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    <title>Hydrology and Climate Change Article Summaries</title>
    <link>https://biblio.quintanasegui.com</link>
    <description>Latest scientific summaries</description>
    <lastBuildDate>Thu, 16 Apr 2026 09:04:49 +0000</lastBuildDate>
    
            <item>
                <title>Gan (2026) Data for: Response of the Atlantic Meridional Overturning Circulation Strength to Precessional Forcing</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.17632_jxvmzvzbds.html</link>
                <description><![CDATA[This study investigates the response and variability of the Atlantic Meridional Overturning Circulation (AMOC) strength to orbital precessional forcing using a suite of Earth System Model simulations. The associated dataset provides model output to diagnose AMOC strength and its variability across different precessional phases.]]></description>
                <pubDate>Thu, 16 Apr 2026 05:13:34 +0000</pubDate>
                <guid>10.17632_jxvmzvzbds</guid>
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            <item>
                <title>陈 (2026) Overland flow dynamics on a cracked soil slope under drying-wetting cycles: insights from infrared thermal imaging</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.17632_2hmdkgfrc4.1.html</link>
                <description><![CDATA[This dataset provides experimental measurements of overland flow dynamics on a cracked soil slope under drying-wetting cycles, offering data for insights into these complex hydrological processes.]]></description>
                <pubDate>Thu, 16 Apr 2026 05:13:17 +0000</pubDate>
                <guid>10.17632_2hmdkgfrc4.1</guid>
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                <title>Duan et al. (2026) Land Surface Temperature Shows Negligible Difference Between Inside and Outside Photovoltaic Power Plants in China</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1029_2026jd046444.html</link>
                <description><![CDATA[This study investigates the effects of ground-mounted photovoltaic (PV) power plants on land surface temperature (LST) across China, finding that PV plants generally induce daytime warming (0.10 °C) and nighttime cooling (−0.09 °C), with effects varying by vegetation type and season.]]></description>
                <pubDate>Thu, 16 Apr 2026 05:12:32 +0000</pubDate>
                <guid>10.1029_2026jd046444</guid>
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                <title>Bian et al. (2026) Differential effects of thinning on soil moisture in planted and natural forests: A global meta-analysis</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1016_j.foreco.2026.123794.html</link>
                <description><![CDATA[A global meta-analysis quantified the effects of thinning on soil moisture, finding an overall increase of 7.83%, with natural forests showing a 1.32 times greater response than planted forests. The study highlights differential responses based on forest origin, thinning intensity, soil type, stand age, and climate.]]></description>
                <pubDate>Thu, 16 Apr 2026 05:11:12 +0000</pubDate>
                <guid>10.1016_j.foreco.2026.123794</guid>
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                <title>Yang et al. (2026) Uniformity in Heavy Precipitation Microphysics During the Northward Advancement of Summer Monsoon in China Unveiled by Objective Weather Typing</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1029_2025gl119983.html</link>
                <description><![CDATA[This study isolates canonical East Asian summer monsoon precipitation using objective synoptic classification of satellite observations, revealing its microphysics are highly uniform and dominated by warm-rain accretion across China, in contrast to non-monsoon systems which favor ice-phase processes.]]></description>
                <pubDate>Thu, 16 Apr 2026 05:09:58 +0000</pubDate>
                <guid>10.1029_2025gl119983</guid>
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            <item>
                <title>Bidabadi et al. (2026) Historical diversion-shortfall characterization and verified operational modeling for off-farm operational risk zoning in Jarghuyeh Irrigation District, Iran</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1016_j.ejrh.2026.103443.html</link>
                <description><![CDATA[This study develops a spatially explicit framework to assess off-farm operational risk in the Jarghuyeh Irrigation District under diversion-flow shortfalls and manual canal operation. It reveals pronounced spatial clustering of vulnerability and risk, escalating from low (0-2%) under normal conditions to extreme (up to 35%) under severe stress, highlighting the limited adaptive capacity of the manual system.]]></description>
                <pubDate>Thu, 16 Apr 2026 05:09:30 +0000</pubDate>
                <guid>10.1016_j.ejrh.2026.103443</guid>
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                <title>Khan et al. (2026) Flood Susceptibility Mapping of the Kosi Megafan Using Ensemble Machine Learning and SAR Data</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.3390_rs18081158.html</link>
                <description><![CDATA[This study developed and validated an ensemble machine learning framework for flood susceptibility mapping in the Kosi Megafan, comparing its performance against established models and a 1D-CNN. The stacked ensemble model achieved the highest performance, identifying high-risk zones with strong agreement with observed flood data and assessing the exposed population.]]></description>
