Uncertainty analysis in river quality management considering failure probability: controllable and uncontrollable input pollutants by Mohsen Dehghani Darmian, Britta Schmalz

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Spatiotemporal Variation Characteristics of Water Pollution and the Cause of Pollution Formation in a Heavily Polluted River in the Upper Hai River by Chunfang Meng, Xiaoyu Song, Kening Tian, Bingxiao Ye, Tianxiu Si

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Soil Erosion Estimation Using Remote Sensing Techniques in Wadi Yalamlam Basin, Saudi Arabia by Jarbou A. Bahrawi, Mohamed Elhag, Amal Y. Aldhebiani, Hanaa K. Galal, Ahmad K. Hegazy, Ebtisam Alghailani

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Modelling Socio-Environmental Sensitivities: How Public Responses to Low Carbon Energy Technologies Could Shape the UK Energy System by Brighid Moran Jay, David Howard, Nick Hughes, Jeanette Whitaker, Gabrial Anandarajah

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Ecosystem Health Assessment and Driving Factor Analysis of Panjin Reach of Liaohe River Basin Based on PSR Model by YANG Heqing, HU Huiqin, ZHANG Qinxu, QIN Mengen, ZHANG Mingliang, HOU Jun

“…To evaluate the ecosystem health of Panjin reach in the Liaohe River Basin,based on the data collected from 2010 to 2020 in the study area,this paper adopts a pressure-state-response (PSR) evaluation model and selects 13 evaluation indicators.The entropy weight method is introduced to calculate the weight,and the fuzzy relation matrix method is adopted to calculate the membership degree.As a result,the comprehensive evaluation index (CEI) in the Panjin section of the Liaohe River is obtained,and then the ecosystem health of the study area is evaluated.The results show that the CEI indexes of this area from 2010 to 2020 are 0.343,0.341,0.279,0.425,0.418,and 0.464 respectively,and the overall ecosystem health changes from an “unhealthy” level to a “generally healthy” level.This study indicates that the total volume of water resources,policies and regulations,construction of protected areas,landscape diversity index,industrial wastewater discharge,and chemical oxygen demand in water have a great influence on the ecosystem health of the study area,with the weight values of 0.209 7,0.179 7,0.141 9,0.136 8,and 0.106 3 respectively.The overall weight of hydrologic and water environment factors involved in all the indicators is 0.620 7,with the effect degree more than half of all indicators.These hydrologic and water environment factors play a more direct role in this area.Therefore,the ecosystem health improvement in the study region requires management and remediation from the perspective of hydrology and the water environment.Thus,to improve the ecosystem health of the study area,it is necessary to carry out the management and regulation from the perspectives of hydrology and the water environment.…”
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Streamflow and sediment simulation in the Song River basin using the SWAT model by Shams Quamar, Pradeep Kumar, Harendra Prasad Singh

“…Thirteen parameters were selected for calibration, with eight identified as highly sensitive, reflecting key hydrological processes of the area. The model was calibrated for the period 1974–1995 and validated from 1996 to 2004, with additional testing using field data collected in 2022–2023 through Acoustic Doppler Current Profiler (ADCP) measurements. …”
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Statistics and Analysis of the Relations between Rainstorm Floods and Earthquakes by Baodeng Hou, Yongxiang Wu, Jianhua Wang, Kai Wu, Weihua Xiao

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Lauric Acid-Modified Nitraria Seed Meal Composite as Green Carrier Material for Pesticide Controlled Release by Bo Bai, Xiaohui Xu, Jingjie Hai, Na Hu, Honglun Wang, Yourui Suo

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Improved urban runoff prediction using high-resolution land-use, imperviousness, and stormwater infrastructure data applied to a process-based ecohydrological model. by Jonathan Halama, Robert McKane, Bradley Barnhart, Paul Pettus, Allen Brookes, Kevin Djang, Vivian Phan, Sonali Chokshi, James Graham

“…The results demonstrate that the newly improved VELMA model allows for more accurate modeling of hydrology within urban watersheds. Being a fate and transport ecohydrology model, the improved hydrologic flow enhances VELMA's current capacity for modeling nutrient, contaminant, and thermal loadings.…”
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Application of Multi-Criteria Decision-Making Models for Assessment of Education Quality in Water Resources Engineering by Mohammad Kazem Ghorbani, Nasser Talebbeydokhti, Hossein Hamidifar, Mehrshad Samadi, Michael Nones, Fatemeh Rezaeitavabe, Shabnam Heidarifar

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Complexity to Forecast Flood: Problem Definition and Spatiotemporal Attention LSTM Solution by Yirui Wu, Yukai Ding, Yuelong Zhu, Jun Feng, Sifeng Wang

“…Considering the significance of modeling attention capability among hydrology factors, we believe extraction of discriminative hydrology factors not only reflect natural rules in physical space, but also optimally model iterations of factors to forecast run-off values in cyber space. …”
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Innovative Research for Geofluid Flow and Solute Transport in Subsurface from Pore to Terrestrial Scales by Jet-Chau Wen, Walter A. Illman, Shujun Ye, Tianchyi Yeh

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Root growth dynamics and allocation as a response to rapid and local changes in soil moisture by S. Ceolin, S. Ceolin, S. J. Schymanski, S. J. Schymanski, D. van Dusschoten, R. Koller, J. Klaus

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Assessing the irrigation water requirement and irrigation water use at a house scale in Las Vegas Valley by Rubab Saher, Thomas Ott

“…Urban irrigation water requirement is a crucial yet uncertain part of urban hydrology. One of the primary reasons is the need for a high-resolution dataset to model the irrigation water requirement. …”
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Controls of lithology and climate over chemical weathering trends: new insights from the precipitation-dominated Dokriani glacier, central Himalaya, India by Shipika Sundriyal, Tanuj Shukla, Shichang Kang, Yulan Zhang, Dwarika Prasad Dobhal, Rajesh Singh

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Attribution Identification of Runoff Changes Based on the Budyko Elasticity Coefficient Method: A Case Study of the Middle and Upper Reaches of the Jinghe River in the Yellow River... by Xueliang Wang, Haolin Li, Weidong Huang, Lemin Wei, Junfeng Liu, Rensheng Chen

“…The Sen’s slope estimator and the Mann–Kendall test (M–K test) are implemented to examine the spatial and temporal trends of the hydrological factors, while the elasticity coefficient method based on Budyko’s theory of hydrothermal coupling is employed to quantify the degree of runoff response to the various influencing factors, from 1971 to 2020. …”
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Land use cover changes abated terrestrial ecosystem carbon sink in China during the past four decades by Xueqing Jiang, Jinxun Liu, Changhui Peng, Huai Chen, Le Wang, Dongxue Yu, Qiuan Zhu

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Causes of the exceptionally high number of fatalities in the Ahr valley, Germany, during the 2021 flood by B. Rhein, B. Rhein, H. Kreibich

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Florida’s Seepage Slope Wetlands by Megan E. Brown, Debbie L. Miller

“…Florida is home to one of North America’s most unique and diverse ecosystems, the seepage slope. Unusual hydrology and frequent fires combine to create an environment that supports a variety of carnivorous and other sun-loving herbaceous plants. …”
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Florida’s Seepage Slope Wetlands by Megan E. Brown, Debbie L. Miller

“…Florida is home to one of North America’s most unique and diverse ecosystems, the seepage slope. Unusual hydrology and frequent fires combine to create an environment that supports a variety of carnivorous and other sun-loving herbaceous plants. …”
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