Search

Architecture can be very influential in enabling health and wellbeing in the residential built environment. In arid regions, health-supportive design would consider major environmental hazards, such as heat and dust, as well as social and cultural factors that influence household size and composition. Under current and projected conditions, the effects of climate change will increase, presenting opportunities and challenges to architects to demonstrate and deliver best practice in climate-appropriate and culturally appropriate housing design. This paper brings together a multidisciplinary team of researchers to identify the current and future needs for tropical semi-arid zone design with a focus on Indigenous communities in northern Central Australia. In a narrative review of the literature and exploratory fieldwork, current and projected impacts of climate change on housing, health, energy systems and behavioural practices are explored in a holistic way. Our findings demonstrate the growing awareness of climate-related issues for remote Indigenous housing but also the lack of place-based studies that might inform adaptation strategies. Overwhelmingly, there is limited understanding of local lived experiences that may be highly significant for developing resilience in a changing climate. Consideration of the beliefs, values and practices of Indigenous people will be integral to design solutions. [ABSTRACT FROM AUTHOR]

Based on an examination of the outlooks and practices held by past and present Negev desert viticulturists vis-à-vis their environs, the article offers insights into how the wine sector can bolster its response to current climate adversity. The discussion fuses bio-archaeological research on the evolution of ancient grape cultivars (Vitis vinifera) in the Negev with an extensive ethnographic inquiry into the ongoing wine revival in arid southern Israel. Ancient DNA analysis of relic grape material led to the identification of an historical Negev viticulture lineage. The findings provide a temporal framework for contextualizing tphe interrelated anthropological data obtained on contemporary dryland viticulturalists and wine makers in Israel. Since the climate in the Negev has remained relatively stable over the last several millennia, it makes for an apt point of comparison via which to gauge the outlooks held by both historical and modern viticulturalists towards the local landscape. We suggest enacting two evidence-based adjustments to counter ecological instabilities: the holistic revival and applied renewal of historical cultivars, and the attendant agronomic routines that sustained their growth in the past. A more nuanced understanding of the unique terroir arid viticulturalists are operating in, together with the learned incorporation of the hardy genetic traits of age-old cultivars, will benefit wine growers to attune their responses to the array of challenges wrought by climate change on the wine industry. It is therefore our hope that the research methodologies and heritage-oriented horticultural perspectives we present in this paper will prove beneficial to broader wine growing regions (pax-Mediterranean and beyond) who are fortunate to likewise possess their own rich viticultural histories and lineages. [ABSTRACT FROM AUTHOR]

Soil salinity assessment methods based on remote sensing data are a common topic of scientific research. However, the developed methods, as a rule, estimate relatively small areas of the land surface at certain moments of the season, tied to the timing of ground surveys. Considerable variability of weather conditions and the state of the earth surface makes it difficult to assess the salinity level with the help of remote sensing data and to verify it within a year. At the same time, the assessment of salinity on the basis of multiyear data allows reducing the level of seasonal fluctuations to a considerable extent and revealing the statistically stable characteristics of cultivated areas of land surface. Such an approach allows, in our opinion, the processes of mapping the salinity of large areas of cultivated lands to be automated considerably. The authors propose an approach to assess the salinization of cultivated and non-cultivated soils of arid zones on the basis of long-term averaged values of vegetation indices and salinity indices. This approach allows revealing the consistent relationships between the characteristics of spectral indices and salinization parameters. Based on this approach, this paper presents a mapping method including the use of multiyear data and machine learning algorithms to classify soil salinity levels in one of the regions of South Kazakhstan. Verification of the method was carried out by comparing the obtained salinity assessment with the expert data and the results of laboratory tests of soil samples. The percentage of "gross" errors of the method, in other words, errors when the predicted salinity class differs by more than one position compared to the actual one, is 22–28% (accuracy is 0.78–0.72). The obtained results allow recommending the developed method for the assessment of long-term trends of secondary salinization of irrigated arable land in arid areas. [ABSTRACT FROM AUTHOR]

