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As arid lands expand across the globe, scholars increasingly turn to the archaeological record for examples of sustainable farming in extreme environments. The arid north coast of Peru was the setting of early and intensive irrigation-based farming; it is also periodically impacted by sudden, heavy rainfall related to the El Niño Southern Oscillation (ENSO) phenomenon. While the sociopolitical effects, technologies, and engineering expertise of these irrigation systems have been thoroughly examined and theorized, little is known about how farmers managed periods of water stress. The aim of this study is to test whether arid zone farming was supported by hybrid, intermittent flood and perennial water source systems in the prehispanic past. An arroyo in the Chicama Valley was selected for preliminary data collection, and these data are presented here: (1) drone photography of the arroyo capturing the aftermath of a recent (2023) rain event; and (2) potassium (K) soil test kit results from samples collected near suspected prehispanic check dam features in the same area. The paper combines these data with comparative examples from the literature to suggest that the prehispanic features functioned as water-harvesting infrastructure. The paper concludes that sustainable, arid zone farming can be supported by hybrid, intermittent flood and perennial water source systems. [ABSTRACT FROM AUTHOR]

Groundwater plays a critical water resources role in arid and semi-arid areas. Quantitative evaluation of groundwater recharge is crucial in hydrogeological investigations. Under the complex hydrogeological and climatic conditions in China's arid and semi-arid regions, groundwater recharge shows significant spatio-temporal heterogeneity. Although there has been much research, including hydrochemical analysis, isotope tracing, in-situ tests and numerical simulations, accurate quantitative groundwater recharge is still a great challenge. This paper reviews the progress in research on groundwater recharge in arid and semi-arid regions of China, focusing on the principles and current applications of the main techniques, as well as the achievements in nine typical arid and semi-arid regions (Tarim Basin, Junggar Basin, Shule River Basin, Heihe River Basin, Yinchuan Plain, Badain Jaran Desert, Loess Plateau, Ordos Plateau, North China Plain). The paper reveals that the chloride mass balance method is a popular method to estimate groundwater recharge rate, whereas stable isotopes and hydrochemistry analyses, as well as the joint use of both, have been widely used in the understanding of groundwater recharge processes and mechanisms in the arid and semi-arid regions of China. Numerical modeling and remote sensing technology will become important approaches to quantify large-scale groundwater recharge. It is also suggested that various estimation methods should be used in combination, in order to improve the reliability of recharge estimates. Furthermore, this review shows that the theoretical research so far still cannot meet the needs of regional development, and the paper highlights some scientific problems that need to be further explored. [ABSTRACT FROM AUTHOR]

Groundwater evapotranspiration (ETg) is a significant component of water and energy balance analyses in arid and semiarid environments; however, it is also one of the most challenging items to estimate. Estimation of ETg using diurnal groundwater-level fluctuation is considered cost-effective and straightforward, while more accurate estimation technology continues to be developed due to the complex set of factors that influence the variation of groundwater level. This paper proposes a method for calculating ETg that combines the analytical solution of the Boussinesq equation and dynamic harmonic regression analysis, which is a nonstationary approach to groundwater-level signal extraction. The presented approach can calculate ETg values with a high time resolution consistent with the groundwater-level monitoring frequency, and it is robust enough to handle large amounts of measurement data. More importantly, this method eliminates the influence of recharge during the groundwater-level-rise stage. The method is tested in bushland dominated by Sminthopsis psammophila in Mu Us Desert (northern China), which has a shallow water table. The results show that this method is easy to perform and it obtains a reasonable estimate of ETg in the unfrozen seasons, regardless of the disturbance of recharge that results in a sharp rise in groundwater level. However, the method does not work well in the frozen seasons because of the physical mechanisms of change in groundwater movement in the vadose zone and a strong barometric effect. Overall, the method provides a step toward accuracy of ETg estimation using diurnal groundwater-level fluctuation, and this paper provides guidelines for its use. [ABSTRACT FROM AUTHOR]

Jenny Davis was among the first small, but significant tranche of women field biologists in the Pacific Region. She was born in Tasmania and developed a fascination with freshwater systems at an early age. Despite the paucity of female role models, freshwater ecology evolved into her research career track at the University of Tasmania where she completed her Honours degree (Zoology; 1976) and PhD (Freshwater Ecology; 1981). Jenny started her first academic position as a Tutor at Murdoch University in 1985. She successfully moved through the academic hierarchy where women continue to be under-represented in the senior ranks. She recently (2021) retired from her administrative and teaching responsibilities at Charles Darwin University (CDU) and approaching 70, is currently a Professor of Freshwater Ecology at CDU. An over-arching theme of her research is to understand the factors influencing the persistence of groundwater and surface water ecosystems. She has worked on the impacts of multiple stressors on springs, wetlands and arid zone waterbodies. She serves as a compelling role model for young scientists struggling to have a satisfying work-life balance. Jenny single-parented a son while conducting field work, teaching, publishing, serving as an academic administrator and being a prolific and successful grant writer. Jenny was also an exceptional mentor to a diverse group of students and post-docs, many of whom have thriving careers in academia, government and industry across Australia. This paper is a biography of a woman who with talent and persistence successfully broke gender barriers in Australian freshwater ecology and academia. Jenny Davis was among the first small, but significant tranche of female field biologists in the Pacific Region. Jenny is one of the few women to be promoted to the academic rank of Professor in Australian sciences. Her current research involves answering two questions: (1) how much water does the environment need; and (2) how important are isolated aquatic waterbodies for the conservation of Australia's freshwater biota? This paper is a brief biography of Jenny. [ABSTRACT FROM AUTHOR]

O'Gorman grounds this argument in a range of sites, stitching them together over seven chapters that explore the dynamic more-than-human histories of certain water landscapes. We are now perhaps overly familiar with accounts of the Murray-Darling Basin as a "biocultural terrain" (96) over which the effects of colonial (mis)management are writ large, not least because of O'Gorman's 2012 book I Flood Country i . Wetlands in a Dry Land: More-Than-Human Histories of Australia's Murray-Darling Basin: By Emily O'Gorman. [Extracted from the article]

The recent paper by Morillas et al. [Morillas, L. et al. Using radiometric surface temperature for surface energy flux estimation in Mediterranean drylands from a two-source perspective, Remote Sens. Environ. 136, 234–246, 2013] evaluates the two-source model (TSM) of Norman et al. (1995) with revisions by Kustas and Norman (1999) over a semiarid tussock grassland site in southeastern Spain. The TSM - in its current incarnation, the two-source energy balance model (TSEB) - was applied to this landscape using ground-based infrared radiometer sensors to estimate both the composite surface radiometric temperature and component soil and canopy temperatures. Morillas et al. (2013) found the TSEB model substantially underestimated the sensible H (and overestimated the latent heat LE ) fluxes. Using the same data set from Morillas et al. (2013), we were able to confirm their results. We also found energy transport and exchange behavior derived from primarily the observations themselves to differ significantly from a number of prior studies using land surface temperature for estimating heat fluxes with one-source modeling approaches in semi-arid landscapes. However, revisions to key vegetation inputs to TSEB and the soil resistance formulation resulted in a significant reduction in the bias and root mean square error (RMSE) between model output of H and LE and the measurements compared to the prior results from Morillas et al. (2013). These included more representative ground-based vegetation greenness and local leaf area index values as well as modifications to the coefficients of the soil resistance formulation to account for the very rough (rocky) soil surface conditions with a clumped canopy. This indicates that both limitations in remote estimates of biophysical indicators of the canopy at the site and the lack of adjustment in soil resistance formulation to account for site specific characteristics, contributed to the earlier findings of Morillas et al. (2013). This suggests further studies need to be conducted to reduce the uncertainties in the vegetation and land surface temperature input data in order to more accurately assess the effects of the transport exchange processes of this Mediterranean landscape on TSEB formulations. [ABSTRACT FROM AUTHOR]

