for months. The spore measurements are also a novel dataset for stormwater model parameterization for biological contamination of urban watersheds.

Tipping Bucket Rain Gauges in Hydrological Research: Summary on Measurement Uncertainties, Calibration, and Error Reduction Strategies

Tipping bucket rain gauges (TBRs) continue to be one of the most widely used pieces of equipment for rainfall monitoring; they are frequently used for the calibration, validation, and downscaling of radar and remote sensing data, due to their major advantages—low cost, simplicity and low-energy consumption. Thus, many works have focused and continue to focus on their main disadvantage—measurement biases (mainly in wind and mechanical underestimations). However, despite arduous scientific effort, calibration methodologies are not frequently implemented by monitoring networks’ operators or data users, propagating bias in databases and in the different applications of such data, causing uncertainty in the modeling, management, and forecasting in hydrological research, mainly due to a lack of knowledge. Within this context, this work presents a review of the scientific advances in TBR measurement uncertainties, calibration, and error reduction strategies from a hydrological point of view, by describing different rainfall monitoring techniques, summarizing TBR measurement uncertainties, focusing on calibration and error reduction strategies, discussing the state of the art and providing future perspectives of the technology.

Fog interception in spruce-fir and mixed northern hardwood forests of Great Smoky Mountains National Park, Southeast USA

Abstract: Fog interception is a significant component of the water balance of Southern Appalachian spruce-fir forests in the Southeast USA. Here, fog interception rates are quantified for spruce-fir and northern hardwood trees in Great Smoky Mountains National Park (GSMNP), Tennessee and North Carolina, as a precursor to examining how interspecific differences in fog interception could affect catchment water balances if there is widespread vegetation change from spruce-fir to hardwoods. A water-balance approach was implemented, based on paired open-site (rainfall) and beneath-canopy (throughfall) electronically recording tipping-bucket rain gauges that were in place in the spruce-fir zone of GSMNP from May to November 2021. Comparing identified fog interception events to actual conditions captured by a webcam, 90% of verifiable events had conditions that were either clearly or potentially favorable for fog interception. Estimated fog interception gain ranged from averages of 0.24 to 0.69 mm day−1, representing 3 to 8% of rainfall. Results are consistent with the expectation of higher fog interception gain for spruce and fir than for birch, the representative hardwood species. Quantification of fog interception rates provides valuable information about ecohydrological processes in ecologically significant Southern Appalachian spruce-fir forests.

Rain Discrimination with Machine Learning Classifiers for Opportunistic Rain Detection System Using Satellite Micro-Wave Links.

In the climate change scenario the world is facing, extreme weather events can lead to increasingly serious disasters. To improve managing the consequent risks, there is a pressing need to have real-time systems that provide accurate monitoring and possibly forecasting which could help to warn people in the affected areas ahead of time and save them from hazards. The oblique earth-space links (OELs) have been used recently as a method for real-time rainfall detection. This technique poses two main issues related to its indirect nature. The first one is the classification of rainy and non-rainy periods. The second one is the determination of the attenuation baseline, which is an essential reference for estimating rainfall intensity along the link. This work focuses mainly on the first issue. Data referring to eighteen rain events were used and have been collected by analyzing a satellite-to-earth link quality and employing a tipping bucket rain gauge (TBRG) properly positioned, used as reference. It reports a comparison among the results obtained by applying four different machine learning (ML) classifiers, namely the support vector machine (SVM), neural network (NN), random forest (RF), and decision tree (DT). Various data arrangements were explored, using a preprocessed version of the TBRG data, and extracting two different sets of characteristics from the microwave link data, containing 6 or 12 different features, respectively. The achieved results demonstrate that the NN classifier has outperformed the other classifiers.

