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Drought Analysis Using Statistical Downscaling Models in Qiantang River Basin

Author: LinShengJi
Tutor: XuYuePing
School: Zhejiang University
Course: Hydrology and Water Resources
Keywords: Arid Multiple time scales SPI Statistical downscaling Support Vector Machine Drought intensity Qiantang River Basin
CLC: P426.616
Type: Master's thesis
Year: 2011
Downloads: 259
Quote: 1
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Abstract


With the population growth, agricultural and industrial water demand increases and changes in the global environment, the drought trend in the further development. The drought has become the most serious natural disaster to affect China's agricultural production. The drought index is the basis for drought monitoring and forecasting, domestic and foreign scholars in recent years has been studied for many drought indicators and methods of evaluation, but not yet work study climate change, the future of the Qiantang River drought conditions, with the global warming, humid areas drought prediction and assessment are also attracted the attention of the crowd. Firstly, the use of DEM extraction flow path of the Qiantang River Basin, digital drainage network and watershed boundaries and other features on this basis to build a digital watershed for late hydrological process simulation and drought time and space analysis. Paper used monthly precipitation data from 23 weather stations from 1951 to 2008 of the Qiantang River Basin, by calculating the cumulative probability of a given time scale, so that it can be calculated in multiple time scales, the analysis of the Qiantang Z index and SPI River Basin station in the drought disaster situations of each quarter, spatial distribution, and trends and analyzes the major drought in the history of the impact of disasters. Climate change under drought prediction using support vector machine. In this paper, from 1961 to 2000 NCEP re-analysis of historical precipitation data from 23 meteorological stations of the data and the Qiantang River, and the use of principal component analysis (PCA) and support vector machine (SVM) is a combination of statistical downscaling methods, the establishment of large-scale climate predictor of Qiantang River meteorological stations monthly precipitation statistics downscaling model; principal component analysis and SVM combined statistical downscaling model is applied to three global climate models HadCM3, Ccsm3, Echam5 in A1B, A2 B1 emission scenarios predictor of fitting the 23 sites of the Qiantang River Basin precipitation change scenarios, as well as to predict the next 30 years (2011 to 2040) of rainfall. Two important indicators of drought duration and drought intensity are quantitative study of the hydrological drought events. Using the analytical methods used to Deriving the drought intensity probability distribution or a certain drought duration drought intensity corresponding conditional probability distribution of difficulties still exist, currently the most commonly used method is to use the existing theoretical distribution to fit the probability distribution or conditional probability distribution of drought intensity The fitting is good or bad depends critically on the parameter estimates of the probability distribution of drought intensity. Assumed that the drought intensity obey GEV distribution based on the use of the linear distance to do a more accurate estimate of the parameters of the probability distribution of drought intensity, calculated different return periods of drought intensity. Focus on analysis of the expected value of the limit of a certain period of time limit drought intensity probability distribution and the Qiantang River Basin drought intensity. The conclusion: Z-Index and SPI calculations made good consistency and more accurate identification of the calendar year drought of the Qiantang River Basin, multi-time-scale SPI is more in line with the actual situation of the Qiantang River. Nine climate change prediction results have their own advantages and disadvantages, the specific models and scenarios evaluation of the the arid effect is not exactly the same. Overall, both climate model HadCM3, Echam5 trends analog effect than Ccsm3 mode. The results of this study has important significance by executing the drought prediction and analysis and provide a reliable scientific support for drought research and monitoring of the sub-humid areas.

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CLC: > Astronomy,Earth Sciences > Atmospheric science (meteorology ) > Meteorological elements,atmospheric phenomenon > Water vapor,condensation,and precipitation > Precipitation > Ordinary precipitation > Precipitation caused by the disaster
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