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Biological soil crusts (biocrusts) constitute a crucial biological component of the soil surface in arid and semi-arid ecosystems. Understanding the variations in soil microbial community assembly across biocrust successional stages is essential for a deeper comprehension of microbial biodiversity and desert ecosystem functioning. However, knowledge about the mechanisms of microbial community assembly and the factors influencing its development remains limited. In this study, we utilized amplicons sequencing to assess the compositions of bacterial and fungal communities in bare sand and three types of biocrusts (light cyanobacterial biocrusts, dark cyanobacterial biocrusts, and moss crusts). Subsequently, we analyzed the ecological processes shaping microbial community composition and structure, along with the influencing factors. Our results revealed a significant increase in bacterial diversity and no significant changes in fungal diversity during biocrust development. The relative abundances of the copiotrophic bacteria (e.g., Actinobacteria, Acidobacteria, and Bacteroidetes) showed significant increases, while oligotrophic bacteria (e.g., Proteobacteria and Firmicutes) decreased over time. Moreover, the relative abundances of Ascomycota, which exhibit strong resistance to adverse environmental conditions, significantly decreased, whereas Basidiomycota, known for their ability to degrade lignin, significantly increased throughout biocrust development. Additionally, stochastic processes (dispersal limitation and drift) predominantly drove the assemblies of both bacterial and fungal communities. However, the relative importance of deterministic processes (homogeneous selection) in bacterial assembly increased during biocrust development. Structural equation modeling indicated that bacterial community assembly was primarily related to soil water content, whereas fungal community assembly was primarily related to total organic carbon. These findings provide a scientific foundation for investigating the formation and development of biocrusts, and further insights into the conservation and sustainable management of biocrust resources under future climate change scenarios. [ABSTRACT FROM AUTHOR]

The over-exploitation of groundwater and the deterioration of its quality have heightened the importance of non-traditional water resources, such as mine water. The study of the water's chemical characteristics and the formation mechanism of high-salinity mine water in semi-arid regions holds significant importance for zero discharge and the resource utilization of mine water in Northwest China. In this study, a total of 38 groundwater and mine water samples were collected to examine the hydrogeochemical characteristics of high-salinity mine water using Piper diagrams and Gibbs diagrams, as well as isotope analyses and ion ratio coefficients. Additionally, the corresponding mine water treatment recommendations were put forward. The results show that the TDS content of groundwater increases with hydrographic depth. The average TDS concentration of Quaternary, Luohe, and Anding groundwater is 336.87, 308.67, and 556.29 mg/L, respectively. However, the TDS concentration of Zhiluo groundwater and mine water is 2768.57 and 3826.40 mg/L, respectively, which belong to high-salinity water. The Quaternary, Luohe, and Anding groundwater hydrochemical type is predominantly HCO3-Ca type, and the Zhiluo groundwater and mine water hydrochemical type is predominantly the SO4-Na type. Furthermore, there is minimal difference observed in δD and δ18O values among these waters. It can be inferred that the Zhiluo Formation in groundwater serves as the primary source of mine water supply, primarily influenced by the processes of concentration caused by evaporation. The high salinity of mine water is closely related to the high salinity of Zhiluo groundwater. The high salinity of groundwater has evolved gradually under the control of the concentration caused by evaporation and rock-weathering processes. The dissolution of salt rock, gypsum, along with other minerals, serves as the material basis for high-salinity groundwater formation. In addition, the evolution of major ions is also affected by cation exchange. The TDS concentration of mine water ranges from 3435.4 mg/L to 4414.3 mg/L, and the combined treatment process of nanofiltration and reverse osmosis can be selected to remove the salt. After treatment, mine water can be used for productive, domestic, and ecological demands. [ABSTRACT FROM AUTHOR]

Fusarium foot and root rot is one of the most important soilborne diseases of cereals, specifically on durum wheat which is the main cultivated species in the Mediterranean regions. This work aimed to evaluate the response of durum wheat and bread wheat to this disease under different climatic conditions. The disease parameters, grain yield loss as well as thousand kernel weight (TKW), heading date and height of plant were evaluated on 29 durum and bread wheat genotypes during two years. Overall, durum wheat grain yield was strongly and negatively correlated with disease parameters, heading date, and positively with plant height and TKW compared to bread wheat. In the drier year, the 24 durum wheat genotypes were more susceptible to the disease than the five bread wheat varieties while some of them showed less disease during the wetter year. Bread wheat maintained the same behavior in both years vs. durum wheat. Grain yield loss was higher on durum wheat compared to bread wheat. It was the same in both years (56 and 51%) for durum wheat and was significantly (p < 0.01) lower in the drier (24%) compared to the wetter year (44%) for bread wheat. This work confirmed the susceptibility of Tunisian durum wheat to the disease compared to bread wheat and calls attention to the potential vulnerability of this important Mediterranean food crop under a hotter, drier climate. More research is needed to investigate adaptation to drought and plant defense mechanisms and to breed for resistance to this disease. [ABSTRACT FROM AUTHOR]

The insufficiency of water resources and the need for potable water constitute a major concern for many countries, especially Morocco, which has experienced a significant increase in water demand due to population growth, economic development, and climatic conditions. To address this issue, Morocco has initiated an ambitious program to establish seawater desalination plants using reverse osmosis technology in semi-arid areas.This study addresses the pressing concern of ensuring the reliability and quality of desalinated water in the Al Hoceima seawater desalination plant, a vital initiative by Morocco to combat water scarcity in semi-arid regions. Employing the Failure Modes, Effects, and Criticality Analysis (FMECA) method, a comprehensive analysis was conducted to identify potential malfunctions compromising water quality and process reliability. Failures were ranked in descending order of criticality, and cumulative criticality was calculated to prioritize improvement actions. The Pareto diagram generated from this analysis helped identify critical failures in the studied system that require prioritized improvement actions. Notably, it was observed that 80% of the criticality corresponded to half of the failures. Consequently, an improvement plan should be developed for 12 out of the 24 predetermined failure modes, focusing on those identified as most critical. Subsequently, an improvement plan was formulated, integrating short-term corrective actions such as optimizing cleaning protocols and medium to long-term preventive measures such as upgrading equipment and implementing redundancy systems. This study contributes novel insights into enhancing process reliability in seawater desalination plants, particularly in semi-arid regions like Morocco, by providing a systematic approach to identify and prioritize potential failures, ensuring the sustainable provision of potable water.

