The Stability of Tide Gauges in the South Pacific Determined from Multiepoch Geodetic Levelling, 1992 to 2010     

Manoj Nilesh Deo  Ramesh Govind  Ahmed El-Mowafy 《Marine Geodesy》2013,36(3):261-284

Tide gauge data is important for determining global or local sea level rise with respect to a global geocentric reference frame. Data from repeated precise levelling connections between the tide gauges and a series of coastal and inland benchmarks, including Continuous GPS (CGPS) benchmarks, are used to determine the stability of tide gauges at 12 locations in the South Pacific. The method for determining this stability is based on a constant velocity model which minimises the net movement amongst a set of datum benchmarks surveyed since the installation of the tide gauges. When assessed at a 95% confidence interval, and with the exception of the Solomon Islands, none of the tide gauges were found to be in motion relative to their CGPS benchmarks. The Solomon Islands estimate is considered to be unreliable since the CGPS benchmark was recently established and has been surveyed fewer than three times. In Tonga and Cook Islands, the tide gauges were found to be disturbed or affected by survey errors whereas the Vanuatu results were affected by earthquakes.  相似文献   

Mapping heatwave vulnerability in Korea   总被引：1，自引：0，他引：1  

Do-Woo Kim  Ravinesh C. Deo  Jong-Seol Lee  Jong-Min Yeom 《Natural Hazards》2017,87(1):35-56

Analysis of event-based soil erosion magnitude with special return periods is essential to appropriately design strategies and adopt soil conservation practices. However, the spatiotemporal variations of soil erosion with different return periods, especially at national level, have not been adequately considered. Therefore, the present study aimed to zone rainfall erosivity index (R factor) as the most dynamic factor affecting variability of soil erosion rate, with different return periods in monthly, seasonal and annual time scales in Iran. Toward this attempt, the kinetic energy and maximum 30-min intensity (I ₃₀) over 12,000 available and accessible events of 70 stations were calculated during the common period of 1984–2004 and the corresponding R factor of the Universal Soil Loss Equation was then computed. Subsequently, the best-fitted frequency distributions were determined in all stations in three time scales using the EasyFit Software. The R factor was accordingly estimated for 2-, 5-, 10-, 25- and 50-year return periods. In addition, the inverse distance weighting technique was employed to determine and analyze the spatial variability patterns of R factor in different time scales using geographic information system. The results indicated that the frequency distributions fitted to study data were different in study time scales due to variability of spatiotemporal patterns of R factor. In addition, no specific spatial pattern of R factor could be recognized for different return periods and time scales. The average annual R factor was also found 1.41 MJ mm ha^?1 h^?1, whereas the respective R factor for different respective return periods of 2, 5, 10, 25 and 50 years was obtained 1.47, 2.62, 3.35, 4.48 and 5.54 MJ mm ha^?1 h^?1. These findings can be used for suitable decision making and effective environmental planning for land management Iran countrywide.  相似文献   

Alternative data-driven methods to estimate wind from waves by inverse modeling     

Mansi Daga  M. C. Deo 《Natural Hazards》2009,49(2):293-310

An attempt is made to derive wind speed from wave measurements by carrying out an inverse modeling. This requirement arises out of difficulties occasionally encountered in collecting wave and wind data simultaneously. The wind speed at every 3-h interval is worked out from corresponding simultaneous measurements of significant wave height and average wave periods with the help of alternative data-driven methods such as program-based genetic programming, model trees, and locally weighted projection regression. Five different wave buoy locations in Arabian Sea, representing nearshore and offshore as well as shallow and deep water conditions, are considered. The duration of observations ranged from 15 months to 29 months for different sites. The testing performance of calibrated models has been evaluated with the help of eight alternative error statistics, and the best model for all locations is determined by averaging out the error measures into a single evaluation index. All the three methods satisfactorily estimated the wind speed from known wave parameters through inverse modeling. The genetic programming is found to be the most suitable tool in majority of the cases.  相似文献   

Groundwater vulnerability assessment in shallow aquifer of Kathmandu Valley using GIS-based DRASTIC model   总被引：1，自引：0，他引：1  

Dhundi Raj Pathak  Akira Hiratsuka  Isao Awata  Luonan Chen 《Environmental Geology》2009,57(7):1569-1578

In this paper, groundwater aquifer vulnerability map has been developed by incorporating the major geological and hydro-geological factors that affect and control the groundwater contamination using GIS based DRASTIC model. This work demonstrates the potential of GIS to derive a map by overlying various spatially referenced digital data layers that portrays cumulative aquifer sensitivity ratings across the Kathmandu Valley, Nepal, providing a relative indication of groundwater vulnerability to contamination. In fact, the groundwater is the major natural resources in Kathmandu for drinking purpose. The decline in groundwater levels due to the over exploitation and thus extracted water from shallow aquifer has been contaminated by the infiltration of pollutants from polluted river and land surface is continuous and serious. As the demand for water for human and industrial use has escalated and at the same time, the engineering and environmental costs are much higher for new water supplies than maintaining the existing sources already in use. Management of groundwater source and protecting its quality is therefore essential to increase efficient use of existing water supplies. Aquifer vulnerability maps developed in this study are valuable tools for environmental planning and predictive groundwater management. Further, a sensitivity analysis has been performed to evaluate the influence of single parameters on aquifer vulnerability assessment such that some subjectivity can be reduced to some extent and then new weights have been computed for each DRASTIC parameters.  相似文献   