Accurate estimation of surface evapotranspiration (ET) in the Heihe River Basin using remote sensing data is crucial for understanding water dynamics in arid regions. In this paper, by coupling physical constraints and machine learning for hybrid modeling, we develop a hybrid model based on surface conductance optimization. A hybrid modeling algorithm, two physical process-based ET algorithms (Penman–Monteith-based and Priestley–Taylor-based ET algorithms), and three pure machine learning algorithms (Random Forest, Extreme Gradient Boosting, and K Nearest Neighbors) are comparatively analyzed for estimating the ET. The results showed that, in general, the machine learning model optimized by parameters was able to better predict the surface conductance of the hybrid model. Driver analyses showed that radiation, normalized difference vegetation index (NDVI), and air temperature had high correlations with ET. The hybrid model had a better prediction performance for ET than the other five models, and it improved the R2 of the two physical process-based algorithms to 0.9, reduced the root mean square error (RMSE) to 0.5 mm/day, reduced the BIAS to 0.2 mm/day, and improved the Kling–Gupta efficiency (KGE) to 0.9. The hybrid model outperformed the others across different time scales, displaying lower BIAS, RMSE, and higher KGE. Spatially, its ET patterns aligned with regional vegetation changes, with superior accuracy in annual ET estimation compared to the other models. Comparison with other ET products shows that the estimation results based on the hybrid model have better performance. This approach not only improves the accuracy of ET estimation but also improves the understanding of the physical mechanism of ET estimation by pure machine learning models. This study can provide important support for understanding ET and hydrological processes under different climatic and biotic vegetation in other arid and semi-arid regions. [ABSTRACT FROM AUTHOR]

The study of ancient irrigation is crucial in the archaeological research of arid regions. It covers a wide range of topics, with the Near East being the focus for decades. However, political instability and limited data have posed challenges to these studies. The primary objective is to establish a standardised method applicable to different arid environments using the Google Earth Engine platform, considering local relief of terrain and seasonal differences in vegetation. This study integrates multispectral data from LANDSAT 5, Sentinel-2, SAR imagery from Sentinel 1, and TanDEM-X (12 m and 30 m) DSMs. Using these datasets, calculations of selected vegetation indices such as the SMTVI and NDVSI, spectral decomposition methods such as TCT and PCA, and topography-based methods such as the MSRM contribute to a comprehensive understanding of landscape irrigation. This paper investigates the influence of modern environmental conditions on the visibility of features like levees and palaeo-channels by testing different methods and parameters. This study aims to identify the most effective approach for each case study and explore the possibility of applying a consistent method across all areas. Optimal results are achieved by combining several methods, adjusting seasonal parameters, and conducting a comparative analysis of visible features. [ABSTRACT FROM AUTHOR]

Land-cover classification based on remote sensing technology has been adopted for decision-making concerning agricultural development, urban planning, and ecosystem protection in arid oasis zones. The semantic segmentation method based on deep learning, as a new paradigm, can effectively overcome the limitations of traditional pixel-based and object-based methods and obtain good classification results from high spatial resolution (HSR) remote sensing images. However, how to extract the exact category boundary and realize the high precision mapping is still a problem. This paper proposes a novel high-resolution feature pyramid attention network (HRFPANet) for land-cover classification. It effectively integrates the advantages of multi-scale feature extraction, attention mechanism, and feature fusion and alleviates boundary inconsistency, roughness, and category fragmentation associated with previous semantic segmentation models. The experimental results show that the mIoU score of HRFPANet is 79.5%, which is 11.5% and 2.6% higher than that of PSPNet and UPerNet, respectively. It proves the proposed model can be used for qualified land-cover mapping in arid oasis zones. Our source code is available at . [ABSTRACT FROM AUTHOR]

Arid zone grassland is a crucial component of terrestrial ecosystems and plays a significant role in ecosystem protection and soil erosion prevention. However, accurately mapping grassland spatial information in arid zones presents a great challenge. The accuracy of remote sensing grassland mapping in arid zones is affected by spectral variability caused by the highly diverse landscapes. In this study, we explored the potential of a rectangular tile classification model, constructed using the random forest algorithm and integrated images from Sentinel-1A (synthetic aperture radar imagery) and Sentinel-2 (optical imagery), to enhance the accuracy of grassland mapping in the semiarid to arid regions of Ordos, China. Monthly Sentinel-1A median value images were synthesised, and four MODIS vegetation index mean value curves (NDVI, MSAVI, NDWI and NDBI) were used to determine the optimal synthesis time window for Sentinel-2 images. Seven experimental groups, including 14 experimental schemes based on the rectangular tile classification model and the traditional global classification model, were designed. By applying the rectangular tile classification model and Sentinel-integrated images, we successfully identified and extracted grasslands. The results showed the integration of vegetation index features and texture features improved the accuracy of grassland mapping. The overall accuracy of the Sentinel-integrated images from EXP7-2 was 88.23%, which was higher than the accuracy of the single sensor Sentinel-1A (53.52%) in EXP2-2 and Sentinel-2 (86.53%) in EXP5-2. In all seven experimental groups, the rectangular tile classification model was found to improve overall accuracy (OA) by 1.20% to 13.99% compared to the traditional global classification model. This paper presents novel perspectives and guidance for improving the accuracy of remote sensing mapping for land cover classification in arid zones with highly diverse landscapes. The study presents a flexible and scalable model within the Google Earth Engine framework, which can be readily customized and implemented in various geographical locations and time periods. [ABSTRACT FROM AUTHOR]

The Forest Fire Danger Index (FFDI) is the main measure used in Australia for estimating fire risk. Recent work by the authors showed that the FFDI forms stable state regimes, nominated as fire climate regimes. These regimes shifted to greater intensity in southern and eastern Australia around the year 2000 and, a decade later, further north. Reductions in atmospheric moisture were the primary contributor. These changes have not been fully incorporated into future projections. This paper compares the recent regime shifts with the most recent national projections of FFDI, published in 2015. They show that for most states and regions, the 2030 upper limit is approached or exceeded by the recent shift, except for two states with large arid zones, South Australia and Western Australia. Methods for attributing past changes, constructing projections, and the inability of climate models to reproduce the recent decreases in atmospheric moisture, all contribute to these underestimates. To address these shortcomings, we make some suggestions to modify efforts aiming to develop seamless predictions and projections of future fire risk. [ABSTRACT FROM AUTHOR]

Open water transposition channels in hot and arid regions, like those in the São Francisco River Integration Project (PISF) in Brazil, suffer significant water losses through evaporation. This paper proposes covering these channels with photovoltaic (PV) panels to reduce evaporation while simultaneously generating clean energy. The research aims to quantify water savings and energy generation potential across all channel lengths and assess whether the generated solar power can substitute grid electricity for powering the transposition pumps during peak hours, thereby enhancing energy efficiency. This study analyzed the state-of-the-art of PV generation and calculated their solar potential. Identified the specific characteristics of PISF channels and watercourses considering the regional geography, meteorology, irradiation, and social peculiarities. And, finally, assessed the feasibility of covering the watercourses with solar panels. The results reveal that covering all current PISF channels with PV panels could save up to 25,000 cubic meters of water per day, significantly contributing to water security and improving the quality of life for the local population. Additionally, the project could generate 1200 gigawatt-hours of electricity annually, meeting the energy demands of the transposition pumps during peak hours and promoting energy efficiency within the project. This research paves the way for utilizing PV technology to address water scarcity challenges and enhance the sustainability of water infrastructure projects in arid regions worldwide. [ABSTRACT FROM AUTHOR]