Total nitrogen (TN) is a critical nutrient for plant growth, and its monitoring in agricultural soil is vital for farm managers. Traditional methods of estimating soil TN levels involve laborious and costly chemical analyses, especially when applied to large areas with multiple sampling points. Remote sensing offers a promising alternative for identifying, tracking, and mapping soil TN levels at various scales, including the field, landscape, and regional levels. Spaceborne hyperspectral sensing has shown effectiveness in reflecting soil TN levels. This study evaluates the efficiency of spectral reflectance at visible near-infrared (VNIR) and shortwave near-infrared (SWIR) regions to identify the most informative hyperspectral bands responding to the TN content in agricultural soil. In this context, we used PRISMA (PRecursore IperSpettrale della Missione Applicativa) hyperspectral imagery with ensemble learning modeling to identify N-specific absorption features. This ensemble consisted of three multivariate regression techniques, partial least square (PLSR), support vector regression (SVR), and Gaussian process regression (GPR) learners. The soil TN data (n = 803) were analyzed against a hyperspectral PRISMA imagery to perform spectral band selection. The 803 sampled data points were derived from open-access soil property and nutrient maps for Africa at a 30 m resolution over a bare agricultural field in southern Morocco. The ensemble learning strategy identified several bands in the SWIR in the regions of 900–1300 nm and 1900–2200 nm. The models achieved coefficient-of-determination values ranging from 0.63 to 0.73 and root-mean-square error values of 0.14 g/kg for PLSR, 0.11 g/kg for SVR, and 0.12 g/kg for GPR, which had been boosted to an R2 of 0.84, an RMSE of 0.08 g/kg, and an RPD of 2.53 by the ensemble, demonstrating the model's accuracy in predicting the soil TN content. These results underscore the potential for using spaceborne hyperspectral imagery for soil TN estimation, enabling the development of decision-support tools for variable-rate fertilization and advancing our understanding of soil spectral responses for improved soil management. [ABSTRACT FROM AUTHOR]

In areas with restriction of water resource access for agricultural activities, one of the most challenging issues is determining irrigation depth in such a way that gets high efficiency. A field experiment was conducted to evaluate three different irrigation scenarios; in which irrigation depth was determined by WASH_1D/2D model and FAO method; as well as rainfed (no irrigation) treatment, in the fine textured soil under potato cultivation. The results showed that simulating method could optimize water use with considering weather forecast data as 6 irrigation events and 12.6 mm depth, compared to 10 irrigation events and 37.3 mm depth for FAO method. A significant difference was observed among gained yield under irrigated and rainfed plots that implied irrigation importance even in rainy season. The applied water efficiency values for simulated and FAO methods was gained as 198 and 70 g/mm, respectively; which indicate the WASH_1D/2D model may be an appropriate choice to determine irrigation depth considering water use optimizing in regions with water supply problems. [ABSTRACT FROM AUTHOR]

The insufficiency of water resources and the need for potable water constitute a major concern for many countries, especially Morocco, which has experienced a significant increase in water demand due to population growth, economic development, and climatic conditions. To address this issue, Morocco has initiated an ambitious program to establish seawater desalination plants using reverse osmosis technology in semi-arid areas. This study addresses the pressing concern of ensuring the reliability and quality of desalinated water in the Al Hoceima seawater desalination plant, a vital initiative by Morocco to combat water scarcity in semi-arid regions. Employing the Failure Modes, Effects, and Criticality Analysis (FMECA) method, a comprehensive analysis was conducted to identify potential malfunctions compromising water quality and process reliability. Failures were ranked in descending order of criticality, and cumulative criticality was calculated to prioritize improvement actions. The Pareto diagram generated from this analysis helped identify critical failures in the studied system that require prioritized improvement actions. Notably, it was observed that 80% of the criticality corresponded to half of the failures. Consequently, an improvement plan should be developed for 12 out of the 24 predetermined failure modes, focusing on those identified as most critical. Subsequently, an improvement plan was formulated, integrating short-term corrective actions such as optimizing cleaning protocols and medium to long-term preventive measures such as upgrading equipment and implementing redundancy systems. This study contributes novel insights into enhancing process reliability in seawater desalination plants, particularly in semi-arid regions like Morocco, by providing a systematic approach to identify and prioritize potential failures, ensuring the sustainable provision of potable water. [ABSTRACT FROM AUTHOR]

Soil degradation is a global problem. Over the last several decades, the effects of land degradation in Tunisia are starting to have increasingly serious socio-economic and environmental repercussions. The agricultural sector is most seriously affected. The Tunisian Sahel, despite its modest topographical conditions, has not escaped this threat, especially upstream of the El Maasra Wadi. The fertile soils and homogeneous topography of this area, which dates to Roman times, are highly favorable to a wide range of agricultural practices. The Central Sahel has a long history of olive-growing, followed by a shift to irrigated farming in the 1970s. Today, it is given a multifunctional and multidimensional importance due to the complexity of conflicts of interest between different users. Rural abandonment, mining activity and pastoral pressure have all been behind the soil crisis, which is still largely unknown in detail in terms of the processes involved, the mechanisms behind them and the pace at which they are occurring. Today, there is an urgent need for tools and reliable methods to diagnose the state of soils, to elucidate the various facets of erosive processes and create the structural conditions necessary for their preservation. In the same vein, this research project was initiated in the Wadi El Maasra watershed to quantify soil losses using two methods: empirical model (USLE equation) and experimental based on the isotopic tracer of the Caesium-137. The two methods showed an almost identical geographical distribution, but slightly different loss rates. The specific soil loss obtained from the USLE model was of the order of 15 t ha-1 year-1, which appears to be largely underestimated compared with the loss rate obtained by the Caesium-137 method, which was of the order of 32 t ha-1 year-1. [ABSTRACT FROM AUTHOR]

The cover management factor is one of the main five factors that is used within the universal soil loss equation to reflect the effect of cropping and management practices on soil erosion rates. It is determined through tables and equations derived in tropical and European conditions, which are not suitable for semi-arid regions with different climate, topography, and soil characteristics. Therefore, this study considers al-Arish basin in Sinai Peninsula, Egypt as a semi-arid study area to generate a cover management factor's equation in terms of the Normalized Difference Vegetation Index using hydrological modeling and satellite images processing. To verify the proposed equation, it was applied to the Derna catchment in Libya and compared with European and tropical ones with respect to the hydrological outputs. Statistical analysis indicates that the proposed equation determines the cover management factor more accurately than those developed for tropical or European regions, as the correlation coefficient between the cover management factor and the hydrological results was 0.71, while it was about 0.20 for the European and tropical, equations, also the degree of agreement between the proposed equation's results and the hydrological simulation was 0.768 while it was 0.001 and 0.02 for the tropical and European equations respectively. By utilizing the newly developed equation, the soil erosion can be estimated more accurately for the semi-arid regions, and a better understanding of the relation between the vegetation cover and soil erosion can be drawn. [ABSTRACT FROM AUTHOR]

