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Flood and drought are natural phenomena whose probability of occurrence increases with changing weather conditions. Climate change has affected the hydrologic cycle's parameters and led to changes in temperature and precipitation pattern, which may increase the probability of occurrence of floods and droughts. Arid and semi‐arid areas are subject to extreme weather conditions and water resources scarcity. This study aims to assess drought and flood in Syria using remote sensing data. Monthly precipitation data have been collected from 10 land stations in the western part of Syria for the period (1991–2009) and satellite images for monthly precipitation from 1983 to 2020 were collected. The land stations data were used to correct the satellite images and correction equation was developed for each station. Standardized Precipitation Index (SPI) is used for analysis of drought and flood. Also, the main parameters for drought and flood, severity, intensity, duration, and the average return time were estimated. The results showed extreme flood events were recorded in 1988, 2002, 2012, and 2019 and extreme drought events were recorded in 1990, 2014, and 2016. The highest severity of drought and flood were recorded in 2014 and 1988 respectively. However, the highest intensity of droughts and floods was recorded in 2016 and 1988, respectively. If land station data are unavailable, as in the case of Syria owing to the protracted war, satellite images may be a useful source of data for drought and flood analysis after correction. This methodology can help in drought/flood analysis and estimate severity, intensity, duration, and the average return time of flood and drought in other locations of the world. The results proved that SPI is a useful tool to predict the time of occurrence of both flood and drought that could help decision‐makers for putting efficient plans for flood and drought risk management that could mitigate the impacts of such risks. [ABSTRACT FROM AUTHOR]

Crop production is a major source of food and livelihood for many people in arid and semi-arid (ASA) regions across the world. However, due to irregular climatic events, ASA regions are affected commonly by frequent droughts that can impact food production. In addition, ASA regions in the Middle East and Africa are often characterised by political instability, which can increase population vulnerability to hunger and ill health. Remote sensing (RS) provides a platform to improve the spatial prediction of crop production and food availability, with the potential to positively impact populations. This paper, firstly, describes some of the important characteristics of agriculture in ASA regions that require monitoring to improve their management. Secondly, it demonstrates how freely available RS data can support decision-making through a cost-effective monitoring system that complements traditional approaches for collecting agricultural data. Thirdly, it illustrates the challenges of employing freely available RS data for mapping and monitoring crop area, crop status and forecasting crop yield in these regions. Finally, existing approaches used in these applications are evaluated, and the challenges associated with their use and possible future improvements are discussed. We demonstrate that agricultural activities can be monitored effectively and both crop area and crop yield can be predicted in advance using RS data. We also discuss the future challenges associated with maintaining food security in ASA regions and explore some recent advances in RS that can be used to monitor cropland and forecast crop production and yield.

Irrigated oases are the main water consumers in arid and semi-arid regions. As plant evapotranspiration (ET) in these regions mainly depends on irrigated water, accurate quantification of evapotranspiration (ET) on the irrigated oases is crucial for allocation and management of irrigation water resources. In this study, we integrated the soil moisture retrieved from Polarimetric L-band Multibeam Radiometer (PLMR) into the Surface Energy Balance System (SEBS) model for improving ET estimates under water stress conditions. The study area is the irrigated oasis in the middle reaches of the Heihe River where airborne and satellite-borne remotely sensed data as well as in situ observations are available through the Heihe Watershed Allied Telemetry Experimental Research (HiWATER). The main goal of this experiment is to monitor the energy-water exchange between near-surface atmosphere and land surface, and to assess its influencing factors within the oasis–desert ecosystem. The soil moisture data were retrieved using the L-band Microwave Emission of the Biosphere (L-MEB) model fed with the airborne dual-polarized and multi-angular viewing of PLMR. The comparison of soil moisture retrieval from PLMR data with the soil moisture measured by a wireless sensor network (WSN) showed good consistency, with an absolute mean error (ME) <0.004 cm 3 cm −3 and a root mean square error (RMSE) value <0.05 cm 3 cm −3 . Further, the actual daily evapotranspiration was estimated using the soil moisture integrated (SM-integrated) SEBS algorithm fed with the Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) images and soil moisture data retrieved from PLMR data. The sensible heat fluxes and daily evapotranspiration ( ET daily ) obtained by the SM-integrated SEBS and the original SEBS were compared with the eddy correlation (EC) measurements collected from HiWATER experiment. The results indicate an obvious improvement when soil moisture information is integrated into the SEBS. This method overcomes the weakness of remote sensing based (RS-based) surface energy balance models of overestimating evapotranspiration particularly in semi-arid and arid regions. It shows a prospect that the combination of optical and microwave remote sensing can further improve the RS-based ET estimation. [ABSTRACT FROM AUTHOR]