Coupling solar-induced chlorophyll fluorescence (SIF) with gross primary productivity (GPP) for ecological function integration research presents numerous uncertainties, especially in ecologically fragile and climate-sensitive arid regions. Therefore, evaluating the suitability of SIF data for estimating GPP and the feasibility of improving its accuracy in the northern region of Xinjiang is of profound significance for revealing the spatial distribution patterns of GPP and the strong coupling relationship between GPP and SIF in arid regions, achieving the goal of "carbon neutrality" in arid regions. This study is based on multisource SIF satellite data and GPP observation data from sites in three typical ecosystems (cultivated and farmlands, pasture grasslands, and desert vegetation). Two precision improvement methods (canopy and linear) are used to couple multiple indicators to determine the suitability of multisource SIF data for GPP estimation and the operability of accuracy improvement methods in arid regions reveal the spatial characteristics of SIF (GPP). The results indicate the following. (1) The interannual variation of GPP shows an inverted "U" shape, with peaks values in June and July. The cultivated and farmland areas have the highest peak value among the sites (0.35 gC/m2/month). (2) The overall suitability ranking of multisource SIF satellite products for GPP estimation in arid regions is RTSIF > CSIF > SIF_OCO2_005 > GOSIF. RTSIF shows better suitability in the pasture grassland and cultivated and farmland areas (R2 values of 0.85 and 0.84, respectively). (3) The canopy method is suitable for areas with a high leaf area proportion (R2 improvement range: 0.05–0.06), while the linear method is applicable across different surface types (R2 improvement range: 0.01–0.13). However, the improvement effect of the linear method is relatively weaker in areas with high vegetation cover. (4) Combining land use data, the overall improvement of SIF (GPP) is approximately 0.11%, and the peak values of its are mainly distributed in the northern and southern slopes of the Tianshan Mountains, while the low values are primarily found in the Gurbantunggut Desert. The annual mean value of SIF (GPP) is about 0.13 mW/m2/nm/sr. This paper elucidates the applicability of SIF for GPP estimation and the feasibility of improving its accuracy, laying the theoretical foundation for the spatiotemporal coupling study of GPP and SIF in an arid region, and providing practical evidence for achieving carbon neutrality goals. [ABSTRACT FROM AUTHOR]

This document discusses the challenges faced by plants in arid and semi-arid regions due to harsh environmental conditions such as limited rainfall, high temperatures, and poor soil nutrition. The document highlights the importance of understanding plant adaptation strategies to extreme environments in order to protect and manage local vegetation and ecosystems. The document presents research papers that cover various aspects of plant adaptation in arid regions, including water uptake mechanisms, physiological and biochemical adaptations, plant-soil microbial interactions, and ecosystem services. The research findings provide insights into how plants in arid regions adapt to environmental changes and maintain ecological balance. However, further research is needed to fully understand the processes and mechanisms of plant adaptation in extreme environments. [Extracted from the article]

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 combination of seasonal shutdowns, water conveyance, cold, and drought can easily lead to the deterioration of the anti-seepage system and loess foundation of the canal, which contributes to the destruction of the slope. To reveal the failure mechanism of the collapsible loess canal slope, this paper is based on the results of laboratory tests and adopts numerical simulations to analyze the stability of the canal slope under different conditions. The results show that the shear strength indexes and elastic modulus E of loess decrease following an exponential pattern with the increase in wetting-drying and freezing-thawing (WD-FT) cycles. The height of the seepage overflow point yields little effect on the water level behind the impermeable membrane, whereas the height of the water level has a significant effect. In the operation period, the slope under any working conditions is in a relatively stable state. However, the slope with a water level of 4.5 m behind the impermeable membrane tends to be unstable after three WD-FT cycles during the shutdown period. By replacing the surface-degraded loess with sand gravel and picking a depth of 0.9–1.2 m, the slope will maintain a long-term stable state. [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]

Copyright of Pixo: Revista de Arquitetura Cidade e Contemporaneidade is the property of Pixo Revista de Arquitetura Cidade e Contemporaneidade and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Facultad Nacional de Agronomía Medellín is the property of Universidad Nacional de Colombia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purpose of this study was to develop analytical tools to find the effectiveness of using aerosols to mitigate the urban heat island effect. Specifically, mineral calcite would be placed in a plume over cities to reflect solar radiation. A secondary goal is to compare the relative efficiencies of releasing the particles from tower heights or from aircraft heights. The aim is to reduce daytime temperatures at the surface. The method was to use a one-dimensional model or a single-column model to predict temperatures and weather conditions at all altitudes over a period of one month. The SCAM6 code was altered to incorporate the new capabilities for introduced aerosols. The pre-existing code considered only windblown dust, so the code was enhanced to handle aerosols that were intentionally produced. The key findings are that calcite as an aerosol does affect the weather. The models predict that in humid regions, calcite is less effective because it interacts with water clouds. In arid regions, calcite should be more effective since there are fewer water clouds to interact with. The result is that it is possible to predict reductions in air temperatures if solar insolation can be reduced. It was shown that temperatures can be reduced by 4 °C in arid regions. The conclusions are that calcite aerosol should be effective at mitigating urban heat islands. However, further work is needed related to economic, health, and ecological concerns. [ABSTRACT FROM AUTHOR]

