Hydrologic Responses to Land Use Change in the Loess Plateau: Case Study in the Upper Fenhe River Watershed by Zhixiang Lu, Songbing Zou, Zuodong Qin, Yonggang Yang, Honglang Xiao, Yongping Wei, Kai Zhang, Jiali Xie

“…The main LULC changes in this watershed from 1995 to 2010 were the transformation of farmland into forests, grassland, and built-up land. The simulation results showed that forested land contributed more than any other LULC class to water yield, but built-up land had most impact due to small initial loss and infiltration. …”
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Machine learning-based energy consumption models for rural housing envelope retrofits incorporating uncertainty: A case study in Jiaxian, China by Taoyuan Zhang, Zao Li, Zihuan Zhang, Yulu Chen, Xia Sun

“…Rural housing envelope retrofits significantly affect energy consumption, yet traditional simulation-based assessments are often time intensive and repetitive. …”
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The Effect of Vegetation Ecological Restoration by Integrating Multispectral Remote Sensing and Laser Point Cloud Monitoring Technology by Mengxi Shi, Shuhan Xing, He Bai, Dawei Xu, Lei Shi

“…The research technology was closer to the actual coverage situation. The simulation image showed that the vegetation coverage in the area has significantly improved after returning farmland to forests. …”
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Modeling water and salt migration in groundwater and vadose zones to assess agricultural sustainability in Karamay Irrigation District by Jiawei Ren, Tongkai Guo, Changyan Tian, Wenxuan Mai, Xiaomin Mao

“…To evaluate the influence of groundwater depth and salinity on soil salinization and analyze the sustainability of agricultural development, this study employed a three-dimensional (3D) water and solute transport model (FEFLOW) to simulate water-salt dynamics in both groundwater and vadose zones across cropland, forest land, and desert. …”
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Compressive Strength Prediction Using Coupled Deep Learning Model with Extreme Gradient Boosting Algorithm: Environmentally Friendly Concrete Incorporating Recycled Aggregate by Mayadah W. Falah, Sadaam Hadee Hussein, Mohammed Ayad Saad, Zainab Hasan Ali, Tan Huy Tran, Rania M. Ghoniem, Ahmed A. Ewees

“…In this research, the capability of the deep learning neural network (DLNN) approach is examined on the simulation of CS of EF concrete. The developed approach is compared to the well-known artificial intelligence (AI) approaches named multivariate adaptive regression spline (MARS), extreme learning machines (ELMs), and random forests (RFs). …”
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Response Relationship Between Runoff and Meteorological Drought and Flood Characteristics in Jialing River Basin by LI Wen-hui, ZHANG Yang, CAO Hui, XING Long, REN Yu-feng, ZHAI Shao-jun, MA Yi-ming, LI Wen-da

“…The findings indicate that emerging machine learning models, such as support vector machines and random forests, can effectively simulate the complex mechanisms through which meteorological drought and flood events affect runoff in the river basin. …”
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Stronger Impact of Extreme Heat Event on Vegetation Temperature Sensitivity under Future Scenarios with High-Emission Intensity by Han Yang, Chaohui Zhong, Tingyuan Jin, Jiahao Chen, Zijia Zhang, Zhongmin Hu, Kai Wu

“…For all the three future scenarios, the regions with high vegetation temperature sensitivity were predominantly located in high latitudes of the Northern Hemisphere, the Tibetan Plateau, and tropical forests. In addition, the impact of extreme heat events on vegetation temperature sensitivity was intensified with increasing carbon emission intensity, particularly in the boreal forests and Siberian permafrost. …”
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Bridging the gap: a new module for human water use in the Community Earth System Model version 2.2.1 by S. I. Taranu, D. M. Lawrence, Y. Wada, Y. Wada, T. Tang, T. Tang, E. Kluzek, S. Rabin, Y. Yao, S. J. De Hertog, S. J. De Hertog, I. Vanderkelen, I. Vanderkelen, I. Vanderkelen, W. Thiery

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Implementing deep soil and dynamic root uptake in Noah-MP (v4.5): impact on Amazon dry-season transpiration by C. A. Bieri, F. Dominguez, G. Miguez-Macho, Y. Fan

“…Most existing state-of-the-art Earth system models do not have the necessary features to simulate subsurface-to-atmosphere moisture variations during dry-downs. …”
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Modeling soil water and salinity dynamics in mangrove swamp rice production system of Guinea Bissau, West Africa by Gabriel Garbanzo, Maria do Rosário Cameira, Paula Paredes, Marina Temudo, Tiago B. Ramos

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Potential Impacts of Land Use Change on Ecosystem Service Supply and Demand Under Different Scenarios in the Gansu Section of the Yellow River Basin, China by Yingchen Bai, Conghai Han, Fangying Tang, Zuzheng Li, Huixia Tian, Zhihao Huang, Li Ma, Xuefan Hu, Jianchao Wang, Bo Chen, Lixiang Sun, Xiaoqin Cheng, Hairong Han