Irrigation of agricultural oases is the main water consumer in semi-arid and arid regions of Northwestern China. The accurate estimation of evapotranspiration (ET) on the oases is extremely important for evaluating water use efficiency so as to reasonably allocate water resources, particularly in semi-arid and arid areas. In this study, we integrated the soil moisture information into surface energy balance system (SEBS) for improving irrigated crop water consumption estimation. The new approach fed with the moderate resolution imaging spectro-radiometer images mapped spatiotemporal ET on the oasis in the middle reach of the Heihe river. The daily ET outputs of the new approach were compared with those of the original SEBS using the eddy correlation observations, and the results demonstrate that the modified SEBS remedied the shortcoming of general overestimating ET without regard to soil water stress. Meanwhile, the crop planting structure and leaf area index spatiotemporal distribution in the studied region were derived from the high-resolution Chinese satellite HJ-1/CCD images for helping analyse the pattern of the monthly ET (ETmonthly). The results show that the spatiotemporal variation of ETmonthly is closely related to artificial irrigation and crop growth. Further evaluation of current irrigation water use efficiency was conducted on both irrigation district scale and the whole middle reach of the Heihe river. The results reveal that the average fraction of consumed water on irrigation district scale is 57% in 2012. The current irrigation water system is irrational because only 52% of the total irrigated amount was used to fulfil plant ET requirement and the rest of the irrigation water recharged into groundwater in the oasis in 2012. However, in view of the whole middle reach of the Heihe river, the irrigation water use efficiency could reach to 66% in 2012. But pumping groundwater for reused irrigation wastes mostly energy instead of water. An improved irrigation water allocation system according to actual ET requirement is needed to increase irrigation efficiency per cubic meter water resource in an effort to save both water and energy. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Global environmental change is a one of humanity's greatest challenges affecting both current and future generations. Many world regions face this threat but are increasing rapidly especially in arid and semiarid climatic zones. As a case study, North Kordofan State of Sudan now has existing risks and vulnerabilities associated with many reasons; some areas affected by environmental and climatic impacts, in addition to ethnic conflicts between nomads and sedentary farmers, as well as with socio-ethnic and socio-political conflicts destabilizing the critical areas on the western and southern parts of the state. The study aimed to address the change during the past decade by overlaying maps of Land Use/ Land Cover (LU/LC) classes in the State acquired at different points in time, as well as to assess the vulnerability associated with the environmental change. Data were collected in two forms; socioeconomic data and multi-temporal satellite data (i.e. LANDSAT TM and ETM) to study the LU/LC changes. The result of the case studies reveals that, an intensive and dynamic rate of deforestation clearly related to admixture dynamic interactions between social and ecological systems. In sum, we urgently need rethinking about the serious threat of environmental change in these areas. Moreover, new strategies and research development are needed to cope with high levels of the change. [ABSTRACT FROM AUTHOR]

Abstract: This study presents a model budget for groundwater in the Central Eastern Desert of Egypt. The stable isotopic composition and hydrochemistry of groundwater samples collected from different aquifers were determined to identify recharge sources and water quality. Stable isotopic values suggest that shallow alluvial and fracture zone aquifers are recharged from seasonal precipitation, while groundwater in deeper sedimentary sub-basins is paleowater that was recharged during periods of less arid regional climate. Hydrochemical analysis indicates elevated salinity in each aquifer type, which is attributed to leaching and dissolution of terrestrial salts and to mixing with marine water. Groundwater from sedimentary sub-basin aquifers can be treated and used for drinking and domestic purposes. Groundwater from shallow alluvial and fracture zone wells is suitable for animal husbandry and mineral ore dressing. A model water budget shows that approximately 4.8×109 m3 of recoverable groundwater is stored in sedimentary sub-basin aquifers, or approximately 550years of water at present utilization rates. [Copyright &y& Elsevier]

Crop production is a major source of food and livelihood for many people in arid and semi-arid (ASA) regions across the world. However, due to irregular climatic events, ASA regions are affected commonly by frequent droughts that can impact food production. In addition, ASA regions in the Middle East and Africa are often characterised by political instability, which can increase population vulnerability to hunger and ill health. Remote sensing (RS) provides a platform to improve the spatial prediction of crop production and food availability, with the potential to positively impact populations. This paper, firstly, describes some of the important characteristics of agriculture in ASA regions that require monitoring to improve their management. Secondly, it demonstrates how freely available RS data can support decision-making through a cost-effective monitoring system that complements traditional approaches for collecting agricultural data. Thirdly, it illustrates the challenges of employing freely available RS data for mapping and monitoring crop area, crop status and forecasting crop yield in these regions. Finally, existing approaches used in these applications are evaluated, and the challenges associated with their use and possible future improvements are discussed. We demonstrate that agricultural activities can be monitored effectively and both crop area and crop yield can be predicted in advance using RS data. We also discuss the future challenges associated with maintaining food security in ASA regions and explore some recent advances in RS that can be used to monitor cropland and forecast crop production and yield. [ABSTRACT FROM AUTHOR]

In semi-arid pasture areas, drought may directly influence livestock production, cause economic losses, and accelerate the processes of desertification along with destructive human activities (i.e., overgrazing). The aim of this article is to analyze the disadvantages of several drought indices derived from remote sensing data and develop a new vegetation drought index (VDI) for monitoring of grassland drought with high temporal frequency (dekad) and fine spatial resolution (1 km). The site-based soil moisture data from the field campaign in 2014 and the fenced biomass values at nine sites from 2000 to 2015 were adopted for validation. The results indicate that the proposed VDI would better reflect the extent, severity, and changes of drought compared with single drought indices or the vegetation health index (VHI); specifically, the VDI is more closely related to site-based soil moisture, with R human increasing to approximately 0.07 compared with the VHI; and with normalized fenced biomass (NFB) values, with average R human increasing to approximately 0.11 compared with the VHI. However, the correlations between VHI and VDI with NFB values are relatively lower in desert steppe regions. Furthermore, regional drought-affected data (RDA) are used to ensure spatial consistency of the evaluation; the VDI map is in good agreement with the RDA map based on field measurements. The presented VDI shows reliable and stable drought monitoring ability, which will play an important role in the future drought monitoring of inland grassland. [ABSTRACT FROM AUTHOR]