The Setifian high-plains region, Northeast of Algeria, grapples with challenges in water resource management. As the water demand intensifies across a diverse range of sectors, assessing groundwater quality becomes indispensable. This article responds to the critical need for a thorough assessment of groundwater quality in the Wadi Boussellam sub-watershed. Employing a GIS-based method, we evaluate groundwater geochemistry by estimating the Water Quality Index (WQI), offering a comprehensive overview of water consumption. The analysis of groundwater samples reveals distinct facies, including calcic bicarbonate, calcic chloride, calcic sulfate, and magnesium sulfate, contributing to an enhanced understanding of the hydrochemical composition in the Setif region. Hydrochemical indices, specifically the WQI, Sodium Adsorption Ratio (SAR), and Na% are applied to assess groundwater suitability for various applications. The results indicate that most crops are generally suitable for irrigation, though they advise exercising caution with regard to human consumption. This study underscores the significance of regular monitoring to avert groundwater contamination and ensure sustainable use in the Setif region, providing insights that emphasize the ongoing necessity for efforts in water resource management and the preservation of this vital resource's quality. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) and its relationship with vegetation indices (VIs) have proven to be effective for monitoring water stress in large-scale crops. Therefore, the objective of this study is to find an appropriate VI to analyse the spatio-temporal evolution of olive water stress using LST images and VIs derived from Landsat 5 and 8 satellites in the semi-arid region of southern Peru. For this purpose, VIs (Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index 2 (EVI2) and Soil Adjusted Vegetation Index (SAVI)) and LST were calculated. The information was processed in Google Earth Engine (GEE) for the period 1985 to 2024, with an interval of every five years for the summer season. The triangle method was applied based on the LST-VIs scatterplot analysis, a tool that establishes wet and dry boundary conditions for the Temperature Vegetation Dryness Index (TVDI). The results indicated a better appreciation of olive orchard water stress over time, with an average of 39% drought (TVDINDVI and TVDISAVI), 24% severe drought (TVDINDVI) and 25% (TVDISAVI) of the total area, compared to TVDIEVI2, which showed 37% drought and 16% severe drought. It is concluded that TVDINDVI and TVDISAVI provide a better visualisation of the water stress map of the olive crop and offer a range of options to address current and future problems in water resource management in the olive sector in semi-arid areas of southern Peru. [ABSTRACT FROM AUTHOR]

On the one hand, this study assesses the evolution of climatological parameters in the Zaër region between 1986 and 2021 and, on the other hand, it studies the effect of climatic variations on cereal and leguminous crop yields between 2000 and 2020, in order to further elucidate the consequences of their fluctuations on crop yields and to mitigate their regression process by making it possible to analyze favorable adaptation strategies for agricultural systems that can be envisaged for the coming decades. The methodology is based on the use of trend curves and statistics (averages and standard deviations) to analyze changes in climatic parameters and their effects on yields. The results show that the average temperature in the Zaër region is set to rise from 19°C in 1986 to 22°C in 2020. Higher temperatures mean lower yields of rainfed cereals and pulses, and average rainfall varies between 330 mm in 1986 and 570 mm in 2021, with rainfall increasing the likelihood of crop failure in the short term and reducing production in the long term. In addition, the rainy season is short (4 to 5 months per year). These characteristics make Zaër's agriculture very sensitive to climate-related threats. Studying seasonal climate forecasts before each rainy season can help farmers to minimize rainfall hazards and thus optimize their crop yields. Keywords: agriculture, climate change, semi-arid regions, crop yield, cultivated area.

On the one hand, this study assesses the evolution of climatological parameters in the Zaër region between 1986 and 2021 and, on the other hand, it studies the effect of climatic variations on cereal and leguminous crop yields between 2000 and 2020, in order to further elucidate the consequences of their fluctuations on crop yields and to mitigate their regression process by making it possible to analyze favorable adaptation strategies for agricultural systems that can be envisaged for the coming decades. The methodology is based on the use of trend curves and statistics (averages and standard deviations) to analyze changes in climatic parameters and their effects on yields. The results show that the average temperature in the Zaër region is set to rise from 19°C in 1986 to 22°C in 2020. Higher temperatures mean lower yields of rainfed cereals and pulses, and average rainfall varies between 330 mm in 1986 and 570 mm in 2021, with rainfall increasing the likelihood of crop failure in the short term and reducing production in the long term. In addition, the rainy season is short (4 to 5 months per year). These characteristics make Zaër’s agriculture very sensitive to climate-related threats. Studying seasonal climate forecasts before each rainy season can help farmers to minimize rainfall hazards and thus optimize their crop yields. [ABSTRACT FROM AUTHOR]

The impact of global climate change on water resources is a pressing concern, particularly in arid and semi-arid regions, where water shortages are becoming increasingly severe. Rainwater harvesting (RWH) offers a promising solution to address these challenges. However, the process of selecting suitable RWH sites is complex. This paper introduces a comprehensive methodology that leverages various technologies and data sources to identify suitable RWH locations in the northern region of Iraq, considering both historical and future scenarios. The study employs remote sensing and geographic information systems to collect and process geospatial data, which are essential for the site selection process. AHP is utilized as a decision-making tool to assess and rank potential RWH locations based on multiple criteria, helping to prioritize the most suitable sites. The WLC approach is used to combine and weigh various factors, enabling a systematic evaluation of site suitability. To account for the uncertainty associated with future climate conditions, a stochastic weather generator is employed to simulate historical and future precipitation data for period (1980–2022) and (2031–2100). This ensures that the assessment considers changing climate patterns. Historical precipitation values ranged from 270 to 490 mm, while future projections indicate a decrease, with values varying from 255 to 390 mm. This suggests a potential reduction in available water resources due to climate change. The runoff for historical rainfall values ranged from 190 mm (poor) to 490 mm (very good). In the future projections, runoff values vary from 180 mm (very poor) to 390 mm (good). This analysis highlights the potential impact of reduced precipitation on water availability. There is a strong correlation between rainfall and runoff, with values of 95% for historical data and 98.83% for future projections. This indicates that changes in precipitation directly affect water runoff. The study incorporates several criteria in the model, including soil texture, historical and future rainfall data, land use/cover, slope, and drainage density. These criteria were selected based on the nature of the study region and dataset availability. The suitability zones are classified into four categories for both historical potential and future projections of RWH zones: very high suitability, covering approximately 8.2%. High suitability, encompassing around 22.6%. Moderate suitability, constituting about 37.4%. Low suitability, accounting for 31.8% of the study region. For the potential zones of RWH in the future projection, the distribution is as follows: very high suitability, approximately 6.1%. High suitability, around 18.3%. Moderate suitability, roughly 31.2%. Low suitability, making up about 44.4% of the study region. The research's findings have significant implications for sustainable water resource management in the northern region of Iraq. As climate change exacerbates water scarcity, identifying suitable RWH locations becomes crucial for ensuring water availability. This methodology, incorporating advanced technology and data sources, provides a valuable tool for addressing these challenges and enhancing the future of water management to face of climate change. However, more investigations and studies need to be conducted in near future in the study region. [ABSTRACT FROM AUTHOR]

Climate change alters the global distribution of leishmaniasis vector sandfly species. However, the possible effect of altering environmental factors on sandfly species varies by species and area. The aim of this study was to project the future potential effect of climate change on the Western Asian occurrence of the sandfly vector species Phlebotomus papatasi and Phlebotomus sergenti and the parasites Leishmania major and Leishmania tropica for 2041–2060 and 2081–2100 compared to their modelled climatic suitability patterns in the reference period 1970–2000. The model results suggest that by 2041–2060 and 2081–2100, in the coastal areas of the Levantine countries and the mid-elevation regions of Western Iran and Southeast Turkey, the climatic suitability of all the studied species is predicted to increase. In contrast, the model results suggest the decline of the populations of the studied vectors as well as the disappearance of the parasites in Iraq, North Saudi Arabia, Kuwait, and the inland regions of Western Asian countries. Considering the present-day population density patterns, it can be said that although in large regions of the region, the climatic suitability values are predicted to decrease, the populated Levantine regions seem to be at risk of climate change-facilitated increase in cutaneous leishmaniasis in the second half of the twenty-first century. The model results suggest that climate change will especially increase the climatic suitability of Leishmania tropica in the Levantine region in the late twenty-first century. [ABSTRACT FROM AUTHOR]

