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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]

Rodents are one of the most abundant and diverse groups of mammals in arid zones. Their population and community dynamics are closely linked to climatic factors and pulses of primary productivity activation. In the future, climatic conditions in arid ecosystems could become more extreme as a consequence of climate change, which could affect the species that inhabit these regions. In this paper, we review the literature on the ecological response of rodents in the world's arid zones, at the population and community levels, to climatological factors (temperature and precipitation), climatic events and the possible impact of climate change. We used the PRISMA protocol to systematically search the literature, and the “vote‐counting” method to count positive, null or negative responses of the rodents. At the population level, rodent density and abundance responded positively to precipitation, while biomass responded negatively and reproduction responded positively to increasing temperature. At the community level, rodent density, biomass and diversity increased after rainfall. El Niño events were positively related to rodent population increases. In contrast, intense storms affected the survival of some species. Rodents with physiological adaptations suited to living in arid areas, for example, the heteromyids, responded positively to precipitation and could suffer fewer negative ecological consequences in the future when exposed to increased temperature and changes in precipitation. [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]

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 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]

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]

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]

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]

Faced with the challenges posed by the need for fertilizers to maintain agricultural production, a biological process of atmospheric nitrogen fixation occurs naturally, which is carried out by a group of symbiotic bacteria that form a very close association with plants of the legume group, among which is the sweet clover (Melilotus spp.). From an ecological point of view, this plant has an essential function due to its good ability to associate with native nitrogen-fixing bacteria of the genus Sinorhizobium. A fundamental aspect is that this plant species can grow normally in alkaline soils, which doubles its importance since, on the one hand, it fixes nitrogen, and on the other hand, it can be incorporated as green manure. With this, the physicochemical properties of the soil are improved, and the levels of organic matter, which is in extremely poor condition in arid zone areas, are increased. Additionally, this species can withstand low temperatures and grow satisfactorily in winter. This paper presents a synthesis of the genus Melilotus and its symbiont Sinorhizobium meliloti and its importance as a potential natural soil improver. [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]

This paper explores water justice struggles in the understudied region of Iraq and Iraqi Kurdistan through a focus on two water justice movements, one civil society campaign, and a related event. While most of the relevant literature in geography and cognate fields has thoroughly dissected inter-State hydropolitical quarrels, discussed water justice from a legal perspective, and analysed water conflicts, less attention has been paid to bottom-up movements, to their visions and actions within a materially and socially challenging environment, and to their engagement with the state. Relying on published material as well as primary research, we show how Iraqi water activists seek to strike a balance between engaging institutions and moving beyond them, across ethno-religious divides and advocacy registers, in their quest to re-signify and re-common waterscapes. We argue that it is not despite all odds, but rather because of all odds, that Iraqi activists showcase such a developed awareness of their role and transformative potential along the rugged path of democratisation. [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]

