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 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 A New Approach for Optimizing Rain Gauge Networks: A Case Study in the Jinjiang Basin

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2252
Author(s):  
Huifeng Wu ◽  
Ying Chen ◽  
Xingwei Chen ◽  
Meibing Liu ◽  
Lu Gao ◽  
...  
Keyword(s):  
Rain Gauge ◽  
Spatiotemporal Variability ◽  
New Approach ◽  
Rain Gauges ◽  
Optimal Network ◽  
Average Rainfall ◽  
Rain Gauge Network ◽  
Monitoring Area ◽  
Hydrological Station

A reasonable rain gauge network can provide valid precipitation information that reflects the spatial and temporal fluctuation characteristics for a given basin. Thus, it is indispensable for designing an optimal network with a minimal number of rain gauges (NRGs) in an optimal location as a means of providing reliable rainfall records, both in terms of the areal average rainfall and the spatiotemporal variability. This study presents a methodological framework that couples the ordinary kriging (OK) method and spatial correlation approach (SCA) to optimize current rain gauge networks, which involves the deletion of redundant gauges and the addition of new rain gauges in the ‘blank’ monitoring area of a basin. This framework was applied to a network of 38 rain gauges in the Jinjiang Basin in southeast China. The results indicated that: (1) the number of rain gauges was reduced from 38 to 11 by using the OK method to determine the redundant rain gauges, which were removed to obtain the ‘base’ rain gauge network. The base rain gauges were mainly distributed in the midstream of this basin. (2) The SCA and OK were employed for obtaining the number and location of new rain gauges in the ‘blank’ monitoring region, respectively. Two new rain gauges in the ‘blank’ monitoring region were identified. One rain gauge was located near the Anxi hydrological station and the other was located in the lower reaches of Anxi sub-basin, respectively. The locations of the two new rain gauges were proven to be reasonable. The number of optimal rain gauges in the Jinjiang Basin was increased to 13. The method proposed in this study provides a novel and simple approach to solve the problems of redundant rain gauges and blank monitoring areas in rain gauge networks. This method is beneficial for improving the optimization level of rain gauge networks and provides a reference for such an optimization.

scholarly journals Evaluation of the High-Resolution CMORPH Satellite Rainfall Product Using Dense Rain Gauge Observations and Radar-Based Estimates

2012 ◽  
Vol 13 (6) ◽  
pp. 1784-1798 ◽  
Author(s):  
Emad Habib ◽  
Alemseged Tamiru Haile ◽  
Yudong Tian ◽  
Robert J. Joyce
Keyword(s):  
Rain Gauge ◽  
Random Errors ◽  
Event Scale ◽  
Entire Study ◽  
Rain Gauges ◽  
Fine Resolution ◽  
Rain Rates ◽  
Climate Prediction Center ◽  
Rain Gauge Network ◽  
Insight Into

Abstract This study focuses on the evaluation of the NOAA–NCEP Climate Prediction Center (CPC) morphing technique (CMORPH) satellite-based rainfall product at fine space–time resolutions (1 h and 8 km). The evaluation was conducted during a 28-month period from 2004 to 2006 using a high-quality experimental rain gauge network in southern Louisiana, United States. The dense arrangement of rain gauges allowed for multiple gauges to be located within a single CMORPH pixel and provided a relatively reliable approximation of pixel-average surface rainfall. The results suggest that the CMORPH product has high detection skills: the probability of successful detection is ~80% for surface rain rates >2 mm h−1 and probability of false detection <3%. However, significant and alarming missed-rain and false-rain volumes of 21% and 22%, respectively, were reported. The CMORPH product has a negligible bias when assessed for the entire study period. On an event scale it has significant biases that exceed 100%. The fine-resolution CMORPH estimates have high levels of random errors; however, these errors get reduced rapidly when the estimates are aggregated in time or space. To provide insight into future improvements, the study examines the effect of temporal availability of passive microwave rainfall estimates on the product accuracy. The study also investigates the implications of using a radar-based rainfall product as an evaluation surface reference dataset instead of gauge observations. The findings reported in this study guide future enhancements of rainfall products and increase their informed usage in a variety of research and operational applications.