Coexistence education is essential in resolving human-wildlife conflicts. Two educational interventions were assessed among school children to understand the effectiveness of distinct approaches used in education campaigns. One had a strong audio-visual component, while the second was based on storytelling. Interventions focused on jaguars and pumas because these species are declining in the Caatinga biome, mainly due to conflicts with humans. Children's socioeconomic backgrounds were assessed. Both interventions significantly enhanced prominence, knowledge and positive perceptions of jaguars and pumas. The audio-visual intervention showed a higher overall positive effect on prominence and perceptions. Storytelling proved a stronger tool for increasing knowledge. Socioeconomic background also proved an important driver in all domains. Nature proximity and parents' education level showed significant influence on children's knowledge, prominence, and perceptions. The outcomes of this study show the importance of using complementary methods and adapting similar initiatives to local social contexts to achieve success. [ABSTRACT FROM AUTHOR]

Rainfall harvesting in arid regions and semi-arid regions increases soil water availability for plant during the growing season, thus increasing crop production. Jordan is facing the most serious water shortages in the Middle East. It is an arid country located east of the Jordan River with a land area of about 90,000-km. Contour stone terraces have been widely used by Jordanian farmers in the hilly areas for soil and water conservation purposes. Traditionally, farms' soil is subjected to systematic deep plowing to break up the surface rocks and then remove stones for installation of stone terraces. A new land reclamation method for water harvesting has been experimented in the hilly parts of Jordan that improves the effectiveness of traditional stone terraces. The method consists of designing semi-circular stone bunds randomly based on the micro topography of land. Semi-circular bunds were located at areas having deep soil pockets and adequate runoff rocky area and do not require deep plowing with minimum land disturbance. This method minimizes soil erosion, maximizes rainfall harvesting due to the high runoff efficiency from runoff rocky areas, and promotes biodiversity. The cost of this method is about 85% less than that of the traditional stone terraces used by Jordanian farmers. Field evaluations showed that semi-circular bunds increased soil moisture and Sage yield in the cropping areas by about 7% and 35% compared to control areas, respectively. The soil depth in some of the cropping terraced areas increased by about 3 and 25 cm at the end of the 2003/2004 and 2016/2017 rainy seasons, respectively. [ABSTRACT FROM AUTHOR]

The research is part of a broader investigation into the impact of various diets, specifically designed with Atriplex halimus and Opuntia Ficus Indica, on multiple factors concerning Barbarine ewes in a semi-arid area of southeastern Algeria. The goal was to assess whether these two plants could offer effective sustainable solutions for addressing drought in the region. This experimental study aimed to investigate the impact of alternative forage such as Opuntia Ficus Indica and Atriplex halimus on milk composition, specifically protein and fat content, in Barbarine ewes within a semi-arid region of Southeast Algeria. A cohort of 24 Barbarine ewes in the lactation phase was enrolled in the study. The subjects were stratified into six distinct groups, each containing four animals, encompassing a control regimen and diets featuring Cactus Inerme, Atriplex halimus, and a combination of both. The control group's diet comprised 0.45 kg of barley and 1.8 kg of barley straw (Control). Contrarily, ewes in the experimental groups (T1 to T5) were provided with barley straw ad libitum along with the following compositions: 100% cactus (T1), 75% cactus + 25% Atriplex (T2), 50% cactus +50% Atriplex (T3), 25% cactus + 75% Atriplex (T4), and 100% Atriplex (T5). Analysis of the results indicated that the treatment group T4 exhibited the highest milk fat content, approaching statistical significance in comparison to the control group, whereas treatment group T1 displayed the lowest mean. Moreover, protein content was notably higher in T4 and T5 than in T3 and T2, with treatment group T1 recording the lowest mean. These results provide valuable insights into the effects of these specific substitute diets on the quality of milk in Barbarine ewes, especially within the context of the semi-arid environments in Algeria. [ABSTRACT FROM AUTHOR]

This article aims to investigate the complex relationship between a local population and its natural and urban environment. The study area, which was previously dominated by cereal cultivation, is currently facing profitability challenges due to climate change, water scarcity, rapid urban expansion, and the overexploitation of aquifers, influenced by changes in agricultural practices, which are disrupting the local ecosystem. This study relies on three interconnected indicators, population growth, climate change effects on agriculture, and the NDVI (Normalized Difference Vegetation Index), and reveals the impact of these factors on agricultural practices. Google Earth Engine was employed to determine the urbanization and greenness indices using scripts. The significant findings of this study demonstrate the remarkable demographic growth of 49.96% during the study period (2000–2020). Furthermore, this growth has led to a new trend towards intensive farming, with a substantial increase in irrigated lands by 44.19% and a multiplication of protected crop lands by 20 times, rising from 19.88 to 405.89 hectares. Additionally, horticultural production surged by 212.4% during the same period. Moreover, groundwater levels shifted from less than 50 m in the northern regions to less than 150 and 300 m in the southern part of the study area. The water potential in the study zone cannot meet the demands of the new agricultural orientation, which tends to deplete local groundwater, potentially causing recurrent shortages of agricultural products. This study underscores the importance of incorporating agricultural production into future urban planning and development programs to maintain a renewed balance between built environments and agriculture in peri-urban areas. [ABSTRACT FROM AUTHOR]

Using satellite imagery for land cover mapping is of utmost importance due to its role played in environmental management and protection, assessment of natural resources and human activities and planning for sustainable development. The objective of this research study is to generate high-resolution land use/land cover maps for the semi-arid regions. First, we introduce a novel district-scale land cover dataset for a semi-arid region spanning over an area of 4978 km2 of Ludhiana district located in the state of Punjab, India. The dataset is composed of multi-temporal, multi-spectral Sentinel-2 satellite images for the year 2020 along with their ground truth mask. Eight major land use/land cover classes were mapped at the pixel level. Second, in order to exploit the spatio-temporal nature of satellite imagery, we employ a 3D encoder–decoder-based semantic segmentation architecture to produce the land cover maps. Third, we show the relevance of incorporating temporal features of satellite data for land use/land cover mapping through experimental results. Mean Intersection over Union (mIoU) and F1 score of 89.30% and 94.35%, respectively, were achieved. This study is vital from the perspective of understanding the dynamics of land use/land cover patterns in the context of agriculturally rich areas experiencing rapid urban population growth and shrinkage of cropland. [ABSTRACT FROM AUTHOR]