• A MGWR-based SMAP soil moisture product downscaling method is proposed. • The method considers the scale differences in the impact of surface variables on soil moisture. • Field validation shows higher accuracy from the downscaled SM than the SMAP SM itself. • This proposed downscaling method performs better than the traditional GWR and MW methods in the semiarid area. Passive microwave remote sensing missions such as Soil Moisture Active Passive (SMAP) are widely used for global soil moisture (SM) estimation. But the low spatial resolution of passive microwave SM products limits their applications at regional and local scales (normally 1–10 km). Using high-resolution auxiliary data to downscale passive microwave SM products is the primary way to obtain high-resolution SM data. However, the existing SM downscaling methods do not entirely account for the scale differences in the impact of various variables on the distribution of SM. To solve this problem, this paper introduced MGWR (Multiscale Geographically Weighted Regression) as a novel way to analyze the scale differences of normalized difference vegetation index (NDVI) and land surface temperature (LST) on the spatial pattern of SM. Accordingly, a new spatial downscaling algorithm for SMAP SM products is proposed and compared with the geographically weighted regression (GWR) algorithm and moving window algorithm (MW). The algorithm was applied to data taken during the SMAP Validation Experiment 2016 (SMAPVEX16), and the downscaled SM evaluated with in situ SM and aircraft observations. These results show that: 1) the SM downscaling conversion function, based on the MGWR, effectively reveals how different surface parameters relate to SM, with LST influencing SM globally and NDVI affecting it locally, 2) compared with GWR and MW, the 1 km SM obtained by the MGWR-based downscaling method showed better spatial agreement with airborne SM in the semiarid region with the ubRMSE decreasing by 0.023 m3/m3 and 0.026 m3/m3 for GWR and MW respectively, 3) when evaluating the 1 km SM with in situ SM in the semiarid region, the SM obtained through MGWR exhibited lower ubRMSE values as compared to both GWR and MW. Specifically, the median ubRMSE values for MGWR, GWR, and MW were 0.043 m3/m3, 0.053 m3/m3, and 0.094 m3/m3, respectively. In conclusion, this study demonstrates that MGWR can effectively improve the accuracy of downscaled SM in semiarid regions. [ABSTRACT FROM AUTHOR]

This paper aims to assess the mean precipitation and precipitation extremes over Iran as simulated by the Regional Climate Model (RegCM4). A simulation spanning 20 years (1991–2010) at a horizontal resolution of 20 Km is driven by the NCEP / NCAR reanalysis. We evaluated the model by comparing simulated precipitation with observations using Bias, Root-Mean-Square Error, and Index of Agreement metrics. We examined the extreme precipitations based on a set of extreme indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) in three categories of intensity (Rx1day and SDII), duration (CDD and CWD), and frequency (R10mm and R20mm). The linear trends are calculated using the Theil–Sen estimator method, and the statistical significance (95% confidence level) is determined by using a modified Mann-Kendall (MMK) trend test. The RegCM4 model satisfactory captured the spatial distribution of precipitation and precipitation extremes, although high bias remained in small parts of Iran, including the northwest and southeast. The northwest bias is due to spring convectional precipitation and the southeast bias could be caused by precipitation from the Asian summer monsoon system, which both of them may not be well simulated by the applied Grell convective scheme. Results indicate that the model reasonably captures Rx1day, SDII, CWD, R10mm, and R20mm Indices over Iran. In good agreement with precipitation observations, the southern coast of the Caspian Sea represents the second-highest extreme precipitation, except for SDII, which is probably due to the high frequency of rainy days in this region. The highest CDD of more than 200 days is found in the arid and semi-arid regions of the southeast. In general, precipitation decreased in most regions of Iran, especially the western, southern, and interior regions. In addition, the results reveal that heavy (R10mm) and very heavy (R20mm) precipitation events have also decreased in the same regions. Results also emphasize an increase in consecutive dry days (CDD) in most parts, especially in the southeast, which deserves more attention in future research. The decreasing trend of precipitation and the increasing trend of CDD show that Iran has become drier in the 2000 s compared to the 1990 s • The Grell convective scheme applied in RegCM4 has been successful in simulating precipitation extremes in Iran. • The RegCM4 has been able to capture precipitation extremes well in Iran. • Consecutive dry days (CDD) are increasing in most parts of Iran. [ABSTRACT FROM AUTHOR]

