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Factors affecting the crop's water footprint to optimize the water use efficiency in the Gaza strip, Palestine

Journal of water and Climate Change 2025年第4期16卷 1443-1458页

作者： Mizyed, Amjad Mogheir, Yunes Hamada, Mazen S. Water Technology joint program Islamic University of Gaza al-Azhar University of Gaza Gaza Palestine Water Resources and Environment – Civil and Environmental Engineering Islamic University of Gaza Gaza Palestine Chemistry Department – Faculty of Science Al Azhar University Gaza Strip Palestine

The agricultural sector in the Gaza Strip consumes more than 51% of the available water, leading to a massive deficit in the water budget. This study employs the water footprint concept as an innovative tool for effective water resources management. It examines the impact of several factors on nine basic crops (olives, citrus, grapes, wheat, tomatoes, potatoes, eggplant, squash, and cucumber) in the aspects of irrigation water consumption, climate parameters, crop patterns, virtual water trade, and achieving the best profits using the CROPWAT program and developing a linear programming model that combines economic benefit and water footprint. The best optimization was attained by changing crop pattern cultivation, as it achieved food security and optimized by 33% the use of green water. Also, the consumption of blue water was reduced by 29.4 million m3 (37%), as well as the productivity of water units increased to 18.5 $/m3 for eggplant, followed by potatoes at 13.9 $/m3, tomatoes at 9.25 $/m3, and cucumbers at 8.74 $/m3. The water footprint has proven its effectiveness in increasing water use efficiency and is considered an effective tool in planning for sustainable water management. © 2025 The Authors.

关键词： Irrigation

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Soil moisture and evapotranspiration responses to precipitation uncertainty using Noah-MP land surface model

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Stochastic environmental Research and Risk Assessment 2025年 1-20页

作者： Lee, Seulchan Park, Jongmin Jeong, Jaehwan Choi, Minha Department of Water Resources Graduate School of Water Resources Sungkyunkwan University Suwon16419 Korea Republic of Division of Environmental Engineering Korea National University of Transportation Chungju27469 Korea Republic of Agriculture-Forestry Bioresources Convergence Center Seoul National University Seoul08826 Korea Republic of School of Civil Architectural Engineering & Landscape Architecture Sungkyunkwan University Suwon16419 Korea Republic of

Accurate precipitation data are crucial for hydrological modeling, particularly in regions with significant climatic variability such as Monsoon Asia. This study assesses the performance of five precipitation products, integrated multi-satellite retrievals for GPM (IMERG), climate hazards group infrared precipitation with station data (CHIRPS), Global Data Assimilation System (GDAS), modern-era retrospective analysis for research and applications, version 2 (MERRA2), and MERRA2 with in-situ corrected precipitation (MERRA2-C) as input forcing in the Noah-MP land surface model (LSM). We also investigate how errors in these precipitation datasets propagate to simulated soil moisture (SM) and evapotranspiration (ET) by analyzing the metric, which is defined as the ratio of the normalized and centered root mean square error (NCRMSE) values of simulated variables to precipitation. The results show that MERRA2-C consistently outperforms the others with the lowest RMSE (3.14 mm/day), the highest Kling–Gupta Efficiency (KGE = 0.56), and the lowest false alarm ratio (FAR = 0.08). Error propagation analysis reveals that high precipitation errors do not always result in proportionally high SM and ET errors, as the propagation rate varies by climate zone, land cover, and topography. Errors propagate more to SM (mean = 0.60) than to ET (0.52), particularly in regions with greater porosity and steep terrains, while ET is more affected by precipitation errors in urban areas. Additionally, small precipitation errors and lower detection capability of light precipitation events in dry regions can lead to significant deviations in SM, while ET is more susceptible in wetter regions. These findings highlight the importance of not only improving precipitation data quality but also refining the LSM’s response to these inputs to enhance the accuracy and reliability of hydrological simulations. © The Author(s) 2025.

关键词： Soil moisture

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The Effect of Building with Nature Structure on Estuary Mitigation: A Case Study of Muara Beting Beach, Muara Gembong, Indonesia 7th

The Effect of Building with Nature Structure on Estuary Miti...

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7th International Conference on Civil engineering and Architecture, ICCEA 2024

作者： Wulandari, Siska Nugroho, Eka Oktariyanto Nugroho, Joko Cahyono, Muhammad Saurena, Alfandias Widyaningtias Asferizal, Ferial Master Program of Water Resource Engineering Faculty of Civil and Environmental Engineering Institut Teknologi Bandung Jl. Ganesha No. 10 Bandung 40132 Indonesia Water Resources Engineering Research Group Faculty of Civil and Environmental Engineering Institut Teknologi Bandung Jl. Ganesha No. 10 Bandung 40132 Indonesia Ministry of Public Works and Housing Jalan Pattimura 20 Jakarta Indonesia Department of Integrated Water Management Engineering Institut Teknologi Sumatera Lampung Indonesia