Understanding the gender dimensions of vulnerability to climate change is crucial for designing effective gender-transformative climate actions. This is particularly crucial in the semi-arid regions of West Africa, a climate change “hotspot” where high dependence on climate-sensitive livelihoods and limited adaptive capacity make agriculture and livelihoods highly vulnerable. In this study we combined semi-structured interviews and focus group discussions with a systematic literature review to analyze gendered household vulnerability to climate change in Cinzana, a semi-arid area of Mali, and identify entry points for gender-transformative adaptation actions. The Livelihood Vulnerability assessment indicated that female-headed households were more vulnerable than male-headed households. Differential socio-demographic profiles, livelihood strategies, social networks, water and food and agricultural production systems were key drivers of the gendered vulnerability patterns. A systematic review of drivers of gendered vulnerability in Mali illustrated how socio-cultural norms and roles assigned to women, and limited women access to and control over productive resources and adaptation technologies make women more vulnerable to climatic and non-climatic risks. We highlight the need of gender transformative approaches to address the structural gender inequality and reduce vulnerability of female-headed households. We outline three pathways for reducing female-headed households’ vulnerability to climate change, including the promotion of gender-smart extension and climate advisory services and empowering women.

ABSTRACT Livestock production in semi-arid areas has been unpredictable due to climate variability, mainly rainfall. This study aims to simulate rangeland production variability affected by rainfall over time and relate it to an adjusted carrying capacity, using forage stock to maximize the potential of production of the system to a specifi c guarantee level. Regression analysis of forage biomass against rainfall was performed for ecological sites in the Brazilian semi-arid region to generate probability distribution curves for the historical rainfall for each location using Monte Carlo approach. Forage biomass variability estimated over time was used as input to the model. The system optimizes forage use at a sustainable stocking rate and uses forage surpluses in good years to fill defi cits during adverse years, due to a certain level of guarantee. As a rule, smallholder farmers would need to maintain a storage of around 1,500 kg ha-1 of DM of forage to maintain an adjusted carrying capacity of 0.11 animal units ha-1, with a guarantee of 95% in the long term, stressing the forage storage capacity as a central component of the model. Since farm size infl uences forage production capacity and mainly forage stock capacity, recommendations to cope with this paradigm are suggested.

The over-exploitation of groundwater and the deterioration of its quality have heightened the importance of non-traditional water resources, such as mine water. The study of the water’s chemical characteristics and the formation mechanism of high-salinity mine water in semi-arid regions holds significant importance for zero discharge and the resource utilization of mine water in Northwest China. In this study, a total of 38 groundwater and mine water samples were collected to examine the hydrogeochemical characteristics of high-salinity mine water using Piper diagrams and Gibbs diagrams, as well as isotope analyses and ion ratio coefficients. Additionally, the corresponding mine water treatment recommendations were put forward. The results show that the TDS content of groundwater increases with hydrographic depth. The average TDS concentration of Quaternary, Luohe, and Anding groundwater is 336.87, 308.67, and 556.29 mg/L, respectively. However, the TDS concentration of Zhiluo groundwater and mine water is 2768.57 and 3826.40 mg/L, respectively, which belong to high-salinity water. The Quaternary, Luohe, and Anding groundwater hydrochemical type is predominantly HCO3-Ca type, and the Zhiluo groundwater and mine water hydrochemical type is predominantly the SO4-Na type. Furthermore, there is minimal difference observed in δD and δ18O values among these waters. It can be inferred that the Zhiluo Formation in groundwater serves as the primary source of mine water supply, primarily influenced by the processes of concentration caused by evaporation. The high salinity of mine water is closely related to the high salinity of Zhiluo groundwater. The high salinity of groundwater has evolved gradually under the control of the concentration caused by evaporation and rock-weathering processes. The dissolution of salt rock, gypsum, along with other minerals, serves as the material basis for high-salinity groundwater formation. In addition, the evolution of major ions is also affected by cation exchange. The TDS concentration of mine water ranges from 3435.4 mg/L to 4414.3 mg/L, and the combined treatment process of nanofiltration and reverse osmosis can be selected to remove the salt. After treatment, mine water can be used for productive, domestic, and ecological demands.

The genus Agave is an endemic species of plants from America, whose center of origin is Mexico. The agaves are plants considered as one of the greatest cultural and botanical resources of the country. Actually the uses more important are the production of fermented (pulque) and distilled beverages like (mezcal and tequila). Due its importance, the aim of this work was to analyze the genetic profile of twenty native agave individuals from eleven species using molecular markers, which were amplicons of mitochondrial cytochrome P450 gene. With the five primers used, approximately 125 fragments were amplified for each Agave species with a size between 50 and 1000 bp. Fragments of 150 to 130 bp were amplified for almost all species, specifically withCYP2B6F-CYP2C19R primer combination. The banding pattern of these amplicons was used to construct a dendrogram that showed three main clusters of Agave species: salmiana, tequilana, and americana. The results obtained in this work may serve as a reference in support of the identification of agave genotypes. [ABSTRACT FROM AUTHOR]

Livestock production in semi-arid areas has been unpredictable due to climate variability, mainly rainfall. This study aims to simulate rangeland production variability aff ected by rainfall over time and relate it to an adjusted carrying capacity, using forage stock to maximize the potential of production of the system to a specific guarantee level. Regression analysis of forage biomass against rainfall was performed for ecological sites in the Brazilian semi-arid region to generate probability distribution curves for the historical rainfall for each location using Monte Carlo approach. Forage biomass variability estimated over time was used as input to the model. The system optimizes forage use at a sustainable stocking rate and uses forage surpluses in good years to fill deficits during adverse years, due to a certain level of guarantee. As a rule, smallholder farmers would need to maintain a storage of around 1,500 kg ha-1 of DM of forage to maintain an adjusted carrying capacity of 0.11 animal units ha-1, with a guarantee of 95% in the long term, stressing the forage storage capacity as a central component of the model. Since farm size influences forage production capacity and mainly forage stock capacity, recommendations to cope with this paradigm are suggested. [ABSTRACT FROM AUTHOR]

Water resource management scenarios have become more crucial for arid to semi-arid regions. Their application prerequisites rigorous hydrological modelling approaches since data are usually exposed to uncertainties and inaccuracies. In this work, Soil Water Assessment Tool (SWAT), an open source semi-distributed, continuous-time, process-based physical hydrological model is used to model hydrological processes and eventually calculate groundwater recharge estimations in Seybouse basin, Northeast Algeria. The model uses estimated rainfall to calibrate the model with observed discharge from hydrometric stations. Model calibration and validation are performed over four hydrometric stations located in the basin. Uncertainty analysis and sensitivity analysis supported the calibration period. SUFI-2 algorithm is used for uncertainty estimations along with a global sensitivity analysis prior to calibration simulations. Simulated flood hydrographs showed generally good accuracy with few misfits on the peaks. The model obtained satisfactory and consistent calibration and validation results for which the Nash score varied from 0.5 to 0.7 for calibration and from −0.1 to 0.6 for validation and R2 from 0.6 to 0.7 for calibration and 0.03 to 0.8 for validation. Moreover, estimated water budget values show strong similarities with the observed values found in the literature. The present work shows that the rigorously calibrated and validated SWAT model can simulate hydrological processes as well as major high and low flows using estimated rainfall data. [ABSTRACT FROM AUTHOR]