Droughts and climate change are causing severe and persistent dust storms in the arid and hot regions. The potential existence of significant relationships between the Oceanic Niño Index (ONI), Indian Ocean Dipole (IOD), and the MERRA-2 dust column mass density data are thus investigated in the State of Kuwait during 1990–2021 as a study case in the hot and arid regions. The findings show that the correlation starts from ONI-DJF (December–January-February) with the Pearson test value of -0.36 and increasing to a value of -0.55 on ONI-AMJ (April-May-June), the same results were obtained when applying the Spearman correlation test. The correlation exists between the July dust column mass density and IOD-January with a value of -0.484 and − 0.544 over Pearson and ' 'Spearman's test, respectively, all estimated p-values are lower than 0.05. The results of the One-Way ANOVA show that the output is pretty straightforward and statistically significant at p > 0.05, which was confirmed by the nonparametric Kruskal–Walli's test and Mann-Whitney Test. This considerable correlation means that active dust storms are linked with La Niña, while light dust storms occur during the El Niño event. A positive correlation occurs between precipitation and ONI - SON (September-October-November), while a negative correlation is found between precipitation and IOD-July. Our preliminary findings in this paper indicate that an appearance of -0.7°C in ONI-DJF could serve as a definitive marker of the La Nina phase and an indicator for at-risk communities to prepare for the expected activity dust storm. [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]

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]

Water scarcity is a global problem that particularly affects islands located in arid regions or regions with limited water resources. This issue has prompted the development of non-conventional water sources such as fossil fuel-powered desalination systems. Concern about the high energy and environmental costs associated with this type of facility has created the ideal framework for the proliferation of desalination projects powered by renewable energies, especially wind energy due to the multiple advantages it offers. This article provides a bibliometric analysis to identify the advances made in wind-powered desalination on islands. While many studies explore wind-powered desalination, none compile references specific to islands. This paper analyses islands' desalination needs and showcases wind-powered systems, exploring their types and uses. Firstly, the most relevant international scientific journals are identified to allow the subsequent selection and quantitative and qualitative analysis of articles directly dealing with wind-powered desalination systems. A total of 2344 articles obtained from the Scopus database were analyzed, of which 144 including 181 case studies were selected. Among the results of this study, an increasing year-on-year trend is observed in the number of published studies tackling wind-powered desalination. Finally, this paper presents a series of maps showing the most relevant facilities, projects, and data in this field, and provides an overview of the lessons learned in the decarbonization of desalination. [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]

Climatic events and other natural-related disasters experienced in the arid and semi-arid lands of northern Kenya negatively affect the pastoral livelihoods of the communities. Addressing vulnerability to climate shocks among pastoral communities of Kenya's Arid and Semi-lands presents a persistent challenge. Cash transfer programmes have increasingly grown as one mode of building household resilience. Understanding the role of cash transfer interventions on household resilience to climate shocks is key to policy programming. This paper aimed at determining the effects of cash transfers on household resilience to climate shocks. The paper evaluated the Hunger Safety Net Program, which is one of the largest unconditional cash transfer programs in Kenya. The Hunger Safety Net Program targeted poor people in northern Kenya including the counties of Turkana, Wajir, Marsabit, and Mandera. To establish the impact the paper compares households which received cash transfers with those that did not receive transfers. The panel fixed effects model was used to determine the effects of cash transfers on household resilience. The results indicate that cash transfers have positive significant effects on household resilience to climate shocks. [ABSTRACT FROM AUTHOR]

Drylands are vast and face threats from climate change and human activities. Traditional reviews cannot capture interdisciplinary knowledge, but bibliometric analysis provides valuable insights. Our study conducted bibliometric research of scientific production on climate change and land degradation in drylands using remote sensing. We examined 1527 Scopus-indexed publications to identify geographic and thematic hotspots, extracting leading authors, journals, and institutions. China leads in publications, followed by the US, Germany, and Australia. The US has the highest citation count. Collaboration networks involve the US, China, and European countries. There has been an exponential increase in remote sensing of land degradation in drylands (RSLDD) publications since 2011. Key journals include "International Journal of Remote Sensing" and "Remote Sensing of Environment". The analysis highlights the growing interest in the field, driven by Australia, the US, and China. Key areas of study are vegetation dynamics and land use change. Future perspectives for this scientific field involve promoting collaboration and exploring emerging technologies for comprehensive land degradation and desertification research. [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]