ISBN: (纸本)9789819661145

The Muara Beting coastal area on the north coast of Java, Indonesia, faces coastal erosion processes that gradually affect the decrease of mangrove land. That process causes the land to be extremely eroded and become closer to the Citarum River. The seawater intrusion occurs within the decreasing land mangroves. If erosion persists, the increased seawater intrusion might result in the convergence of the pond area with the Citarum River. This study aims to simulate and analyze how the “Building with Nature” building can be applied as a mitigation strategy through Delft3D simulations. Data was collected through field surveys, satellite image analysis, and library observations to evaluate the impact of the proposed solutions. The simulations used bathymetry, sediment characteristics, wind, tide, and river discharge measurements for input data. Apart from simulating natural conditions, several scenarios were also arranged based on the placement of permeable structures combined with the floodway. The best scenario was selected from where cumulative sedimentation and erosion and the cross-sectional depth show best. This study's findings will be intended to assist Muara Beting’s coastal community in reconstructing pond land that has been harmed by coastal erosion, allowing the locals to carry on with their pond-related livelihoods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Building with Nature Coastal erosion Delft3D Muara Beting sedimentation

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Response of bacterial communities and soil chemistry to flood durations and recovery phases

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environmental Science and Pollution Research 2025年第15期32卷 9429-9442页

作者： Sao, Sochan Praise, Susan Nishiyama, Masateru Ann, Vannak Phung, Luc Duc Watanabe, Toru The United Graduate School of Agricultural Sciences Iwate University 18-8 Ueda 3-Chome Iwate Morioka020-8550 Japan Faculty of Hydrology and Water Resources Engineering Institute of Technology of Cambodia PO Box 86 Russian Federation Blvd Phnom Penh120404 Cambodia Department of Food Life and Environmental Sciences Faculty of Agriculture Yamagata University 1-23 Wakaba-Machi Yamagata Tsuruoka997-8555 Japan

Flooding profoundly impacts soil bacterial communities;however, the underlying mechanisms remain poorly understood. This study investigated how flooding (3, 8, and 16 days) and post-flooding (immediately and 2, 5, and 30 days) durations affect soil physicochemical properties, bacterial communities, and their interactions—crucial factors in floodplain nutrient and carbon cycling. The results showed that bacteria constituted 99.9% of the total microbial composition, while archaea, contributing only 0.1%, had a negligible impact on soil traits. At 2–5 days after flooding (DAF), elevated soil electrical conductivity (EC) and pH enhanced soil bacterial abundance and activity, leading to increased water-extractable dissolved organic carbon (DOC), water-extractable total dissolved nitrogen, and biological production (BIX), accompanied by the degradation of soil organic matter (SOM) and aromatic compounds (SUVA254). These changes indicated robust interactions between soil bacterial communities and physicochemical properties affected by flooding events. However, these relationships weakened at 30 DAF, suggesting potential transitions from anaerobic to aerobic conditions in post-flooding soils after 5 DAF. Structural equation modelling indicated that an extended post-flooding duration increased BIX, accompanied by SOM and DOC degradation, providing nutrients and energy to soil microbes and consequently leading to increased bacterial diversity. This study underscores the significant impact of flooding and post-flooding durations on soil bacterial community composition and diversity, mediated by changes in EC, pH, SOM, and DOM, potentially influencing nutrient cycling in floodplains. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Physicochemical properties

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Drought propagation in an Andean basin in South America: a spatio-temporal analysis approach with monitoring indices

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Arabian Journal of Geosciences 2025年第3期18卷 1-21页

作者： Ocampo-Marulanda, Camilo Mera-Franco, Julián David Lizcano, Víctor Augusto Carvajal-Escobar, Yesid Canchala, Teresita Zorrilla-Millan, Daniel Felipe Caicedo-Bravo, Eduardo Water Resources Engineering and Soil Research Group (IREHISA) School of Natural Resources and Environmental Engineering Universidad del Valle Cali Colombia Graduate Program in Biometrics and Applied Statistics Department of Statistics and Informatics Federal Rural University of Pernambuco Recife Brazil School of Exact Sciences and Engineering Universidad Sergio Arboleda Bogotá Colombia Programa de Ingeniería Ambiental Facultad de Ingeniería Universidad Mariana Pasto Colombia School of Electrical and Electronic Engineering Universidad del Valle Cali Colombia

Drought is a climatic phenomenon that has increased in severity over time. This study analyzed drought spread in the Alto Patía basin (13,047 km2) in South America, applying the Standardized Precipitation Index (SPI), Vegetation Health Index (VHI), and Streamflow Drought Index (SDI) to assess meteorological, agricultural, and hydrological drought, respectively. Synchronous and asynchronous correlations were estimated, and Wavelet analysis was conducted to verify relationships among drought types. Results show that the lag between drought types varies based on the intensity, temporal continuity, and spatial extent of meteorological drought. A lag of zero months (1–2 months) was observed between meteorological and hydrological drought when moderate (severe) meteorological drought partially (fully) covers the basin. Agricultural drought, however, does not always correspond to meteorological drought during isolated rainfall events. As the first study in Colombia to systematically connect these drought types, this research addresses a gap in understanding how drought impacts progress across systems in regions with complex rainfall patterns. These findings offer critical insights into the interdependencies among drought types, supporting enhanced drought monitoring and early warning systems in similar climatic regions. By identifying specific lags between meteorological and hydrological droughts, this study provides practical guidance for land management, water conservation, and crop planning, offering a foundation for future research on drought resilience strategies.