                <pubDate>Thu, 16 Apr 2026 05:18:57 +0000</pubDate>
                <guid>10.3390_rs18081158</guid>
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            <item>
                <title>Liu et al. (2026) Microphysical Characteristics of a Squall Line Modulated by the Northeast China Cold Vortex Using Polarimetric Radar and Disdrometer Observations</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.3390_rs18081163.html</link>
                <description><![CDATA[This study comprehensively analyzes the microphysical processes within a Northeast China Cold Vortex (NCCV)-influenced squall line using polarimetric radar and disdrometer data, revealing that convective rain exhibits a continental-type raindrop size distribution (DSD) driven by vigorous ice-phase processes, contrasting with Mei-yu events.]]></description>
                <pubDate>Thu, 16 Apr 2026 05:18:38 +0000</pubDate>
                <guid>10.3390_rs18081163</guid>
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            <item>
                <title>Bechtold et al. (2026) Hourly ISIMIP3b bias-adjusted atmospheric climate input data</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.48364_isimip.170328.html</link>
                <description><![CDATA[This dataset provides hourly CMIP6-based, bias-adjusted atmospheric climate input data, derived by temporally disaggregating daily ISIMIP3b data using the Teddy tool, for use in climate impact analysis.]]></description>
                <pubDate>Wed, 15 Apr 2026 05:18:59 +0000</pubDate>
                <guid>10.48364_isimip.170328</guid>
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            <item>
                <title>Sadeghzadeh et al. (2026) A Paradigm Shift to Automated Machine Learning for Local and External Reference Evapotranspiration Estimation with Uncertainty Implication</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.3390_w18080927.html</link>
                <description><![CDATA[This study evaluates various automated machine learning (AutoML) algorithms coupled with base models for estimating daily reference evapotranspiration (ET0) across three diverse climatic regions. The research demonstrates that hybrid AutoML models significantly improve ET0 estimation accuracy and generalizability compared to standalone models, with optimal performance being dependent on the specific climatic conditions.]]></description>
                <pubDate>Wed, 15 Apr 2026 05:09:43 +0000</pubDate>
                <guid>10.3390_w18080927</guid>
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                <title>Shukla et al. (2026) Atmospheric drivers of the 26 May 2025 heavy rainfall event over mumbai: insights from observations and reanalysis</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1007_s11069-026-08118-5.html</link>
                <description><![CDATA[This study investigates the atmospheric drivers of a very heavy rainfall event (0.18 m in 24 hours) over Mumbai on 26 May 2025, combining observations and reanalysis data. It reveals that the event was caused by a synergistic interaction of early monsoon onset, abundant moisture influx from the Arabian Sea, strong coastal moisture convergence, high atmospheric instability, and the dominance of low-base deep convective clouds.]]></description>
                <pubDate>Tue, 14 Apr 2026 05:06:51 +0000</pubDate>
                <guid>10.1007_s11069-026-08118-5</guid>
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            <item>
                <title>Li et al. (2026) Physics-Prior-Guided Feature Pyramid Network for Unified Multi-Angle Spectral–Polarimetric Cloud Detection</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.3390_rs18081150.html</link>
                <description><![CDATA[This study proposes a novel deep learning framework, the Multi-angle Polarization Feature Pyramid Structure (MP-FPS), to enhance cloud detection by leveraging joint spectral analysis and multi-angle polarization data. Evaluated on the global POLDER-3 dataset, MP-FPS achieves a mean Intersection over Union (mIoU) of 0.8662, surpassing the official baseline by 12.4%.]]></description>
                <pubDate>Thu, 16 Apr 2026 05:20:04 +0000</pubDate>
                <guid>10.3390_rs18081150</guid>
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            <item>
                <title>Alraddawi et al. (2026) Pseudo-Monthly Raman Lidar Dataset for Reference Water Vapor Observations in the UTLS</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.3390_rs18081144.html</link>
                <description><![CDATA[This study evaluates 11 years of pseudo-monthly water vapor mixing ratio (WVMR) profiles from a UV Raman lidar at Réunion Island against MLS-Aura, ERA5, and GRUAN radiosondes, revealing systematic dry biases in MLS and GRUAN relative to the lidar, while ERA5 shows better agreement and is proposed for an alternative lidar calibration.]]></description>
                <pubDate>Thu, 16 Apr 2026 05:19:48 +0000</pubDate>
                <guid>10.3390_rs18081144</guid>
            </item>
            
            <item>
                <title>Li et al. (2026) Spatiotemporal Variability and Dominant Driving Factors of Soil Moisture in the Yellow River Basin from 1982 to 2024</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.3390_agronomy16080791.html</link>
