Earths Future最新文献

{"title":"Warmer Climate Reduces the Carbon Storage, Stability and Saturation Levels in Forest Soils","authors":"Yuntao Wu,&nbsp;Ziyang Peng,&nbsp;Xin Wang,&nbsp;Junsheng Huang,&nbsp;Lu Yang,&nbsp;Lingli Liu","doi":"10.1029/2024EF004988","DOIUrl":"https://doi.org/10.1029/2024EF004988","url":null,"abstract":"<p>Forest soils store about one-fifth of the global terrestrial biosphere carbon stock. However, our understanding of how soil geochemical, plant and microbial factors regulate forest soil organic carbon (SOC) storage, stability, and saturation levels remains limited. Here, we conducted a sampling campaign across a 5000-km natural forest transect in China, measuring climate, geochemical factors and SOC fractions with varying stability. Additionally, we compiled a global data set of SOC fractions in major forest biomes. Our field survey and global synthesis consistently demonstrate that warmer climates not only reduce the content of labile particle organic matter (POM), but also decrease the typically stable mineral-associated organic matter (MAOM), leading to a significant decline in total soil carbon storage. Additionally, warmer climates promote the crystallization of Fe/Al oxides, which decreases the formation efficiency of Fe/Al oxide associated organic complexes. Consequently, the mineralogical carbon saturation level declines from boreal forests (37%) to tropical forests (25%). Our findings underscore that, beyond the well-established climate impacts, soil geochemical properties play a pivotal role in shaping forest SOC composition and saturation levels across latitudes. This highlights that colder regions harbor larger and more stable carbon pools, and that ongoing climate warming and associated soil geochemical properties shift could potentially lead to a decline in soil carbon storage and its capacity to mitigate climate change.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"13 2","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF004988","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short-Term Memory and Regional Climate Drive City-Scale Water Demand in the Contiguous US","authors":"Wenjin Hao,&nbsp;Andrea Cominola,&nbsp;Andrea Castelletti","doi":"10.1029/2024EF004415","DOIUrl":"https://doi.org/10.1029/2024EF004415","url":null,"abstract":"<p>Gaining insights into current and future urban water demand patterns and their determinants is paramount for water utilities and policymakers to formulate water demand management strategies targeted to high water-using groups and infrastructure planning strategies. In this paper, we explore the complex web of causality between climatic and socio-demographic determinants, and urban water demand patterns across the Contiguous United States (CONUS). We develop a causal discovery framework based on a Neural Granger Causal (NGC) model, a machine learning approach that identifies nonlinear causal relationships between determinants and water demand, enabling comprehensive water demand determinants discovery and water demand forecasting across the CONUS. We train our convolutional NGC model using large-scale open water demand data collected with a monthly resolution from 2010 to 2017 for 86 cities across the CONUS and three Köppen climate regions—Arid, Temperate, and Continental—utilizing this globally recognized climate classification system to ensure a robust analysis across varied environmental conditions. We discover that city-scale urban water demand is primarily driven by short-term memory effects. Climatic variables, particularly vapor pressure deficit and temperature, also stand out as primary determinants across all regions, and more evidently in Arid regions as they capture aridity and drought conditions. Our model achieves an average <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mi>R</mi>\u0000 <mn>2</mn>\u0000 </msup>\u0000 </mrow>\u0000 <annotation> ${R}^{2}$</annotation>\u0000 </semantics></math> higher than 0.8 for one-month-ahead prediction of water demand across various cities, leveraging the Granger causal relationships in different spatial contexts. Finally, the exploration of temporal dynamics among determinants and water demand amplifies the interpretability of the model results. This enhanced interpretability facilitates discovery of urban water demand determinants and generalization of water demand forecasting.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"13 1","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF004415","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Model Assessment of Groundwater Recharge Across Europe Under Warming Climate","authors":"Rohini Kumar,&nbsp;Luis Samaniego,&nbsp;Stephan Thober,&nbsp;Oldrich Rakovec,&nbsp;Andreas Marx,&nbsp;Niko Wanders,&nbsp;Ming Pan,&nbsp;Falk Hesse,&nbsp;Sabine Attinger","doi":"10.1029/2024EF005020","DOIUrl":"https://doi.org/10.1029/2024EF005020","url":null,"abstract":"<p>Climate change threatens the sustainable use of groundwater resources worldwide by affecting future recharge rates. However, assessments of global warming's impact on groundwater recharge at local scales are lacking. This study provides a continental-scale assessment of groundwater recharge changes in Europe, past, present, and future, at a <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>(</mo>\u0000 <mrow>\u0000 <mn>5</mn>\u0000 <mo>×</mo>\u0000 <mn>5</mn>\u0000 </mrow>\u0000 <mo>)</mo>\u0000 </mrow>\u0000 <annotation> $(5times 5)$</annotation>\u0000 </semantics></math> <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mtext>km</mtext>\u0000 <mn>2</mn>\u0000 </msup>\u0000 </mrow>\u0000 <annotation> ${text{km}}^{2}$</annotation>\u0000 </semantics></math> resolution under different global warming levels (1.5, 2.0, and 3.0 K). Utilizing multi-model ensemble simulations from four hydrologic and land-surface models (HMs), our analysis incorporates E-OBS observational forcing data (1970–2015) and five bias-corrected and downscale climate model (GCMs) data sets covering the near-past to future climate conditions (1970–2100). Results reveal a north-south polarization in projected groundwater recharge change: declines over 25%–50% in the Mediterranean and increases over 25% in North Scandinavia at high warming levels (2.0–3.0 K). Central Europe shows minimal changes (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mo>±</mo>\u0000 </mrow>\u0000 <annotation> $pm $</annotation>\u0000 </semantics></math>5%) with larger uncertainty at lower warming levels. The southeastern Balkan and Mediterranean region exhibited high sensitivity to warming, with changes nearly doubling between 1.5 and 3.0 K. We identify greater uncertainty from differences among GCMs, though significant uncertainties due to HMs exist in regions like the Mediterranean, Nordic, and Balkan areas. The findings highlight the importance of using multi-model ensembles to assess future groundwater recharge changes in Europe and emphasize the need to mitigate impacts in higher warming scenarios.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"13 1","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF005020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Increasing Health Burdens Driven by Global Trade Induced Air Pollution","authors":"Ruifei Li,&nbsp;Yu Luo,&nbsp;Xu Zhu,&nbsp;Jin Zhang,&nbsp;Pei Hua,&nbsp;Zhenyu Wang,&nbsp;Wenyu Yang,&nbsp;Qiuwen Chen,&nbsp;Hui Li","doi":"10.1029/2024EF004814","DOIUrl":"https://doi.org/10.1029/2024EF004814","url":null,"abstract":"<p>Globalization has led to an increasing geographical separation of primary input, consumption and production, and consequently to a substantial transboundary transfer of air pollution and associated health burdens through international trade. Here, we develop an integrated framework to determine the consumption- and income-based global atmospheric emissions, and quantify the drivers of associated health impacts from 2000 to 2015, and evaluate the impacts of international trade on PM_2.5-related deaths by hypothetical scenarios. Results show that consumption transferred more primary PM_2.5 emissions (2.2 Mt, 23.5%) and caused more additional mortality (241,000 deaths) through international trade than primary input (emission: 1.1 Mt, 12.3%, mortality: 167,000 deaths) in 2015. Top three key sectors contributed to more than half of emission flow driven by consumption (commercial, construction, electrical and machinery) and primary inputs (commercial, petroleum, and mining). Health benefits of reduced emissions intensity, which avoided 1.4 million deaths, were largely offset by not only increases in consumption and primary input levels but also population vulnerability, resulting in the increase in mortality (0.8 million) from 2000 to 2015. Changes in primary input (1.2 million deaths) contributed more to the rise in health burdens than changes in consumption (1.0 million deaths). Hypothetical scenarios show that the participation of Western Europe in international trade contributed to the reduction in global health burden, while the USA gained health benefits from international trade. Accordingly, our findings provide profound suggestions for future policy decisions from different perspectives and demonstrate that optimizing global supply chain through cooperation would mitigate the PM_2.5-related health impacts.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"13 1","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF004814","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143119846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Future Changes in Winter-Time Extratropical Cyclones Over South Africa From CORDEX-CORE Simulations","authors":"Sandeep Chinta,&nbsp;C. Adam Schlosser,&nbsp;Xiang Gao,&nbsp;Kevin Hodges","doi":"10.1029/2024EF005289","DOIUrl":"https://doi.org/10.1029/2024EF005289","url":null,"abstract":"<p>Extratropical cyclones (ETCs) significantly impact mid-latitude weather patterns and are crucial for understanding the societal implications of regional climate variability, climate change, and associated extreme weather. In this study, we examine the projected future changes in winter-time ETCs over South Africa (SA) using simulations from CORDEX-CORE Africa. We utilized three regional climate models, each driven by three different global climate models that simulate both the current climate and a future climate experiencing strong human-induced warming. From these, we assess changes in ETC frequency, track density, intensity, storm severity, and associated rainfall. The results indicate a significant reduction in the aggregate ETC frequency and track density, although track density is projected to increase prominently along the western coastal regions. Models show mixed trends in cyclone intensity projections, but overall results indicate weaker future cyclones, with reduced peak relative vorticity and increased minimum sea level pressure. Examining the Meteorological Storm Severity Index reveals notable regional variations in future storm severity. Average rainfall associated with ETCs is projected to decrease across SA, especially around Cape Town, highlighting a potential shift in the spatial distribution of rainfall with substantial consequences for water supply. We further investigated extreme ETCs (EETCs) and found that the trends for EETCs are generally similar to those for ETCs, with a notable decrease in frequency and regional variations in storm severity. These findings underscore the importance of developing targeted adaptation strategies to address the projected impacts of future ETCs on SA's climate and communities.