scholarly journals Comparison of Entropy Methods for an Optimal Rain Gauge Network: A Case Study of Daegu and Gyeongbuk Area in South Korea

2020 ◽  
Vol 10 (16) ◽  
pp. 5620
Author(s):  
Taeyong Kwon ◽  
Junghyun Lim ◽  
Seongsim Yoon ◽  
Sanghoo Yoon
Keyword(s):  
Conditional Entropy ◽  
Rain Gauge ◽  
Optimal Number ◽  
Severe Drought ◽  
Prediction Errors ◽  
Joint Entropy ◽  
Spatio Temporal ◽  
Rain Gauge Network ◽  
Better Than

To reduce hydrological disasters, it is necessary to operate rain gauge stations at locations where the spatio-temporal characteristics of rainfall can be reflected. Entropy has been widely used to evaluate the designs and uncertainties associated with rain gauge networks. In this study, the optimal rain gauge network in the Daegu and Gyeongbuk area, which requires the efficient use of water resources due to low annual precipitation and severe drought damage, was determined using conditional and joint entropy, and the selected network was quantitatively evaluated using the root mean square error (RMSE). To consider spatial distribution, prediction errors were generated using kriging. Four estimators used in entropy calculations were compared, and weighted entropy was calculated by weighting the precipitation. The optimal number of rain gauge stations was determined by calculating the RMSE reduction and the reduction ratio according to the number of selected rain gauge stations. Our findings show that the results of conditional entropy were better than those of joint entropy. The optimal rain gauge stations showed a tendency wherein peripheral rain gauge stations were selected first, with central stations being added afterward.

scholarly journals Evaluation of IMERG Level-3 Products in Depicting the July to October Rainfall over Taiwan: Typhoon Versus Non-Typhoon

2021 ◽  
Vol 13 (4) ◽  
pp. 622
Author(s):  
Wan-Ru Huang ◽  
Pin-Yi Liu ◽  
Ya-Hui Chang ◽  
Cheng-An Lee
Keyword(s):  
Real Time ◽  
Tropical Rainfall Measuring Mission ◽  
Temporal Variations ◽  
Rain Gauge ◽  
Advantages And Disadvantages ◽  
Level 3 ◽  
Spatio Temporal ◽  
Typhoon Season ◽  
Early Late ◽  
Better Than

This study assesses the performance of satellite precipitation products (SPPs) from the latest version, V06B, Integrated Multi-satellitE Retrievals for Global Precipitation Mission (IMERG) Level-3 (including early, late, and final runs), in depicting the characteristics of typhoon season (July to October) rainfall over Taiwan within the period of 2000–2018. The early and late runs are near-real-time SPPs, while final run is post-real-time SPP adjusted by monthly rain gauge data. The latency of early, late, and final runs is approximately 4 h, 14 h, and 3.5 months, respectively, after the observation. Analyses focus on the seasonal mean, daily variation, and interannual variation of typhoon-related (TC) and non-typhoon-related (non-TC) rainfall. Using local rain-gauge observations as a reference for evaluation, our results show that all IMERG products capture the spatio-temporal variations of TC rainfall better than those of non-TC rainfall. Among SPPs, the final run performs better than the late run, which is slightly better than the early run for most of the features assessed for both TC and non-TC rainfall. Despite these differences, all IMERG products outperform the frequently used Tropical Rainfall Measuring Mission 3B42 v7 (TRMM7) for the illustration of the spatio-temporal characteristics of TC rainfall in Taiwan. In contrast, for the non-TC rainfall, the final run performs notably better relative to TRMM7, while the early and late runs showed only slight improvement. These findings highlight the advantages and disadvantages of using IMERG products for studying or monitoring typhoon season rainfall in Taiwan.

scholarly journals Multisensor Comparison and Numerical Modeling of Atmospheric Water Fields: A VOLTAIRE Case Study over Cyprus

2008 ◽  
Vol 23 (4) ◽  
pp. 674-701 ◽  
Author(s):  
Stefano Mariani ◽  
Christophe Accadia ◽  
Nazario Tartaglione ◽  
Marco Casaioli ◽  
Marco Gabella ◽  
...  
Keyword(s):  
Water Vapor ◽  
Mediterranean Sea ◽  
Rain Gauge ◽  
Limited Area ◽  
Atmospheric Water ◽  
Limited Area Model ◽  
Trmm Pr ◽  
Rain Gauge Network ◽  
Total Column