Simple Summary: This work aims to analyze flocks' management practices and sheep breeders' perceptions of the impact of climate change to enhance the resilience of the sheep production systems in the Tunisian semi-arid region. The results revealed three main sheep production systems: the agro-pastoral rain-fed system (AGPRF), the agro-pastoral irrigated system (AGPI), and the agro-sylvo-pastoral system (AGSP). Each production system is characterized by specific management and productive parameters that are used by farmers to build resilience actions. However, farmers' climate change perceptions are mostly the same across the three sheep production systems: a decrease in precipitation and an increase in temperatures and extreme events, which negatively influence feedstuff availability and costs. Global climate change inflicts unambiguous risks on agricultural systems and food security. Small ruminants are known for their ability to adapt to changing environmental conditions. This paper aims to characterize sheep production systems in a vulnerable agricultural zone and the breeders' perceptions of climate change to apprehend challenges that they are confronting, and formulate resilience actions. The data analysis is based on 94 semi-structured surveys of sheep farmers carried out in the Tunisian semi-arid region. The PCA analysis results revealed three main sheep production systems. The agro-pastoral rain-fed system (AGPRF) is dominant (55%), with large farms and common pastures integrating cereals and fodder. The agro-pastoral irrigated system (AGPI: 20%) is characterized by small-area and forage irrigation (1.8 ha) and a smaller number of ewes but a greater use of animal feed supplementation. The agro-sylvo-pastoral system (AGSP: 25%) is a system where grazing is based on common lands and using tree sub-products, while the agricultural area is exclusively used to cultivate cereal crops. Sheep breeders' climate perceptions are summarized as unpredictable climate events, a decrease in precipitation, and an increase in temperature. Resilience actions principally consist of reducing flocks' numbers, using alternative local feed, fodder, and water resources, and building more shelters and planting more trees in the grazing areas. Nevertheless, cost-effectiveness should be considered in such vulnerable zones to insure the sheep production systems' sustainability. [ABSTRACT FROM AUTHOR]

This study aims to quantify meteorological–hydrological drought propagations and examine the potential impacts by climatic variability, LULC change (LULC), and human regulations. An integrated observation-modeling framework quantifies drought propagation intervals and assesses mechanisms influencing hydrological droughts. Meteorological droughts are characterized using the Standardized Precipitation Evapotranspiration Index (SPEI), and hydrological droughts are assessed through the Standardized Streamflow Index (SSI) across diverse climatic zones. Cross-correlation analysis between SPEI and SSI time series identifies the lag time associated with the highest correlation as the drought propagation interval. Mechanisms are investigated via a coupled empirical-process modeling framework incorporating the Soil and Water Assessment Tool (SWAT). Discrepancies between simulated and observed SSI time series help quantify the extent of human regulation impacts on hydrological drought characteristics and propagation. The Yellow River Basin (YRB), divided into six subzones based on climate characteristics, is selected as the case study. Key findings include: (1) Meteorological droughts were extremely severe across most YRB during the 1990s, while the 2000s showed some mitigation primarily due to precipitation increases. (2) Hydrological droughts and propagation times from meteorology to hydrology demonstrated substantial spatiotemporal variability. In general, summer propagation times were shorter than other seasons. (3) Propagation times were shorter in arid regions with cropland or built-up land cover versus grassland and woodland, while the reverse held for humid regions. (4) Human regulations prolonged propagation times, likely due to reservoir regulations designed to overcome water deficits. While the YRB is the focus of this paper, the methodologies and findings are applicable to other regions worldwide to enhance drought forecasting and water resource management. In various hydrological and climatic contexts worldwide. [ABSTRACT FROM AUTHOR]

Altay Prefecture, a typical arid region in northwestern China, has experienced the climate transition from warming-drying to warming-wetting since 1980s and has attracted widespread attention. Nonetheless, it is still unclear how climate change has influenced the distribution of vegetation in this region. In this paper, a reaction–diffusion model of the climate–vegetation system is proposed to study the impact of climate change (precipitation, temperature and carbon dioxide concentration) on vegetation patterns in Altay Prefecture. Our results indicate that the tendency of vegetation growth in Altay Prefecture improved gradually from 1985 to 2010. Under the current climate conditions, the increase of precipitation results in the change of vegetation pattern structures, and eventually vegetation coverage tends to be uniform. Moreover, we found that there exists an optimal temperature where the spot vegetation pattern structure remains stable. Furthermore, the increase in carbon dioxide concentration induces vegetation pattern transition. Based on four climate change scenarios of the Coupled Model Intercomparison Project Phase 6 (CMIP6), we used the power law range (PLR) to predict the optimal scenario for the sustainable development of the vegetation ecosystem in Altay Prefecture. [ABSTRACT FROM AUTHOR]

Irrigation activities are important for sustaining food production and account for 70 % of total global water withdrawals. In addition, due to increased evapotranspiration (ET) and changes in the leaf area index (LAI), these activities have an impact on hydrology and climate. In this paper, we present a new irrigation scheme within the land surface model ORCHIDEE (ORganising Carbon and Hydrology in Dynamic EcosystEms)). It restrains actual irrigation according to available freshwater by including a simple environmental limit and using allocation rules that depend on local infrastructure. We perform a simple sensitivity analysis and parameter tuning to set the parameter values and match the observed irrigation amounts against reported values, assuming uniform parameter values over land. Our scheme matches irrigation withdrawals amounts at global scale, but we identify some areas in India, China, and the USA (some of the most intensively irrigated regions worldwide), where irrigation is underestimated. In all irrigated areas, the scheme reduces the negative bias of ET. It also exacerbates the positive bias of the leaf area index (LAI), except for the very intensively irrigated areas, where irrigation reduces a negative LAI bias. The increase in the ET decreases river discharge values, in some cases significantly, although this does not necessarily lead to a better representation of discharge dynamics. Irrigation, however, does not have a large impact on the simulated total water storage anomalies (TWSAs) and its trends. This may be partly explained by the absence of nonrenewable groundwater use, and its inclusion could increase irrigation estimates in arid and semiarid regions by increasing the supply. Correlation of irrigation biases with landscape descriptors suggests that the inclusion of irrigated rice and dam management could improve the irrigation estimates as well. Regardless of this complexity, our results show that the new irrigation scheme helps simulate acceptable land surface conditions and fluxes in irrigated areas, which is important to explore the joint evolution of climate, water resources, and irrigation activities. [ABSTRACT FROM AUTHOR]

The Ebinur Lake Basin is an ecologically sensitive area in an arid region. Investigating its land use and land cover (LULC) change and assessing and predicting its ecosystem service value (ESV) are of great importance for the stability of the basin's socioeconomic development and sustainable development of its ecological environment. Based on LULC data from 1990, 2000, 2010, and 2020, we assessed the ESV of the Ebinur Lake Basin and coupled the grey multi-objective optimization model with the patch generation land use simulation model to predict ESV changes in 2035 under four scenarios: business-as-usual (BAU) development, rapid economic development (RED), ecological protection (ELP), and ecological–economic balance (EEB). The results show that from 1990 to 2020, the basin was dominated by grassland (51.23%) and unused land (27.6%), with a continuous decrease in unused land and an increase in cultivated land. In thirty years, the total ESV of the study area increased from 18.62 billion to 67.28 billion yuan, with regulation and support services being the dominant functions. By 2035, cultivated land increased while unused land decreased in all four scenarios compared with that in 2020. The total ESV in 2035 under the BAU, RED, ELP, and EEB scenarios was 68.83 billion, 64.47 billion, 67.99 billion, and 66.79 billion yuan, respectively. In the RED and EEB scenarios, ESV decreased by 2.81 billion and 0.49 billion yuan, respectively. In the BAU scenario, provisioning and regulation services increased by 6.05% and 2.93%, respectively. The ELP scenario, focusing on ecological and environmental protection, saw an increase in ESV for all services. This paper can assist policymakers in optimizing land use allocation and provide scientific support for the formulation of land use strategies and sustainable ecological and environmental development in the inland river basins of arid regions. [ABSTRACT FROM AUTHOR]

