Drought is a widespread natural hazard resulting from an extended period of reduced rainfall, with significant socioeconomic and ecological consequences. Drought severity can impact food security globally due to its high spatial and temporal coverage. The primary objective of this paper consists of a comparative spatiotemporal analysis of environmental extremes (drought/wetness) through the estimation of a twelve-month Standardized Precipitation Index (SPI12) between three distinct vulnerable agricultural regions in the Mediterranean basin (i.e., Spain, Lebanon and Tunisia), under a climate change environment in the last 38 years (1982–2020). The added value of this paper lies in the simultaneous estimation of temporal and spatial variability of drought and wetness periodic events, paying special attention to the geographical patterns of these extremes both in annual and interannual (seasonal) time scales. The results indicated that Spain and Tunisia (western Mediterranean) exhibit similar patterns over the studied period, while Lebanon demonstrates contrasting trends. Comparing the two extreme dry hydrological years, the Spanish study area faced the highest drought intensity, areal extent and duration (SPI12 = −1.18; −1.84; 28–78%; 9–12 months), followed by the Lebanese (SPI12 = −1.28; −1.39; 37–50%; 7–12 months) and the Tunisian ones (SPI12 = −1.05; −1.08; 10–34%; 8 months). Concerning the wettest hydrological years, the Lebanese study domain has recorded the highest SPI12 values, areal extent and duration (SPI12 = 1.58; 2.28; 66–83%; 8–11 months), followed by the Tunisian (SPI12 = 1.55; 1.79; 49–73%; 7–10 months) and Spanish one (SPI12 = 1.07; 1.99; 21–73%; 4–11 months). The periodicity of drought/wetness episodes is about 20 years in Spanish area and 10 years in the Lebanese area (for drought events), whereas there seems no periodicity in the Tunisian one. Understanding the spatial distribution of drought is crucial for targeted mitigation strategies in high-risk areas, potentially avoiding broad, resource-intensive measures across entire regions.
Agroclimatic classification identifies zones for efficient use of natural resources leading to optimal and non-optimal crop production. The aim of this paper is the development of a methodology to determine sustainable agricultural zones in three Mediterranean study areas, namely, “La Mancha Oriental” in Spain, “Sidi Bouzid” in Tunisia, and “Bekaa” valley in Lebanon. To achieve this, time series analysis with advanced geoinformatic techniques is applied. The agroclimatic classification methodology is based on three-stages: first, the microclimate features of the region are considered using aridity and vegetation health indices leading to water-limited growth environment (WLGE) zones based on water availability; second, landform features and soil types are associated with WLGE zones to identify non-crop-specific agroclimatic zones (NCSAZ); finally, specific restricted crop parameters are combined with NCSAZ to create the suitability zones. The results are promising as compared with the current crop production systems of the three areas under investigation. Due to climate change, the results indicate that these arid or semi-arid regions are also faced with insufficient amounts of precipitation for supporting rainfed annual crops. Finally, the proposed methodology reveals that the employment and use of remote sensing data and methods could be a significant tool for quickly creating detailed, and up to date agroclimatic zones.
Abstract. Risk assessment constitutes the first part within the risk management framework and involves evaluating the importance of a risk, either quantitatively or qualitatively. Risk assessment consists of three steps, namely risk identification, risk estimation and risk evaluation. Nevertheless, the risk management framework also includes a fourth step, i.e., the need for feedback on all the risk assessment undertakings. However, there is a lack of such feedback, which constitutes a serious deficiency in the reduction of environmental hazards at the present time. Risk identification of local or regional hazards involves hazard quantification, event monitoring including early warning systems and statistical inference. Risk identification also involves the development of a database where historical hazard information and hazard effects are included. Similarly, risk estimation involves magnitude–frequency relationships and hazard economic costs. Furthermore, risk evaluation consists of the social consequences of the derived risk and involves cost-benefit analysis and community policy. The objective of this review paper is twofold. On the one hand, it is to address meteorological hazards and extremes within the risk management framework. Analysis results and case studies over Mediterranean ecosystems with emphasis on the wider area of Greece, in the eastern Mediterranean, are presented for each of the three steps of risk assessment for several environmental hazards. The results indicate that the risk management framework constitutes an integrated approach for environmental planning and decision-making. On the other hand, it sheds light on advances and current trends in the considered meteorological and environmental hazards and extreme events, such as tornadoes, waterspouts, hailstorms, heat waves, droughts, floods, heavy convective precipitation, landslides and wildfires, using recorded datasets, model simulations and innovative methodologies.
