为评估干旱特征,开发了三种多层级标准化干旱指数 (TMSDI)
Aamina Batool1, Veysi Kartal2, Zulfiqar Ali3
1College of Statistical Sciences, University of the Punjab, Lahore, Pakistan.
Environmental monitoring and assessment
|February 11, 2025
概括
这项研究引入了三种多级标准化干旱指数 (TMSDI) 以更好地监测干旱. 新指数与标准化降水指数 (SPI) 有着很强的相关性,这证明了气候分析的有效性.
科学领域:
- 环境科学 环境科学
- 气候科学 气候科学
- 水文学的水文学
背景情况:
- 干旱是影响全球水资源,农业和生态系统的重大自然灾害.
- 由于干旱的复杂性,监测和预测干旱是具有挑战性的.
- 人类活动加剧了干旱的影响,需要先进的评估工具.
研究的目的:
- 介绍和评估新的三种多级标准化干旱指数 (TMSDI).
- 评估TMSDI与SPI和SPTI等既定干旱指数之间的相关性.
- 分析长期干旱模式和概率.
主要方法:
- 使用降水,温度和NDVI数据开发TMSDI.
- 跨多个时间尺度 (1-48个月) 的TMSDI,SPI和SPTI之间的相关性分析.
- 马尔科夫链分析的应用,以确定干旱条件的稳定状态概率.
主要成果:
- TMSDI与标准化降雨指数 (SPI) 呈现出一致且强烈的相关性.
- 在TMSDI和标准化降雨温度指数 (SPTI) 之间观察到较弱的相关性.
- 分析表明,长期来看,极端干旱比极端潮湿更有可能发生.
结论:
- TMSDI是一个可靠和准确的工具,用于监测各种时间尺度和气候因素的干旱.
- 该指数与SPI的密切联系凸显了其在以降水为基础的干旱评估中的有用性.
- 调查结果表明,由于极端干旱的可能性更高,需要采取主动干旱管理战略.
相关概念视频
Precipitation and Co-precipitation
1.7K
Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
1.7K
Responses to Drought and Flooding
10.6K
Water plays a significant role in the life cycle of plants. However, insufficient or excess of water can be detrimental and pose a serious threat to plants.
10.6K
Precipitation Processes
408
The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
408
Precipitation Gravimetry
5.1K
Precipitation gravimetry is based on converting an analyte into a sparingly soluble precipitate, which is separated by filtration and weighed. An ideal precipitate should be pure, insoluble, of known composition, and easily filtered from the reaction mixture.
In determining nickel by gravimetric analysis, a precipitant of ethanolic dimethylglyoxime is added to a hot nickel salt solution. This is quickly followed by the dropwise addition of dilute ammonia solution until precipitation occurs. A...
In determining nickel by gravimetric analysis, a precipitant of ethanolic dimethylglyoxime is added to a hot nickel salt solution. This is quickly followed by the dropwise addition of dilute ammonia solution until precipitation occurs. A...
5.1K
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
39
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
39
Calculating Standard Deviation
7.3K
The standard deviation is the most common measure of variation. It is a value that tells us how far a data value is from the mean value in a dataset. Further, the standard deviation is always a positive value or zero.
The standard deviation value is small when all the data is concentrated close to the mean. Here the data exhibits low variation. The standard deviation value is larger when the data values are more spread out from the mean. Here, the data displays high...
The standard deviation value is small when all the data is concentrated close to the mean. Here the data exhibits low variation. The standard deviation value is larger when the data values are more spread out from the mean. Here, the data displays high...
7.3K


