Rain gauge

Summary

A rain gauge (also known as udometer, pluviometer, pluviameter, ombrometer, and hyetometer) is an instrument used by meteorologists and hydrologists to gather and measure the amount of liquid precipitation over a predefined area, over a period of time. It is used to determine the depth of precipitation (usually in mm) that occurs over a unit area and measure rainfall amount. History The first known rainfall records were kept by the Ancient Greeks, at around 500 BCE. People living in India began to record rainfall in 400 BCE The readings were correlated against expected growth. In the Arthashastra, used for example in Magadha, precise standards were set as to grain production. Each state storehouse was equipped with a rain gauge to classify land for taxation purposes..Rainfall measurement was also mentioned in the Jewish text in Palestine. In 1247, the Song Chinese mathematician and inventor Qin Jiushao invented Tianchi basin rain and snow gauges to reference rain, and sno

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This project studied hydrological models used in the catchment of the Petite Chamberonne north-west of Lausanne. In a first step, input data have been analysed and prepared for the spatially explicit, conceptual hydrological model SEHR-ECHO. It has been proved that rainfall data can be taken and homogeneously distributed over the catchment from a nearby rain gauge (Crissier). The 9 months of discharge data proved to be of good quality; 9 months of data however is rather short for automatic calibration. Unique annual events influence the calibration of the hydrological model strongly and had to be removed and tested manually. First results showed a mediocre performance of the standard version of SEHR-ECHO. In order to improve the results of the simulation, several adaptations of the model have been tested. The best variant showed to be SEHR-ECHO, using reservoirs in series (instead of parallel) and Horton’s mechanism for surface runoff production (instead of Dunne’s mechanism). A NSE of 0.77 has been achieved. Based on this hydrological model, two types of pesticide transport models have been developed and tested. Though not yet calibrated (due to the lack of data), it has been observed that the two models give results that are sensitive to the chemical properties of the simulated pesticide and that the results show similarities to what has been observed in previous studies (e.g. [Leu et al., 2004a]). A further effort in calibration using more date will have to be undertaken in order to improve and validate the hydrological simulations. At last, the pesticide transport model will have to be calibrated and its results interpreted once data is available.

2013

Analysis of Rainfall Data by Simple Good Sense: is Spatial Statistics Worth the Trouble ?

Reinhard Furrer

This paper discusses the use of simple good sense in the spatial prediction of rainfall measurements in Switzerland. The method consists of a forecast based on the values of the available observations combined with topographic knowledge of the Swiss territory. Comparison of our subjective estimates with the true measurements is completed and yields surprisingly good results.

1998

Knowledge of extreme precipitation phenomena is of crucial importance to the safety of civil engineering works and for electricity production management in a country of lakes and mountains like Switzerland. In order to study the distribution in space and the evolution of strong rain episodes, the work presented here relies on the complementary approaches of field observation and numerical simulation. The experimental portion of this project relies on a novel, acousticbased, rain metrology instrument. Based on the results, a methodology for the determination of raindrop size distribution (disdrometer facility) and rainfall rate (rain gauge facility) has been developed and is described in the present dissertation. In addition, numerical modelling and simulation methods were developed with the aim of calculating — for a given watershed topography — the Probable Maximum Precipitation (PMP). The method relies on the separation of the different phenomenological contributions and on the climatic characterization of atmospheric situations leading to extreme rain events. Boundary and initial conditions are represented by theoretical profiles of the wind speed, wind direction, temperature, and water contents, turbulent energy and dissipation rate variables. The numerical model calculates the consequent wind and rain fields within the simulation domain for the desired atmospheric situation. The hydrodynamic code (CFX4) is based on the finite volume approach and is particularly adapted to complex geometries, allowing an excellent representation of the topography. The code is partially open and several specific atmospheric models were implemented. Microphysics schemes considered are Kessler's warm classic scheme (1969) and the Caniaux detailed scheme (1993). The latter includes solid ice particles, aggregates and graupel and allows the simulation of convective as well as orographic cloud system precipitation cycles. Sensitivity studies of the results with respect to the dominant parameters of each situation, lead to a maximisation procedure successfully applied to convective as well as frontal precipitation. The work shows that the maximisation method consisting of maximising severe events into critical events can be more effective than using statistical approaches. Use of this method compensates for the relative lack of measurement facilities in many regions.

EPFL2004