“…Firstly, all scenarios project an increase in built-up land, primarily from unused land, shrubland, grassland, and cropland. Forest land and water bodies remain stable. Secondly, water provision increases, but demand grows faster, leading to supply–demand imbalances, with high-risk areas in the north, central, and east. …”
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Spatiotemporal evolution and prediction of land use change and carbon storage in ionic rare earth mining areas based on the YOLOv11–SegFormer–InVEST–PLUS integrated model by Zhenghao Zhu, Shen Zhao, Qiangfeng Li, Zongbin Shi, Yuxuan Wu, Lu Wang

“…The PLUS model further simulates future trajectories under varying scenarios. …”
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Using Machine Learning to Assess the Effects of Biochar-Based Fertilizers on Crop Production and N₂O Emissions in China by Yuan Zeng, Sujuan Chen, Yunpeng Li, Li Xiong, Cheng Liu, Muhammad Azeem, Xiaoting Jie, Mei Chen, Longjiang Zhang, Jianfei Sun

“…The artificial neural network (ANN) model outperformed random forest (RF) and support vector machine (SVM) in predicting N₂O emissions (R²: 0.99; EF: 0.99), while all models showed high accuracy for crop yields (R², EF: 0.98–0.99). …”
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Differential analysis of the quality and soil microhabitat of Epimedium koreanum Nakai under different cultivation methods by Yonggang Zhang, Yonggang Zhang, Huiling Hou, Huiling Hou, Yanxia Li, Yanxia Li, Kexin Li, Kexin Li, Hongmei Lin, Hongmei Lin

“…Rhizosphere microorganisms influence the growth and active component accumulation of medicinal plants; however, the detailed composition, diversity, and connections to soil properties and medicinal herb active components in E. koreanum remain under-researched.MethodsIllumina NovaSeq technology was used to study the differences in rhizosphere microbial diversity and composition and pharmacodynamic constituents among cultivation methods, including wild tending (WT), bionic cultivated in forest (FP), and simulated habitat cultivation (SC).ResultsCompared with estimates for WT, SC and FP resulted in higher contents of active components in E. koreanum. …”
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Depth dependence of soil organic carbon additional storage capacity in different soil types by the 2050 target for carbon neutrality by C. Chirol, C. Chirol, G. Séré, P.-O. Redon, C. Chenu, D. Derrien, D. Derrien

“…The simulated realistic SOC accrual over 25 years in the whole region of study was one-fifth of the the maximum SOC accrual. …”
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Can adaptations of crop and soil management prevent yield losses during water scarcity? A modeling study by M. Heinz, M. Heinz, M. Heinz, M. E. Turek, M. E. Turek, B. Schaefli, B. Schaefli, A. Keiser, A. Holzkämper, A. Holzkämper

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Effect of tropical climates on the quality of commonly used antibiotics: the protocol for a systematic review and meta-analysis by Johnstone Thitiri, Moses Ngari, Christina W Obiero, James A Berkley, Tsegaye Melaku, Sultan Suleman, Gemmechu Hasen, Sileshi Belew, Jimmy Shangala

“…The degree of heterogeneity will be evaluated by the inverse of variance (I2). Forest plots will be used to present the meta-analysis data.Ethics and dissemination Ethical approval is not required as the study is a systematic review. …”
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Assessing national exposure to and impact of glacial lake outburst floods considering uncertainty under data sparsity by H. Chen, Q. Liang, J. Zhao, S. B. Maharjan

“…In the innovative framework, multi-temporal imagery is utilised with a random forest model to extract glacial lake water surfaces. …”
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Future Habitat Shifts and Economic Implications for Ophiocordyceps sinensis Under Climate Change by Liangliang Chen, Hongfen Teng, Songchao Chen, Yin Zhou, Dan Wan, Zhou Shi

“…This study utilizes a comprehensive dataset on O. sinensis occurrences and employs a multi‐model approach (constructed by Classification Tree Analysis [CTA], Flexible Discriminant Analysis [FDA], Generalized Boosted Model [GBM], Generalized Linear Models [GLM], Multivariate Adaptive Regression Splines [MARS], Random Forest [RF], and MaxEnt models) to simulate its potential suitable habitat distribution on the TP under current and future climate change scenarios (SSP1‐2.6 and SSP5‐8.5). …”
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Enhancing Wireless Sensor Network performance: A Novel Adaptive Grid-Based Clustering Hierarchy protocol by Mohammad Ridwan, Teguh Wahyono, Irwan Sembiring, Rini Darmastuti

“…Wireless Sensor Networks (WSNs) are essential for data collection in remote and energy-constrained environments such as forests and deserts. However, traditional clustering protocols like LEACH often face limitations including uneven energy consumption, inefficient Cluster Head (CH) selection, and high communication overhead, which collectively degrade network performance. …”
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