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"13 1","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF005289","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physics-Based Hazard Assessment of Compound Flooding From Tropical and Extratropical Cyclones in a Warming Climate","authors":"Ali Sarhadi,&nbsp;Raphaël Rousseau-Rizzi,&nbsp;Kerry Emanuel","doi":"10.1029/2024EF005078","DOIUrl":"https://doi.org/10.1029/2024EF005078","url":null,"abstract":"<p>Recent efforts to assess coastal compound surge and rainfall-driven flooding hazard from tropical (TCs) and extratropical cyclones (ETCs) in a warming climate have intensified. However, challenges persist in gaining actionable insights into the changing magnitude and spatial variability of these hazards. We employ a physics-based hydrodynamic framework to numerically simulate compound flooding from TCs and ETCs in both current and future climates, focusing on the western side of Buzzards Bay in Massachusetts. Our approach leverages hydrodynamic models driven by extensive sets of synthetic TCs downscaled from CMIP6 climate models. We also perform a far less extensive analysis of ETCs using a previously produced event set, dynamically downscaled using the WRF model driven by a single CMIP5 model. This methodology quantifies how climate change may reshape the compound flooding hazard landscape in the study area. Our findings reveal a significant increase in TC-induced compound flooding hazard due to evolving climatology and sea level rise (SLR). Although compound flooding induced by ETCs increases mostly in coastal areas due to SLR, inland areas exhibit almost no change, and some even show a decline in rainfall-driven flooding from high-frequency ETC events toward the end of the century compared to the current climate. Our methodology is transferable to vulnerable coastal regions, serving as a tool for adaptive measures in populated areas. It equips decision-makers and stakeholders with the means to mitigate the destructive impacts of compound flooding arising from both current and future TCs, and shows how the same methodology might be applied to ETCs.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"13 1","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF005078","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From InSAR-Derived Subsidence to Relative Sea-Level Rise—A Call for Rigor","authors":"P. S. J. Minderhoud,&nbsp;M. Shirzaei,&nbsp;P. Teatini","doi":"10.1029/2024EF005539","DOIUrl":"https://doi.org/10.1029/2024EF005539","url":null,"abstract":"<p>Coastal subsidence, the gradual sinking of coastal land, considerably exacerbates the impacts of climate change-driven sea-level rise (SLR). While global sea levels rise, land subsidence often increases relative SLR locally. Thiéblemont et al. (2024, https://doi.org/10.1029/2024ef004523) reached a remarkable milestone by providing a continental-scale estimate of vertical land motion (VLM) across European coastal zones by utilizing European Ground Motion Service (EGMS) data, obtained from Interferometric Synthetic Aperture Radar (InSAR) data from Sentinel-1 satellites. Their findings reveal widespread coastal subsidence, with nearly half of the coastal floodplains, including major cities and ports, subsiding at rates exceeding 1 mm/yr, thereby exacerbating relative SLR. The study emphasizes the critical role of InSAR-data calibration, indicating that the EGMS geodetic reference frame significantly influences VLM estimates. This study highlights the need for a robust InSAR-data processing framework to accurately interpret VLM and its relationship to relative SLR. The processing pipeline should ensure internal consistency of SAR data and rigorously assess output accuracy, considering also post-processing effects. Correct interpretation of results is essential as InSAR satellites measure reflector movement, which may not always align with land surface movement, particularly in urban areas. Ignoring these discrepancies can lead to underestimation of subsidence rates. While InSAR data offers valuable research opportunities, it poses risks of oversimplification and misinterpretation, especially when linked to sea-level change. We call for standardized processing workflows and cross-disciplinary collaboration, essential for accurate VLM interpretations, particularly in coastal cities and river deltas, to ultimately enhance the reliability of relative SLR projections and inform effective coastal management strategies.