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 Multifractal Comparison of Reflectivity and Polarimetric Rainfall Data from C- and X-Band Radars and Respective Hydrological Responses of a Complex Catchment Model

2017 ◽  
Author(s):  
Igor Paz ◽  
Bernard Willinger ◽  
Auguste Gires ◽  
Laurent Monier ◽  
Christophe Zobrist ◽  
...  
Keyword(s):  
Hydrological Model ◽  
Radar Data ◽  
Rain Gauge ◽  
Distributed Hydrological Model ◽  
Space Resolution ◽  
Rain Gauges ◽  
X Band ◽  
Distributed Simulations ◽  
Rain Gauge Network ◽  
Catchment Model

This paper presents a comparison between rain gauges, C-band and X-band radar data over an instrumented and regulated catchment of the Paris region, as well as their respective hydrological impacts with the help of flow observations and a semi-distributed hydrological model. Both radars confirm the high spatial variability of the rainfall down to their space resolution (respectively one kilometer and 250 m) and therefore underscore limitations of semi-distributed simulations. The use of the polarimetric capacity of the Météo-France C-band radar was limited to corrections of the horizontal reflectivity and its rainfall estimates are adjusted with the help of a rain gauge network. On the contrary, neither calibration was performed for the polarimetric X-band radar of the Ecole des Ponts ParisTech (below called ENPC X-band radar), nor any optimization of its scans. In spite of that and the non-negligible fact that the catchment was much closer to the C-band radar than to the X-band radar (20 km vs. 40 km), the latter seems to perform at least as well as the former, but with a higher scale resolution. This characteristic was best highlighted with the help of a multifractal analysis of the respective radar data, which also shows that the X-band radar was able to pick up a few extremes that were smoothed out by the C-band radar.

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.

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.

Validation of PERSIANN Precipitation Product Using TAWN Rain Gauge Network Over Different Agro-climatic Zones in Tamil Nadu

2021 ◽  
Vol 108 (september) ◽  
pp. 1-6
Author(s):  
Venkadesh Samykannu ◽  
◽  
Pazhanivelan S ◽  
Keyword(s):  
High Altitude ◽  
Tamil Nadu ◽  
Rain Gauge ◽  
Northeast Monsoon ◽  
Data Set ◽  
Climatic Zones ◽  
Rain Gauges ◽  
Precipitation Estimation ◽  
Cauvery Delta ◽  
Rain Gauge Network

Currently, several satellite-precipitation products were developed using multiple algorithms to estimate rainfall. This study carried out using Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) product over seven agro-climatic zones of Tamil Nadu during the northeast monsoon (NEM) season of October to December for 2015-2017 (three years) against 118 rain-gauges data of Tamil Nadu Agricultural Weather Network (TAWN). The performance compares aggregated seasonal scale of rainfall using continuous (CC, RMSE, and NRMSE) statistical approaches. It was observed that PERSIANN is accurate in the high-altitude hilly zone and the Cauvery delta zone. For 2015, 2016, and 2017, the correlation values were 0.77, 0.52, and 0.71, respectively. The highest RMSE value was measured for northeast zone (NEZ) during 2015 (222.17 mm), and the lowest was determined for 22.63 in the High-altitude hilly zone (HAHZ) during 2016 and NRMSE had less errors during all three seasons. The study concluded that the PERSIANN data set could be useful substitute for rain-gauge precipitation data.

Spatially-distributed IDF curves for Center-Southern Chile using IMERG

2020 ◽  
Author(s):  
Mauricio Zambrano-Bigiarini ◽  
Cristóbal Soto Escobar ◽  
Oscar M. Baez-Villanueva
Keyword(s):  
Spatial Distribution ◽  
Rain Gauge ◽  
Temporal Scales ◽  
Rain Gauges ◽  
South Central ◽  
Idf Curves ◽  
The Impact ◽  
Term Rain ◽  
Precipitation Events