Ocena przydatności disdrometru laserowego i radaru meteorologicznego do szacowania wielkości opadów deszczu = Assessment of the suitability of the laser disdrometer and meteorological radar for rainfall estimation

Measurements of precipitation conducted at the WULS-SGGW meteorological station in Warsaw in 2012-2014 and 2019-2020 using a tipping-bucket rain gauge and the laser disdrometer (Parsivel) as well as data obtained from the meteorological radar allowed to collect data enabling the assessment of the usefulness of the disdrometer and radar for estimating rainfalls. The data for the entire study period were used for analysis the correlation relationship between the 24-hour rainfall depths estimated on the basis of the rain gauge and the disdrometer. From the data set for the years 2012-2014, 21 individual events were selected for further analysis, for which rainfall data estimated on the basis of radar in the form of a PAC hydrological product were also available. The rainfall data from the disdrometer and radar were used for analysis the correlation relationships between them and corresponding measurements from the rain gauge. The scope of the study also included a comparison of the values of rainfall totals estimated for 21 single events using the disdrometer and radar in relation to data measured with the rain gauge. The simple method of adjusting the depths of rainfall estimated on the basis of the disdrometer proposed in this paper, was able to reduce significantly the differences in the values of rainfall totals for single events between the data from the disdrometer and the rain gauge.

Radar Reflectivity of Micro Rain Radar (MRR2) At 16.44180N, 80.620E of India

To improve accurate standards of Radar Reflectivity Z, Rainfall Rates RR, and even to monitor small size precipitation particles Z-R relation is derived in this work with the help of Micro Rain Radar. Formerly, taking rain/precipitation data from ground-based rain gauges (Cylindrical, Optical, Weighing, Tipping Bucket Rain Gauges, Disdrometers, etc.,) currently, in this work using METEK MRR (Micro Rain Radar) of Frequency Modulated Continuous Wave System which reads the vertical structure of precipitation particles and hence named as vertical profile radar which operates at 24.2 GHz and height up to 6000m/6kms with an increment step size of 200m respectively to monitor the frozen hydrometeors. It is installed at (16.440 N, 80.620 E) K L University, 29 meters above the sea level (ASL) in CARE LAB. The METEK is manufacturer of micro rain radar, to know the Radar Reflectivity of precipitation, it is observing the amount of power received to the radar receiver after hitting the precipitation particles with respect to the transmitted power of the radar. This proposed work considered distinctive rain conditions at different heights ASL ranging from 200m 1200m 2200m, and derived Z-R relations respectively. This work has been provided significant natural disasters such as Geophysical, Hydrological, Climatological and Meteorological pre-intimation easily using METEK MRR.

Quality control procedures for sub-hourly rainfall data: An investigation in different spatio-temporal scales in Brazil

• 1st automatic quality control on sub-hourly scale applied to Brazil rainfall dataset. • An automatic procedure that does not use a reference quality-controlled dataset. • Rainfall properties were used to spatially identify malfunctioning gauges. • 93.6% of high-quality and 78.6% of poor-quality gauges were correctly identified. There has been an increase in the intensity of rainfall extreme events. These events have a high contribution to hazards in urban areas, such as flash flooding, and landslides, which lead to social, economic, and environmental damage. Sub-hourly rainfall information has a critical role in the assessment of such natural disasters. However, precipitation gauge networks in developing countries still lack high-quality data. This study presents a new automatic quality control procedure (A-QCP) for sub-hourly rainfall data in Brazil, analysing 7 years (2014–2020) of tipping bucket rain gauge (TBRG) data from over 3,000 gauges per year provided by CEMADEN’s (Brazilian National Centre for Monitoring and Early Warnings of Natural Disasters) rain gauge network as a case study. The A-QCP developed separately examines each year through a series of single-gauge tests in which each station was considered independently, going through procedures to assess possible equipment malfunctions through data analysis like long rainless periods or with constant tips due to clogging, spurious rainfall peaks, and long periods of missing data. Then, nearest neighbour analysis was performed through spatial outlier detection using Local Moran’s Index. The performance of the method was evaluated through a confusion matrix, which compared the procedures’ results with a reference dataset created using visual and independent analyses. After the application of the proposed A-QCP to the whole database, the results show that the procedure was able to correctly identify 78.6 % of faulty rain gauges for the whole period, with less than 8 % of functioning rain gauges removed from the final High-Quality database. It was also noted that the best performing filters were the first ones applied, showing that the procedure works best on the identification of gross errors, with diminished efficiency in finding malfunctions after the sequential removal of Poor-Quality rain gauges.