This study focused on monitoring the water status of vegetation and soil by exploiting the synergy of optical and microwave satellite data with the aim of improving the knowledge of water cycle in cultivated lands in Egyptian Delta and Tunisian areas. Environmental analysis approaches based on optical and synthetic aperture radar data were carried out to set up the basis for future implementation of practical and cost-effective methods for sustainable water use in agriculture. Long-term behaviors of vegetation indices were thus analyzed between 2000 and 2018. By using SAR data from Sentinel-1, an Artificial Neural Network-based algorithm was implemented for estimating soil moisture and monthly maps for 2018 have been generated to be compared with information derived from optical indices. Moreover, a novel drought severity index was developed and applied to available data. The index was obtained by combining vegetation soil difference index, derived from optical data, and soil moisture content derived from SAR data. The proposed index was found capable of complementing optical and microwave sensitivity to drought-related parameters, although ground data are missing for correctly validating the results, by capturing drought patterns and their temporal evolution better than indices based only on microwave or optical data.. [ABSTRACT FROM AUTHOR]

Monitoring snowmelt dynamics in mountains is crucial to understand water releases downstream. Sentinel-1 (S-1) synthetic-aperture radar (SAR) has become one of the most widely used techniques to achieve this aim due to its high frequency of acquisitions and all-weather capability. This work aims to understand the possibilities of S-1 SAR imagery to capture snowmelt dynamics and related changes in streamflow response in semi-arid mountains. The results proved that S-1 SAR imagery was able not only to capture the final spring melting but also all melting cycles that commonly appear throughout the year in these types of environments. The general change detection approach to identify wet snow was adapted for these regions using as reference the average S-1 SAR image from the previous summer, and a threshold of −3.00 dB, which has been assessed using Landsat images as reference dataset obtaining a general accuracy of 0.79. In addition, four different types of melting-runoff onsets depending on physical snow condition were identified. When translating that at the catchment scale, distributed melting-runoff onset maps were defined to better understand the spatiotemporal evolution of melting dynamics. Finally, a linear connection between melting dynamics and streamflow was found for long-lasting melting cycles, with a determination coefficient (R2) ranging from 0.62 to 0.83 and an average delay between the melting onset and streamflow peak of about 21 days. [ABSTRACT FROM AUTHOR]

Underground mining operations are known to result in extensive surface subsidence, introducing a multitude of disturbances to surface vegetation, with particularly severe environmental impacts in the fragile ecosystems of arid and semi-arid regions. This study focuses on the Daliuta mining area located in semi-arid zones, selecting four distinct areas for data analysis. Areas A, B, and C fall within the mining perimeter and have all been affected by mining-related disturbances. Following coal extraction, Areas A and B underwent artificial rehabilitation measures, including fracture infilling and sea buckthorn plantation; Area C was left in its natural state without any artificial interference. Area D, unaffected by mining activities, was designated as the control group. The research utilized 60 Landsat satellite images spanning from 1988 to 2022. Employing the Normalized Difference Vegetation Index (NDVI) and the Fractional Vegetation Cover (FVC), the study classified the experimental zone’s vegetation cover and degradation into six levels, ranging from low to high. By comparing the average vegetation cover over an extended period, changes across different vegetation cover levels, and the degree of vegetation degradation before and after mining, the study assessed the impact of underground mining on surface vegetation. The conclusions drawn are as follows: Mining operations caused significant damage to the vegetation in Areas A and B, yet artificial restoration measures notably improved the vegetation quality, with an overcompensation effect observed in Area A, suggesting the potential for ecological restoration efforts to create a vegetative environment that exceeds its original condition in the long term. Mining activities also induced continuous ecological adverse effects in Area C, but the natural regeneration process progressively restored the vegetation to pre-mining levels over time. Based on these findings, the study reveals the spatiotemporal patterns of vegetation damage and recovery across different mining periods and land reclamation stages. It proposes a restoration strategy for mine areas in semi-arid regions that prioritizes natural regeneration supported by artificial guidance. This work provides valuable insights and guidance for assessing the impact of underground coal mining on surface vegetation in semi-arid areas, as well as for the rehabilitation and ecological reconstruction of mine areas, emphasizing the necessity and urgency of conducting environmental assessments and implementing restoration measures.

Evapotranspiration is one of the most significant variables used to determine runoff, hydrological balances, and climate change studies. In semi-arid conditions, there is a need to evaluate various alternatives to establish reference evapotranspiration (ETo), given that climate change scenarios sometimes do not provide information on diverse climate variables. Several alternatives for obtaining evapotranspiration are analyzed in this study and compared with the Penman-Monteith method, modified by FAO (PMFAO56). Due to limited daily climate information, it is necessary to consider different options for determining reference evapotranspiration. In the present work, methods based on temperature (Hargreaves, Hargreaves 1, Hargreaves 2, and Baier-Robertson) and radiation (Caprio, Irmark 1, Irmark 2, Irmark 3, Makkink, Priestley-Taylor and Hasen) were investigated. The best performance for the semi-arid Jucar River Basin was determined by Hargreaves methods. Regional calibration of Hargreaves methods, Hargreaves 1 and Hargreaves 2, were performed for each sub-basin. HIGHLIGHTS The reference evapotranspiration at a daily scale improves the quality for current and climate modeling.; PMFAO56 method is a standardized method for estimating evapotranspiration but alternative evapotranspiration Hargreaves methods provide adequate performance for semi-arid regions.; Calibration of the daily evapotranspiration method improves the results.; In the absence of climate variables, daily temperature-based models can be used.;

Total nitrogen (TN) is a critical nutrient for plant growth, and its monitoring in agricultural soil is vital for farm managers. Traditional methods of estimating soil TN levels involve laborious and costly chemical analyses, especially when applied to large areas with multiple sampling points. Remote sensing offers a promising alternative for identifying, tracking, and mapping soil TN levels at various scales, including the field, landscape, and regional levels. Spaceborne hyperspectral sensing has shown effectiveness in reflecting soil TN levels. This study evaluates the efficiency of spectral reflectance at visible near-infrared (VNIR) and shortwave near-infrared (SWIR) regions to identify the most informative hyperspectral bands responding to the TN content in agricultural soil. In this context, we used PRISMA (PRecursore IperSpettrale della Missione Applicativa) hyperspectral imagery with ensemble learning modeling to identify N-specific absorption features. This ensemble consisted of three multivariate regression techniques, partial least square (PLSR), support vector regression (SVR), and Gaussian process regression (GPR) learners. The soil TN data (n = 803) were analyzed against a hyperspectral PRISMA imagery to perform spectral band selection. The 803 sampled data points were derived from open-access soil property and nutrient maps for Africa at a 30 m resolution over a bare agricultural field in southern Morocco. The ensemble learning strategy identified several bands in the SWIR in the regions of 900–1300 nm and 1900–2200 nm. The models achieved coefficient-of-determination values ranging from 0.63 to 0.73 and root-mean-square error values of 0.14 g/kg for PLSR, 0.11 g/kg for SVR, and 0.12 g/kg for GPR, which had been boosted to an R2 of 0.84, an RMSE of 0.08 g/kg, and an RPD of 2.53 by the ensemble, demonstrating the model’s accuracy in predicting the soil TN content. These results underscore the potential for using spaceborne hyperspectral imagery for soil TN estimation, enabling the development of decision-support tools for variable-rate fertilization and advancing our understanding of soil spectral responses for improved soil management.

