Assessment of »True« Variability of Small Rainfall Events in a Small Mountainous Watershed in the Summer

1982 ◽  
Vol 13 (4) ◽  
pp. 205-212 ◽  
Author(s):  
Lawrence C. Nkemdirim ◽  
Brian D. Meller
Keyword(s):  
Spatial Distribution ◽  
Standard Error ◽  
Rain Gauge ◽  
Rainfall Amount ◽  
Rainfall Events ◽  
Mountainous Watershed ◽  
Rainfall Volume ◽  
Areal Rainfall ◽  
The Relationship ◽  
Rain Gauge Network

The standard error of mean areal rainfall was calculated for various densities of rain gauge network in a small mountainous watershed in the summer of 1978. It is shown that a) the optimum gauge density required to assess mean rainfall is about 3 gauges/km2; b) the »true« variability in the spatial distribution of rainfall decreases with increasing rainfall amount; and c) the relationship between »true« variability and rainfall volume is linear in that watershed.

scholarly journals Influence of the rain gauge network on the performance of a hydrological lumped model applied at different basin scales

RBRH ◽  
2018 ◽  
Vol 23 (0) ◽  
Author(s):  
Stefany Correia de Paula ◽  
Rutineia Tassi ◽  
Daniel Gustavo Allasia Piccilli ◽  
Francisco Lorenzini Neto
Keyword(s):  
Spatial Distribution ◽  
Monitoring Network ◽  
Rain Gauge ◽  
Network Density ◽  
Low Density ◽  
Rainfall Runoff ◽  
Lumped Model ◽  
Rain Gauges ◽  
The Poor ◽  
Rain Gauge Network

ABSTRACT In this study was evaluated the influence of the rainfall monitoring network density and distribution on the result of rainfall-runoff daily simulations of a lumped model (IPH II) considering basins with different drainage scales: Turvo River (1,540 km2), Ijuí River (9,462 km2), Jacuí River (38,700 km2) and Upper Uruguay (61,900 km2). For this purpose, four rain gauge coverage scenarios were developed: (I) 100%; (II) 75%; (III) 50% and (IV) 25% of the rain gauges of the basin. Additionally, a scenario considering the absence of monitoring was evaluated, in which the rainfall used in the modeling was estimated based on the TRMM satellite. Was verified that, in some situations, the modeling produced better results for scenarios with a lower rain gauges density if the available gauges presented better spatial distribution. Comparatively to the simulations performed with the rainfall estimated by the TRMM, the results obtained using rain gauges’ data were better, even in scenarios with low rain gauges density. However, when the poor spatial distribution of the rain gauges was associated with low density, the satellite’s estimation provided better results. Thus, was conclude that spatial distribution of the rain gauge network is important in the rainfall representation and that estimates obtained by the TRMM can be presented as alternatives for basins with a deficient monitoring network.

scholarly journals Estimation of convective precipitation: the meteorological radar versus an automatic rain gauge network

2005 ◽  
Vol 2 ◽  
pp. 103-109 ◽  
Author(s):  
M. C. Llasat ◽  
T. Rigo ◽  
M. Ceperuelo ◽  
A. Barrera
Keyword(s):  
Rain Rate ◽  
Rain Gauge ◽  
Space Distribution ◽  
Convective Precipitation ◽  
Precipitation Event ◽  
Convective Rainfall ◽  
Rainfall Events ◽  
Rain Gauges ◽  
Meteorological Radar ◽  
Rain Gauge Network

Abstract. The estimation of convective precipitation and its contribution to total precipitation is an important issue both in hydrometeorology and radio links. The greatest part of this kind of precipitation is related with high intensity values that can produce floods and/or damage and disturb radio propagation. This contribution proposes two approaches for the estimation of convective precipitation, using the β parameter that is related with the greater or lesser convective character of the precipitation event, and its time and space distribution throughout the entire series of the samples. The first approach was applied to 126 rain gauges of the Automatic System of Hydrologic Information of the Internal Basins of Catalonia (NE Spain). Data are series of 5-min rain rate, for the period 1996-2002, and a long series of 1-min rain rate starting in 1927. Rainfall events were classified according to this parameter. The second approach involved using information obtained by the meteorological radar located near Barcelona. A modified version of the SCIT method for the 3-D analysis and a combination of different methods for the 2-D analysis were applied. Convective rainfall charts and β charts were reported. Results obtained by the rain gauge network and by the radar were compared. The application of the β parameter to improve the rainfall regionalisation was demonstrated.

