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The Prediction, Early-warning For Snowmelt Flood And Decision Support Based On '3S' Technologies In Xinjiang

Posted on:2010-10-29Degree:DoctorType:Dissertation
Country:ChinaCandidate:Z H LiuFull Text:PDF
GTID:1101360278461411Subject:Cartography and Geographic Information Engineering
Abstract/Summary:PDF Full Text Request
China,especially Xinjiang, is a country or region with wide snow distribution, snow disaster and spring flood frequently-occurring. Under the background of global climate change there is a tendency to increase the flood disaster frequency, particular glacier and snow melt floods, whose loss is very large. The prevention of each disaster should be based on an early-warning. Only to ravel the snowmelt mechanism, runoff and processes, to monitor, predict snowmelt flood and early-warning, to institute some effective measures before the disaster could be avoided or reduced in the lowest. Remote Sensing (RS), Geographical Information System (GIS), Global Positioning System (GPS), Compute technology and atmospheric numeric forecasting mode provide a powerful foundation and guarantee for monitoring the snow information in larger area and setting up the distributed snowmelt runoff model and the DSS for snowmelt flood early-warning. Therefore it has an important significance and a great deal of social, economic and ecological benefits for disaster prevention and reduction to extract the information of snow and melt, analyze and calculate with models, provide the flood early-warning to government in real time and precision.This research made the extraction of the information of underlying surface and snow in the study area (Juntanghu watershed in the northern slope of Tianshan Mountain) based on'3S'technology and higher resolution DEM according to the features of the spring snowmelt flood in Xinjiang. This study using the atmospheric mode WRF2.2 and Chinese national bureau T213L13 data 24h meteorological field was forecasted from Feb. to March 2008 in the study area. Then the distributed Xinjiang snowmelt runoff model was drived by the forecasted meteorological field from WRF and snow melt data to forecast snowmelt flood processes. And the disaster and early-warning grade of floods were calculated and assessed by the early-warning model of snowmelt flood. With the DSS for snowmelt flood early-warning in Xinjiang the early-warning could be provided for decision maker to assist decision making, to provide the technical and informational support for disaster prevention and reduction.This study paid attention to the modeling snowmelt flood and decision making for early-warning and put forward correspondent ideas and approaches. The study contents and conclusions are following: (1) Based on'3S'and computer technology this study developed a GIS spatial analysis module including sub-module of watershed information extraction in the DSS for snowmelt flood early-warning. It finished the task extracting watershed information, such as DEM, slope, aspect of slope, flow direction, river network etc., is not depend on the other GIS software, and the spatial and temporal resolution may be adjusted by need as far as possible. The results are good.(2) It was analyzed and verified that the snow and melt information extracted from the MODIS image data with higher temporal resolution and by GIS technology, meanwhile, by means of GPS to investigate it in local field. The results indicated: the precision of snow cover extracted by snow fractional (SF) is more than that of normalized difference snow index (NDSI). The average precision of snow cover by SF is below 8% of relative error. On the foundation of grading snow depth the double linear regression model which inversed the snow depth during stable snow period was set up. Through a test the average absolute error is 1.47cm, the mean relative error is below 10.96%. But this model is unsuited for snow melting period.(3) According to the Split Window Algorithms of Qin Zhihao and so on the land surface temperature (LST) during snow melting period in study area was obtained by the interpretation and calculation from MODIS data. By test the error is from 0.5 to 3.0℃, and if the algorithm is modified locally the results can be met the need of model input.(4) The limited-region 24-hour Numeric Weather Forecasting System is established by using the new generation atmospheric model——Weather Research and Forecasting Model (WRF) V2.2 with the initial fields and lateral boundaries provided by the T213 L31 from Chinese National Meteorological Bureau. The predicted spatial resolution is 1km, the temporal is 1h. The predicted results accorded with the observed on the whole, have got a good effect.(5) The self-design distributed snowmelt runoff model based on energy balance, water balance and'3S'technology was established in this study. It is designed that taking RS(MODIS,ETM)data and the observed data on spot as the main data sources, model parameters with spatial and temporal difference should be processed in spatial distributed form. In application the distributed Xinjiang snowmelt runoff model was drived by the forecasted meteorological field from WRF and snow melt data to forecast snowmelt flood processes. The results indicate: the predicted runoff process fitted close to the observed.(6) This study established an early-earning mode and standard which is adequate for the local situation. In the study of early-warning index the main factors which can affect snowmelt flood disaster were selected, such as causing disaster factor, bearing disaster factor and the contributive factor of facilities for flood control, for not only the magnitude, grade and spatial and temporal distribution of snowmelt flood should be considered, but also the local economic and social situation should be integrated. The quantitative early-warning index which reflects comprehensively the risk size of local flood regards as the basis to grade the early-warning of spring snowmelt flood in Xinjiang.(7) To meet the need of early-earning decision this study designed the structure of Decision Support System (DSS) for snowmelt flood early warning in Xinjiang. Based on the structure of B/S and J2EE, the general frame and the methods of software realization in the DSS were put forward, including design of general frame, the selection of development environment and programming way. The applied example shows: this DSS is an effective tool for automatic obtaining of model parameters, data transition between models, visualization of model results. And the application of J2EE technology in the DSS was realized. The effect of design is good.At the end of the dissertation, the author draws a conclusion and puts forward some key problems and developing trends for future works.
Keywords/Search Tags:'3S'technology, snow information extraction, WRF, Coupling atmospheric and hydrologic models, Distributed snowmelt runoff model, DSS for snowmelt flood early warning
PDF Full Text Request
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