Abstract This paper presents a study performed within the framework of the European Union’s (EU) VOLTAIRE project (Fifth Framework Programme). Among other tasks, the project aimed at the integration of the Tropical Rainfall Measuring Mission (TRMM) data with ground-based observations and at the comparison between water fields (precipitation and total column water vapor) as estimated by multisensor observations and predicted by NWP models. In particular, the VOLTAIRE project had as one of its main objectives the goal of assessing the application of satellite-borne instrument measures to model verification. The island of Cyprus was chosen as the main “test bed,” because it is one of the few European territories covered by the passage of the TRMM Precipitation Radar (PR) and it has a dense rain gauge network and an operational weather radar. TRMM PR provides, until now, the most reliable space-borne spatial high-resolution precipitation measurements. Attention is focused on the attempt to define a methodology, using state-of-the-art diagnostic methods, for a comprehensive evaluation of water fields as forecast by a limited area model (LAM). An event that occurred on 5 March 2003, associated with a slow cyclone moving eastward over the Mediterranean Sea, is presented as a case study. The atmospheric water fields were forecast over the eastern Mediterranean Sea using the Bologna Limited Area Model (BOLAM). Data from the Cyprus ground-based radar, the Cyprus rain gauge network, the Special Sensor Microwave Imager (SSM/I), and the TRMM PR were used in the comparison. Ground-based radar and rain gauge data were merged together in order to obtain a better representation of the rainfall event over the island. TRMM PR measurements were employed to range-adjust the ground-based radar data using a linear regression algorithm. The observed total column water vapor has been employed to assess the forecast quality of large-scale atmospheric patterns; such an assessment has been performed by means of the Hoffman diagnostic method applied to the entire total column water vapor field. Subsequently, in order to quantify the spatial forecast error at the finer BOLAM scale (0.09°), the object-oriented contiguous rain area (CRA) analysis was chosen as a comparison method for precipitation. An assessment of the main difficulties in employing CRA in an operational framework, especially over such a small verification domain, is also discussed in the paper.

Assessing the potential of using telecommunication microwave links in urban drainage modelling

2013 ◽  
Vol 68 (8) ◽  
pp. 1810-1818 ◽  
Author(s):  
M. Fencl ◽  
J. Rieckermann ◽  
M. Schleiss ◽  
D. Stránský ◽  
V. Bareš
Keyword(s):  
Urban Areas ◽  
Rainfall Variability ◽  
Rain Gauge ◽  
Urban Drainage ◽  
Rainfall Runoff ◽  
Urban Catchment ◽  
Flow Prediction ◽  
Spatial Coverage ◽  
Spatio Temporal

The ability to predict the runoff response of an urban catchment to rainfall is crucial for managing drainage systems effectively and controlling discharges from urban areas. In this paper we assess the potential of commercial microwave links (MWL) to capture the spatio-temporal rainfall dynamics and thus improve urban rainfall-runoff modelling. Specifically, we perform numerical experiments with virtual rainfall fields and compare the results of MWL rainfall reconstructions to those of rain gauge (RG) observations. In a case study, we are able to show that MWL networks in urban areas are sufficiently dense to provide good information on spatio-temporal rainfall variability and can thus considerably improve pipe flow prediction, even in small subcatchments. In addition, the better spatial coverage also improves the control of discharges from urban areas. This is especially beneficial for heavy rainfall, which usually has a high spatial variability that cannot be accurately captured by RG point measurements.

scholarly journals Comparison of Semivariogram Models in Rain Gauge Network Design

MATEMATIKA ◽  
2019 ◽  
Vol 35 (2) ◽  
pp. 157-170
Author(s):  
Mohd Khairul Bazli Mohd Aziz ◽  
Fadhilah Yusof ◽  
Zalina Mohd Daud ◽  
Zulkifli Yusop ◽  
Mohammad Afif Kasno
Keyword(s):  
Variance Reduction ◽  
Evaluation Process ◽  
Exponential Model ◽  
Rain Gauge ◽  
Optimal Number ◽  
Optimal Choice ◽  
Semivariogram Model ◽  
Rain Fall ◽  
Validation Technique ◽  
Rain Gauge Network

The well-known geostatistics method (variance-reduction method) is commonly used to determine the optimal rain gauge network. The main problem in geostatistics method to determine the best semivariogram model in order to be used in estimating the variance. An optimal choice of the semivariogram model is an important point for a good data evaluation process. Three different semivariogram models which are Spherical, Gaussian and Exponential are used and their performances are compared in this study. Cross validation technique is applied to compute the errors of the semivariograms. Rain-fall data for the period of 1975 – 2008 from the existing 84 rain gauge stations covering the state of Johor are used in this study. The result shows that the exponential model is the best semivariogram model and chosen to determine the optimal number and location of rain gauge station.

scholarly journals A Bayesian copula-based spatio-temporal method for multivariate drought risk analysis: A case study of the Balkhash Lake Basin