scholarly journals Rainfall estimation over the Wadi Dhuliel arid catchment, Jordan from GSMaP_MVK+

2011 ◽  
Vol 8 (1) ◽  
pp. 1665-1704 ◽  
Author(s):  
E. Abushandi ◽  
B. Merkel
Keyword(s):  
Rain Gauge ◽  
Rainfall Distribution ◽  
Temporal And Spatial Distribution ◽  
Rain Gauges ◽  
Daily Data ◽  
Independent Form ◽  
The Relationship ◽  
Rain Gauge Network ◽  
Annual Time ◽  
Mlr Model

Abstract. The GSMaP_MVK+ (Global Satellite Mapping of Precipitation) dataset was used to evaluate the precipitation rates over the Wadi Dhuliel arid catchment in Northeast Jordan for the period of January 2003 to March 2008. The scarcity of the ground rain gauge network alone did not adequately show the detailed structure of the rainfall distribution, independent form interpolation techniques used. This study combines GSMaP_MVK+ and ground rain gauges to produce accurate, high-resolution datasets. Three meteorological stations and six rain gauges were used to adjust and compare GSMaP_MVK+ estimates. Comparisons between GSMaP_MVK+ measurements and ground rain gauges records showed distinct regions where they correlate, as well as areas where GSMaP_MVK+ systematically over- and underestimated ground rain gauge records. A multiple linear regression (MLR) model was used to derive the relationship between rainfall and GSMaP_MVK+ in conjunction with temperature, relative humidity, and wind speed. The MLR equations were defined for the three meteorological stations. The "best" fit of MLR model for each station was chosen and used to interpolate a multiscale temporal and spatial distribution. Results show that the rainfall distribution over the Wadi Dhuliel is characterized by clear west-east and north-south gradients. Estimates from the monthly MLR model were more reasonable than estimates obtained using daily data. The adjusted GSMaP_MVK+ performed well in capturing the spatial patterns of the rainfall at monthly and annual time scales while daily estimation showed some weakness in light and moderate storms.

scholarly journals Precipitation Estimates from Commercial Microwave Links: Practical Approaches to Wet-antenna Correction

2021 ◽  
Author(s):  
Jaroslav Pastorek ◽  
Martin Fencl ◽  
Jörg Rieckermann ◽  
Vojtěch Bareš
Keyword(s):  
Rainfall Intensity ◽  
Rain Gauge ◽  
Model Parameters ◽  
Rainfall Events ◽  
Precipitation Estimates ◽  
Attenuation Models ◽  
Using Data ◽  
Quantitative Precipitation Estimates ◽  
Rain Gauge Network ◽  
Commercial Microwave Links

An inadequate correction for wet antenna attenuation (WAA) often causes a notable bias in quantitative precipitation estimates (QPEs) from commercial microwave links (CMLs) limiting the usability of these rainfall data in hydrological applications. This paper analyzes how WAA can be corrected without dedicated rainfall monitoring for a set of 16 CMLs. Using data collected over 53 rainfall events, the performance of six empirical WAA models was studied, both when calibrated to rainfall observations from a permanent municipal rain gauge network and when using model parameters from the literature. The transferability of WAA model parameters among CMLs of various characteristics has also been addressed. The results show that high-quality QPEs with a bias below 5% and RMSE of 1 mm/h in the median could be retrieved, even from sub-kilometer CMLs where WAA is relatively large compared to raindrop attenuation. Models in which WAA is proportional to rainfall intensity provide better WAA estimates than constant and time-dependent models. It is also shown that the parameters of models deriving WAA explicitly from rainfall intensity are independent of CML frequency and path length and, thus, transferable to other locations with CMLs of similar antenna properties.