Bioclimatic architecture is a sustainable design approach that aims to create buildings that put local climate characteristics into consideration and utilize the natural environment to achieve thermal comfort and reduce energy consumption. Among the various strategies used in bioclimatic architecture, natural ventilation stands out as a cost-effective and eco-friendly method that allows for the flow of air through buildings to provide cooling and improve indoor air quality without relying on mechanical systems. With the growing concerns surrounding climate change and sustainable development, the use of natural ventilation techniques is becoming increasingly vital in buildings design. This paper investigates the importance of natural ventilation as one of the bioclimatic architecture strategies for sustainable building design in hot-arid regions characterized by extreme weather conditions, by providing an overview of the various natural ventilation strategies, including singlesided, double-sided, wind-induced, and stack ventilation and identifies the key factors affecting air movement to enhance thermal comfort and indoor air quality inside spaces. The research findings reveal a set of design guidelines that can be implemented to optimize natural ventilation in hot-arid regions. These guidelines cover building orientation, form, vegetation, and the design of openings and natural ventilation strategies that are most suitable for this climate. [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]

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]

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]

Snowmelt floods are highly hazardous meteorological disasters that can potentially threaten human lives and property. Hence, snowmelt susceptibility mapping (SSM) plays an important role in flood prevention systems and aids emergency responders and flood risk managers. In this paper, a method of identifying snowmelt flood hazards is proposed, and a large‐scale snowmelt flood hazard zonation scheme based on historical recordings and multisource remote sensing data is established. To assess the quality of our approach, the proposed model was tested in the cold and arid region of Xinjiang, China. Overall, 140 historical snowmelt flood events and 27 explanatory factors were selected to construct a geospatial dataset for SSM of the contemporary period. GridSearchCV was used to comprehensively search the candidate parameters from the grid of given parameters obtained with the random forest (RF) algorithm. Then, the geospatial dataset was divided into two subsets: 70% for training and 30% for testing. Next, SSM results were obtained with the RF algorithm using optimized parameters. The results indicate that our optimized RF classifier performs well for the task of SSM, with a high AUC value (0.975) for the test dataset. The validation and analysis suggest that the proposed method can efficiently identify snowmelt flood hazards in undersampled arid areas at a regional scale. [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]

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]

Floods destroy crop production; nevertheless, the extent of their impact on farmers' livelihoods in developing countries has been poorly investigated. This paper contributes to the growing evidence-based assessment of the impacts of shocks on communities. It assessed the post-disaster livelihood of farmers affected by the 2012 flooding in the semi-arid zone of Benin. To this end, a survey was conducted on 228 farmers in two municipalities of the flood-prone part of the semi-arid zone of Benin (Malanville, Karimama). Information on the well-being of households was collected using semi-structured interviews. Data were analyzed using income and consumption approaches focusing on poverty and on subjective assessment using happiness approach. Additionally, a probit model was used for a poverty assessment. The survey revealed that flooded farmers were amongst the poorest in the study system. Seven variables determined poverty in this study: household size, location, the percentage of the farm size that was flooded, fishing, the farmer's gender, farm size, and "holding a secondary activity". Regarding happiness, 99% of the flooded farmers were unhappier after the flood in 2012. The results clearly show that being subjected to floods increases the incidence of poverty. The capacity of flood risk management and governance should be strengthened in the study system. [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 the process of agricultural development in arid and semi-arid areas, the carbon fixation capacity of vegetation can be affected to different degrees, but research on its driving factors is lacking. Consequently, this paper focuses on the Weiku Oasis in Xinjiang as its research area, in which the carbon fixation capacity of vegetation is estimated with the chemical equation of a photochemical reaction, using methods such as linear system models and Geodetector to analyze the relationship between cropland expansion characteristics and the carbon fixation capacity of vegetation from 1990 to 2020. The influence of land-use changes on the space differentiation of carbon fixation was elucidated through a time series relationship, and the synergistic effects of nine influencing factors on the carbon fixation capacity during the process of vegetation changes were discussed. The results were as follows: (1) In the process of agricultural development, the proportions of cultivated land area and spatial agglomeration had significant negative correlations with carbon sequestration, and the significance was rising, but the effect of cultivated land area proportion was more significant. (2) Through temporal sequential cooperativity analysis, when other land-use types were converted into cultivated land, the carbon fixation capacity of vegetation suddenly and significantly decreased in the initial year of the transformation, but the effect of cultivated land reclamation on the carbon fixation capacity of vegetation did not have a significant time lag. Moreover, after a certain period of time, cultivated land can gradually recover part of its lost carbon fixation capacity. (3) Among the nine driving factors, potential evapotranspiration is the most prominent in explaining the carbon fixation capacity of vegetation. This single-factor pairwise interaction presents the relationship between bivariate enhancement and nonlinear enhancement. When terrain factors interact with other factors, the enhancement effect of the influence on the carbon fixation capacity of vegetation has an obvious promotion effect. However, the change in the carbon fixation capacity of vegetation is more significantly influenced by potential evapotranspiration and the interaction between the normalized difference vegetation index (NDVI) and other factors. This research is helpful to understanding the basic theories related to the change in the carbon fixation capacity of vegetation during the process of agricultural development in arid and semi-arid areas, as well as providing theoretical reference for ecological environment construction and sustainable development. [ABSTRACT FROM AUTHOR]