                <description><![CDATA[This study analyzed 43 years of data to assess soil moisture dynamics in the Yellow River Basin, revealing a statistically significant basin-wide decline, spatial variability, and the identification of key climatic drivers, highlighting the risk of ecosystems approaching tipping points.]]></description>
                <pubDate>Wed, 15 Apr 2026 05:05:44 +0000</pubDate>
                <guid>10.3390_agronomy16080791</guid>
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            <item>
                <title>Ying et al. (2026) Warming-driven compound floods from extreme temperature and precipitation in global glacier covered areas</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1016_j.ejrh.2026.103433.html</link>
                <description><![CDATA[This study investigates how global warming intensifies compound flood hazards in glacier regions by enhancing the temporal synchronization of extreme temperature and precipitation, finding that flood magnitudes can increase by over 60% under 3–4 °C warming, particularly for long-duration events.]]></description>
                <pubDate>Tue, 14 Apr 2026 05:05:33 +0000</pubDate>
                <guid>10.1016_j.ejrh.2026.103433</guid>
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            <item>
                <title>Wang et al. (2026) Exploring the effects of antecedent rainfall characteristic on streamflow variability in a karst catchment</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1016_j.ejrh.2026.103440.html</link>
                <description><![CDATA[This study investigates the influence of antecedent rainfall characteristics on streamflow dynamics in a karst catchment using machine learning models. It found that antecedent rainfall, particularly extreme events and consecutive drought days, critically influences streamflow, with climate change being the predominant driver (73.8%) of variability.]]></description>
                <pubDate>Tue, 14 Apr 2026 05:05:12 +0000</pubDate>
                <guid>10.1016_j.ejrh.2026.103440</guid>
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            <item>
                <title>Chen et al. (2026) Reduced Spring Extratropical Cyclone Activity Over the East Asian Subtropical Region has Suppressed Regional Precipitation From 1979 to 2023</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1029_2025jd045731.html</link>
                <description><![CDATA[This study analyzes extratropical cyclone (EC) characteristics and their linkage to precipitation in the East Asian subtropical region during spring (1979–2023), revealing significant decreasing trends in both EC genesis and precipitation, primarily driven by non-uniform near-surface warming that suppresses ECs, subsequently weakening dynamic ascent and moisture transport.]]></description>
                <pubDate>Tue, 14 Apr 2026 05:07:32 +0000</pubDate>
                <guid>10.1029_2025jd045731</guid>
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            <item>
                <title>Rosen et al. (2026) Modelling forest dynamics using integral projection models and repeat lidar</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1002_rse2.70050.html</link>
                <description><![CDATA[This study integrates repeat airborne lidar data with an integral projection model (IPM) to analyze forest-wide demography in response to environmental drivers. It successfully modeled the survival, growth, and life expectancy of approximately 40,000 eucalypt trees over a decade, revealing distinct responses of small and large trees to competition and soil moisture, with drier conditions reducing life expectancy, especially for larger trees.]]></description>
                <pubDate>Tue, 14 Apr 2026 05:04:46 +0000</pubDate>
                <guid>10.1002_rse2.70050</guid>
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            <item>
                <title>Li et al. (2026) Subseasonal Forecasting of Snow Cover and Cold Compound Extremes: Insights From MPAS‐A Over Midlatitude East Asia</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1029_2025jd045631.html</link>
                <description><![CDATA[This study evaluates the subseasonal forecast skill of snow cover and cold compound extremes in midlatitude East Asia using MPAS-A, finding detectable skill up to three pentads, but highlighting that biases from underestimated snowfall and the choice of snow cover fraction scheme significantly impact forecast accuracy.]]></description>
                <pubDate>Mon, 13 Apr 2026 05:04:13 +0000</pubDate>
                <guid>10.1029_2025jd045631</guid>
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            <item>
                <title>Yang et al. (2026) Leaf thermal infrared imaging and lightweight deep learning enable early detection of water stress in watermelon for precision irrigation</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1016_j.agwat.2026.110344.html</link>
                <description><![CDATA[This study proposes a thermal-imaging-based deep learning approach to classify watermelon water-stress status for precision irrigation. It systematically evaluates nine deep learning models, identifying EfficientNet-B0 as the most suitable for field deployment due to its optimal balance of high accuracy (0.99) and computational efficiency (0.39 GFLOPs, 8.81 ms inference latency).]]></description>
                <pubDate>Mon, 13 Apr 2026 05:02:28 +0000</pubDate>
                <guid>10.1016_j.agwat.2026.110344</guid>
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