Tecoma stans is a widely distributed tall ornamental shrub in the plains of Indian subcontinent and is considered an invasive species across Argentina, Australia, South Africa, Pacific Islands and tropical regions of Asia. Besides having an ornamental significance, T. stans has been extensively investigated for its pharmaceutical applications as a source of bioactive compounds. In addition, the shrub is cultivated commercially as a potted flowering plant. We believe that T. stans, being a hardy, invasive and aggressively growing species, holds a considerable potential and a promising solution for re-greening waste and degraded lands outside its invasive range, due to its wider adaptability and drought tolerant characteristics. The shrub is an excellent source of pollen and nectar, that attracts diverse insect-pollinators and several species of birds. The prudent plantation of this shrub has the potential to restore the ecology of barren landscapes, that can change its perspective of 'being invasive' to 'being ecologically healthy' across the tropical, semi-arid and subtropical regions worldwide. This paper reviews the current updates on ecology, life cycle including morphology, plant growth characteristics, flowering phenology, reproductive biology, breeding system and fruiting of T. stans. In addition, details on insect-pollinator diversity and natural regeneration potential have also been discussed, besides highlighting its therapeutic and landscape use. [ABSTRACT FROM AUTHOR]

In environmentally sensitive areas, especially the arid and semi-arid regions, the greening stability process and its influencing factors can directly affect the sustainable development of the ecological environment. In this study, multi-source remote sensing data such as land use/cover data, MODIS NDVI, and soil moisture, methods such as stability index, vegetation quantitative remote sensing, and Geodetector were employed to analyze the sustainability of the greening process in the Mu Us Sandy in 2000–2020, which were viewed from three aspects: changes in stability of land use types and function, soil moisture change and influencing factors on greening stability. The results showed that, (1) From the stability of land use types, continuous stable ecological land accounted for more than 50%, showing that decreased from northwest toward southeast. (2) From the functional stability, NDVI showed a fluctuated growth (0.035/a), with an increasing distribution pattern from northwest to southeast. Additionally, Vegetation changes were unstable and concentrated in the western part of the study area (OtogBanner and Otog Front Banner), while the eastern part was stable, in which vegetation improvement took the main position. Moreover, mobile dunes almost disappeared, and semi-fixed dunes decreased and gradually shrank to the west of the sandy area, while fixed dunes soared and were concentrated in the middle of the sandy land. (3) From the soil moisture change, soil moisture at different underground depths showed an overall increasing trend, but the deep soil moisture was higher than the shallow, and spatial distribution varied greatly. (4) From the influencing factors, natural factors significantly influence greening stability, among which precipitation had a particularly profound impact, and interactions with other natural and social factors were higher explanatory. The paper aims to explore whether the ecological environment is developing in a good and orderly direction in the Mu Us Sandy Land, and the potential factors that cause its changes, to provide a theoretical basis for scientific governance in the Mu Us Sandy Land and other arid and semi-arid areas in the future. [ABSTRACT FROM AUTHOR]

Lanzhou City is located in the semi-arid region of northwest China, which experiences serious desertification. Moreover, the high intensity of land development, with the accelerated industrialization and urbanization, causes increasingly aggravated conflict between humans and the environment. Exploring the response of the ecological environment quality to the natural environment and anthropogenic activities is important to protect the sustainable development of urban economic construction and the environment. Based on the Google Earth Engine (GEE) platform, this paper constructed a modified Remote Sensing Ecological Index (MRSEI) model which could reflect the ecological environment quality by integrating the desertification index (DI) into the Remote Sensing Ecological index (RSEI) model. This paper explores the spatiotemporal variation in the environmental quality from 2000 to 2020 in Lanzhou, China, and analyzes the natural and anthropogenic factors affecting the environment quality in terms of temperature, precipitation, gross domestic product (GDP), land use, night lighting, and population. The results showed that the mean value of MRSEI ranged from 0.254 to 0.400. The area undergoing fast growth in ecological quality was in the northwestern part of Lanzhou, and the area of decrease was in the central part. Various factors have different degrees of influence on the ecosystem, with temperature, precipitation, and land use having a greater impact, and GDP and population having a limited impact. Precipitation and temperature showed a strong impact when interacting with other factors, demonstrating that precipitation and temperature were also key factors affecting MRSEI. Overall, climate change and the implementation of ecological restoration projects have led to an improvement in the quality of the ecological environment in Lanzhou. This study provides a reference for understanding the spatiotemporal changes in the ecological environment in semi-arid Lanzhou and is conducive to formulating proper protection strategies. [ABSTRACT FROM AUTHOR]

Atriplex canescens is widely cultivated as drought and salt-tolerant fodder in arid regions of Northwest China, which is used for photoremediation of degraded land and soil and water conservation. To explore the growth performance of A. canescens when exposed to drought and salt stress, seedlings were treated with a range of drought stress (WC1: 75 ± 3.6%, WC2: 49 ± 2.9% and WC3: 27 ± 2.5% of soil water content) and the corresponding drought stress with additional sodium salt supplementation (NaCl:Na2SO4 = 1:1 with the total concentration of Na+ set to 150 mM). The findings of this paper indicated that moderate sodium salt could stimulate the growth of A. canescens and effectively alleviate the deleterious impact of drought stress by increasing the turgor potential (ψt) and relative water content (RWC) and decreasing the leaf water osmotic potential (ψs). Furthermore, the photosynthetic capacity was improved and the negative effects of drought stress on photosystem II (PSII) were mitigated. The extra 150 mM sodium salt also markedly increased the contribution of Na+ to ψs and the contribution of betaine to ψs. In summary, these results indicate that A. canescens can adapt to drought stress by accumulating enough Na+ for osmotic adjustment (OA). Additionally, this paper is aimed to provide a fundamental basis for the utilization and cultivation of A. canescens as a favored pasture crop in the Qaidam basin, thus increasing the ecological and environmental benefits for arid regions worldwide. [ABSTRACT FROM AUTHOR]

Satellite-derived soil moisture fields received attention due to their large spatial coverage and spatial resolution that suits many applications. The sensors used vary from passive (e.g., LANDSAT-8) to active (e.g., SENTINEL-1) with varying accuracy problems. Passive sensing can only determine relative indices between pixels within a vegetation class and not the real value of moisture. Active sensing suffers from the sensitivity of its detecting behaviour to the level of moisture (anomalous backscatter). The above problems impose limitations on the application without frequent ground-based calibration. The paper investigates possible models to improve the estimation of soil moisture using the powers of the two sensors. In addition, a Hydrologic Surface Moisture indicator (HSM) is included as a third source of information. The paper tests modeling combinations of the three soil moisture predictors (Landsat-8, Sentinel-1, and HSM). The models are validated using in-situ measurements. The results showed that Landsat-8 data can be rescaled using HSM to provide the actual soil moisture in the soil. On the other side, it is possible to remove the anomaly from the Sentinel-1 backscatter using either Landsat-8 or HSM. The elimination of the above problems explained a significant portion of the differences between the two sensors. [ABSTRACT FROM AUTHOR]

