|Drought is one of the most significant environmental disasters, especially in arid and semi-arid regions. Drought indices as a tool for management practices seeking to deal with the drought phenomenon are widely used around the world. One of these indicators is the Palmer drought severity index (PDSI), which is used in many parts of the world to assess the drought situation and continuation. In this study, the drought state of Fars Province in Iran was evaluated by using the PDSI over 1995–2014 according to meteorological data from six weather stations in the province. A statistical downscaling model (SDSM) was used to apply the output results of the general circulation model in Fars Province. To implement data processing and prediction of climate data, a statistical period 1995–2014 was considered as the monitoring period, and a statistical period 2019–2048 was for the prediction period. The results revealed that there is a good agreement between the simulated precipitation (R2>0.63; R2, determination coefficient; MAE<0.52; MAE, mean absolute error; RMSE<0.56; RMSE, Root Mean Squared Error) and temperature (R2>0.95, MAE<1.74, and RMSE<1.78) with the observed data from the stations. The results of the drought monitoring model presented that dry periods would increase over the next three decades as compared to the historical data. The studies showed the highest drought in the meteorological stations Abadeh and Lar during the prediction period under two future scenarios representative concentration pathways (RCP4.5 and RCP8.5). According to the results of the validation periods and efficiency criteria, we suggest that the SDSM is a proper tool for predicting drought in arid and semi-arid regions.|
|The water deficit in arid and semi-arid regions is the primary limiting factor for the development of urban greenery and forestation. In addition, planting the species that consume low levels of water is useful in arid and semi-arid regions that have poor water management measures. Leaf water potential (Ψ) is a physiological parameter that can be used to identify drought resistance in various species. Indeed, Ψ is one of the most important properties of a plant that can be measured using a pressure chamber. Drought avoiding or drought resistant species have a lower Ψ than plants that use normal or high levels of water. To determine drought resistance of species that are suitable for afforestation in arid urban regions, we evaluated twenty woody species in the Isfahan City, central Iran. The experimental design was random split-split plots with five replications. The species were planted outdoor in plastic pots and then subjected to treatments that consisted of two soil types and five drip irrigation regimes. To evaluate the resistance of each species to drought, we used the Ψ and the number of survived plants to obtain the drought resistance index (DRI). Then, cluster analysis, dendrogram, and similarity index were used to group the species using DRI. Result indicates that the evaluated species were classified into five groups: (1) high water consuming species (DRI>–60 MPa); (2) above normal water consuming species (–60 MPa≥DRI>–90 MPa); (3) normal water consuming species (–90 MPa≥DRI>–120 MPa); (4) semi-drought resistant species (–120 MPa≥DRI>–150 MPa); and (5) drought resistant species (DRI≤–150 MPa). According to the DRI, Salix babylonica L., Populus alba L., and P. nigra L. are high water consuming species, Platanus orientalis L. and Albizia julibrissin Benth are normal water consuming species, and Quercus infectoria Oliv. and Olea europaea L. can be considered as drought resistant species.|
|Net primary production (NPP) is an indicator of rangeland ecosystem function. This research assessed the potential of the Carnegie Ames Stanford Approach (CASA) model for estimating NPP and its spatial and temporal changes in semi-arid rangelands of Semirom County, Iran. Using CASA model, we estimated the NPP values based on monthly climate data and the normalized difference vegetation index (NDVI) obtained from the MODIS sensor. Regression analysis was then applied to compare the estimated production data with observed production data. The spatial and temporal changes in NPP and light utilization efficiency (LUE) were investigated in different rangeland vegetation types. The standardized precipitation index (SPI) was also calculated at different time scales and the correlation of SPI with NPP changes was determined. The results indicated that the estimated NPP values varied from 0.00 to 74.48 g C/(m2?a). The observed and estimated NPP values had different correlations, depending on rangeland conditions and vegetation types. The highest and lowest correlations were respectively observed in Astragalus spp.-Agropyron spp. rangeland (R2=0.75) with good condition and Gundelia spp.-Cousinia spp. rangeland (R2=0.36) with poor and very poor conditions. The maximum and minimum LUE values were found in Astragalus spp.-Agropyron spp. rangeland (0.117 g C/MJ) with good condition and annual grasses-annual forbs rangeland (0.010 g C/MJ), respectively. According to the correlations between SPI and NPP changes, the effects of drought periods on NPP depended on vegetation types and rangeland conditions. Annual plants had the highest drought sensitivity while shrubs exhibited the lowest drought sensitivity. The positive effects of wet periods on NPP were less evident in degraded areas where the destructive effects of drought were more prominent. Therefore, determining vegetation types and rangeland conditions is essential in NPP estimation. The findings of this study confirmed the potential of the CASA for estimating rangeland production. Therefore, the model output maps can be used to evaluate, monitor and optimize rangeland management in semi-arid rangelands of Iran where MODIS NPP products are not available.|