scholarly journals A Study of the Influence of the Spatial Distribution of Rain Gauge Networks on Areal Average Rainfall Calculation

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1635 ◽  
Author(s):  
Jiho Lee ◽  
Soojun Kim ◽  
Hwandon Jun
Keyword(s):  
Spatial Distribution ◽  
Estimation Error ◽  
Case Analysis ◽  
Rain Gauge ◽  
Spatial Characteristic ◽  
Rain Gauges ◽  
First Case ◽  
Average Rainfall ◽  
Major River ◽  
Rain Gauge Network

Estimating the AAR (Areal Average Rainfall) is an essential process when determining the accurate amount of available water resources and building the input data which is integral to the Rainfall-Runoff Analysis. To estimate the AAR, using rain gauge networks that are spatially well distributed is ideal. In this study, the spatial characteristics of the rain gauge networks for the five major river basins in South Korea are considered and the amount of influence the spatial distribution has on the estimation of the AAR is evaluated. For this purpose, the estimation error for AAR is calculated for two cases. The first case (Analysis 1) compares the value of the estimation error of the AAR from two different basins where one has well distributed rain gauges while the other does not. The second case (Analysis 2) estimates the estimation error of two different rain gauge distributions for the same basin. The spatial characteristic of the rain gauge network is evaluated by using the NNI (Nearest Neighbour Index), while the Arithmetic Mean Method, Thiessen Method and the Estimation Theory are applied to calculate the AAR. From Analysis 1, we are able to prove that the estimation error of the AAR is relatively small in the basins with that have spatially well distributed rain gauge networks whereas the estimation error is relatively large when the spatial distribution of the rain gauge network is clustered. Also, results from Analysis 2 showed that not only is the spatial distribution of the rain gauge networks important, but that the density has a significant influence on accurately calculating the AAR. The results from this study can be applied towards the ideal establishment of the rain gauge networks.

scholarly journals Areal rainfall estimation using moving cars as rain gauges – a modelling study

2009 ◽  
Vol 6 (4) ◽  
pp. 4737-4772
Author(s):  
U. Haberlandt ◽  
M. Sester
Keyword(s):  
River Basin ◽  
Research Question ◽  
Rain Gauge ◽  
Indicator Kriging ◽  
High Time Resolution ◽  
Rainfall Estimation ◽  
Time Step ◽  
Rain Gauges ◽  
Areal Rainfall ◽  
Rain Gauge Network

Abstract. Optimal spatial assessment of short-time step precipitation for hydrological modelling is still an important research question considering the poor observation networks for high time resolution data. The main objective of this paper is to present a new approach for rainfall observation. The idea is to consider motorcars as moving rain gauges with windscreen wipers as sensors to detect precipitation. This idea is easily technically feasible if the cars are provided with GPS and a small memory chip for recording the coordinates, car speed and wiper frequency. This study explores theoretically the benefits of such an approach. For that a valid relationship between wiper speed and rainfall rate considering uncertainty was assumed here. A simple traffic model is applied to generate motorcars on roads in a river basin. Radar data are used as reference truth rainfall fields. Rainfall from these fields is sampled with a conventional rain gauge network and with several dynamic networks consisting of moving motorcars. Those observed point rainfall data from the different networks are then used to calculate areal rainfall for different scales. Ordinary kriging and indicator kriging are applied for interpolation of the point data with the latter considering uncertain rainfall observation by cars e.g. according to a discrete number of windscreen wiper operation classes. The results are compared with the true values from the radar observations. The study is carried out for the 3300 km2 Bode river basin located in the Harz Mountains in Northern Germany. The results show, that the idea is theoretically feasible. Only a small portion of the cars needed to be equipped with sensors for sufficient areal rainfall estimation. Regarding the required sensitivity of the potential rain sensors in cars it could be shown, that often a few classes for rainfall observation are enough for satisfactory areal rainfall estimation. The findings of the study suggest also a revisiting of the rain gauge network optimisation problem.