Dry root rot (DRR) caused by Rhizoctonia bataticola [(Taub.) Butler] is an emerging disease of chickpea (Cicer arietinum L.) and a serious constraint to chickpea production in warm and arid regions. To identify the genomic regions conferring resistance to DRR, a total of 182 F9 derived Recombinant Inbred Lines (RILs) were developed from the cross between a susceptible line BG 212 and moderately resistant breeding line ICCV 08305. The parental lines and RILs were screened against Rb 6 isolate of R. bataticola using paper towel method under controlled environment at ICRISAT during 2016 and 2017. The RILs were genotyped with cost-effective SNP genotyping platform, Affymetrix® Axiom®CicerSNP array. As a result, a high-density genetic map with 13,110 SNP markers spanning 1224.11 cM with an average inter marker distance of 0.09 cM was developed. A single minor QTL ('qDRR-8') explaining 6.70% PVE with LOD scores 3.34 was identified on CaLG08 for DRR resistance which could be further explored for mining candidate genes and the linked SNP markers could be further validated for application in marker-assisted selection of DRR resistance in chickpea breeding programs. [ABSTRACT FROM AUTHOR]

In the quest for a sustainable farming system around the world, organic farming has emerged as the most promising alternative system that can offer solutions to the growing sustainability issues associated with the current input-intensive agriculture system. Organic farming is also becoming increasingly important due to a significant rise in the demand for organic food across the world. Realizing the importance of organic agriculture in the current Indian agricultural scenario, the Government of India has taken several initiatives to promote organic farming across the country. As a result, there has been a considerable increase in different dimensions of organic farming especially in India over the last decade. However, studies have found that organic farming practices in India are more suited to a few specific regions (such as rain-fed zones, low-productivity areas, hills, and arid zones) as compared to the other parts of the country. In this backdrop, this paper attempts to evaluate the state-wise progress of organic farming in India. To measure the inter-state variation in the performance of organic farming, a composite index has been constructed by taking into account four different performance dimensions viz. area covered under organic cultivation, volume of organic production, volume of organic export, and number of producers practicing organic farming. The result suggests a wide disparity in performances in respect of organic farming among the states in India. Interestingly, the states that have performed well in organic farming are found to have a higher level of organic carbon stock in their soil. This shows the influence of agroclimatic conditions on the organic cultivation practices as popularly postulated in the literature. [ABSTRACT FROM AUTHOR]

Rock glaciers are important hydrological reserves in arid and semi-arid regions. Their activity states can indicate the existence of permafrost. To help further explore the development mechanisms of rock glaciers in semi-arid and humid transition regions, this paper provides a detailed rock glacier inventory of the Guokalariju (also known as Goikarla Rigyu) area of the Tibetan Plateau (TP) using a manual visual interpretation of Google Earth Pro remote sensing imagery. We also estimated the water volume equivalent (WVEQ) in the study area for the first time. Approximately 5057 rock glaciers were identified, covering a total area of ∼404.69 km 2. Rock glaciers are unevenly distributed within the three sub-regions from west to east, with 80 % of them concentrated in the central region, where climatic and topographic conditions are most favorable. Under the same ground temperature conditions, increases in precipitation are conducive to rock glaciers forming at lower altitudes. Indeed, the lower limit of rock glaciers' mean altitude decreased eastward with increasing precipitation. Estimates of the water storage capacity of rock glaciers obtained by applying different methods varied considerably, but all showed the potential hydrological value of rock glaciers. The possible water storage in the subsurface ice of rock glacier permafrost was 1.32–3.60 km 3. The ratio between the amount of subsurface ice stored in rock glaciers and surface ice stored in local glaciers falls within the range of 1:2.32 to 1:1.26 , with an average ratio of 1:1.69. In the west region, where the climate is the driest, the water storage capacity of rock glaciers was estimated to be up to twice as large as that of the sub-region's glaciers. Changes in water resources and permafrost stability in the area where rock glaciers occur will have implications for regional water resource management, disaster prevention, and sustainable development strategies. [ABSTRACT FROM AUTHOR]

In recent years, solar-powered, passive adsorption-based air–water harvesting has shown tremendous potential in addressing freshwater shortages in arid regions. Although remarkable progress has been witnessed in unlocking the potential of new adsorbents in the laboratory, the productivity of freshwater is still limited by the slow adsorption kinetic, the large latent heat of water evaporation, and the efficiency of condensation. In this work, superhygroscopic porous gels consisting of titanium nitride, hydroxypropyl methylcellulose, and LiCl (THL) were developed and demonstrated to have a unique high water uptake of 1.18–6.43 gwatergsorbent−1 at 25 °C and 15%–90% relative humidity. To validate the feasibility of THL for moisture extraction, reasonable energy management of the water harvester was carried out, and the potential daytime outdoor water collection in summer and winter reached 3.82 and 2.98 lwater kgsorbent−1 day−1, respectively, at relative humidity of ∼60% and ∼30%. The implementation strategy proposed in this paper provides a reliable path for solar-driven AWH, confirming the adaptability and possibility of achieving high yield freshwater production in real scenarios of practical significance. [ABSTRACT FROM AUTHOR]

The remote villages in arid and semi-arid inland regions of Rajasthan state in India and many other countries are dependent on brackish groundwater for potable uses. Generally, community RO (Reverse Osmosis) plants are installed for brackish water treatment in rural agglomerations where the MLD (Minimal liquid discharge) scheme is followed which includes pre-treatment and pre-concentration technologies, that consumes relatively low energy than thermal technologies for ZLD (Zero liquid discharge). This paper discusses the application of hybrid processes involving MLD technologies such as IEX (Ion Exchange), NF (Nanofiltration), RO, FO (Forward Osmosis) and UF (Ultrafiltration). for brackish water treatment. The impact of feed water quality and operational parameters such as flux, feed flow rate and transmembrane pressure are discussed. Further, performance indicators such as salt rejection, recovery, energy consumption and scaling propensity are discussed to evaluate the feasibility of various configurations. The findings of this review indicate NF as impressive membrane technology for conjunction with IEX, RO and UF. Further, the use of FO or NF as a pre-treatment for RO has been found to reduce the scaling propensity of RO membranes; and the use of UF as a pre-treatment for NF has been found to reduce the propensity of organic fouling on NF membranes. Also, IEX as a pre-treatment can be coupled with low-pressure RO/NF to remove the scale-causing divalent ions and enhance recovery along with an option of reusing RO/NF reject water for regeneration of IEX column. [ABSTRACT FROM AUTHOR]

Continuous evapotranspiration (ET) data with high spatial resolution are crucial for water resources management in irrigated agricultural areas in arid regions. Many global ET products are available now but with a coarse spatial resolution. Spatial-temporal fusion methods, such as the spatial and temporal adaptive reflectance fusion model (STARFM), can help to downscale coarse spatial resolution ET products. In this paper, the STARFM model is improved by incorporating the temperature vegetation dryness index (TVDI) into the data fusion process, and we propose a spatial and temporal adaptive evapotranspiration downscaling method (STAEDM). The modified method STAEDM was applied to the 1 km SSEBOP ET product to derive a downscaled 30 m ET for irrigated agricultural fields of Northwest China. The STAEDM exhibits a significant improvement compared to the original STARFM method for downscaling SSEBOP ET on Landsat-unavailable dates, with an increase in the squared correlation coefficients (r2) from 0.68 to 0.77 and a decrease in the root mean square error (RMSE) from 10.28 mm/10 d to 8.48 mm/10 d. The ET based on the STAEDM additionally preserves more spatial details than STARFM for heterogeneous agricultural fields and can better capture the ET seasonal dynamics. The STAEDM ET can better capture the temporal variation of 10-day ET during the whole crop growing season than SSEBOP. [ABSTRACT FROM AUTHOR]