This paper analyzes spatial and temporal changes of aridity in Argentina (1961–2022). The aridity degree, using Climatic Research Unit (CRU) monthly data, was defined through six climate types classified by De Martonne Aridity Index (DMI). Argentina presents a very arid, arid and semiarid region that extends from Puna to Patagonia, alongside two humid and very humid regions: one located in the Chaco-Pampas Plains and Mesopotamia, and another in the Patagonian Andes. Between these regions, there are subhumid areas with marked aridity variations. These structures persist over time, but advances or setbacks were observed in their bordering areas, with significant changes in the Andes (leading to more arid conditions) and the southwestern Pampas Plains (leading to more humid conditions) during the historical period. The contribution of temperature and precipitation changes to these DMI changes was quantified, indicating that precipitation modulated the DMI spatial changes, while temperature intensified or weakened the change magnitudes. The extension variations of the arid and semiarid regions in Argentina were related to three climate variability modes (El Niño – Southern Oscillation [ENSO], Pacific Decadal Oscillation [PDO] and South Atlantic Ocean Dipole [SAOD]). Significant correlations were found with PDO (r < 0) and SAOD (r > 0), which indicate that an increase in the area occupied by arid and semiarid climates are associated with PDO negative phase or SAOD positive phase. Moreover, when these phases occur simultaneously, the expansion of arid and semiarid regions is larger than under the action of an individual forcing. [ABSTRACT FROM AUTHOR]

The land in the South Tasikmalaya Regency is dominated by dry land with a steep and hilly land contour. In addition, the area has a shallow soil solum, so it has a high potential for erosion and landslides. Therefore, it is necessary to innovate an integrated cultivation system that is economically feasible, but still maintains environmental sustainability. In this research, the aim is to formulate a model for the development of integrated plantation polyculture farming (IPPF) for the welfare of farmers. The method in this study uses a mixed method design. The location of the research carried out is in the Tasikmalaya Regency. The data used are the results of interviews and questionnaires to 250 IPPF farmers. The data used were obtained by multistage cluster random sampling. The sustainable IPPF development model was analysed using Structural Equation Modelling (SEM). This analysis is used to determine the various potential capital factors for agricultural development on the sustainable development of the IPPF and farmers' welfare. The results of the study show that the potential development capital [natural resources (SDA) capital, economic capital, socio-cultural capital, physical capital, and multifunctional IPPF], jointly or partially affect the IPPF sustainability. Human resource capital has no effect on the sustainable IPPF development, while the sustainable IPPF development affects the farmers' welfare levels, and the potential agricultural development capital and its multifunctionality affect the sustainable IPPF development and farmers' welfare. The IPPF development model that improves the welfare of farmers is carried out through the development of specific local superior commodities, increasing the added value and cooperation, developing access to credit, regenerating farmers, sustainable assistance and infrastructure improvements. The results of this study are expected to be a reference for the government in improving IPPF sustainability to achieve the welfare of its farmers. Apart from that, the model that has been developed can make a contribution to science in the form of a comprehensive analysis of the factors that influence the sustainability of IPPF. [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]

Photovoltaic systems (PV) have been extensively used worldwide as a reliable and effective renewable energy resource due to their environmental and economic merits. However, PV systems are prone to several environmental and weather conditions that impact their performance. Amongst these conditions is dust accumulation, which has a significant adversative impact on the solar cells' performance, especially in hot and arid regions. This study provides a comprehensive review of 278 articles focused on the impact of dust on PV panels' performance along with other associated environmental factors, such as temperature, humidity, and wind speed. The review highlights the importance of modelling dust accumulation along with other ecological factors due to their interactive nature, and the differences between cleaning techniques and schedules effectiveness. Moreover, the study provides a review of statistical and artificial intelligence models used to predict PV performance and its prediction accuracies in terms of data size and complexity. Finally, the study draws attention to several research gaps that warrant further investigation. Among these gaps is the need for proper dynamic optimisation models for cleaning schedules and a more advanced machine and deep learning models to predict dust accumulation while considering environmental and ageing factors. [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]