The Setifian high-plains region, Northeast of Algeria, grapples with challenges in water resource management. As the water demand intensifies across a diverse range of sectors, assessing groundwater quality becomes indispensable. This article responds to the critical need for a thorough assessment of groundwater quality in the Wadi Boussellam sub-watershed. Employing a GIS-based method, we evaluate groundwater geochemistry by estimating the Water Quality Index (WQI), offering a comprehensive overview of water consumption. The analysis of groundwater samples reveals distinct facies, including calcic bicarbonate, calcic chloride, calcic sulfate, and magnesium sulfate, contributing to an enhanced understanding of the hydrochemical composition in the Setif region. Hydrochemical indices, specifically the WQI, Sodium Adsorption Ratio (SAR), and Na% are applied to assess groundwater suitability for various applications. The results indicate that most crops are generally suitable for irrigation, though they advise exercising caution with regard to human consumption. This study underscores the significance of regular monitoring to avert groundwater contamination and ensure sustainable use in the Setif region, providing insights that emphasize the ongoing necessity for efforts in water resource management and the preservation of this vital resource’s quality.

Schlumberger configuration was used to carry out 34 vertical electrical sounding (VES) measurements for estimating and characterizing the shallow Quaternary aquifer parameters and its vulnerability to surficial contamination in the region of Khanasser Valley, Northern Syria. The data of VES are interpreted by the curve matching technique (CMT) and WinResist software package to get one dimensional (1D) geoelectrical solution model for each study VES point. The electrical conductivity (EC), total dissolved solids (TDS), porosity (Ø%), the overburden protective capacity (OPC), and the corrosion (Corr) of the study aquifer were revealed by parameters of longitudinal conductance and transverse resistance of Dar-Zarrouk results. The protective capacity for the shallow Quaternary aquifer is classified as 56% poor, indicating high vulnerability to contamination, 5.9% weak, 14.7% moderate, 20.6% good, and 2.9% excellent. The ratings of corrosivity for the study region are classified as 26.5% slightly corrosive (SC), 61.8% moderately corrosive (MC), 5.9% very strongly corrosive (VSC), and 5.9% practically noncorrosive (PNC). HIGHLIGHTS VES data are 1D interpreted to get the optimum model for each study VES point.; Longitudinal conductance and transverse resistance are used to evaluate EC, TDS, Ø%, OPC, and Corr of the study aquifer.; 56% of the study area has a high vulnerability to contamination, 5.9% weak, 14.7% moderate, 20.6% good, and 2.9% excellent.;

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Land surface temperature (LST) and its relationship with vegetation indices (VIs) have proven to be effective for monitoring water stress in large-scale crops. Therefore, the objective of this study is to find an appropriate VI to analyse the spatio-temporal evolution of olive water stress using LST images and VIs derived from Landsat 5 and 8 satellites in the semi-arid region of southern Peru. For this purpose, VIs (Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index 2 (EVI2) and Soil Adjusted Vegetation Index (SAVI)) and LST were calculated. The information was processed in Google Earth Engine (GEE) for the period 1985 to 2024, with an interval of every five years for the summer season. The triangle method was applied based on the LST-VIs scatterplot analysis, a tool that establishes wet and dry boundary conditions for the Temperature Vegetation Dryness Index (TVDI). The results indicated a better appreciation of olive orchard water stress over time, with an average of 39% drought (TVDINDVI and TVDISAVI), 24% severe drought (TVDINDVI) and 25% (TVDISAVI) of the total area, compared to TVDIEVI2, which showed 37% drought and 16% severe drought. It is concluded that TVDINDVI and TVDISAVI provide a better visualisation of the water stress map of the olive crop and offer a range of options to address current and future problems in water resource management in the olive sector in semi-arid areas of southern Peru.

ABSTRACT Water reservoirs were built in the semi-arid region to mitigate the effects of drought and water scarcity. However, these reservoirs are subject to variables that impact the volume and quality of the stored water, with the contribution of such nutrients as Total Nitrogen (TN) and Total Phosphorus (TP) being one of the main factors in intensifying the eutrophication process. The aim of this study was to quantify the principal inputs and outputs of nutrients (N and P) and calculate the nutrient balance, in order to verify the influence of seasonality on the import and export of these nutrients in surface reservoirs of the semi-arid region of Brazil. Seven campaigns were carried out between 2015 and 2016, with water samples collected at five points in the Pereira de Miranda reservoir and four in the General Sampaio reservoir. The inflow of nutrients was greater when the inflow rate of the water was higher. The balance showed the accumulation of 22.8 tons of TN and 2.8 tons of TP in the Pereira de Miranda reservoir, and 13 tons of TN and 1.5 tons of TP in the General Sampaio. These reservoirs are therefore retaining nutrients, acting as a storage site for nutrients transported by surface runoff in the basin of the Curu River. This increase in storage occurred mainly during the rainy season, when nutrient retention by the reservoirs impaired water quality, resulting in eutrophication, and making it difficult to meet the uses for which the reservoirs were intended.

Long records of tree‐ring maximum latewood density (MXD) measurements in conifers have been successfully employed to reconstruct summer temperature changes globally. Yet, the potential of MXD as a proxy in semi‐arid, low‐latitude regions for reconstructing either temperature or hydroclimate variability remains largely unexplored. Here, we developed a MXD data set of Chinese pine from semi‐arid northern China, and investigated its sensitivity to different climate variables. We found that the annual self‐calibrated Palmer Drought Severity Index from previous August to current July displays the strongest influence on the MXD variation. The entire MXD chronology (covering 1736–2020) is highly consistent with nearby tree‐ring‐based annual precipitation and drought reconstructions at decadal timescales, confirming a temporally stable hydroclimate signal in our MXD record. In particular, the rapid wetting trend during the 2010–2020 period is well captured by the MXD data. This novel study has wide implications for future use of tree‐ring density data to reconstruct past climate changes globally. Plain Language Summary: Tree‐ring maximum latewood density (MXD) is normally identified as carrying a temperature signal in cold high‐altitude or high‐latitude regions. Very few studies have been conducted in areas with a semi‐arid climate. Whether MXD also in such regions can be used as a temperature proxy still needs confirmation. We developed a MXD chronology from Chinese pine trees located in the northern China where temperatures show significant warming trends, but precipitation has not increased during the instrumental period. Correlation with various climate parameters indicates that this tree‐ring MXD record contains a significant hydroclimate signal. The strongest correlation is found with the annual self‐calibrated Palmer Drought Severity Index calculated from previous August to current July. We further noticed that other published MXD chronologies, based on different tree species, also can reflect precipitation or hydroclimate signals when growing in drought‐dominated climatic environments. The generally detected temperature signal in MXD data is not supported by our study, meaning caution should be taken before using MXD data as a proxy for temperature in drought‐prone regions. Key Points: A Chinese pine maximum latewood density (MXD) chronology covering the 1736–2020 period is developed for a semi‐arid region in northern ChinaTree‐ring MXD and width show consistent high‐ and low‐frequency variations limited by common hydroclimate variablesChinese pine tree‐ring MXD in semi‐arid northern China is an indicator of hydroclimate rather than temperature [ABSTRACT FROM AUTHOR]

