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    <title>Hydrology and Climate Change Article Summaries</title>
    <link>https://biblio.quintanasegui.com</link>
    <description>Latest scientific summaries</description>
    <lastBuildDate>Tue, 15 Sep 2026 06:58:52 +0000</lastBuildDate>
    
            <item>
                <title>Mehr et al. (2026) Improving Meteorological Drought Forecasting Through a CPO ‐Tuned VMD ‐Liquid Neural Network</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1002_joc.70590.html</link>
                <description><![CDATA[The study develops a hybrid CPO-VMD-LNN model for one-month-ahead meteorological drought forecasting, which significantly outperforms SARIMA, LSTM, and standalone LNN models in the Urmia Lake Basin.]]></description>
                <pubDate>Tue, 15 Sep 2026 04:53:33 +0000</pubDate>
                <guid>10.1002_joc.70590</guid>
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                <title>González et al. (2026) Assessing Meteo-HySEA performance for Adriatic meteotsunami events</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1007_s11069-026-08351-y.html</link>
                <description><![CDATA[This study evaluates the new Meteo-HySEA model against the AdriSC-ADCIRC system for simulating meteotsunamis in the Adriatic Sea, finding that Meteo-HySEA effectively captures sea-level oscillation dynamics and is suitable for operational forecasting.]]></description>
                <pubDate>Mon, 14 Sep 2026 07:25:43 +0000</pubDate>
                <guid>10.1007_s11069-026-08351-y</guid>
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                <title>Talpur et al. (2026) Hydroclimatic variability and trend analysis of the Arno River basin, Tuscany, Italy</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1007_s40899-026-01399-5.html</link>
                <description><![CDATA[This study analyzes hydroclimatic trends in the Arno River basin from 1994 to 2023, identifying significant warming in summer and autumn but no significant monotonic trends in precipitation or streamflow.]]></description>
                <pubDate>Mon, 14 Sep 2026 05:42:06 +0000</pubDate>
                <guid>10.1007_s40899-026-01399-5</guid>
            </item>
            
            <item>
                <title>Eltahir et al. (2026) Horizon-Dependent Solar Irradiance Forecasting with Boosted Trees, and Seasonal Baselines Based on Measurements in Sudan</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.3390_s26185778.html</link>
                <description><![CDATA[The study proposes a leakage-safe, horizon-specific forecasting framework for solar irradiance, demonstrating that boosted trees are most effective for short-term predictions while seasonal combinations prevail at longer lead times.]]></description>
                <pubDate>Mon, 14 Sep 2026 07:13:00 +0000</pubDate>
                <guid>10.3390_s26185778</guid>
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            <item>
                <title>Unknown (2026) Multilayer soil moisture deficit amplifies drought impacts on global ecosystems</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1038_s41561-026-02082-2.html</link>
                <description><![CDATA[The study finds that droughts are significantly more damaging when moisture deficits occur simultaneously across multiple soil layers, as this eliminates vertical hydrological buffering and threatens global carbon uptake.]]></description>
                <pubDate>Sat, 12 Sep 2026 06:44:22 +0000</pubDate>
                <guid>10.1038_s41561-026-02082-2</guid>
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            <item>
                <title>Cloutier-Gervais et al. (2026) Evaluation of the Canadian Regional Climate Model in Simulating Extratropical Cyclones Over Northeastern North America</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1029_2026jd046756.html</link>
                <description><![CDATA[This study evaluates the Canadian regional climate model (CRCM) v6 in simulating extratropical cyclones (ETCs) over northeastern North America, demonstrating that a 2.5-km convection-permitting configuration improves the representation of extreme precipitation and wind speed biases compared to a 12-km configuration.]]></description>
                <pubDate>Sat, 12 Sep 2026 06:32:07 +0000</pubDate>
                <guid>10.1029_2026jd046756</guid>
            </item>
            