Desertification in karst is an effect of climate change and not sustainable anthropogenic activities, the combination of which, however, causes the gradual loss of karst natural resources, such as soil, vegetation, and groundwater. A considerable percentage of global karst areas is found in drylands, characterized by negative water balance and scarce presence of soils. High fragility of the karst environment, and its vulnerability to land degradation and pollution because of the peculiar anisotropic setting, environmental dynamics, and of the direct connection between the surface and the subsurface, are at the origin of the severe problems deriving from desertification processes in karst. In addition to natural drivers, such as geology and topography, karst desertification is generally due to four main factors, mostly or partly related to human activity: deforestation, improper land use, groundwater overexploitation, and climate changes. Through the analysis of a collection of studies conducted in several karst territories around the world, the present paper aims to provide an overview of the processes leading to desertification risks in karst areas. Emphasizing the need to preserve these fragile environments, characterized by peculiar features and precious freshwater resources, this review summarizes the main situations at the global scale of rocky desertification in karst, at the same time providing indications for developing innovative and multi-disciplinary approaches addressed toward mitigation of the risk related to desertification in karst. [ABSTRACT FROM AUTHOR]

• Connectivity of riparian vegetation, transpiration and evaporation was assessed. • Evaporation is lower (18 %−34 %) near high riparian vegetation density (NDVI ≥ 0.6). • Riparian vegetation actively lower evaporation up to 90 m from the reservoir margin. • Riparian vegetation transpiration and reservoir evaporation ratios are equivalent. • 275,000 people may be supplied per day by the evapotranspiration losses. Understanding the combined open water reservoir evaporation and riparian vegetation transpiration (evapotranspiration) is important for water resource management in semiarid regions like the Brazilian Dryland region. Existing research has explored reductions in open water evaporation due to riparian vegetation transpiration, but evidence for this interdependence in this region is not well understood. The aim of this study was to estimate the connectivity (impact and maximum distance of action) between riparian vegetation and its transpiration and reservoir evaporation, as well as the ratio of the volume losses by transpiration and evaporation, using Landsat 5 and 8 in a Brazilian Dryland environment. Evaporation and transpiration were estimated using the Surface Energy Balance System for Water and the Surface Energy Balance System models, respectively, from 1985 to 2020. A Class A Pan and the Penman-Monteith equation were used, for reference reservoir evaporation and vegetation transpiration, respectively. The occurrence of riparian vegetation was associated with the Normalized Difference Vegetation Index. Both models performed well, with root mean square error ≤ 0.80 mm/day. The riparian vegetation transpiration demonstrated a high negative correlation (R²>0.7) with evaporation, suggesting the vegetation acts to reduce evaporation (average of 30 %) up to a maximum distance of 90 m from the reservoir shoreline. This is explained by the adjacent riparian vegetation-induced reduction in radiation inputs due to shading at the reservoir margin, a lowering of wind speeds and increases in air humidity from transpiration. The ratio of riparian vegetation transpiration to reservoir evaporation within a buffer of 150 m is approximately equal. Combined riparian vegetation and reservoir evapotranspiration equates to the daily water supply for ∼275,000 people. The paper explains and quantifies the connectivity between riparian vegetation transpiration and reservoir evaporation, thereby providing a model for improved reservoir water balance estimates, which can aid regional water resources planning, development, and management. [ABSTRACT FROM AUTHOR]

A rich insect fauna is found in the Cretaceous (Aptian) Nova Olinda Member of the Crato Formation in the Araripe Basin, northeastern Brazil. The Crato Formation was deposited close to the centre of the supercontinent Gondwana, prior to significant rifting. In this paper, we analyzed remains of 1135 insect specimens, representing 55 families, within two limestone facies of the Nova Olinda Member: pale yellow and dark gray limestones. We collected taphonomical data and assessed the paleoecological significance of insect faunas in terms of their distribution and interaction with the paleoenvironment. The insect fauna is dominanted by fully terrestrial taxa despite preservation in an aquatic paleoenvironment. Considering both facies, the distribution of insect families is similar throughout the Nova Olinda Member, which excludes possible overlapping of one entomofauna over another. The pale yellow limestones near the top of the section are richer in fossil insect content and show a higher incidence of aquatic and semiaquatic insects preserved in dorsoventral view compared to the dark gray limestones. This suggests that the Crato insects preserved in the pale yellow limestones experienced short transport distances or prolonged decay or both. In contrast, insects preserved in the dark gray limestones appear proportionally with higher degrees of disarticulation than those preserved in the pale yellow limestones, indicating that these insects underwent a higher degree of postmortem transport in the biostratinomic stage. Compared to descriptions of other Early Cretaceous assemblages, the taxonomic literature of Crato Paleoentomofauna shows distinct differences. The Yixian and Zaza formations are described as being dominated by beetles and wasps. The Crato Formation, however, is relatively richer in Paleoptera species. Both the sedimentary facies studied and the paleoentomological content reveal a complex ecosystem inserted in a depositional setting, similar to modern long-standing wetlands, and where periodically flooded zones were surrounded by dry lands with xeromorphic vegetation. • Crato insects preserved in the dark gray limestones appear proportionally with higher degrees of disarticulation. • The paleoentomological content reveals an ecosystem inserted in a setting similar to modern long-standing wetlands. • Compared to other Early Cretaceous assemblages, the Crato Paleoentomofauna is relatively richer in Paleoptera species. [ABSTRACT FROM AUTHOR]