<p>The Intensity-Duration-Frequency (IDF) curves are crucial for urban drainage design and to mitigate the impact of extreme precipitation events and floods. However, many regions lack a high-density network of rain gauges to adequately characterise the spatial distribution of precipitation events. In this work we compute IDF curves for the South-Central Chilean region (26-56°S) using the latest version of the Integrated Multi-satellitE Retrievals for GPM (IMERGv06B) for 2001-2018, with a spatial resolution of 0.10° and half-hourly temporal frequency.</p><p><br>First, we evaluated the performance of IMERGv06B against 344 rain gauge stations at daily, monthly and annual temporal scales using a point-to-pixel approach. The modified Kling-Gupta efficiency (KGE’) and its components (linear correlation, bias, and variability ratio) were selected as continuous indices of performance. Secondly, we fit maximum precipitation intensities from 14 long-term rain gauge stations to three probability density functions (Gumbel, Log-Pearson Type III, and GEV II) to evaluate: i) the impact of using 15-year rainfall time series in the computation of IDF curves instead of using the typical long-term periods (~ 30 years); and ii) to select the best distribution function for the study area. The Gumbel distribution was selected to obtain the maximum annual intensities for each grid-cell within the study area for 12 durations (0.5, 1, 2, 4, 6, 8, 10, 12, 18, 24, 48, and 72 h) and 6 return periods (T=2, 5, 10, 25, 50, and 100 years).</p><p><br>The application of the Wilcoxon Mann-Whitney test indicates that differences between IDF curves obtained from 15 years of records at the 14 long-term rain gauges and those derived from 25 years of record (or more) are not statistically significant, and therefore, 15 years of record are enough (although not optimal) to compute the IDF curves. Also, our results show that IMERGv06B is able to represent the spatial distribution of precipitation at daily, monthly and annual temporal scales over the study area. Moreover, the obtained precipitation intensities showed high spatial variability, mainly over the Near North (26.0-32.2°S) and the Far South (43.7-56.0°S). Additionally, the intensities from Central Chile (32.2-36.4°S) to the Near South (36.4-43.7°S) were systematically higher compared to the intensities described in older official governmental reports, suggesting an increase in precipitation intensities during recent decades.</p>

scholarly journals Geographic segmentation, spatial dependencies, and evaluation of the relative position of rain-gauges based on gridded data of mean monthly precipitation: application in Nigeria

2016 ◽  
Vol 49 (1) ◽  
pp. 107-122 ◽  
Author(s):  
V. G. Aschonitis ◽  
G. O. Awe ◽  
T. P. Abegunrin ◽  
K. A. Demertzi ◽  
D. M. Papamichail ◽  
...  
Keyword(s):  
Relative Position ◽  
Principal Component ◽  
Spatiotemporal Analysis ◽  
Rain Gauge ◽  
Spatiotemporal Variability ◽  
Monthly Precipitation ◽  
Rain Gauges ◽  
Spatial Dependencies ◽  
The Mean ◽  
Rain Gauge Network

Abstract The aim of the study is to present a combination of techniques for (a) the spatiotemporal analysis of mean monthly gridded precipitation datasets and (b) the evaluation of the relative position of the existing rain-gauge network. The mean monthly precipitation (P) patterns of Nigeria using ∼1 km2 grids for the period 1950–2000 were analyzed and the position of existing rain-gauges was evaluated. The analysis was performed through: (a) correlations of P versus elevation (H), latitude (Lat) and longitude (Lon); (b) principal component analysis (PCA); (c) Iso-Cluster and maximum likelihood classification (MLC) analysis for terrain segmentation to regions with similar temporal variability of mean monthly P; (d) use of MLC to create reliability classes of grid locations based on the mean clusters’ characteristics; and (e) analysis to evaluate the relative position of 33 rain-gauges based on the clusters and their reliability classes. The correlations of mean monthly P versus H, Lat, Lon, and PCA highlighted the spatiotemporal effects of the Inter Tropical Discontinuity phenomenon. The cluster analysis revealed 47 clusters, of which 22 do not have a rain-gauge while eight clusters have more than one rain-gauge. Thus, more rain-gauges and a better distribution are required to describe the spatiotemporal variability of P in Nigeria.

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