Special Issue "Precipitation Measurement Instruments: Calibration, Accuracy and Performance"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology and Hydrogeology".

Deadline for manuscript submissions: closed (15 April 2021).

Special Issue Editor

Prof. Dr. Luca Giovanni Lanza
E-Mail Website
Guest Editor
Dipartimento di Ingegneria Civile, Chimica e Ambientale (DICCA), University of Genoa, Italy
Interests: physical/stochastic hydrology; precipitation measurement instruments; modeling space-time rainfall fields; floods and flash floods; basin hydrology; distributed hydrological modeling; river geomorphology; sustainable urban hydrology; storm water quality/water treatment
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Precipitation is one of the most challenging among environmental measurements, since accurate determination of the amount of water that would ultimately land on a well-defined portion of the ground surface in undisturbed conditions is a difficult task. This is the aim of so-called in situ measurements at the ground, with the instrument located precisely where the information is sought, therefore at one single location, immersed in the precipitation process. In situ precipitation gauges provide the only direct measurements of precipitation at the ground and are usually referred to as the “ground truth” in precipitation monitoring.

Many types of instruments and measurement techniques are developed and in operational use. Most of these techniques are well described and understood, but new instruments are appearing (especially noncatching instruments), which still need deeper testing and investigation. All instruments are subject to both systematic (bias) and random measurement errors, depending on the construction of the device, the measuring principle, the algorithms used for data interpretation and correction, installation issues, environmental factors, etc.

This Special Issue will focus on the science of precipitation measurements, the measuring principles, new or improved technologies, the assessment of measurement accuracy and performance and the uncertainty budget, calibration methods and laboratory testing, comparison of instruments, and field measurement campaigns. Review papers on the state-of-the-art as well as new research and innovative studies are encouraged.

Prof. Luca G. Lanza
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • atmospheric precipitation measurements
  • measuring principles
  • technology
  • intercomparison
  • measurement accuracy
  • calibration
  • uncertainty

Published Papers (5 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessArticle
On Neglecting Free-Stream Turbulence in Numerical Simulation of the Wind-Induced Bias of Snow Gauges
Water 2021, 13(3), 363; https://doi.org/10.3390/w13030363 - 31 Jan 2021
Viewed by 439
Abstract
Numerical studies of the wind-induced bias of precipitation measurements assume that turbulence is generated by the interaction of the airflow with the gauge body, while steady and uniform free-stream conditions are imposed. However, wind is turbulent in nature due to the roughness of [...] Read more.
Numerical studies of the wind-induced bias of precipitation measurements assume that turbulence is generated by the interaction of the airflow with the gauge body, while steady and uniform free-stream conditions are imposed. However, wind is turbulent in nature due to the roughness of the site and the presence of obstacles, therefore precipitation gauges are immersed in a turbulent flow. Further to the turbulence generated by the flow-gauge interaction, we investigated the natural free-stream turbulence and its influence on precipitation measurement biases. Realistic turbulence intensity values at the gauge collector height were derived from 3D sonic anemometer measurements. Large Eddy Simulations of the turbulent flow around a chimney-shaped gauge were performed under uniform and turbulent free-stream conditions, using geometrical obstacles upstream of the gauge to provide the desired turbulence intensity. Catch ratios for dry snow particles were obtained using a Lagrangian particle tracking model, and the collection efficiency was calculated based on a suitable particle size distribution. The collection efficiency in turbulent conditions showed stronger undercatch at the investigated wind velocity and snowfall intensity below 10 mm h−1, demonstrating that adjustment curves based on the simplifying assumption of uniform free-stream conditions do not accurately portray the wind-induced bias of snow measurements. Full article
Show Figures

Figure 1

Open AccessFeature PaperArticle
Parameterization of the Collection Efficiency of a Cylindrical Catching-Type Rain Gauge Based on Rainfall Intensity
Water 2020, 12(12), 3431; https://doi.org/10.3390/w12123431 - 06 Dec 2020
Cited by 1 | Viewed by 553
Abstract
Despite the numerous contributions available in the literature about the wind-induced bias of rainfall intensity measurements, adjustments based on collection efficiency curves are rarely applied operationally to rain records obtained from catching-type rain gauges. The many influencing variables involved and the variability of [...] Read more.
Despite the numerous contributions available in the literature about the wind-induced bias of rainfall intensity measurements, adjustments based on collection efficiency curves are rarely applied operationally to rain records obtained from catching-type rain gauges. The many influencing variables involved and the variability of the results of field experiments do not facilitate the widespread application of adjustment algorithms. In this paper, a Lagrangian particle tracking model is applied to the results of computational fluid dynamic simulations of the airflow field surrounding a rain gauge to derive a simple formulation of the collection efficiency curves as a function of wind speed. A new parameterization of the influence of rainfall intensity is proposed. The methodology was applied to a cylindrical gauge, which has the typical outer shape of tipping-bucket rain gauges, as a representative specimen of most operational measurement instruments. The wind velocity is the only ancillary variable required to calculate the adjustment, together with the measured rainfall intensity. Since wind is commonly measured by operational weather stations, its use adds no relevant burden to the cost of meteo-hydrological networks. Full article
Show Figures