2021 ◽  
Author(s):  
Xin Yang ◽  
Yongping Li
Keyword(s):  
Risk Analysis ◽  
Temporal Analysis ◽  
Lake Basin ◽  
Drought Risk ◽  
Severe Drought ◽  
Drought Event ◽  
Spatio Temporal ◽  
Guarantee Rate ◽  
East West

In this study, a Bayesian copula spatio-temporal drought risk analysis (BCSDA) method is developed through coupling Bayesian copula and spatio-temporal analysis into a general framework. BCSDA can effectively identify drought characteristics and reveal the temporal and spatial variation, as well as analyze drought risk at different guaranteed rates based on the influence of multivariate interaction. Then, BCSDA is applied to the Balkhash Lake Basin (a typical arid watershed in Central Asia) for analyzing drought risk during 1901-2017. Major findings are: (i) Balkhash Lake Basin suffered 53 drought events in 1901-2017, and the most severe drought event occurred in October 1973 to January 1977, which lasted for 40 months and developed into an extreme drought during April 1975 to June 1976, affecting 335,800 square kilometers of the study basin; (ii) most of the drought events developed in the direction of east-west, and Lli River delta and the alluvial plain were the most severe of drought (47.2%), followed by the plateau desert area (28.3%) and the arid grassland in north of Balkhash Lake (24.5%); (iii) drought shows significant seasonality which usually began in spring and summer (64.2%) and ended in summer and autumn (66.0%); (iv) in Balkhash Lake Basin, multivariate characteristics (duration, severity and area) would significantly affect drought risk; (v) the range of drought risk would be [1.9%, 18.1%], [3.7%, 33.1%], [8.7%, 46.0%], [16.0%, 55.1%] and [27.6%, 59.8%] when guarantee rate is 0.99, 0.98, 0.95, 0.90 and 0.80.

scholarly journals A GIS methodology for the analysis of weather radar precipitation data

2003 ◽  
Vol 5 (2) ◽  
pp. 113-126 ◽  
Author(s):  
M. A. Gad ◽  
I. K. Tsanis
Keyword(s):  
Weather Radar ◽  
Radar Data ◽  
Rain Gauge ◽  
Precipitation Data ◽  
Rain Gauge Data ◽  
Gis Environment ◽  
Arcview Gis ◽  
The City ◽  
Rain Gauge Network

A GIS multi-component module was developed within the ArcView GIS environment for processing and analysing weather radar precipitation data. The module is capable of: (a) reading geo-reference radar data and comparing it with rain-gauge network data, (b) estimating the kinematics of rainfall patterns, such as the storm speed and direction, and (c) accumulating radar-derived rainfall depths. By bringing the spatial capabilities of GIS to bear this module can accurately locate rainfall on the ground and can overlay the animated storm on different geographical features of the study area, making the exploration of the storm's kinematic characteristics obtained from radar data relatively simple. A case study in the City of Hamilton in Ontario, Canada is used to demonstrate the functionality of the module. Radar comparison with rain gauge data revealed an underestimation of the classical Marshal & Palmer Z–R relation to rainfall rate.

scholarly journals Parasite invasion following host reintroduction: a case study of Yellowstone's wolves

2012 ◽  
Vol 367 (1604) ◽  
pp. 2840-2851 ◽  
Author(s):  
Emily S. Almberg ◽  
Paul C. Cross ◽  
Andrew P. Dobson ◽  
Douglas W. Smith ◽  
Peter J. Hudson
Keyword(s):  
Good Health ◽  
Sarcoptes Scabiei ◽  
High Morbidity ◽  
Resource Quality ◽  
Parasite Invasion ◽  
Spatio Temporal ◽  
Canid Species ◽  
The Impact ◽  
Better Than

Wildlife reintroductions select or treat individuals for good health with the expectation that these individuals will fare better than infected animals. However, these individuals, new to their environment, may also be particularly susceptible to circulating infections and this may result in high morbidity and mortality, potentially jeopardizing the goals of recovery. Here, using the reintroduction of the grey wolf ( Canis lupus ) into Yellowstone National Park as a case study, we address the question of how parasites invade a reintroduced population and consider the impact of these invasions on population performance. We find that several viral parasites rapidly invaded the population inside the park, likely via spillover from resident canid species, and we contrast these with the slower invasion of sarcoptic mange, caused by the mite Sarcoptes scabiei . The spatio-temporal patterns of mange invasion were largely consistent with patterns of host connectivity and density, and we demonstrate that the area of highest resource quality, supporting the greatest density of wolves, is also the region that appears most susceptible to repeated disease invasion and parasite-induced declines. The success of wolf reintroduction appears not to have been jeopardized by infectious disease, but now shows signs of regulation or limitation modulated by parasites.

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.

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