Comprehensive evaluation of precipitation analyses using a very dense rain gauge network in southeast Austria

2020 ◽  
Author(s):  
Esmail Ghaemi ◽  
Ulrich Foelsche ◽  
Alexander Kann ◽  
Gottfried Kirchengast ◽  
Juergen Fuchsberger
Keyword(s):  
Temporal Resolution ◽  
Comprehensive Evaluation ◽  
Analysis Data ◽  
Radar Data ◽  
Rain Gauge ◽  
Accurate Estimation ◽  
Wet Season ◽  
Rainfall Events ◽  
Rainfall Analysis ◽  
Rain Gauge Network

<p>Precipitation is one of the most important inputs of meteorological and hydrological models and also flood warning systems. Thus, accurate estimation of rainfall is essential for improving the reliability of the models and systems. Although remote sensing (RS) techniques for rainfall estimation (e.g., weather radars and satellite microwave imagers) have improved significantly over the last decades, rain gauges are still more reliable and widely used for this purpose and also for the evaluation of RS estimates. Since the characteristics of a rainfall event can change rapidly in space and time, the accuracy of rain gauge estimation is highly dependent on the spatial and temporal resolution of the gauge network.</p><p>The main aim of this study is to evaluate the ability of the Integrated Nowcasting through Comprehensive Analysis (INCA) of the Central Institute for Meteorology and Geodynamics (ZAMG) to detect and estimate rainfall events. This is done by using 12 years of data from a very dense rain gauge network, the WegenerNet Feldbach region, as a reference, and comparing its data to the INCA analyses. INCA rainfall analysis data are based on a combination of ZAMG ground station data, weather radar data, and high-resolution topographic data. The system provides precipitation rate data with a 1 km spatial grid resolution and 15 minutes temporal resolution. The WegenerNet includes 155 ground stations, almost uniformly spread over a moderate hilly orography area of about 22 km × 16 km.</p><p>After removing outliers and scale WegenerNet data to 1 km, the accuracy of INCA to detect and estimate rainfall events was investigated using 12 years of the dataset. The results show that INCA can detect rainfall events relatively well. It was found that INCA overestimates the rainfall amount between 2012 and 2014, and generally overestimates precipitation for light rainfall events. For heavy rainfall events, however, an underestimation of INCA is prominent in most events. Based on the results, the difference between INCA and WegenerNet estimates is relatively higher during the wet season in the summer half-year (May-September). It is worth pointing out that INCA performs better in detecting and estimating rainfall around the two ZAMG stations located within the study area.</p>

Investigation of Orographic Precipitation over an Isolated, Three-Dimensional Complex Topography with a Dense Gauge Network, Radar Observations, and Upslope Model

2019 ◽  
Vol 76 (11) ◽  
pp. 3387-3409 ◽  
Author(s):  
Lin-Wen Cheng ◽  
Cheng-Ku Yu
Keyword(s):  
Three Dimensional ◽  
Local Maximum ◽  
Rain Gauge ◽  
Complex Topography ◽  
Rainfall Events ◽  
Radar Observations ◽  
Local Maxima ◽  
The Difference ◽  
Rain Gauge Network ◽  
Northern Taiwan

Abstract This study uses a dense rain gauge network, radar observations, and an upslope model to document the detailed aspects of precipitation over Da-Tun Mountain (DT) of northern Taiwan under prevailing northeasterly monsoonal flow. DT is one of the most concentrated areas of heavy rainfall in Taiwan, with a size of ~15 km and a terrain peak of ~1 km (MSL), and it constitutes a concave ridge with two windward ridge arms that encompass a funnel-shaped valley. Twenty-one rainfall events identified over DT from January 2011 to February 2015 are chosen for analysis. More than half of the studied cases exhibit two local maxima of rainfall over the ridge arms, and asymmetric characteristics between these two maxima are evident. The other frequent rainfall pattern, observed as upstream winds are more from the east-northeast, is characterized by a local maximum of precipitation inside the valley. Analyses from the upslope model confirm that the occurrence of the windward maxima of rainfall is primarily caused by upslope lifting, and their asymmetric characteristics are closely related to the difference in the azimuthal variations of slope steepness between the two ridge arms. The observed characteristics of rainfall intensities inside the valley, however, cannot be well described by the upslope model. It is found that the lateral flow confluence induced by the deflected flows over the ridge arms may play an essential role in intensifying upslope-forced precipitation within the valley. This effect emerges as upstream winds are roughly parallel to the central axis of funneling regions located between the ridge arms.