Simple Summary: Acute hepatitis, which is a rising public health issue globally, is mostly caused by the hepatitis E virus (HEV). There is a potential risk of camel-borne zoonotic HEV infection in the desert regions of the Middle East and Africa, where camels frequently interact with human populations and camel-derived food products constitute a component of the food chain. To better understand the current state of this subject, the current work's objective is to provide a scientific review of the detection of HEV genotypes seven and eight in camels around the world. Until today, no review paper has been published compiling and discussing the reports available on HEV in camels. More studies are required to ascertain the prevalence of HEV infection in camels worldwide. Additionally, because camels are utilized as a form of transportation in many countries and because HEV in these animals may pose a threat to public health, there is a possibility of foodborne transmission through contaminated camel products. Hepatitis E virus (HEV) represents a major cause of acute hepatitis and is considered an emerging public health problem around the world. In the Middle East's and Africa's arid regions, where camels frequently interact with human populations and camel-derived food products are a component of the food chain, camel-borne zoonotic HEV infection is a potential threat. To date, no review paper has been published on HEV in camels. As such, the purpose of the current work is to provide a scientific review of the identification of HEV genotypes seven and eight in camels worldwide to have a better understanding of the current status of this topic and to identify gaps in the current knowledge. Searches were carried out in the electronic databases PubMed, Mendeley, Web of Science, and Scopus, including studies published until 31 December 2022 (n = 435). Once the databases were checked for duplicate papers (n = 307), the exclusion criteria were applied to remove any research that was not relevant (n = 118). As a result, only 10 papers were found to be eligible for the study. Additionally, in eight of the ten studies, the rates of HEV infection were found to be between 0.6% and 2.2% in both stool and serum samples. Furthermore, four studies detected HEV genotype seven in dromedary camels, and two studies have shown HEV genotype eight in Bactrian camels. Interestingly, these genotypes were recently reported in camels from the Middle East and China, where one human infection with HEV genotype seven has been associated with the consumption of contaminated camel meat and milk. In conclusion, more research will be needed to determine the prevalence of HEV infection in camels around the world as well as the risk of foodborne transmission of contaminated camel products. As camels are utility animals in several countries, HEV in these animals may pose a potential risk to public health. [ABSTRACT FROM AUTHOR]

With the warming and humidification process in the Northwest Arid Zone over the past 30 years, the runoff of a vast majority of rivers has been affected to different degrees. In this paper, the runoff from the Weigan River, a typical inland river in the arid zone of Northwest China, is taken as an example, and seven types of CMIP6 data are selected with the help of a SWAT model to predict the runoff volume of the Weigan River in the next 30 years under climate change. The results show that (1) the SWAT model can simulate the runoff from the Weigan River well and has good applicability in this study area. (2) With an increase in radiative forcing, the temperature, precipitation and runoff in the study area show an increasing trend. (3) Under the four radiative forcing scenarios in 2030 and 2050, the runoff from the Weigan River out of the mountain is predicted to be maintained at 25.68 to 30.89 × 108 m3, which is an increase of 1.35% to 21.91% compared with the current runoff, of which the contribution to the increase in future runoff caused by the changes in temperature and precipitation is 68.71% and 27.24%, respectively. It is important to explore the impact of climate change on the runoff from the Weigan River to understand the impact of climate change on the Northwest Arid Region scientifically and rationally, and to provide a scientific basis for evaluating the risk of climate change and formulating policies to deal with it. [ABSTRACT FROM AUTHOR]

The global climate has undergone great changes in recent decades, which has a significant impact on the vegetation system, especially in arid and semi-arid areas. Based on a dynamic model, this paper studied the response of vegetation pattern to climate change in Qinghai Lake, a typical semiarid region. The conditions for Turing instability of the equilibrium were obtained by mathematical analysis. The numerical experiments showed the influence of different climitic factors (carbon dioxide concentrations [CO2], temperature and precipitation) on vegetation pattern. The results showed that the robustness of the vegetation system was enhanced as precipitation or [CO2] increased. Furthermore, we presented evolution of vegetation system under different climate scenarios to forecast the future growth of vegetation. We compared the various climate scenarios with representative concentration pathways (RCP2.6, RCP4.5, RCP8.5). The results revealed that RCP2.6 scenario was a desired climate scenario for Qinghai Lake. Our study also highlighted the measures to avoid desertification by the method of optimal control. We expect that this study will provide theoretical basis for vegetation protection. [ABSTRACT FROM AUTHOR]

Water is a critical input to agricultural production in arid regions. Understanding irrigator perspectives and determining their information and technical needs are critical to increasing water conservation while maintaining profitable yields. This paper summarizes survey data for 140 irrigators operating in the High Plains Aquifer portion of southcentral Kansas. We document adoption of different farm management practices, key challenges facing irrigators, information gaps, and qualitative information obtained from openended questions. Survey response patterns are discussed in the context of local water use conflicts and water governance. [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]