Groundwater exploitations in semi‐arid regions result in significant declines of groundwater levels and streamflow and even trigger seasonal streamflow drying up, which may bring adverse impacts on riparian ecosystems. It is critical to explore future streamflow changes caused by variable climate scenarios and groundwater exploitation intensities; however, a comprehensive assessment of the streamflow drying up frequency remains lacking. Furthermore, the thresholds of controlling factors beyond which streamflow drying up occurs have rarely been explored. Here we develop an integrated surface water‐groundwater model for the Taoer River Basin (TRB), a typical semi‐arid watershed in northeast China. We apply the model to multiple future scenarios to reveal the frequency of potential streamflow drying up and explore the thresholds of controlling factors of streamflow drying up based on a decision tree method. We find that the groundwater level in the lower region of the TRB (LTRB) is hard to recover to the riverbed elevation and the streamflow drying up frequency is still high unless the groundwater exploitation is reduced by 50%. However, this leads to a competition between the ecological and economic objectives. Our results also show that the streamflow drying up frequency in the LTRB is very sensitive to the upstream water inflow that can be regulated through the reservoir operation or inter‐basin water diversion, indicating the importance of a basin scale strategic management. The findings of this paper can help policy makers sustainably exploit water resources in semi‐arid regions. [ABSTRACT FROM AUTHOR]

In a human-dominated world, access to sustainable water resources has led to complex management policies that affect hydrological droughts. Applying the best approach to assess the contribution of these human-made changes to hydrological droughts is still underexplored. In this study, the individual and joint impacts of dam and inter-basin water transfer projects are quantified for the characteristic changes of hydrological drought using a developed data-based framework and were tested in a semi-arid, data-scarce basin in central Iran. The proposed data-based framework combines the upstream–downstream comparison method and the individual–station–drought analysis. This framework could properly assess the individual and joint contributions of dam and water transfer projections to making aggravations or alleviations in hydrological drought. It identified the dam and joint impacts of the dam with water transfer by 66 and 55%, respectively, as the most effective human intervention to alleviate the duration of hydrological drought. The proposed framework gives the flexibility to form different comparative analyses by using different types of flow data to assess the impacts of human interventions. This framework is also applicable in other regions to quantify the contributions of point-based human interventions to hydrological droughts. The comprehensive knowledge of solutions to alleviate the adverse impacts of droughts can reduce the damage in water-stressed regions. HIGHLIGHTS This study proposed a new framework to separate human impacts on hydrological droughts.; This study assessed the most effective contribution of human impacts to drought alleviation.; The results showed both aggravation and alleviation contributions of human impacts.; This study is an effective framework to apply in data-scarce and semi-arid regions.; The framework can separate combined or individual impacts of any point-based interventions.;

In order to understand the ecophysiology of sub-Sahelian tree species and to optimize their use in agroforestry, studies on tree root distribution are essential. The aim of this study was to investigate the root distribution of three sub-Sahelian tree species, Adansonia digitata, Faidherbia albida and Borassus akeassii, in three sites along a precipitation and soil gradient in Senegal. Root density maps observed on trench walls and soil-coring methods were used to characterize variations in root density of mature trees. Coarse and fine root distribution was strongly influenced by the site conditions, with root density being highest in the humid site for all tree species. B. akeassii had the highest root density compared to the other two species. Fine root biomass was concentrated in the 0–30 cm soil layer for A. digitata and from 30 to 60 cm for B. akeassii and F. albida. Laterally, the fine root biomass decreased substantially with increasing distance from the trees. Understanding the root distribution of sub-Sahelian tree species across climatic conditions could help to reduce competition between crops and perennials in agroforestry parklands. [ABSTRACT FROM AUTHOR]

Introduction: Canola is one of the most important oilseed crops all over the world. This oilseed crop is mainly utilized for its high oil content (with about 40-45% oil). However, in recent years, the area under cultivation of canola has decreased due to water scarcity. Applying drought-tolerant cultivars with high water use efficiency can help to develop the area under cultivation of canola and increase canola production. Therefore, the current study was conducted to assess the water use efficiency of spring canola cultivars in warm and temperate climates. Material and methods: This study investigated different cultivars as a strategy for increasing canola production and improving its water use efficiency under different climate types in Khuzestan and Lorestan provinces. For this purpose, four locations including Khoramabad and Kuhdasht in Lorestan Province as semiarid climate regions and Dezful, and Shushtar in Khuzestan Province as hot and arid climate regions were selected. Daily long-term climatic data (including minimum and maximum temperatures, rainfall, and global radiation) were collected for these locations from Iran Meteorological Organization. In this study, Hyola308 (early-maturity), Hyola401 (mid-maturity), and RGS003 (late-maturity) cultivars were used. In order to simulate the growth and yield of canola in different locations, the APSIM-Canola model was employed. OriginPro 9.1 software was used for all statistical analyses and the generation of figures. Results and discussion: The results showed that grain yield, biomass, water use efficiency, grain weight, actual evapotranspiration, the average temperature during the canola growth period, and the length of the canola growth period were substantially affected by cultivar and region (climate type). According to the results, the highest grain yield and water use efficiency (3037 kg ha-1 and 6.9 kg mm-1 ha-1, respectively) were achieved for the mid-maturity cultivar (Hyola401). Furthermore, simulation results revealed that temperate and semiarid regions compared to hot and arid regions increased grain yield, biomass and water use efficiency by 2507 kg ha-1, 10100 kg ha-1, and 2.7 kg mm-1 ha-1, respectively. Khorramabad × Hyola401 treatment had the highest water use efficiency, grain yield, and biomass (9 kg mm-1 ha-1, 4954, and 17943 kg ha-1, respectively) due to lower the average temperature during the canola growth period (10.9 ° C) and higher the length of the canola growth period (2424.9 day), while the lowest amount of these traits was recorded in Dezful × Hyola308 treatment (5 kg mm-1 ha-1, 1369, and 5514 kg ha-1, respectively). Conclusion: The results indicated that expanding canola cultivation in temperate regions can be used to boost canola production in Iran and to improve the sustainability of canola cultivation agroecosystems. Also, using a mid-maturity cultivar such as Hyola401 in both temperate and hot climate conditions can increase water use efficiency and sustainability of canola production agroecosystems through higher production per water consumption. [ABSTRACT FROM AUTHOR]