The quantity of freshwater available per person in the world has been proceeded to decrease due to a combination of factors, including population increase, water pollution, inadequate planning and management of transboundary water, and inefficient operation of water supply and distribution systems. There is a direct water source to cease increasing potential for water scarcity, crisis and associated conflicts around the world in the future called rainwater harvesting that is an ancient technique enjoying a revival in popularity due to the inherent quality of rainwater and interest in reducing consumption of treated water. Rainwater harvesting is included as an innovative site design strategy to minimise runoff based on LID practices. The present study on literature attempts to offer a comprehensive account of the above issues and also some important guidelines for advancing research in this direction. Assessments of past, present and future statuses of the world's water are reviewed.
Abstract The spatio-temporal variability of daily precipitation series was investigated in a semiarid region of central Macedonia in northern Greece, Ten years of daily rainfall records for seven stations in the region constituted the data base. The spatial characteristics were examined by drawing composite correlation diagrams for the cool (October-March) season and the warm (April-September) season, and the results confirmed the regional homogeneity of the data sets. Furthermore, the temporal analysis indicated that the non-rainy days constituted the major portion of days throughout the year at all the stations. Similarly, light rainfall represented the majority of rainy days. Moreover, the annual rainfall variation showed high values in March, April and November with low values occurring in the summer and autumn. A sharp increase of rainfall between the 185th and the 195th day of the year must be taken into account when the harvest is scheduled. Harmonic and Power Spectrum analyses applied to the annual variation of rain depths using 5-day intervals revealed significant periodicities of 26, 122, 365 and 55 days. Finally the analysis of the annual variation of rain occurrences. revealed periodicities of 365 and 122 days.
The supply of water needed for maximum crop growth, total water consumption, and the determination of capacity of canals and reservoirs constitute the important parts of an irrigation and drainage project.The Penman-Monteith method, approved by the FAO, is the standard for calculating the evapotranspiration of reference crop.(Gang et al. 2006).This method requires a large amount of climate data, but sometimes a number of meteorological parameters, such as radiation, temperature, and precipitation, are not available (Mayer & Isomer 2002; Almoux et al., 2005).It may be noted that the sensitivity of evapotranspiration to meteorological parameters is not the same in different regions; hence it may be necessary to more precisely estimate some of the parameters.While estimating evapotranspiration by the Penman-Monteith FAO 56 model and the fuzzy inference system, An sari and Moradi (2011) found that solar radiation was the most effective parameter.SabziParvar et al. (2007) evaluated the sensitivity of the Penman-Monteith FAO-56, Jensen-Hayes, and Hargreaves models to weather parameters and found that evapotranspiration was most sensitive to solar radiation parameters and air temperature.On estimating evapotranspiration by the Penman-Monteith method for 64 stations from different climatic regions of China, Thomas (2000) found that solar radiation had the highest impact in the south, and wind speed, relative humidity, and maximum temperature were the main factors in the northeast, the center, and northwest of China.Some of the weather parameters can be estimated and some measured.Erfanian and Babaii (2013) compared three models for estimating radiation, including hybrid models, modified Daneshyar and Sabbaghin a study on evapotranspiration in Tabriz, Iran, and found that the hybrid model had a higher accuracy than the two other models.Comparing hybrid and Angstrom-Prescott models at 14 stations in Japan, Yang et al. ( 2001) concluded that the hybrid model performed better than did the Angstrom-Abstract: Evapotranspiration plays a fundamental role in agricultural water management.Its calculation requires weather data, such as radiation, which are often not available and should be estimated indirectly.This study employed the Ref-ET software for estimating radiation for the period of 1970-2011 under two different climates of Rasht and Isfahan.Results showed that for Isfahan, the first method (minimum and maximum temperature difference) was satisfied with KRS=0.17,indicating good results.For Rasht, radiation was estimated using the third method (K RS ) assuming K RS =0/44, and the evapotranspiration relative to the values of evapotranspiration in the presence of data was acceptable.Also, results of evapotranspiration derived from the Turque equation in Isfahan and results of the Penman-Monteith FAO relation for Rasht were more acceptable.
Abstract The natural variability of precipitation in agricultural regions both in time and space is modelled using extensions of Box & Jenkins (1976) methodology based on the ARMA procedure. This broad class of aggregate regional models belongs to the general family of Space-Time Autoregressive Moving Average (STARMA) processes. The paper develops a three-stage iterative procedure for building a ST ARMA model of multiple precipitation series. The identified model is STMA (13). The emphasis is placed on the three stages of the model building procedure, namely identification, parameter estimation and diagnostic checking. In the parameter estimation stage the polytope (or simplex) method and three further classical nonlinear optimization algorithms are used, namely two conjugate gradient methods and a quasi-Newton method. The polytope method has been adopted and the developed model performed well in describing the spatio-temporal characteristics of the multiple precipitation series. Application has been attempted in a rural watershed in southern Canada.
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