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"13 1","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF005539","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143117938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global Impact Assessment of Internal Climate Variability on Maize Yield Under Climate Change","authors":"Guoyong Leng","doi":"10.1029/2024EF004888","DOIUrl":"https://doi.org/10.1029/2024EF004888","url":null,"abstract":"<p>Internal climate variability (ICV) is well-known to mask forced climate change patterns and is thus expected to also impact crop yield trends. To date, a global picture of ICV effect on crop yield projection remains unclear, which inhibits effective adaptation and risk management under climate change. By combining initial condition large ensembles from multiple climate models with machine-learning based crop model emulators, an ensemble of 2002 global maize yield simulations are conducted. The ICV effect is quantified for by the middle and end of 21st century under the business-as-usual scenario. ICV is shown to have significant influence on both the magnitude and sign of future yield change, with relatively higher impact in the top producing countries. The results imply that future yield projections considering relatively limited samples of ICV can be highly misleading as they may, by chance, indicate low yield loss risk in areas which will, instead, be at high risk (or vice versa). Further analysis reveals that the ICV effect is 2.30 ± 0.02 and 1.25 ± 0.03 times larger for yield projections than temperature and precipitation projections, respectively, suggesting an amplification of ICV effect from climate system to agricultural system. This study highlights that crop yield projections are substantially more uncertain than climate projections under the influence of ICV.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"13 1","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF004888","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143117943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-Resolution Downscaling of Disposable Income in Europe Using Open-Source Data","authors":"Mehdi Mikou,&nbsp;Améline Vallet,&nbsp;Céline Guivarch,&nbsp;David Makowski","doi":"10.1029/2024EF004576","DOIUrl":"https://doi.org/10.1029/2024EF004576","url":null,"abstract":"<p>Income maps have been extensively used for identifying populations vulnerable to global changes. The frequency and intensity of extreme events are likely to increase in coming years as a result of climate change. In this context, several studies have hypothesized that the economic and social impact of extreme events depend on income. However, to rigorously test this hypothesis, fine-scale spatial income data is needed, compatible with the analysis of extreme climatic events. To produce reliable high-resolution income data, we have developed an innovative machine learning framework, that we applied to produce a European 1 km-gridded data set of per capita disposable income for 2015. This data set was generated by downscaling income data available for more than 120,000 administrative units. Our learning framework showed high accuracy levels, and performed better or equally than other existing approaches used in the literature for downscaling income. It also yielded better results for the estimation of spatial inequality within administrative units. Using SHAP values, we explored the contribution of the model predictors to income predictions and found that, in addition to geographic predictors, distance to public transport or nighttime light intensity were key drivers of income predictions. More broadly, this data set offers an opportunity to explore the relationships between economic inequality and environmental degradation in health, adaptation or urban planning sectors. It can also facilitate the development of future income maps that align with the Shared Socioeconomic Pathways, and ultimately enable the assessment of future climate risks.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"13 1","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF004576","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Attribution and Risk Projections of Hydrological Drought Over Water-Scarce Central Asia","authors":"Xinfeng Wu,&nbsp;Wenhui Tang,&nbsp;Feng Chen,&nbsp;Shijie Wang,&nbsp;Zulfiyor Bakhtiyorov,&nbsp;Yuxin Liu,&nbsp;Yansong Guan","doi":"10.1029/2024EF005243","DOIUrl":"https://doi.org/10.1029/2024EF005243","url":null,"abstract":"<p>Central Asia (CA), a typical arid and semiarid region, has experienced worsening droughts, adversely impacting agricultural production and socioeconomic development. However, the evolution of hydrological droughts in CA remains unclear. Here, we used instrumental streamflow and reanalysis to demonstrate a decline in surface runoff in CA since the 1990s, with 44.6% and 33.2% of the area dominated by reductions in snowmelt and precipitation, respectively. We found that global warming contributes to the long-term decrease in surface runoff, while short-term fluctuations in surface runoff are caused by the El Niño-Southern Oscillation, such as southern CA drying induced by decreasing precipitation during La Niña. We project the future hydrological drought characteristics based on state-of-the-art global hydrological simulations and found increasing duration and severity of hydrological droughts in CA, especially in the Amu Darya basin, and the Caspian Sea East Coast basin. These increasing droughts are exacerbated by higher anthropogenic emissions, posing high-level risks to 39.01% of land area and 35.9% of human population under an extremely high emissions scenario. These findings highlight the need for improved water conservation technologies and concerted development strategies should be considered by national policy makers in this water-scarce and climatically sensitive region.</p>","PeriodicalId":48748,"journal":{"name":"Earths Future","volume":"13 1","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024EF005243","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}