            <item>
                <title>Huang et al. (2026) Ecological drought evolution analysis and risk assessment based on three-dimensional Copula function and cloud model</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.2166_hydro.2026.100.html</link>
                <description><![CDATA[The study develops an Ecological Drought Index (EDI) using a three-dimensional Copula function to analyze the spatiotemporal patterns and risk uncertainties of ecological droughts in the Yellow River Basin.]]></description>
                <pubDate>Sat, 12 Sep 2026 06:02:07 +0000</pubDate>
                <guid>10.2166_hydro.2026.100</guid>
            </item>
            
            <item>
                <title>Ahmed et al. (2026) Three decades of vegetation change in Jabel Marra: climate drivers and post-conflict vegetation dynamics</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1007_s12665-026-13109-7.html</link>
                <description><![CDATA[This study analyzed vegetation dynamics in the Jabel Marra region of Sudan from 1994 to 2024, finding a significant increase in greenness primarily driven by precipitation and temperature variability.]]></description>
                <pubDate>Sat, 12 Sep 2026 05:36:36 +0000</pubDate>
                <guid>10.1007_s12665-026-13109-7</guid>
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            <item>
                <title>Moradian et al. (2026) Climate change intensifies the temporal persistence of droughts through a shift from seasonal to prolonged drought regimes</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1007_s44274-026-01028-0.html</link>
                <description><![CDATA[This study analyzes the temporal symmetry and persistence of global meteorological droughts using CMIP6 projections, finding a transition from seasonal droughts toward more persistent, multi-year drought regimes under future climate scenarios.]]></description>
                <pubDate>Sat, 12 Sep 2026 04:53:41 +0000</pubDate>
                <guid>10.1007_s44274-026-01028-0</guid>
            </item>
            
            <item>
                <title>Qian et al. (2026) Asymmetric Relationship Between the East China September Precipitation and El Niño‐Southern Oscillation in the Decaying Phases Over the Past Three Decades</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1002_joc.70584.html</link>
                <description><![CDATA[This study examines the asymmetric impact of decaying El Niño and La Niña events on September precipitation in East China, finding that La Niña leads to significant precipitation deficits while El Niño results in weak positive anomalies.]]></description>
                <pubDate>Fri, 11 Sep 2026 06:03:43 +0000</pubDate>
                <guid>10.1002_joc.70584</guid>
            </item>
            
            <item>
                <title>Yasmeen et al. (2026) An adaptive deep learning framework for multi-temporal crop and drought stress monitoring in precision agriculture</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1038_s41598-026-70304-z.html</link>
                <description><![CDATA[The study proposes a hybrid deep learning framework combining Convolutional Neural Networks (CNN) and Vision Transformers (ViT) to monitor crop and drought stress using multi-temporal Sentinel-2 satellite imagery.]]></description>
                <pubDate>Fri, 11 Sep 2026 05:52:53 +0000</pubDate>
                <guid>10.1038_s41598-026-70304-z</guid>
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            <item>
                <title>Toe et al. (2026) Machine Learning-Based Reconstruction of Missing Meteorological Observations Using Reanalysis and Satellite Data in West Africa</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.3390_atmos17090884.html</link>
                <description><![CDATA[This study develops a machine learning framework to reconstruct missing hourly meteorological data in West Africa by integrating in situ AWS observations with ERA5-Land reanalysis and GPM satellite products.]]></description>
                <pubDate>Fri, 11 Sep 2026 04:53:39 +0000</pubDate>
                <guid>10.3390_atmos17090884</guid>
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            <item>
                <title>Massari et al. (2026) Detecting Irrigation From Spectral Differences Between Satellite and Modeled Soil Moisture Across the Contiguous United States</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1029_2026gl123183.html</link>
                <description><![CDATA[The study presents a wavelet-based method to detect irrigation by analyzing spectral differences between Noah-MP model simulations and SMOS satellite soil-moisture observations across the contiguous United States.]]></description>
                <pubDate>Thu, 10 Sep 2026 05:07:12 +0000</pubDate>
                <guid>10.1029_2026gl123183</guid>
            </item>
            