Surface emissivity (ε) is used to characterize surfaces and to determine surface temperature from thermal radiation data. While in many applications it is treated as a constant, it is known to change with surface water content. Several ASTER/SEVERI based studies have speculated that diurnal changes in ε over deserts are linked to diurnal soil water content cycles resulting from water vapor adsorption during the night and subsequent evaporation during the day. This paper aims, for the first time, to validate the relationship between diurnal changes in surface ε and the changes in soil water content due to water vapor adsorption and evaporation under natural conditions. Measurements were conducted with a 6-band infrared radiometer, designed to validate ASTER bands 10–14, with study-specific recalibration for improved accuracy of ε. The evaluation included two different approaches to determine ε : using a single reference band (1B) and using the temperature/emissivity separation algorithm (TES). water content. While the TES has proven itself in many applications, it was found that for the soils studied (sand and loess) the use of 1B approach gave more consistent results for ε changes with soil water content than TES. Emissivity could be a powerful tool to characterize little studied soil water content changes in arid regions, but will require better characterization of surface properties to quantify the relationship between ε and soil water content for various soil types. Additional challenges to upscale this method include properly accounting for air irradiance and spatial heterogeneity. Meeting these main challenges will lead the way to detect small changes in soil water content under dry conditions at larger scales. Whether these are a result of water vapor adsorption or other processes, detecting such small changes in soil water content will provide new insights into desert hydrology. • On-ground validation of an infrared radiometer with ASTER bands. • Calibration and measuring protocol for minute changes in emissivity. • Observed emissivity changes of 0.2–0.6 due to water vapor adsorption. • Main challenges: air radiance, surface heterogeneity, and soil spectral properties. • Potential for new insights into desert hydrology. [ABSTRACT FROM AUTHOR]

