Abstract
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.
Highlights
Introduction distributed under the terms andPrecipitation can be considered among the major variables that are frequently used to trace the extent and magnitude of climate variability [1]
Except for Bordj Bou Naama station, the Innovative Polygon Trend Analysis (IPTA) charts of the other stations do not show a regular polygon. This is due to the fact that the arithmetic average of the monthly total precipitation data is not constant and the data does not change systematically
The Innovative Polygon Trend Analysis Method was applied to total monthly precipitation data of seven stations in the Wadi Sly Basin in a 50-year period
Summary
Introduction distributed under the terms andPrecipitation can be considered among the major variables that are frequently used to trace the extent and magnitude of climate variability [1]. Gautam et al [2] and Chen et al [3] showed that hanging patterns of precipitation are among the chief consequences attributed to climate variability. Precipitation seasonality and variability are important factors to understand in hydrological processes in a catchment; they are paramount for many sectors of the economy, like agricultural [4], and they have serious environmental implications that can greatly influence the food security and ecological sustainability of the different regions on the world [5]. Juez et al [6] showed that forest can influence hydrological dynamics and delay catchments response on high precipitation. An increase of forest area in catchments can protect against the effect of climate change on water resources
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