The human population continues to grow, and specific efforts must be made in order to meet foreseeable food demands. In this paper, it is suggested that an IoT-based fuzzy control system be used for smart soil monitoring systems. This study is based on the semi-arid regions of India. A fuzzy classifier is used to categorize the real-time data into three parameters, such as sodium, potassium, and calcium, based on the proposed model, which gets trained from a dataset and then chooses the optimal solution. The real-time data are collected from NPK sensors, which are suitable for sensing the content of nitrogen, phosphorus, and potassium in the territory, which helps in determining the fertility of the soil by facilitating the systematic assessment of the soil condition. With the aid of this system, a farmer would be able to monitor soil health in a real-time environment and also track the growth of their plants. Farmers will be able to enhance productivity while decreasing resource waste with the aid of an IoT-enabled fuzzy system. Experimental data have been collected from Mahoba district, Uttar Pradesh provinces in India, and the results show that the suggested system is a more reliable and precise concept used for precision farming that will certainly enhance the overall production of crops with better quality. These results obtained with the help of the proposed model system have been compared with the existing one with data accuracy that has been improved and well accepted. [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]

Spent coffee ground (SCG) consists of the remainder left after brewing the coffee grounds. Due to its valuable composition, SCG can provide sufficient nutrients and support plant growth, particularly in arid agricultural lands where soil fertility needs to be improved. However, the effects of SCG are highly dependent on their nature (raw or treated) and the application rate. SCG treatments namely composting and vermi-composting or pyrolysis could result in a more useful product for agricultural use, making it easy to overcome the SCG phytotoxic effect. In this paper a critical review of the researches on SCG was presented. The aim of this review was (1) to highlight the difference between the characteristics of composted, vermi-composted and pyrolyzed SCG with respect to the raw one, and (2) to outline their impacts on both of the physico-chemical properties of the soil as well as the growth of plant. In summary, adding raw SCG may have benefits for physical chemical properties of the soil but not for plant growth, because of the phytotoxic components including polyphenols. Therefore, the application of raw SCG for plant production purposes, even at low rates (equivalent to 2.5%) is not recommended. The negative effect on plant growth can be overcome by SCG vermi-composting or composting/pyrolysis at 270 and 400 °C. Therefore, vermi-composting can be efficiently applied for SCG pre-treatment before their reuse as a soil fertilizer to ameliorate the properties of the soil and subsequently plant nutrition. [ABSTRACT FROM AUTHOR]

Climate change has brought about credible changes in arid landscapes which have resulted in further challenges for pastoralists who require good quality rangeland resources to sustain their livestock. This study assessed local level coping and adaptivemanagement strategies by pastoralists in Namibia and South Africa using a capital assets approach, and also explored non-climate related barriers that increase their vulnerability to climate change. A case study approach was used, which included focus group discussions and semi-structured interviews. The main findings of the research indicate that pastoralists have been exposed to increased temperature extremes and droughts of varying duration over time which reduced the quality and quantity of forage and resulted in losses of income and animal health. The 46 different coping and adaptation strategies used by pastoralists included financial (n =15), natural (n = 15), human (n =12), physical (n = 2) and social (n = 2) capital. Of these, 61% of the strategies were common between the two countries. Strategies included income diversification, supplementary feeding and livestock mobility. Pastoralists had to overcome a hierarchy of barriers to implement their coping and adaptation strategies, which were largely related to human capital in Namibia and to natural capital in South Africa. These barriers included a lack of access to grazing lands, land degradation and the loss of traditional knowledge to manage livestock and rangeland resources. Policy development should take these barriers into account while building on the foundation of existing adaptation strategies to reduce the vulnerability to climate change of pastoralists in dryland regions. [ABSTRACT FROM AUTHOR]

This article explores the recent history of early warning systems in Kenya, determining key features of the entangled political, technical and conceptual processes that prefigure contemporary drought management there. In doing so, it draws out wider implications regarding drought and anticipatory action across Africa's drylands, considering the friction between the dynamics of disaster risk management that structure formal early warning systems and those that shape pastoralist engagements with the volatile and uncertain worlds they inhabit. Surveying recent literature on pastoralism's unique relationship with uncertainty, and associated forms of networked, relational resilience, it reflects on some of the inherent limitations of current approaches to "local knowledge" in the humanitarian sphere. In doing so, it emphasises the need for new, creative approaches to early warning and anticipatory action, which are not merely established via the external synthesis of data but are rather oriented around local pastoralist drought preparation and mitigation strategies and comprise enough flexibility to adapt to a fast-shifting terrain of challenges and possibilities. [ABSTRACT FROM AUTHOR]

