Investigating the Reliability of Stationary Design Rainfall in a Mediterranean Region under a Changing Climate

Abstract

Extreme rainfall events have been more frequent in recent decades, potentially as a climate change effect. This has been leading to a higher risk of the failure of existing hydraulic infrastructures, and to a higher awareness regarding the unreliability of design rainfall calculated with reference to historical data recorded in the last century. With this in mind, the present study questions the stationary assumption of the rainfall Depth–Duration–Frequency curves commonly used in Sicily, the biggest island of the Mediterranean Sea. Quantiles derived from the most up-to-date regional method, regarding Sicily, based on observations in the period 1928–2010, have been compared with those extracted from a high-resolution dataset related to the period 2002–2022, provided by the SIAS agency. The results showed a remarkable underestimation of the rainfall quantiles calculated with the regional approach, especially at the shortest durations and low return periods. This means that new hydraulic works should be designed with reference to longer return periods than in the recent past, and those that currently exist may experience a higher risk of failure. Future investigation of this aspect is crucial for enhancing the effectiveness of water management and detecting hydrological risks under a changing climate.

Hydrological Properties of Rill Erosion on a Soil from a Drought-Prone Area during Successive Rainfalls as a Result of Microorganism Inoculation

“…Rill erosion is formed due to flow concentration and is considered a transitional stage from surface erosion to rill and gully erosions [11,[16][17][18]. Generally, various rainfall characteristics, including intensity, duration, frequency, and erosivity [3,[19][20][21], hydraulic flow characteristics such as shear stress [22,23], depth and velocity [11,14,[24][25][26], as well as rill characteristics including depth, length, width, and density affect soil and water loss [11,14,27]. In this case, the behavior of rill development during successive rainfalls due to significant changes in soil components and its hydrological response is of considerable importance.…”

Spatiotemporal analysis and predicting rainfall trends in a tropical monsoon-dominated country using MAKESENS and machine learning techniques

“…Many studies 19 – 21 have examined the spatiotemporal patterns of rainfall in climatic zones across the world 22 – 25 . Some research has been conducted on the semi-regional scale of rainfall variability 26 – 29 . Throughout the past 100 years, the amount of rainfall on Earth has increased by around 2% 14 , but according to IPCC 30 , its growth has always been unequal in terms of time and space.…”

“…Ren et al 35 observed for the annual average rainfall over the Tibetan Plateau in China, similar trends have been seen during the previous few decades, also the same pattern in India 33 , 36 , in northwest Pakistan 17 , 18 , and in the China-Pakistan Economic Corridor area 37 . However, the Yellow River Basin, China 38 , the Mediterranean region 29 , and Iran have all seen a decline in annual mean rainfall 19 . A significant upward trend in annual, monsoon, and pre-monsoon rainfalls has lately been found in Bangladesh, according to a growing number of earlier research 39 – 41 .…”

“…Recent years have seen several studies done on rainfall trends around the world 17 , 26 , 29 , 31 , 50 – 52 , and in Bangladesh 40 , 42 , 43 , 53 , 54 . Most of the studies used the Simple linear trend 55 , the Mann–Kendall test 33 , 40 , the Mann–Kendall and Spearman’s rho tests 17 , 46 , Spearman’s rank test 23 , Pre-Whitening approach 57 to detect the rainfall trend.…”