Figure 1

Open AccessArticle
Comparison Study of Multiple Precipitation Forcing Data on Hydrological Modeling and Projection in the Qujiang River Basin
Water 2020, 12(9), 2626; https://doi.org/10.3390/w12092626 - 19 Sep 2020
Cited by 2 | Viewed by 787
Abstract
As a key factor in the water cycle and climate change, the quality of precipitation data directly affects the hydrological processes of the river basin. Although many precipitation products with high spatial and temporal resolutions are now widely used, it is meaningful and [...] Read more.
As a key factor in the water cycle and climate change, the quality of precipitation data directly affects the hydrological processes of the river basin. Although many precipitation products with high spatial and temporal resolutions are now widely used, it is meaningful and necessary to investigate and evaluate their merits and demerits in hydrological applications. In this study, two satellite-based precipitation products (Tropical Rainfall Measurement Mission, TRMM; Integrated Multi-satellite Retrievals for GPM, IMERG) and one reanalysis precipitation product (China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model, CMADS) are studied to compare their streamflow simulation performance in the Qujiang River Basin, China, using the SWAT model with gauged rainfall data as a reference. The main conclusions are as follows: (1) CMADS has stronger precipitation detection capabilities compared to gauged rainfall, while TRMM results in the most obvious overestimation in the four sub-basins. (2) In daily and monthly streamflow simulations, CMADS + SWAT mode offers the best performance. CMADS and IMERG can provide high quality precipitation data for data-scarce areas, and IMERG can effectively avoid the overestimation of streamflow caused by TRMM, especially on a daily scale. (3) The runoff projections of the three modes under RCP (Representative Concentration Pathway) 4.5 was higher than that of RCP 8.5 on the whole. IMERG + SWAT overestimates the surface water resources of the basin compared to CMADS + SWAT, while TRMM + SWAT provides the most stable uncertainty. These findings contribute to the comparison of the differences among the three precipitation products and provides a reference for the selection of precipitation data in similar regions. Full article
Show Figures

Figure 1

Open AccessArticle
A Homogeneous Dataset for Rainfall Trend Analysis in the Calabria Region (Southern Italy)
Water 2020, 12(9), 2541; https://doi.org/10.3390/w12092541 - 11 Sep 2020
Cited by 1 | Viewed by 502
Abstract
In order to investigate the tendency in rainfall amount in Calabria (southern Italy), in this work, monthly rainfall series were first tested for homogeneity and then a trend analysis was performed. In particular, a homogenization approach based on the Climatol method was applied [...] Read more.
In order to investigate the tendency in rainfall amount in Calabria (southern Italy), in this work, monthly rainfall series were first tested for homogeneity and then a trend analysis was performed. In particular, a homogenization approach based on the Climatol method was applied to homogenize monthly climatological series. Then, the Mann–Kendall non-parametric test and the Theil–Sen estimator were applied to evaluate the presence of trends and their significance in the monthly, seasonal and annual rainfall series. Moreover, the trend slopes were further evaluated with a linear regression analysis. At the annual scale, results evidenced a decreasing trend mainly in the north-eastern part of the region. At the seasonal scale, a spatial distributed negative trend in winter, and a positive trend in summer, mainly localized in the north-western part of the region, were identified. Finally, on a monthly scale negative trends spreading across the region were detected in January and December, with an opposite behavior in July and especially in September, when almost the entire region presented a positive trend. Full article
Show Figures

Figure 1

Open AccessArticle
Evaluation of Radar-Gauge Merging Techniques to Be Used in Operational Flood Forecasting in Urban Watersheds
Water 2020, 12(5), 1494; https://doi.org/10.3390/w12051494 - 23 May 2020
Cited by 3 | Viewed by 1132
Abstract
Demand for radar Quantitative Precipitation Estimates (QPEs) as precipitation forcing to hydrological models in operational flood forecasting has increased in the recent past. It is practically impossible to get error-free QPEs due to the intrinsic limitations of weather radar as a precipitation measurement [...] Read more.
Demand for radar Quantitative Precipitation Estimates (QPEs) as precipitation forcing to hydrological models in operational flood forecasting has increased in the recent past. It is practically impossible to get error-free QPEs due to the intrinsic limitations of weather radar as a precipitation measurement tool. Adjusting radar QPEs with gauge observations by combining their advantages while minimizing their weaknesses increases the accuracy and reliability of radar QPEs. This study deploys several techniques to merge two dual-polarized King City radar (WKR) C-band and two KBUF Next-Generation Radar (NEXRAD) S-band operational radar QPEs with rain gauge data for the Humber River (semi-urban) and Don River (urban) watersheds in Ontario, Canada. The relative performances are assessed against an independent gauge network by comparing hourly rainfall events. The Cumulative Distribution Function Matching (CDFM) method performed best, followed by Kriging with Radar-based Error correction (KRE). Although both WKR and NEXRAD radar QPEs improved significantly, NEXRAD Level III Digital Precipitation Array (DPA) provided the best results. All methods performed better for low- to medium-intensity precipitation but deteriorated with the increasing rainfall intensities. All methods outperformed radar only QPEs for all events, but the agreement is best in the summer. Full article
Show Figures

Figure 1

Back to TopTop