            <item>
                <title>Adamo et al. (2026) Soil Moisture, Irrigation Actuator and Weather Dataset from a Multi-Sector Precision-Irrigation</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.17632_c837v6p8ph.html</link>
                <description><![CDATA[This dataset provides high-resolution soil moisture, weather, and irrigation actuator telemetry from a multi-crop precision-irrigation farm in Italy to facilitate the development of actionable irrigation management models.]]></description>
                <pubDate>Tue, 08 Sep 2026 06:54:40 +0000</pubDate>
                <guid>10.17632_c837v6p8ph</guid>
            </item>
            
            <item>
                <title>Afzal et al. (2026) Contrasting roles of climate change and land-use change on runoff dynamics in a semi-humid monsoon watershed of China</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1038_s41598-026-67812-3.html</link>
                <description><![CDATA[This study quantifies the individual and combined impacts of climate variability and land-use change on runoff in the Dongwan Watershed, China. It finds that climate change is the primary driver of runoff dynamics, while land-use change acts as a secondary, moderating factor.]]></description>
                <pubDate>Tue, 08 Sep 2026 06:11:25 +0000</pubDate>
                <guid>10.1038_s41598-026-67812-3</guid>
            </item>
            
            <item>
                <title>Nash et al. (2026) Annual and Seasonal Rainfall Variability in Mozambique During the Nineteenth Century</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1002_joc.70578.html</link>
                <description><![CDATA[This study presents the first annually and seasonally resolved documentary rainfall reconstructions for Mozambique from 1817 to 1900, revealing significant spatial-temporal variability and non-stationary relationships with ENSO.]]></description>
                <pubDate>Tue, 08 Sep 2026 05:56:35 +0000</pubDate>
                <guid>10.1002_joc.70578</guid>
            </item>
            
            <item>
                <title>Jiang et al. (2026) Impacts of Urbanization on Compound Heat and Drought Events in the Beijing–Tianjin–Hebei Region Based on Explainable Machine Learning</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.3390_land15091649.html</link>
                <description><![CDATA[This study quantifies the impact of urbanization on compound heat and drought events (CHDEs) in the Beijing–Tianjin–Hebei region, finding that urban expansion significantly increases the frequency, duration, and severity of these events.]]></description>
                <pubDate>Wed, 09 Sep 2026 06:05:41 +0000</pubDate>
                <guid>10.3390_land15091649</guid>
            </item>
            
            <item>
                <title>Morales et al. (2026) Soil Moisture Persistence and Integrated Drought-State Variability in a Semi-Arid Andean Region</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.3390_hydrology13090237.html</link>
                <description><![CDATA[This study examines soil moisture persistence and coupled drought-state variability in the southern Peruvian Andes to improve drought monitoring. It introduces an Integrated Drought State (IDS) index to synthesize the delayed responses of land-surface conditions relative to precipitation anomalies.]]></description>
                <pubDate>Wed, 09 Sep 2026 05:53:52 +0000</pubDate>
                <guid>10.3390_hydrology13090237</guid>
            </item>
            
            <item>
                <title>Tantray et al. (2026) Enhancing soil hydrothermal efficiency through spectral-selective mulching and drip irrigation in broccoli (Brassica oleracea var. italica L.)</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1186_s12870-026-09860-5.html</link>
                <description><![CDATA[This study evaluates the impact of various mulching materials on soil properties and broccoli yield, finding that silver plastic mulch optimizes productivity while organic mulch enhances soil health.]]></description>
                <pubDate>Sun, 06 Sep 2026 09:13:50 +0000</pubDate>
                <guid>10.1186_s12870-026-09860-5</guid>
            </item>
            
            <item>
                <title>Shen et al. (2026) SMFS-RF: a knowledge-guided machine-learning method for crop phenology extraction from fine-resolution vegetation index data</title>
                <link>https://biblio.quintanasegui.com/summaries/2026/10.1016_j.rse.2026.115632.html</link>
                <description><![CDATA[The study introduces SMFS-RF, a knowledge-guided machine learning framework that combines shape model fitting with random forest regression to accurately extract eight key rice phenological stages from fine-resolution NDVI data.]]></description>
                <pubDate>Sun, 06 Sep 2026 06:49:34 +0000</pubDate>
                <guid>10.1016_j.rse.2026.115632</guid>
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