Accurately grasping the distribution and area of cotton for agricultural irrigation scheduling, intensive and efficient management of water resources, and yield estimation in arid and semiarid regions is of great significance. In this paper, taking the Xinjiang Shihezi oasis agriculture region as the study area, extracting the spectroscopic characterization (R, G, B, panchromatic), texture feature (entropy, mean, variance, contrast, homogeneity, angular second moment, correlation, and dissimilarity) and characteristics of vegetation index (normalized difference vegetation index/NDVI, ratio vegetation index/DVI, difference vegetation index/RVI) in the cotton flowering period before and after based on GF-6 image data, four models such as the random forests (RF) and deep learning approach (U-Net, DeepLabV3+ network, Deeplabv3+ model based on attention mechanism) were used to identify cotton and to compare their accuracies. The results show that the deep learning model is better than that of the random forest model. In all the deep learning models with three kinds of feature sets, the recognition accuracy and credibility of the DeepLabV3+ model based on the attention mechanism are the highest, the overall recognition accuracy of cotton is 98.23%, and the kappa coefficient is 96.11. Using the same Deeplabv3+ model based on an attention mechanism with different input feature sets (all features and only spectroscopic characterization), the identification accuracy of the former is much higher than that of the latter. GF-6 satellite image data in the field of crop type recognition has great application potential and prospects. [ABSTRACT FROM AUTHOR]

Biological soil crusts (biocrusts) are complex communities of micro‐ and macro‐organisms dwelling at the soil surface in dryland regions worldwide, which contribute to important ecological functions in these areas. Biocrusts may reach different developmental stages, associated to autogenic succession of specific phototrophic organisms. However, notwithstanding the large amount of existing literature, little is known regarding the relationship between biocrust stages of development and soil nutrient dynamics. In this opinion paper, we specifically focused on soil nitrogen, and compared the total nitrogen content and potential nitrogenase activity of different developmental types of biocrust (‐covered) soils. Based on published reports, we looked at a possible relationship between nitrogen content at the soil surface and biocrust development, discussing the potential mechanisms leading to the observed soil nitrogen content heterogeneity. The results showed that a higher nitrogen content remained associated to the presence of moss‐dominated biocrusts, and this biocrust morphotype was characterized by a lower potential nitrogenase activity compared to the cyanobacteria‐ and/or lichen‐dominated biocrusts. We hypothesized that these seemingly contradictory findings might be attributed to three potential mechanisms: nitrogen inheritance, nutrient retention and nutrient transfer, which we hereby examined one by one. Altogether, our opinion supports the theory of biocrust succession from incipient cyanobacteria‐dominated stages to more 'mature' stages dominated by mosses. We stress how the heterogeneous distribution of soil nitrogen, which is closely related with biocrust development and community types, eventually affects regional and even global nitrogen dynamic and storage. [ABSTRACT FROM AUTHOR]

This paper presents the results of a detailed review of the research literature on how nomadic pastoralists are being affected by climate change, how they are adapting, and challenges with using traditional knowledge in adaptation. It focuses on research that investigates local, and particularly traditional, knowledge of water, pasture, their variability, and livestock. This knowledge underpins nomadic livelihoods, so is a foundation for effective adaptation. Changes in the total amount of precipitation, and particularly shifts in its timing, and increases in the frequency and intensity of extreme events, are having the greatest impacts on herding livelihoods. Herders in drylands worldwide face common adaptation challenges: declining traditional water sources and pasture degradation. Herders' adaptation strategies fall into five major categories: movement to areas with better water and pasture, improving seasonal access to water, improving seasonal access to feed, shifts in herd composition, and livelihood diversification. Movement is central to nomads' adaptation, yet, as climate change takes hold, restrictions on movement are increasing for both socio-economic reasons and climate reasons. Many papers emphasised the importance of combining traditional knowledge and current science to guide adaptation decision-making at household, locality, and national levels. There is widespread concern about the decline in traditional knowledge. All the papers reviewed emphasised the need to support passing on traditional know-how. Herder women's know-how, in particular, is marginalised in the research literature, so their traditional knowledge should be a focus in further research. Herders' adaptations are mostly localised, incremental, and have a relatively short-term focus. As nomadic pastoralism moves further outside the range of historical experience, the possibility of more profound transformations looms. [ABSTRACT FROM AUTHOR]

The Caspian Sea level (CSL) is strongly sensitive to climate‐induced changes in its water balance components, especially evaporation from its surface as the main expenditure component of the Caspian Sea's (CS) water budget. Projecting evaporation and determining associated uncertainties obtained from such studies are critical for reliably predicting future CSL fluctuations and developing mitigation and adaptation strategies. This paper studies the projected changes in evaporation from the CS using 18 global climate models (GCMs) from the latest Coupled Model Intercomparison Project phase 6 (CMIP6) and Meyer's semi‐empirical formula. Future evaporation projections are constructed employing a weighted combination of the top‐ranked GCMs, including all ensemble members of selected individual models in a probabilistic framework. This study estimates late 21st century median evaporation of 945, 1016, 1105 and 1173 mm under the low‐emission, medium‐emission, medium‐to‐high emission and high‐emission scenarios, respectively. The weighted multimodel ensemble suggests CS's annual mean evaporation is projected to substantially increase by 3.9%, 13.2%, 20% and 27.9% under SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5, respectively, for the late 21st century against the reference period. According to the spatial distribution of evaporation, arid eastern regions of CS experience higher evaporation than semi‐arid western and southwestern temperate regions. Additionally, the northwestern continental regions experience the least evaporation over the CS. [ABSTRACT FROM AUTHOR]

Indigofera oblongifolia Forssk. locally known as 'Goilia or Jhil', is an important underutilized leguminous browse shrub for small ruminants in hot arid region of India and traditionally utilized for its medicinal value. Its irregular patchy distribution was observed in depression of rocky areas, bunds of farmer fields and along the depression on the road sides in Jaisalmer and Pali district during collection. Soil samples collected from Pali district have high level of pH and electrical conductivity as compared to Jaisalmer which indicates its suitability to saline areas. It exhibited good plant growth under Jodhpur conditions with respect to plant height (171.5 cm), number of branches (47.9) and canopy diameter (100–210 and 115–180 cm in north-south and east-west direction, respectively) after 12 months of planting in fields under protected condition. Morphological characterization showed the presence of high coefficient of variation (%) in the number of raceme per branch (27.3) followed by raceme length (22.9), pod length (21.0) and least in pod width (8.1). Phytochemical results revealed that leaves of I. oblongifolia contained considerable amounts of total phenols (31.44 mg g−1), flavonoids (29.73 mg g−1) and antioxidant capacity (6.26 FRU g−1) which make its suitability as a browse species to ruminants in rangelands. Along with these finding, its traditional knowledge and utilization are detailed in this paper as to hasten further research on its various aspects for its sustainable utilization in rangelands or in alternate land use systems in the Indian hot arid region. [ABSTRACT FROM AUTHOR]

The Tarim Basin is a large inland arid basin in the arid region of northwest China and has been experiencing significant "warming and wetting" since 1987. As a result, the purpose of this paper is to determine whether the climate transition phenomenon occurred in the Tarim Basin as well as the role of atmospheric circulation in this process. We use meteorological data and atmospheric circulation indexes to study the seasonal trends of climate change in this region from 1987 to 2020 to understand how they are affected by atmospheric circulation. The findings show that, from 1987 to 2020, the Tarim Basin experienced significant warming and wetting; with the exception of the winter scale, all other seasonal scales exhibited a clear warming and wetting trend. From the perspective of spatial distribution, most of the areas showed a significant warming trend, and the warming amplitude around the basin is greater than that in the central area of the basin. However, there are significant regional differences in precipitation change rates. Meanwhile, wavelet analysis shows that there is a significant oscillation period of 17–20 years between climate change and the atmospheric circulation index during 1987–2020. The correlation analysis shows that the Pacific decadal oscillation (PDO) and El Niño-Southern Oscillation (ENSO) are the main influencing factors of climate change in the Tarim Basin at different seasonal scales, while the teleconnection of the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) is low and the PDO dominates the summer and autumn temperature changes in the Tarim Basin. The research results of this paper show that, despite the warming and wetting trends since 1987 in the Tarim Basin, the climate type did not change. From 1987 to 2020, the main teleconnection factors of climate change in the Tarim Basin were PDO and ENSO. [ABSTRACT FROM AUTHOR]