Higher Water Yield but No Evidence of Higher Flashiness in Tropical Montane Cloud Forest (TMCF) Headwater Streams

There have been conflicting findings on hydrological dynamics in tropical montane cloud forests (TMCFs)—attributed to differences in climate, altitude, topography, and vegetation. We contribute another observation-based comparison between a TMCF (8.53 ha; 1906 m.a.s.l.) and a tropical lowland rainforest (TLRF) (5.33 ha; 484 m.a.s.l.) catchment in equatorial Sabah, Malaysian Borneo. In each catchment, a 90° v-notch weir was established at the stream’s outlet and instrumented with a water-level datalogger that records data at 10-min intervals (converted to discharge). A nearby meteorological station records rainfall at the same 10-min intervals via a tipping bucket rain gauge connected to a datalogger. Over five years, 91 and 73 storm hydrographs from a TMCF and a TLRF, respectively, were extracted and compared. Various hydrograph metrices relating to discharge and flashiness were compared between the TMCF and TLRF while controlling for event rainfall, rainfall intensity, and antecedent moisture. Compared to the TLRF, storm-event runoff in the TMCF was up to 169% higher, reflecting the saturated conditions and tendency for direct runoff. Instantaneous peak discharge was also higher (up to 6.6x higher) in the TMCF. However, despite high moisture and steep topography, stream responsiveness towards rainfall input was lower in the TMCF, which we hypothesise was due to its wide and short catchment dimensions. Baseflow was significantly correlated with API20, API10, and API7. Overall, we found that the TMCF had higher runoff, but higher moisture condition alone may not be sufficient to govern flashiness.

LONG-TERM WATER BALANCE IN SMALL CATCHMENTS IN THE ATLANTIC FOREST OF SOUTHEAST BRAZIL

The Atlantic Forest (Mata Atlântica) supplies millions of people with fresh water. Long-term studies of its catchments are essential for an understanding of the hydrological processes involved. A study of the annual water balance maintained in small catchments of the Walter Emmerich Forest Hydrology Laboratory (LHFWE), Serra do Mar State Park, Brazil, was carried out over a period of 20 years (catchment A), 26 years (catchment B) and 30 years (catchment D). The basic hydrological equation P = Q + ET ± ∆S was used. Rainfall (P) was measured with tipping bucket rain gauges installed in clearings. Streamflow (Q) was measured in gauging stations equipped with continuous stage recorders. Soil water storage change (∆S) was considered equal to zero. Evapotranspiration (ET) was calculated by the difference between P and Q. Average annual rainfall of the catchments was high with a mean of 1960 mm and wide interannual variability. The average streamflow was 1432 mm, corresponding to 73% of the rainfall, indicating remarkable water yield in the catchments. The average annual evapotranspiration was 32.2% for catchment A, 24.5% for B and 24.4% for D. These percentages are smaller than those obtained in studies carried out in other tropical forests, including the Atlantic Forest biome.

Pendulum-Based River Current Energy Converter for Hydrometric Monitoring Systems

Energy harvesting from flowing water is important for supplying hydrometric monitoring systems. Nevertheless, it is challenging due to the chaotic water flow in only one main direction and the relatively weak energy profile. In this paper, a novel energy harvester has been proposed, designed, and validated. The converter consists of a pendulum, a gearbox, two overrunning clutches, a spiral spring, and a generator. By coupling the kinetic energy via an oscillating mass equipped with a magnetic spring, it is possible to accommodate the power supply, electronics, and sensors with data transmission in a completely closed, encapsulated, stable housing without an interface to the outside. In addition, an energy management circuit and a battery charging circuit were developed that could be housed in the sealed enclosure. The pendulum transducer prototype was tested with the developed online hydrometric measurement station, which consists of a multi-channel data logger with a cellular modem and a tipping bucket rain gauge sensor. The overall system was successfully validated by experimental studies in a river.