Spatial-Temporal Evolution of Drought Characteristics Over Hungary Between 1961 and 2010

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An integration of bioclimatic, soil, and topographic indicators for viticulture suitability using multi-criteria evaluation: a case study in the Western slopes of Jabal Al Arab-Syria

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GIS-based multi-criteria decision making for delineation of potential groundwater recharge zones for sustainable resource management in the Eastern Mediterranean: a case study

In light of population growth and climate change, groundwater is one of the most important water resources globally. Groundwater is crucial for sustaining many vital sectors in Syria, including industrial and agricultural sectors. However, groundwater exploitation has significantly escalated to meet different water needs especially in the post-war period and the earthquake disaster. Therefore, the goal was this study delineation of the groundwater potential zones (GPZs) by integrating the analytic hierarchy process (AHP) method in a geographic information systems (GIS) within the AlAlqerdaha river basin in western Syria. In this study, ten criteria were used to map the spatial distribution of GPZs, including slope, geomorphology, drainage density, land use/land cover (LU/LC), lineament density, lithology, rainfall, soil, curvature and topographic wetness index (TWI). GPZs map was validated by using the location of 74 wells and the Receiver Operating Characteristic Curve (ROC). The findings suggest that the study area is divided into five GPZs: very low, 21.39 km2 (10.87%); low, 52.45 km2 (26.65%); moderate, 65.64 km2 (33.35%); high, 40.45 km2 (20.55%) and very high, 16.90 km2 (8.58%). High and very high zones mainly corresponded to the western regions of the study area. The conducted spatial modeling indicated that the AHP-based GPZs map showed a remarkably acceptable correlation with wells locations (AUC = 87.7%, n = 74), demonstrating the precision of the AHP–GIS as a rating method. The results of this study provide objective and constructive outputs that can help decision-makers to optimally manage groundwater resources in the post-war phase in Syria

An integration of bioclimatic, soil, and topographic indicators for viticulture suitability using multi-criteria evaluation: a case study in the Western slopes of Jabal Al Arab—Syria

In the 21st century, geographic information systems (GIS) have become one of the leading technologies in different sectors for development and planning, particularly in modern agricultural management. Moreover, recent advances in GIS tools and methods have helped decision-makers as well as farmers to find optimal sites for production of different crops. The cultivation of vineyards and grapes is one of the most important agricultural activities in the Al-Sweidaa governorate—Syria, which has been suffering from a decrease in annual productivity in conjunction with an increase in the annual demand for grapes and wine products, particularly in recent decades. Therefore, the aim of this research was to establish a new method for analyzing the optimum regions for economic viticulture production in the Western Slopes of Jabal Al Arab in the Al-Sweidaa governorate by using multi-criteria evaluation (MCE). To this end, a field survey was conducted and a soil sample was collected for physical and chemically analysis, and a 1984–2014 MRm.30-meter resolution dataset of climatic variables for the Al-Sweidaa governorate was set up as well. The results show that suitable areas are concentrated in the higher part of the study area (the eastern part) where climate and soil are favourable, and did not show any relevant limitations. Conversely, the lower part of the study area (the western) has unfavourable climate and soil chemical and physical fertility; therefore grape production is only possible if irrigation is applied and the fertility properties of the soil are improved, particularly the percentage of organic matter and the soil texture

High-Resolution Precipitation Modeling in Complex Terrains Using Hybrid Interpolation Techniques: Incorporating Physiographic and MODIS Cloud Cover Influences

The inclusion of physiographic and atmospheric influences is critical for spatial modeling of orographic precipitation in complex terrains. However, attempts to incorporate cloud cover frequency (CCF) data when interpolating precipitation are limited. CCF considers the rain shadow effect during interpolation to avoid an overly strong relationship between elevation and precipitation in areas at equivalent altitudes across rain shadows. Conventional multivariate regression or geostatistical methods assume the precipitation–explanatory variable relationship to be steady, even though this relation is often non-stationarity in complex terrains. This study proposed a novel spatial mapping approach for precipitation that combines regression-kriging (RK) to leverage its advantages over conventional multivariate regression and the spatial autocorrelation structure of residuals via kriging. The proposed hybrid model, RK (GT + CCF), utilized CCF and other physiographic factors to enhance the accuracy of precipitation interpolation. The implementation of this approach was examined in a mountainous region of southern Syria using in situ monthly precipitation data from 57 rain gauges. The RK model’s performance was compared with conventional multivariate regression models (CMRMs) that used geographical and topographical (GT) factors and CCF as predictors. The results indicated that the RK model outperformed the CMRMs with a root mean square error of 2 range of 0.75–0.96. The findings of this study showed that the incorporation of MODIS–CCF with physiographic variables as covariates significantly improved the interpolation accuracy by 5–20%, with the largest improvement in modeling precipitation in March

Estimation of soil erosion risk in southern part of Syria by using RUSLE integrating geo informatics approach

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An evapotranspiration deficit-based drought index to detect variability of terrestrial carbon productivity in the Middle East

The primary driver of the land carbon sink is gross primary productivity (GPP), the gross absorption of carbon dioxide (CO2) by plant photosynthesis, which currently accounts for about one-quarter of anthropogenic CO2 emissions per year. This study aimed to detect the variability of carbon productivity using the standardized evapotranspiration deficit index (SEDI). Sixteen countries in the Middle East (ME) were selected to investigate drought. To this end, the yearly GPP dataset for the study area, spanning the 35 years (1982–2017) was used. Additionally, the Global Land Evaporation Amsterdam Model (GLEAM, version 3.3a), which estimates the various components of terrestrial evapotranspiration (annual actual and potential evaporation), was used for the same period. The main findings indicated that productivity in croplands and grasslands was more sensitive to the SEDI in Syria, Iraq, and Turkey by 34%, 30.5%, and 29.6% of cropland area respectively, and 25%, 31.5%, and 30.5% of grass land area. A significant positive correlation against the long-term data of the SEDI was recorded. Notably, the GPP recorded a decline of &gt;60% during the 2008 extreme drought in the north of Iraq and the northeast of Syria, which concentrated within the agrarian ecosystem and reached a total vegetation deficit with 100% negative anomalies. The reductions of the annual GPP and anomalies from 2009 to 2012 might have resulted from the decrease in the annual SEDI at the peak 2008 extreme drought event. Ultimately, this led to a long delay in restoring the ecosystem in terms of its vegetation cover. Thus, the proposed study reported that the SEDI is more capable of capturing the GPP variability and closely linked to drought than commonly used indices. Therefore, understanding the response of ecosystem productivity to drought can facilitate the simulation of ecosystem changes under climate change projections.Validerad;2022;Nivå 2;2022-02-03 (johcin)</p