This paper examines a feature-level fusion framework for detecting and mapping land degradation (LD) and enabling sustainable land management (SLM) in semi-arid areas using optical sensors and Synthetic Aperture Radar (SAR) satellite data. The objectives of this review were to (i) determine the trends and geographical location of land degradation mapping publications, (ii) to identify and report current challenges pertaining to mapping LD using multiscale remote sensing data, (iii) to recommend a way forward for monitoring LD using multiscale remote sensing data. The study reviewed 78 peer-reviewed research articles published over the past 24 years (1998–2022). Image fusion has the potential to be more useful in various remote sensing applications than individual sensor image data, making it more informative and valuable in the interpretation process. In addition, this review discusses the importance of SAR and optical image fusion, pixel-level techniques, applications, and major classes of quality metrics for objectively assessing fusion performance. The literature review alluded that the SAR and optical image fusion in the detection and mapping of land degradation and enabling sustainable land management has not been fully explored. Advanced techniques such as the fusion of SAR and optical satellite imageries need to be incorporated for the detection and mapping of LD, as well as the promotion of SLM in halting LD in South African drylands and around the world. We conclude that there is scope for further research on the fusion of SAR and optical images, as new micro-wave and optical sensors with higher resolution are introduced on a regular basis. The results of this review contribute to a better understanding of the applications of SAR and optical image fusion in future research in the severely degraded drylands of southern Africa. The fusion of SAR and optical data still remains an open challenge. The future of different remote sensing applications lies in this kind of fusion. Land degradation is one of the greatest challenges amongst the environmental problems in South Africa, causing a reduction in the capacity of the land to perform ecosystem functions and services that support society and development. Yet, in South Africa, there are no studies that have widely investigated the potential for a fusion of SAR and optical data to detect and map land degradation and SLM practices. This paper established a baseline for understanding the application of a fusion of SAR and optical data as rapid tools for mapping, monitoring, and evaluating LD, as well as the impacts of SLM practices in South Africa's degraded drylands. [ABSTRACT FROM AUTHOR]

Drylands are diverse and dynamic ecosystems that have been occupied by humans throughout the Holocene. Nonetheless, drylands are often conceived of as marginal, rare, and inimical to human livelihoods. This Special Issue interrogates the interactions between humans and arid and aridifying environments to investigate how drylands offer unique risks and opportunities to their resilient inhabitants. This article introduces the 11 environmental archeology papers and 1 discussion paper in this Special Issue, the proceedings of a 2021 virtual workshop on the topics of risk and resilience. Each contribution explores a different geographic and chronological context around the globe. We also introduce three subthemes of this Special Issue: "Multi-Scalar Analysis," "Abundance and Diversity," and "Cascading Risks." Collectively, a key strength of the case studies in this volume is the range of environmental archeology methods and datasets that they showcase. These authors draw out details within a multi-scalar understanding of risk and risk perception in the particular contexts in which they work. As we face compounding contemporary risks associated with the global impacts of a changing climate, it is more important than ever to recognize the range of human relationships with aridification, and the dynamic, localized socio-environmental histories of drylands. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to determine and evaluate the calibration curve for low-cost electronic sensors in soils from a reclaimed and degraded area in the Brazilian semiarid region. Design/methodology/approach: The probes were made, programmed and inserted in soil previously conditioned in polyethylene cylinders. The sets "cylinder + probe + soil" were subjected to saturation for a period of 24 h and, subsequently, gravitational drainage at room temperature and daily weighings were performed. When the set reached constant weight, the samples were taken to dry in an oven at 105°C to determine the dry mass and later, determine the gravimetric moisture and convert it into volumetric. The volumetric moistures obtained were related to measured frequency variations and the adjustments were analyzed by regression, which was subjected to analysis of variance (p = 0.05), and related by a third-degree polynomial equation whose quality of the fit was verified with coefficient of determination (R2). Findings: The obtained moistures were related to the estimated moistures and evaluated by the root-mean-square error and straight 1:1. The results demonstrate that the sensors are not accurate for moistures in saturation, but representative and statistically acceptable results for moistures up to field capacity. Originality/value: This paper has not been published before in its current, or similar form. [ABSTRACT FROM AUTHOR]

The Caatinga biome is presented in the vegetation where the Brazilian semiarid region predominates, with a great variety of native species, and facheiro is one of the most important species because of its wide range in the semiarid region in northeastern Brazil. Therefore, the knowledge of the germinative behavior of the Caatinga species is essential to subsidize conservationist actions in this ecosystem. This study aimed to determine the effect of temperature and substrate on the germination and vigor of facheiro's seeds. These seeds were obtained from ripe fruits collected in three localities of the Agreste of Paraíba: Arara, Bananeiras, and Boa Vista. After extraction, the seeds were placed to dry on paper for one week in a laboratory environment. Subsequently, the experiment was started by testing four temperatures: 20, 25, 30, and 20-30 °C. The germination test was conducted with four replications of 50 seeds distributed in "gerbox" boxes and placed in bio-oxygen demand (BOD) chambers using as a substrate the germitest paper, with a photoperiod of 12 hours. The statistical design was randomized in a 3 × 4 factorial arrangement (3 localities and 4 temperatures). A significant effect was observed for populations and substrates. The best substrate for germination was the germitest, while the substrate vermiculite presented a good performance, and the substrate soil presented low germination. Therefore, seeds presented the best vigor in the germitest paper, mainly with a temperature of 25 °C where the best performance for all localities was found. The vigor of seeds in the localities of Bananeiras and Boa Vista, temperatures of 25, 30, and 20-30 °C, and substrate germitest paper provided the highest vigor. The germitest substrate is the recommended substrate for the germination of the species, maximizing its physiological potential and being able to accelerate conservation projects for the species. [ABSTRACT FROM AUTHOR]

The rapidly growing world population and the accompanying increase in concrete production to meet building and infrastructure needs have led to significant increase in potable water consumption, which resulted in several environmental problems. This paper investigates the feasibility of replacing potable water with highly mineralized treated wastewater in concrete mixing in order to make concrete production more eco-friendly in an arid region. Concrete specimens were prepared using saline treated wastewater (saline-TWW) as mixing water and compared to those mixed with distilled water (DW) and with the performance requirements given by the mixing water quality standards. The results revealed that the concrete mixes produced using saline-TWW exhibited higher early strength and a similar long-term strength than the control mix produced using DW. It was also found that the use of saline-TWW increased the setting times of cement paste but had no remarkable effect on the workability of fresh concrete mixture. Furthermore, the microstructural characteristics of the hardened concrete were assessed by water-permeability test, SEM image analysis, and X-ray diffraction tests. The results revealed that saline-TWW concrete exhibited a more compact microstructure and smaller pore sizes than their counterparts of DW, which means an improvement in the durability of saline-TWW concrete. Moreover, an electrochemical test was conducted to estimate the extent of corrosion of the steel embedded in reinforced mortar specimens prepared using saline-TWW and DW. The electrochemical test results showed that the use of 100% saline-TWW as mixing water of concrete resulted in a high corrosion rate of the embedded steel. [ABSTRACT FROM AUTHOR]

