2 research outputs found

    基于遥感的滑坡和洪水对土地覆盖变化影响的研究——以吉尔吉斯斯坦纳伦河盆地为例

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    目前,包括吉尔吉斯斯坦在内的世界各国受突发事件的风险逐年增加。在吉尔吉斯斯坦,共有 5000 个山体滑坡区, 3103 条河流受泥沙影响。现有的风险和新的威胁要求在预防和应对紧急情况时寻求新的方法。本文介绍了自然灾害带来的后果:洪水和山体滑坡对纳伦河流域土地覆盖的影响。洪水和山体滑坡是造成人类,财产和环境灾难性损失的自然灾害之一。 不能避免和阻止它的发生,但可以通过有效途径减少其影响,如建立预警防范系统、基于社区的灾害管理培训等。通过绘制用于识别高风险区域的洪水和滑坡地图可以达到实现预警防范的目的。风险评估有利于城市基础设施建设者和风险管理者在极端天气中制定应对自然灾害的应急措施。本研究的目的是利用遥感卫星图像和地理信息系统工具结合气候,地质和河流流量数据,为纳伦河流域创建山体滑坡和洪水路线的风险图。在本研究中,使用了 Landsat TM / ETM + / OLI 和 SRTM DEM 数据。对洪水,滑坡和土地覆盖变化进行了准确性评估。最终所有使用的数据都叠加到ArcMap 中,以便为研究区编制滑坡和洪水风险地图。研究结果表明,洪水是研究区的主要自然灾害。根据结果显示,大约 10%的面积被归类为洪水高危区, 43%被归类为中等风险区, 34%被类归为低风险区,而只有 15%被归类为没有已知洪水风险区。对于山体滑坡测绘,对滑坡发生的 8 个因素(斜率,曲率,海拔, TWI, NDVI, NDSI,土地覆盖,降水)进行了统计分析。频率比模型和对比预测模型分别利用总数据的 72.1%和 69%进行预测分析。最后,对不同年份的土地覆盖变化进行了评估。创建了 500 米和 1000 米的河岸带缓冲区。结果显示: 500 米缓冲区发生了 39%-42%的变化, 1000 米缓冲区发生了 18%-21%。没有发生变化的区域约为 33%-37%

    Hydrological Forecasting under Climate Variability Using Modeling and Earth Observations in the Naryn River Basin, Kyrgyzstan

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    The availability of water resources in Central Asia depends greatly on snow accumulation in the mountains of Tien-Shan and Pamir. It is important to precisely forecast water availability as it is shared by several countries and has a transboundary context. The impact of climate change in this region requires improving the quality of hydrological forecasts in the Naryn river basin. This is especially true for the growing season due to the unpredictable climate behavior. A real-time monitoring and forecasting system based on hydrological watershed models is widely used for forecast monitoring. The study’s main objective is to simulate hydrological forecasts for three different hydrological stations (Uch-Terek, Naryn, and Big-Naryn) located in the Naryn river basin, the main water formation area of the Syrdarya River. We used the MODSNOW model to generate statistical forecast models. The model simulates the hydrological cycle using standard meteorological data, discharge data, and remote sensing data based on the MODIS snow cover area. As for the forecast at the monthly scale, the model considers the snow cover conditions at separate elevation zones. The operation of a watershed model includes the effects of climate change on river dynamics, especially snowfall and its melting processes in different altitude zones of the Naryn river basin. The linear regression models were produced for monthly and yearly hydrological forecasts. The linear regression shows R2 values of 0.81, 0.75, and 0.77 (Uch-Terek, Naryn, and Big-Naryn, respectively). The correlation between discharge and snow cover at various elevation zones was used to examine the relationship between snow cover and the elevation of the study. The best correlation was in May, June, and July for the elevation ranging from 1000–1500 m in station Uch-Terek, and 1500–3500 m in stations Naryn and Big-Naryn. The best correlation was in June: 0.87; 0.76; 0.84, and May for the elevation ranging from 1000–3500 m in station Uch-Terek, and 2000–3000 m in stations Naryn and Big-Naryn. Hydrological forecast modeling in this study aims to provide helpful information to improve our under-standing that the snow cover is the central aspect of water accumulation
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