Remote sensing of atmospheric water vapour from Bhaskara IISAMIR data and its comparison withNOAA-7 water vapour data     

P. N. Pathak  B. S. Gohil  A. Sarkar 《Journal of Earth System Science》1985,94(3):237-247

Applying the method of ‘statistical linear regression’, atomspheric water vapour over oceanic areas has been estimated from the 19GHz and 22 GHz data of the satellite microwave radiometer (SAMIR) system onboard the Bhaskara II satellite. In the absence of any simultaneousin situ measurements on water vapour over ocean, theSAMIR-derived water vapour data have been compared with like data from theNOAA-7 satellite. It is suggested that a positive bias seen in theSAMIR data could be due to calibration errors in the basic data. In view of the observed bias, the original regression equation is modified and then used to obtain water vapour distributions over ocean for winter and south-west monsoon seasons usingSAMIR data of several orbits.  相似文献   

Bat algorithm for dam–reservoir operation     

Mohammad Ethteram  Sayed-Farhad Mousavi  Hojat Karami  Saeed Farzin  Ravinesh Deo  Faridah Binti Othman  Kwok-wing Chau  Saeed Sarkamaryan  Vijay P. Singh  Ahmed El-Shafie 《Environmental Earth Sciences》2018,77(13):510

Optimizing reservoir operation rule is considered as a complex engineering problem which requires an efficient algorithm to solve. During the past decade, several optimization algorithms have been applied to solve complex engineering problems, which water resource decision-makers can employ to optimize reservoir operation. This study investigates one of the new optimization algorithms, namely, Bat Algorithm (BA). The BA is incorporated with different rule curves, including first-, second-, and third-order rule curves. Two case studies, Aydoughmoush dam and Karoun 4 dam in Iran, are considered to evaluate the performance of the algorithm. The main purpose of the Aydoughmoush dam is to supply water for irrigation. Hence, the objective function for the optimization model is to minimize irrigation deficit. On the other hand, Karoun 4 dam is designed for hydropower generation. Three different evaluation indices, namely, reliability, resilience, and vulnerability were considered to examine the performance of the algorithm. Results showed that the bat algorithm with third-order rule curve converged to the minimum objective function for both case studies and achieved the highest values of reliability index and resiliency index and the lowest value of the vulnerability index. Hence, the bat algorithm with third-order rule curve can be considered as an appropriate optimization model for reservoir operation.  相似文献   

Corrosion of cast iron pipelines buried in Fraser River silt subject to climate-induced moisture variations     

Azoor  Rukshan  Asselin  Edouard  Deo  Ravin  Kodikara  Jayantha  Wijewickreme  Dharma 《Acta Geotechnica》2021,16(3):873-884

Acta Geotechnica - Experiments were carried out to characterise the influence of soil water retention properties on the corrosion of a cast iron specimen buried in Fraser River silt. The corrosion...  相似文献   

Predicting pipeline corrosion in heterogeneous soils using numerical modelling and artificial neural networks     

Azoor  Rukshan  Deo  Ravin  Shannon  Benjamin  Fu  Guoyang  Ji  Jian  Kodikara  Jayantha 《Acta Geotechnica》2022,17(4):1463-1476

Acta Geotechnica - The influence of soil heterogeneity on the corrosion of underground metallic pipelines and the resulting evolution of localised corrosion patches were examined. A field-validated...  相似文献   

Real time wave forecasting using neural networks     

M.C. Deo  C. Sridhar Naidu 《Ocean Engineering》1998,26(3):191-203

Forecasting of ocean wave heights, with warning time of a few hours or days, is necessary in planning many operation-related activities in the ocean. Such information is currently derived by numerically solving the differential equation representing wave energy balance. The solution procedure involved is extremely complex and calls for very large amounts of meteorological and oceanographic data. This paper presents a complementary and simple method to make a point forecast of waves in real time sense based on the current observation of waves at a site. It incorporates the technique of neural networks. The network involved is first trained by different algorithms and then used to forecast waves with lead times varying from 3 to 24 h. The results of different training algorithms are compared with each other. The neural output is further compared with the statistical AR models.  相似文献   

Trend Analysis of Groundwater Levels and Assessment of Regional Groundwater Drought: Ghataprabha River Basin,India     

Pathak  Abhishek A.  Dodamani  B. M. 《Natural Resources Research》2019,28(3):631-643

Natural Resources Research - Groundwater drought is a relatively new concept, particularly in the Indian subcontinent, where groundwater levels are declining rapidly. The present study focuses on...  相似文献