安徽省干旱灾害风险图研究

发布时间：2018-03-08 02:14

本文选题：干旱灾害风险图　切入点：农业干旱　出处：《合肥工业大学》2013年硕士论文　论文类型：学位论文

【摘要】：区域干旱已成为全球气候变化背景下典型的极端自然现象。干旱作为当今世界气候变化背景下的典型的自然现象，正在广泛的影响世界上相当多的国家。近年来受到生态环境破坏和气候变化的影响，以及人口急剧增长、工业发展和城市化进程加快，致使农业供水量有所减少，农业缺水量进一步加大，使得农业干旱出现频次不断增长，旱灾损失呈现明显加重的趋势。对干旱灾害风险图的编制研究，可有效地加强对旱灾管理，促进水资源的合理分配，并提高地区的抗旱减灾能力。基于此种情况，论文从具体农作物入手，通过计算农作物供水和需水两方面，结合作物生长函数，建立区域干旱灾害风险图具体编制方法，并在安徽省淮北平原地区进行实证研究，，主要取得了如下结果：（1）分析了安徽淮北平原地区供水指标的时空规律。通过对淮北平原16县市多年实测数据分析研究：地下水埋深呈现由淮北平原地区北部向南部递减的趋势，只有局部地区有些许变异；土壤含水率却在不同作物的不同生长期，呈现不同的情况，基本呈现西部向东部递增的趋势，但在部分生长期，东部边缘地区的土壤含水率较低。（2）优选了研究区的“作物—水”模型。根据地区具体情况，主要考虑显著性、相关系数和各个模型水分敏感系数变化规律等对“作物与水模型”进行筛选，最终选定各方面相对较好，且模型结构形式较好的Jensen模型。（3）确定了研究区“作物—水”模型参数。根据1996年~2000年的实验数据，应用最小二乘法和遗传算法，率定模型参数，结果表明：两种方法率定的结果相差较为明显，且由于其中最小二乘法率定的参数结果出现小于零，不符合客观规律。经过仔细的分析比较，认定利用遗传算法率定的结果符合实际。（4）淮北平原地区干旱灾害损失的空间分布特征分析。以小麦和玉米两种淮北地区的典型作物作为代表，结果表明：小麦分蘖期损失以涡阳县和濉溪县为界，西部地区明显较东部地区为高；玉米损失中部较大，其他地区较小。同种作物在相同生长期内，随着无有效降雨天数增加，各地区损失逐渐加大且趋势完全相同；同种作物不同生长期或是不同作物不同生长期，损失趋势不相同。
[Abstract]:Regional drought has become a typical extreme natural phenomenon in the context of global climate change. Which is affecting a considerable number of countries in the world... in recent years as a result of ecological destruction and climate change, as well as rapid population growth, accelerated industrial development and urbanization, resulting in a reduction in agricultural water supply, Agricultural water shortage is further increased, which makes the frequency of agricultural drought increase continuously, and the drought losses show a trend of aggravation. The compilation and study of drought disaster risk map can effectively strengthen drought management and promote the rational allocation of water resources. Based on this situation, the paper starts with the concrete crops, through calculating the two aspects of crop water supply and water demand, combining with the crop growth function, establishes the concrete method of compiling the regional drought disaster risk map. An empirical study was carried out in Huaibei Plain of Anhui Province. The main results are as follows:. 1) the temporal and spatial regularity of water supply index in Huaibei Plain area of Anhui Province is analyzed. Based on the experimental data of 16 counties and cities in Huaibei Plain for many years, the groundwater buried depth shows a decreasing trend from the north to the south of Huaibei Plain area. There is only some variation in local area, but the soil moisture content is different in different growing period of different crops, and it is increasing gradually from west to east, but in some growing period, the soil moisture content in the eastern edge area is lower than that in the eastern edge area. (2) the "crop-water" model in the research area was selected. According to the specific situation of the region, the "crop and water model" was screened by considering the significance, the correlation coefficient and the variation law of the water sensitivity coefficient of each model. Finally, the Jensen model which is relatively good in all aspects and has a better structure is selected. According to the experimental data from 1996 to 2000, the model parameters are determined by using the least square method and genetic algorithm. The results show that the difference between the two methods is obvious. Because the parameter result of least square method is smaller than zero, it does not accord with the objective law. After careful analysis and comparison, it is concluded that the result determined by genetic algorithm is in line with the reality. 4) the spatial distribution characteristics of drought disaster losses in Huaibei Plain were analyzed. The typical crops of wheat and maize were taken as the representative. The results showed that the wheat losses at tillering stage were bounded by Guoyang County and Suixi County. In the same growing period, with the increase of the number of days without effective rainfall, the losses of the same crop increased gradually and the trend was the same. Different growth stages of the same crop or different growth period of different crops, the loss trend is different.
【学位授予单位】：合肥工业大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：P426.616;P285

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