scholarly journals Analysis of the Relationship between Banded Orographic Convection and Atmospheric Properties Using Factorial Discriminant Analysis and Neural Networks

2010 ◽  
Vol 49 (4) ◽  
pp. 646-663 ◽  
Author(s):  
A. Godart ◽  
E. Leblois ◽  
S. Anquetin ◽  
N. Freychet
Keyword(s):  
Neural Networks ◽  
Potential Temperature ◽  
Rain Gauge ◽  
Meteorological Model ◽  
Rainfall Events ◽  
Moisture Fluxes ◽  
Orographic Convection ◽  
Discriminant Factorial Analysis ◽  
New Variables ◽  
The Relationship

Abstract The relationship between banded orographic convection and atmospheric properties is investigated for a region in the south of France where the associated rainfall events are thought to represent a significant portion of the hydrologic input. The purpose is to develop a method capable of producing an extensive database of banded orographic convection rainfall events from atmospheric sounding data for this region where insufficient rain gauge data and little or no suitable radar or satellite data are available. Two statistical methods—discriminant factorial analysis (DFA) and neural networks (NNs)—are used to determine 16 so-called elaborated nonlinear variables that best identify rainfall events related to banded orographic convection from atmospheric soundings. The approach takes rainfall information into account indirectly because it “learns” from the results of a previous study that explored meteorological and available rainfall databases, even if incomplete. The new variables include wind shear, low-level moisture fluxes, and gradients of the potential temperature in the lower layers of the atmosphere, and they were used to create an extensive database of banded orographic convection events from the archive of atmospheric soundings. Results of numerical simulations using the nonhydrostatic mesoscale (Méso-NH) meteorological model validate this approach and offer interesting perspectives for the understanding of the physical processes associated with banded orographic convection. DFA proves to be useful to determine the most discriminant factors with a physical meaning. Neural networks provide better results, but they do not allow for physical interpretation. The best solution is therefore to use the two methods together.

scholarly journals Assessment of rain-gauge networks using a probabilistic GIS based approach

2013 ◽  
Vol 45 (4-5) ◽  
pp. 551-562 ◽  
Author(s):  
Mojtaba Shafiei ◽  
Bijan Ghahraman ◽  
Bahram Saghafian ◽  
Saket Pande ◽  
Shervan Gharari ◽  
...  
Keyword(s):  
Probabilistic Approach ◽  
Rain Gauge ◽  
Rainfall Estimation ◽  
Acceptance Probability ◽  
Rain Gauges ◽  
Basin Scale ◽  
Gis Environment ◽  
Areal Rainfall ◽  
Rain Gauge Network ◽  
Hydrological Applications

Rain-gauge networks provide estimates of areal rainfall as a crucial input for hydrological applications. Hence, it is important to quantify the performance of a rain-gauge network and evaluate the contribution of each rain-gauge to the overall accuracy of areal rainfall estimation at basin scale. This paper evaluates the performance and augmentation of a rain-gauge network in a large basin in Iran. A probabilistic approach combined with a geographic information system (GIS) framework is applied, in order to assess the accuracy of point rainfall in terms of acceptance probability. A simple equation for calculating the acceptance probability is presented which facilitates the application of the probabilistic approach in a GIS environment. This approach analyzes the number and location of rain-gauges and quantifies each gauge's contribution to the accuracy of rainfall estimation over the study area. Results show that among 33 existing gauges, only 21 have significant effect on areal rainfall estimation while other 12 gauges have marginal contribution to the accuracy of the network. Also, by applying an augmentation algorithm, an optimal rain-gauge network with 28 gauges is formed.

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