The vadose zone serves as a crucial link for the mutual transformation of atmospheric, surface, ecological, and groundwater systems. Infiltration recharge in the vadose zone is a key step in the Earth's water cycle and plays an extremely important role in the sustainable development of groundwater resources, particularly in arid and semi-arid regions. However, under the influence of extreme climatic conditions and intense human activity, the vadose zone has thickened in many places globally. Changes in the vadose zone structure lead to alterations in the infiltration process. Researchers have attempted to quantify this process using various methods. However, it has been found that conventional monitoring methods are inadequate to effectively describe the complex infiltration recharge process under the multifactorial influence of a deep vadose zone. Through an analysis of relevant literature published from 2000 to 2023 regarding deep vadose zone infiltration recharge, this paper identifies four contentious bottlenecks: (1) effective monitoring and simulation of deep vadose zone infiltration recharge, (2) modes of deep infiltration recharge, (3) issues related to the quantity and recharge period of precipitation and irrigation infiltration recharge, and (4) quantification of spatial variations and scale effects of infiltration recharge. After reviewing the latest developments in infiltration recharge monitoring and simulation and systematically analyzing the influencing factors and mechanisms of deep vadose zone infiltration recharge, this study provides answers to the aforementioned issues. The combined use of monitoring and numerical simulation methods, taking into account infiltration recharge scenarios and scales, can enhance the reliability and accuracy of the calculation results. Additionally, piston flow may not be the primary mode of water movement in the deep vadose zones. Understanding the modes and characteristics of water movement, as well as the differences in suction and desorption processes, is fundamental for accurately describing nonlinear infiltration recharge processes. Furthermore, the measured average vertical infiltration rates of the deep vadose zone vary widely from 0.14 to 500 mm/d globally. In the North China Plain, vertical infiltration recharge rates range from 133 to 300 mm/a. These significant differences are related to the research scale, external conditions, and internal soil structure within the vadose zone. Finally, a systematic analysis of the driving factors of nonlinear infiltration recharge in the deep vadose zone is a prerequisite for quantifying spatial variations and scale effects. Only by fully considering the interactions and contributions of various driving factors can the spatiotemporal variations in soil infiltration be effectively quantified. Therefore, our research team suggests that future studies on deep vadose zone infiltration recharge should focus on establishing a unified layout for large-scale, multi-point, synchronous, in situ, and long-term monitoring; constructing relationships between the vadose zone structure and hydraulic characteristics; and conducting comprehensive studies on the overall water cycle in the Earth's surface layers, with the deep vadose zone as the core. These will help build a research system for the spatiotemporal infiltration recharge of water in the deep vadose zone at multiple layers and scales, achieving the closest approximation to a realistic description of the deep vadose zone infiltration recharge. [ABSTRACT FROM AUTHOR]

[Display omitted] • NDVI shows an overall increasing trend from 2000 to 2020. • The Hexi region shows a warming and wetting trend. • Extreme precipitation is more important for NDVI. • The lag effect of NDVI on climate extremes varies by indicators and spaces. Climate extremes significantly affects vegetation dynamics, and understanding the relationship between dryland vegetation and climate extremes is crucial for regional ecological security and disaster warning. According to meteorological and satellite remote sensing data, the paper analyses the dynamics of normalized difference vegetation index (NDVI) and climate extremes in the Hexi region from 2000 to 2020 using Theil-Sen Median, Mann-Kendall and linear regression methods; the relationship between climate extremes and vegetation dynamics is revealed using Pearson correlation and boosted regression trees (BRT) models. On this basis, the time-lag effect of NDVI in response to climate extremes was further investigated. The results show that the NDVI in the Hexi region increased from 2000 to 2020, with significant greening (67.72 %) and a small amount of degradation concentrated in the desert in the northwest and the oasis in the southeast. The correlation between climate extremes indicators and NDVI shows a large spatial heterogeneity, with extreme precipitation showing a high importance for all regions except oasis. NDVI has no lag or 1 month lag for extreme temperature, no lag for max 1-day precipitation amount (Rx1day) for areas other than mountainous areas, and a 3-month lag for max 5-day precipitation amount (Rx5day) for extensive areas. The results of this study could serve as a reference for the study of the relationship between vegetation dynamics and climate extremes in arid and semi-arid regions, and provide a theoretical basis for the establishment of scientific and reasonable strategies for regional vegetation restoration and conservation. [ABSTRACT FROM AUTHOR]