Drought seriously endangers the development of agro‐pastoral ecotone in arid and semi‐arid regions. However, drought evolution characteristics of semi‐arid sandy grassland and its drivers are not well understood in the complex climate change context. Thus, in this paper, the revised standardized precipitation evaporation indices on one‐month (SPEI‐1) and growing‐season (SPEI‐6) scale, flash drought and dry spells (DS) were calculated as drought indicators, and the temporal variabilities and meteorological drivers of drought in Horqin Sandy Land during the growing period (April–September) from 2007 to 2021 were studied. The results showed that SPEI‐1 and SPEI‐6 exhibited negative trends and periodic change. This drought aggravation was manifested in increased grades and numbers of drought months. Flash droughts can occur every month during the growing season. And its occurrence was not only positively correlated with all drought events in frequency but also synchronized in time. The increased number of DS showed an asymmetrical shift towards 7‐day‐and‐longer DS. SPEI sensitivity to precipitation (P) was noticeably higher than to atmospheric evapotranspiration demand (AED) at both monthly and growing season scales. SPEI sensitivity to AED was modulated by P amounts, which was higher during low P period. Apart from the amounts of P and AED, their temporal variability also strongly determined how they affect the drought severity. P was also the main driver for flash drought and long DS, but AED with larger amount and higher variability is the reason for their aggravation. Our results demonstrate the complexity of drought intensification in semi‐arid sandy grasslands and highlight the important role of AED anomalies in it. [ABSTRACT FROM AUTHOR]

Commercialization of agriculture in patriarchal rural Pakistan has transformed women's critical roles in pulses production and has re-organised the gendered division of labour in what used to be widely known as a 'women's crop'. Pulses are grown in the marginal and arid lands by small-holder farming families where women care for the crops as an extension of their other caring roles for the households. Based on an ethnographic study of women pulse farmers in Pakistan, this paper examines the complex relations of women with the crop and the challenges they face. It argues that the restoration of a caring relationship between women and the pulses crop through a re-animation of multispecies contact zones may be a way to ensure everyday food provisioning in rural Punjab, maintain traditional socio-cultural and ecological relationships, understand the masculinity that has pushed women to the margins, and value women's contribution, experience, and knowledge in agriculture. [ABSTRACT FROM AUTHOR]

Using the Gravity Recovery and Climate Experiment (GRACE) satellite to monitor groundwater storage (GWS) anomalies (GWSAs) at the local scale is difficult due to the low spatial resolution of GRACE. Many attempts have been made to downscale GRACE-based GWSAs to a finer resolution using statistical downscaling approaches. However, the time-lag effect of GWSAs relative to environmental variables and optimal model parameters is always ignored, making it challenging to achieve good spatial downscaling, especially for arid regions with longer groundwater infiltration paths. In this paper, we present a novel spatial downscaling method for constructing GRACE-based 1 km-resolution GWSAs by using the back propagation neural network (BPNN) and considering the time-lag effect and the number of hidden neurons in the model. The method was validated in Alxa League, China. The results show that a good simulation performance was achieved by adopting varying lag times (from 0 to 4 months) for the environmental variables and 14 hidden neurons for all the networks, with a mean correlation coefficient (CC) of 0.81 and a mean root-mean-square error (RMSE) of 0.70 cm for each month from April 2002 to December 2020. The downscaled GWSAs were highly consistent with the original data in terms of long-term temporal variations (the decline rate of the GWSAs was about −0.40 ± 0.01 cm/year) and spatial distribution. This study provides a feasible approach for downscaling GRACE data to 1 km resolution in arid regions, thereby assisting with the sustainable management and conservation of groundwater resources at different scales. [ABSTRACT FROM AUTHOR]

The paper compares different approaches to the reconstruction of environmental conditions from rodent fossil complexes, namely, the bioclimatic method and the method of reconstructing soil and plant conditions considering voles. For the reconstruction, data from ten localities in Western Siberia dated to the second half of the Middle Pleistocene were analyzed. The bioclimatic method allowed us to reconstruct the arid climatic zone in the south of Western Siberia (the Pre-Altai Plain and the Middle Irtysh) and the moderately cold and arctic climate for the localities situated northwards. The method of reconstruction of soil and vegetation conditions showed the predominance of xerophytic plant communities for the southern localities and mesophytic, mesohygrophytic, and hygrophytic for the northern ones. As additional indicators of environmental conditions, specialized species were proposed: subterranean animals (Siberian zokor and northern mole voles) and briophages (West Siberian lemming). [ABSTRACT FROM AUTHOR]

Arthropods play an essential role in steppe ecosystems. However, studies testing the overall response of terrestrial arthropods to overgrazing are scarce. The problem is particularly worrisome in Central Asia, while, to date, only a very few broader studies have been conducted in this region. We investigated how epigeic terrestrial arthropod assemblages respond to different livestock grazing pressure in two ecozones in SE Mongolia by examining their structure using pitfall traps. We also assessed which groups can be utilised as the most efficient indicators of grazing intensity. Our analyses demonstrated that the habitat type, grazing intensity, and the interaction of these variables had a significant effect on the overall species composition and abundance. However, the grazing intensity caused different changes in the composition of arthropod communities in both studied ecozones. Contrary to the semi-desert, in the steppe habitat, the grazing had the strongest impact in the moderately grazed site. It is most likely because steppe-dwelling species are more sensitive to loss of plant biomass and changes in habitat structure. We also found that the most representative species within and from different groups can react differently to changing grazing intensities, indicating with their presence the characteristics of the respective habitat. Such differences should also be considered when elaborating the management plan of conserved species but also when applying grazing management in different habitat types. Our survey is one of the most comprehensive in Central Asia and should help implement further, more targeted studies in the corresponding habitats. In meadow steppes and other arid habitats, livestock grazing is one of the most severe causes of desertification and leads to an overall decline in vegetation cover, plant species richness and aboveground biomass, and, consequently, most often negatively affects arthropod diversity. Although the impact of grazing on arthropod diversity has already been the subject of numerous studies, most of them were focused only on a single or small number of arthropods and were conducted outside Central Asia (e.g., there is only one paper dealing with analyses of several arthropod groups conducted in Mongolia, where over 40% of the human population depends on pastoral livestock production and up to 90% of its territory belongs to various arid areas). We hypothesise that the overall diversity of different arthropod groups will change according to the grazing intensities, and these changes will depend on the habitat type and will differ between arthropod groups. Our analyses demonstrated that the habitat type, grazing intensity, and the interaction of these two variables significantly impacted the overall species composition and abundance. Our results highlight that the different terrestrial arthropod groups and representative species of the most abundant groups can react differently to changes in grazing intensity, and such differences should be considered when elaborating the management plan of conserved species and when applying grazing management in different habitat types. Our results also highlight that the species diversity alone cannot indicate the changes in species composition along the grazing intensity, and one should also consider the individual needs of specific species while investigating the impact of grazing on arid habitats. [ABSTRACT FROM AUTHOR]

Meeting current needs without compromising future generations' ability to meet theirs is the only path toward achieving environmental sustainability. As the most valuable natural resource, soil faces global, regional, and local challenges, from quality degradation to mass losses brought on by salinization. These issues affect agricultural productivity and ecological balance, undermining sustainability and food security. Therefore, timely monitoring and accurate mapping of salinization processes are crucial, especially in semi-arid and arid regions where climate variability impacts have already reached alarming levels. Salt-affected soil mapping has enormous potential thanks to recent progress in remote sensing. This paper comprehensively reviews the potential of remote sensing to assess soil salinization. The review demonstrates that large-scale soil salinity estimation based on remote sensing tools remains a significant challenge, primarily due to data resolution and acquisition costs. Fundamental trade-offs constrain practical remote sensing applications in salinization mapping between data resolution, spatial and temporal coverage, acquisition costs, and high accuracy expectations. This article provides an overview of research work related to soil salinization mapping and monitoring using remote sensing. By synthesizing recent research and highlighting areas where further investigation is needed, this review helps to steer future efforts, provides insight for decision-making on environmental sustainability and soil resource management, and promotes interdisciplinary collaboration. [ABSTRACT FROM AUTHOR]