|Drought acutely affects economic sectors, natural habitats and communities. Understanding the past spatial and temporal patterns of drought is crucial because it facilitates the forecasting of future drought occurrences and informs decision-making processes for possible adaptive measures. This is especially important in view of a changing climate. This study employed the World Meteorological Organization (WMO)-recommended standardized precipitation index (SPI) to investigate the spatial and temporal patterns of drought in Zambia from 1960 to 2016. The relationship between the occurrence of consecutive dry days (CDD; consecutive days with less than 1 mm of precipitation) and SPI was also investigated. Horizontal wind vectors at 850 hPa during the core of the rainy season (December–February) were examined to ascertain the patterns of flow during years of extreme and severe drought; and these were contrasted with the patterns of flow in 2007, which was a generally wet year. Pressure vertical velocity was also investigated. Based on the gamma distribution, SPI successfully categorized extremely dry (with a SPI value less than or equal to –2.0) years over Zambia as 1992 and 2015, a severely dry (–1.9 to –1.5) year as 1995, moderately dry (–1.4 to –1.0) years as 1972, 1980, 1987, 1999 and 2005, and 26 near normal years (–0.9 to 0.9). The occurrence of CDD was found to be strongly negatively correlated with SPI with a coefficient of –0.6. Further results suggest that, during wet years, Zambia is influenced by a clockwise circulating low-pressure zone over the south-eastern Angola, a second such zone over the northern and eastern parts, and a third over the Indian Ocean. In stark contrast, years of drought were characterized by an anti-clockwise circulating high-pressure zone over the south-western parts of Zambia, constraining precipitation activities over the country. Further, wet years were characterized by negative pressure vertical velocity anomalies, signifying ascending motion; while drought years were dominated by positive anomalies, signifying descending motion, which suppresses precipitation. These patterns can be used to forecast drought over Zambia and aid in strategic planning to limit the potential damage of drought.|
Since 1960, the steppe regions of North Africa have been subject to an increasing desertification, including the degradation of traditional pastures. The initially dominant species (Artemisia herba-alba, Lygeum spartum and Stipa tenacissima) declined and were progressively replaced by other species (Atractylis serratuloides and Salsola vermiculata) that are more tolerant to the new conditions. It is not clear whether these changes are due to anthropogenic reasons or climatic determinism. We have carried out a statistical analysis of the climate to detect putative rainfall changes during the 20th century in the Algerian steppes based on data from 9 meteorological stations, including 2 Saharan stations (El Oued and Touggourt), 3 pre-Saharan stations (Biskra, Laghouat and Ain Sefra) and 4 steppe stations (Djelfa, Saida, Méchéria and El-Bayadh) located in the arid high plains, which represent the bioclimate diversities of the region. Previous studies suggested that significant rainfall changes for the 20th century only had records in the south of the Oran region. Most of the studies, however, looked at restricted territories over limited periods, and did not integrate the rainiest period 2004–2014. Our work is designed to integrate all the longest time series of meteorological data available for the steppe regions of Algeria. Our results confirm the spatial rainfall distribution (significant rainfall changes only recorded in the southwestern region) evidenced by previous studies, and reveal a decreasing rainfall gradient from northeastern to southwestern Algeria. Moreover, the results reveal a trend of significant decrease of rainfall in the southern Oran region, marked by two drought periods in 1980–1985 and 1999–2003. However, with the exception of the southwestern region, rainfall overall has not declined since the beginning of the 20th century. While less marked in other regions, the drought appear to have affected all territories of the Algerian steppe. Consequently, our study implies that the climate was not a leading influence in the on-going degradation of the vegetation cover of steppe landscapes. Such a vegetation evolution thus appears to be have been determined more by human activities than by climate forcing.
The Palmer drought severity index (PDSI), standardized precipitation index (SPI), and standardized precipitation evapotranspiration index (SPEI) are used worldwide for drought assessment and monitoring. However, substantial differences exist in the performance for agricultural drought among these indices and among regions. Here, we performed statistical assessments to compare the strengths of different drought indices for agricultural drought in the North China Plain. Small differences were detected in the comparative performances of SPI and SPEI that were smaller at the long-term scale than those at the short-term scale. The correlation between SPI/SPEI and PDSI considerably increased from 1- to 12-month lags, and a slight decreasing trend was exhibited during 12- and 24-month lags, indicating a 12-month scale in the PDSI, whereas the SPI was strongly correlated with the SPEI at 1- to 24-month lags. Interestingly, the correlation between the trend of temperature and the mean absolute error and its correlation coefficient both suggested stronger relationships between SPI and the SPEI in areas of rapid climate warming. In addition, the yield–drought correlations tended to be higher for the SPI and SPEI than that for the PDSI at the station scale, whereas small differences were detected between the SPI and SPEI in the performance on agricultural systems. However, large differences in the influence of drought conditions on the yields of winter wheat and summer maize were evident among various indices during the crop-growing season. Our findings suggested that multi-indices in drought monitoring are needed in order to acquire robust conclusions.