[Display omitted] • Five discharge datasets have median correlation coefficients > 0.6 with the observations. • Overestimation of monthly mean flow is more common than underestimation. • GRFR showed the best estimate at around 40% of the locations. • None of the models provides good estimates for rivers and streams in arid regions. High-resolution global flow discharge datasets are critical to understand the terrestrial water cycle and river ecosystem services. Recently, a number of global hydrological models have been developed to capture global river flow dynamics at locally relevant scales. However, the relative accuracy of these simulated flow discharges is largely unknown. In this paper, using the largest observed streamflow datasets from > 26,000 gauging stations, we evaluated the performance of monthly and sub-monthly flow variation (1980–2014) generated from five major global hydrological models, Catchment-based Macro-scale Floodplain model (CaMa-Flood), Global Flood Awareness System (GloFAS-reanalysis), Global Reach-level Flood Reanalysis (GRFR), PCRaster GLOBal Water Balance model (PCR-GLOBWB), and Water Global Assessment and Prognosis (WaterGAP). Significant spatial heterogeneity in model performance was identified. We found that estimates by all five discharge datasets have a relatively high correlation with the observations (medians > 0.6). But none of them showed adequate correlations between simulated and observed flows for systems in Southwest or Central U.S.A., South Africa, or South Australia. Across all models, overestimation of monthly mean flow was more common than underestimation and high flows at a sub-monthly scale were more accurately characterized than low flows. Performance of all models was poor in Africa and Oceania. No single model performed universally best at all gauging stations, but GRFR showed the best estimate at around 40 % of the locations. None of the models provided satisfying estimates for rivers and streams in arid regions. We also found a significant negative effect of flow regulation on the predictive accuracy of all models. Our study highlights the importance of thorough evaluation of global discharge datasets before their local and regional application and provides guidance for future enhancement of global hydrological models. [ABSTRACT FROM AUTHOR]

• Drought followed by extreme rain/flooding exposed vulnerabilities in Ceará, Brazil. • Adaptative strategies in dry periods may become maladaptive during extreme rain. • Impacts of and responses to drought, extreme rain, and flooding are interrelated. • Hydrometereological extremes should be considered together in semi-arid regions. As climates continue to change, semi-arid rainfall regimes are projected to become increasingly more extreme, with longer dry periods and fewer, but more intense, heavy rainfall events. This process of hydroclimatic intensification increases the risk associated with successive extreme climate hazards, such as drought and then heavy rainfall, in the same area. However, the development of effective adaptation strategies to drought, heavy rainfall, and flood hazards is hampered by the lack of integrated analyses that consider the interactions among these hazards and responses to them. To increase understanding of these interactions, this paper examines impacts of and adaptive actions taken in response to prolonged drought (2012–2018) and subsequent extreme rainfall and flooding (March and April 2023) in the semi-arid region of Ceará, Northeast Brazil. We find that policies and adaptive measures focus primarily on drought hazard, while preparation for extreme rainfall events and flooding is scant. Management plans and long-term adaptive strategies are being developed for drought and not other extreme hydrometeorological events. Additionally, emergency measures for extreme rainfall and flooding are much less structured than those for drought. As such, the paradigm "Convivência com o semiárido" ("Living with the semi-arid region") remains limited to adapting to drought hazard, ultimately hindering adequate extreme rainfall and drought responses. To promote more effective adaptive strategies in the context of hydroclimatic intensification in semi-arid regions, drought, heavy rainfall, and flood responses must be considered in a more integrated manner to create management plans to prepare for the potential impacts of these hazards into the future. [ABSTRACT FROM AUTHOR]

• Quantitatively describes the groundwater recharge process for lakes. • Constructed a model for the groundwater table-lake area relationship in groundwater-dependent lakes in arid regions. • Suggested a groundwater depth of 1.73 m to maintain stable lake area within the Hetao Irrigation District. • Constructed model can serve as an effective reference tool for groundwater management and the protection of lake ecosystems. The groundwater table constitutes a significant factor in sustaining the ecosystems of lakes in arid regions. To elucidate the mechanism by which variations in groundwater tables affect lake areas, this paper presents a case study of a typical groundwater-fed lake in China's Hetao Irrigation District. An analytical model correlating groundwater tables with lake areas was developed to simulate and predict the impact of changes in groundwater tables on lake areas. The findings indicate that the analytical model adeptly simulates the lake area dynamics of the groundwater-fed lake cluster (Taerhu lake cluster) from 1998 to 2018, achieving a Nash-Sutcliffe efficiency (NSE) value exceeding 0.6 and a root mean square error (RMSE) value below 0.1 square kilometers. Maintaining a groundwater depth at 1.73 m ensures the stability of the lake area; a decrease in groundwater depth to 1.93 m would result in a 79.5 % reduction in lake area. The model constructed in this study offers a crucial tool for the ecological protection of lakes and groundwater management in arid regions. [ABSTRACT FROM AUTHOR]