This article analyses the indispensable role of sustainable agricultural intensification practices (SAIP) in meeting the needs of a burgeoning human population with limited planetary resources and examines the role of various stakeholders in the adoption of these practices by local farmers. The study setting is the Upper West, a semi-arid region of Ghana. The study employs a stakeholder salience theory and a mixed-method design. Firstly, qualitative data were collected and analysed as a basis for formulating a structured questionnaire administered to beneficiary farmers, which were then analysed using marginal effects from logistic regression. Notably, the study found four sustainable crop cultivation practices and three eco-friendly crop storage methods promoted in the area. Furthermore, the engagement of stakeholders like selected farmers, Traditional authorities, and implementing NGOs had statistically significant effects on the adoption of SAIP. However, these effects were smaller when compared to the direct involvement of all beneficiary farmers in the planning and implementation of the intervention. This suggests that while technocrats and authorities are important, they alone cannot achieve the desired impact of development interventions. Beneficiary farmers are the most critical stakeholders in adopting and promoting SAIP. The article further proposes a conceptual framework for implementing SAIP in agro-based rural communities. This research therefore underscores the importance of sustainable agricultural intensification practices in a resource-constrained world and emphasizes the central role of beneficiary farmers in driving the success of such initiatives. [ABSTRACT FROM AUTHOR]

Climate change has brought about credible changes in arid landscapes which have resulted in further challenges for pastoralists who require good quality rangeland resources to sustain their livestock. This study assessed local level coping and adaptivemanagement strategies by pastoralists in Namibia and South Africa using a capital assets approach, and also explored non-climate related barriers that increase their vulnerability to climate change. A case study approach was used, which included focus group discussions and semi-structured interviews. The main findings of the research indicate that pastoralists have been exposed to increased temperature extremes and droughts of varying duration over time which reduced the quality and quantity of forage and resulted in losses of income and animal health. The 46 different coping and adaptation strategies used by pastoralists included financial (n =15), natural (n = 15), human (n =12), physical (n = 2) and social (n = 2) capital. Of these, 61% of the strategies were common between the two countries. Strategies included income diversification, supplementary feeding and livestock mobility. Pastoralists had to overcome a hierarchy of barriers to implement their coping and adaptation strategies, which were largely related to human capital in Namibia and to natural capital in South Africa. These barriers included a lack of access to grazing lands, land degradation and the loss of traditional knowledge to manage livestock and rangeland resources. Policy development should take these barriers into account while building on the foundation of existing adaptation strategies to reduce the vulnerability to climate change of pastoralists in dryland regions. [ABSTRACT FROM AUTHOR]

This article explores the recent history of early warning systems in Kenya, determining key features of the entangled political, technical and conceptual processes that prefigure contemporary drought management there. In doing so, it draws out wider implications regarding drought and anticipatory action across Africa's drylands, considering the friction between the dynamics of disaster risk management that structure formal early warning systems and those that shape pastoralist engagements with the volatile and uncertain worlds they inhabit. Surveying recent literature on pastoralism's unique relationship with uncertainty, and associated forms of networked, relational resilience, it reflects on some of the inherent limitations of current approaches to "local knowledge" in the humanitarian sphere. In doing so, it emphasises the need for new, creative approaches to early warning and anticipatory action, which are not merely established via the external synthesis of data but are rather oriented around local pastoralist drought preparation and mitigation strategies and comprise enough flexibility to adapt to a fast-shifting terrain of challenges and possibilities. [ABSTRACT FROM AUTHOR]

Infrastructure resilience is a critical issue in arid regions due to the unpredictability of extreme rainfall events influenced by climate change. Accordingly, the integration of artificial intelligence (AI) in engineering solutions to address such climatic challenges is important. This study aims to review AI-based engineering solutions for infrastructure resilience in arid areas against extreme rainfall and most importantly critically analyzes their sustainability benefits. By evaluating existing AI-based engineering solutions, this research highlights how these technologies can contribute to sustainable development goals (SDGs) and eventually aims to help set new standards in infrastructure resilience. The significance of this study lies in its potential to advance sustainable development goals by enhancing the resilience of critical infrastructure and equipping arid regions with innovative solutions to withstand adverse weather conditions. Expected outcomes of this study are anticipated to provide pivotal insights for policymakers, engineers, and urban planners, promoting the adoption of intelligent, sustainable infrastructure practices that are in line with global sustainability targets. Finally, this research promotes the adoption of AI solutions in infrastructure resilience and lays the groundwork for future explorations in this field. Highlights: AI solutions can improve infrastructure resilience and resource management in arid regions with extreme rainfall events. Using AI solutions in arid regions with extreme rainfall events aligns with SDGs for sustainable, resilient development. The study promotes working to develop cost-effective AI solutions for arid region resilience. [ABSTRACT FROM AUTHOR]