Associations between winter atmospheric teleconnections in drought and haze pollution over Southwest China

Analysis of monthly average precipitation of Wadi Ouahrane basin in Algeria by using the ITRA, ITPAM, and TPS methods

Precipitation is one of the most significant components for the basin's hydrological cycle. Numerous features of a basin's water circulation may be affected by the chronological, geographical, and seasonal fluctuation of precipitation. It could be an important factor that influences hydrometeorological phenomena including floods and droughts. In this research, the innovative trend risk analysis (ITRA), innovative trend pivot analysis (ITPAM), and trend polygon star (TPS) methodologies of visualizing precipitation data are used to detect precipitation changes at six stations in Algeria's Wadi Ouahrane basin from 1972 to 2018. ITRA graphs show the direction of the precipitation trend (increasing-decreasing) and the trend risk class. Disparities in the polygons generated by the arithmetic mean and standard deviation ITPAM graphs demonstrate variations in precipitation seasonally and in the seasonal precipitation trends (increasing or decreasing) between sites. The TPS maps depict monthly variations in precipitation and highlight the autumn and spring transitions between the dry and wet seasons.

The Innovative Polygon Trend Analysis (IPTA) as a Simple Qualitative Method to Detect Changes in Environment—Example Detecting Trends of the Total Monthly Precipitation in Semiarid Area

Precipitation is a crucial component of the water cycle, and its unpredictability may dramatically influence agriculture, ecosystems, and water resource management. On the other hand, climate variability has caused water scarcity in many countries in recent years. Therefore, it is extremely important to analyze future changes of precipitation data in countries facing climate change. In this study, the Innovative Polygon Trend Analysis (IPTA) method was applied for precipitation trend detection at seven stations located in the Wadi Sly basin, in Algeria, during a 50-year period (1968–2018). In particular, the IPTA method was applied separately for both arithmetic mean and standard deviation. Additionally, results from the IPTA method were compared to the results of trend analysis based on the Mann–Kendall test and the Sen’s slope estimator. For the different stations, the first results showed that there is no regular polygon in the IPTA graphics, thus indicating that precipitation data varies by years. As an example, IPTA result plots of both the arithmetic mean and standard deviation data for the Saadia station consist of many polygons. This result means that the monthly total precipitation data is not constant and the data is unstable. In any case, the application of the IPTA method showed different trend behaviors, with a precipitation increase in some stations and decrease in others. This increasing and decreasing variability emerges from climate change. IPTA results point to a greater focus on flood risk management in severe seasons and drought risk management in transitional seasons across the Wadi Sly basin. When comparing the results of trend analysis from the IPTA method and the rest of the analyzed tests, good agreement was shown between all methods. This shows that the IPTA method can be used for preliminary analysis trends of monthly precipitation.

Spatial and Temporal Analysis of Dry and Wet Spells in the Wadi Cheliff Basin, Algeria

The Mediterranean Basin, located in a transition zone between the temperate and rainy climate of central Europe and the arid climate of North Africa, is considered a major hotspot of climate change, subject to water scarcity and drought. In this work, dry and wet spells have been analyzed in the Wadi Cheliff basin (Algeria) by means of annual precipitation observed at 150 rain gauges in the period 1970–2018. In particular, the characteristics of dry and wet spells (frequency, duration, severity, and intensity) have been evaluated by means of the run theory applied to the 12-month standardized precipitation index (SPI) values. Moreover, in order to detect possible tendencies in the SPI values, a trend analysis has been performed by means of two non-parametric tests, the Theil–Sen and Mann–Kendall test. The results indicated similar values of frequency, severity, duration, and intensity between the dry and the wet spells, although wet events showed higher values in the extreme. Moreover, the results of the trend analysis evidenced a different behavior between the northern side of the basin, characterized by a negative trend in the 12-month SPI values, and the southern side, in which positive trends were detected.