[Display omitted] • Spring drought factors include snow cover, precipitation, temperature, and soil moisture. • Established a variance analysis projection pursuit model (ANOVA PPM) • ANOVA PPM achieves a balance between overall dispersion and local aggregation. Due to the influence of snow cover and soil freeze–thaw processes in the early spring, the characteristics of spring drought in cold regions are different from those in other regions. This paper takes Qiqihar, a cold and semiarid grain production area in Northeast China, as the study area. Based on factors such as snow cover in the early spring period and precipitation, temperature, evapotranspiration, and soil moisture during the spring sowing period, a projection pursuit model with analysis of variance (ANOVA PPM) was used to analyze the spatiotemporal variation characteristics of regional spring drought. For the ANOVA PPM, based on the grouping of the projection points, local aggregation is measured by the mean square within groups, and overall dispersion is measured by the mean square between groups, thus achieving comparability and balance between overall dispersion and local aggregation. The spatial analysis of spring drought showed that, from a spatial perspective, there were significant spatial differences in spring drought in different subregions, and spring drought was closely related to latitude, with significant differences occurring at different latitudes. The northern region is relatively light, while the central and southern regions are more severe. From a temporal perspective, there are significant differences in spring droughts between different decades (1980 s, 1990 s, 2000 s and 2010 s). Overall, spring drought first intensifies and then decreases. [ABSTRACT FROM AUTHOR]

• The runoff, sediment load and runoff erosion power decreased significantly. • Compared with runoff, runoff erosion power-sediment relationship is better. • The power function of runoff erosion power and sediment is better than linear. • Erosion in particular geographic locations responds strongly to runoff erosion power. In recent years, the acceleration of urbanization in the Yangtze River Economic Belt (YREB) has brought about problems such as soil erosion, ecosystem degradation and decline in ecological service functions. Therefore, this paper selects the Fujiang River Basin (FRB) in Upper Yangtze River (UYR), and analyzes the relationship between runoff erosion power (REP) and sediment transport (ST) on the basis of analyzing the variation characteristics of hydrological elements. Based on SWAT model, a variety of scenarios are set up to quantitatively analyze the impact of different land use changes on runoff and ST and REP in the basin. The results indicated that: (1) The annual precipitation in FRB from 1960 to 2018 did not change significantly, while the annual runoff, annual ST and annual REP decreased significantly. Compared with runoff and runoff depth, the relationship between sediment transport modulus (STM) and REP is the best, especially the power function between them is better than the linear function. (2) The results of the evaluation indexes of the simulation results of the SWAT model based on the measured runoff and sediment data from 2008 to 2018 are pass and above, that is, the simulation results are considered reliable. (3) Under the five scenarios of conversion of sloping farmland to forest, conversion of dry land to paddy field and conversion of grassland to bushland and forest land, the runoff and ST in the basin decreased but the overall range was small. The simulation results of SWAT model show that the erosion of specific areas in the basin shows the greatest degree of weakening with the decrease of REP. [ABSTRACT FROM AUTHOR]

The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide. • An integrated framework combining DBN, SD, PLUS and InVEST models was proposed. • Impact of natural and socioeconomic factors on ESs was determined under climate scenarios. • The spatial pattern of ESs was optimized and partitioned using DBNs. • ESs in arid oasis urban agglomerations are mainly affected by natural factors. [ABSTRACT FROM AUTHOR]