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Leveraging historical datasets to quantify the recovery of an impaired stream entering Yellowstone National Park

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Discover Conservation 2025年第1期2卷 1-22页

作者： Ray, Andrew M. Yoder, Alysa M. Ertel, Brian D. Henderson, Tom H. Mebane, Christopher A. National Park Service Bozeman USA National Park Service Pecos USA Hydrologic Sciences Graduate Group Department of Land Air and Water Resources University of California Davis USA U.S. Geological Survey Oregon Water Science Center Bend USA National Park Service Yellowstone Center for Resources Native Fish Conservation Program Yellowstone National Park USA Montana Department of Environmental Quality Abandoned Mine Lands Program Helena USA Boise USA

environmental impacts from surface mining can extend beyond the lifetime of mining operations, persist for decades prior to formal clean-up, and span multiple jurisdictional boundaries. Using a case study from Soda Butte Creek which enters Yellowstone National Park, we demonstrate how existing datasets and longitudinal studies can be integrated to document early stages of recovery following reclamation. Nearly three decades of previous studies provided a baseline for biological and water quality impairments from a former mill and tailings site. Direct comparisons of water quality data, macroinvertebrate community summaries, and fish abundance data from references reaches and common locations pre- and post-reclamation were used to quantify whether desired ecological benchmarks were met and characterize rates of recovery. Our results indicated that response times of water quality, macroinvertebrates, and fish to reclamation were relatively rapid and measured in years rather than decades. Specifically, concentrations of total metals below the former mill and tailings site were lower than pre-reclamation levels. Five years post reclamation (2015 to 2019), median total iron concentrations were just 3% of levels measured the decade (2000 to 2010) before reclamation began. Macroinvertebrate metrics (richness and abundance of sensitive groups) below the former mill and tailing sites were formerly a fraction of reference conditions. Post-reclamation, total taxa richness and stonefly abundance estimates at the formerly impaired site were equal to the mean multi-reach proportional estimates for other mainstem reference sites. Lessons learned from Soda Butte Creek could be used to inform and support other data-driven assessment work.

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Estimation of Flood Inundation Area Using Soil Moisture Active Passive Fractional water Data with an LSTM Model

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Sensors 2025年第8期25卷 2503-2503页

作者： Febrian, Rekzi D. Kim, Wanyub Lee, Yangwon Kim, Jinsoo Choi, Minha Department of Global Smart City Sungkyunkwan University Suwon440-746 Korea Republic of Major of Geomatics Engineering Division of Earth Environmental System Science Pukyong National University Busan48513 Korea Republic of Department of Water Resources Graduate School of Water Resources Sungkyunkwan University Suwon440-746 Korea Republic of School of Civil Architectural Engineering & Landscape Architecture Sungkyunkwan University Suwon440-746 Korea Republic of

Highlights: What are the main findings? High performance of area under the curve (AUC) and confusion-matrix-based evaluation index from an LSTM model. Complex terrain and dense vegetation reduce flood detection performance. What is the implication of the main finding? A high accuracy estimation of fractional water (FW) in areas near water bodies. Fluctuations in measured FW and producing a false positive (FP) and false negative (FN) detection. Accurate flood monitoring and forecasting techniques are important and continue to be developed for improved disaster preparedness and mitigation. Flood estimation using satellite observations with deep learning algorithms is effective in detecting flood patterns and environmental relationships that may be overlooked by conventional methods. Soil Moisture Active Passive (SMAP) fractional water (FW) was used as a reference to estimate flood areas in a long short-term memory (LSTM) model using a combination of soil moisture information, rainfall forecasts, and floodplain topography. To perform flood modeling in LSTM, datasets with different spatial resolutions were resampled to 30 m spatial resolution using bicubic interpolation. The model’s efficacy was quantified by validating the LSTM-based flood inundation area with a water mask from Senti-nel-1 SAR images for regions with different topographic characteristics. The average area under the curve (AUC) value of the LSTM model was 0.93, indicating a high accuracy estimation of FW. The confusion matrix-derived metrics were used to validate the flood inundation area and had a high-performance accuracy of ~0.9. SMAP FW showed optimal performance in low-covered vegetation, seasonal water variations and flat regions. The estimates of flood inundation areas show the methodological promise of the proposed framework for improved disaster preparedness and resilience. © 2025 by the authors.

关键词： Soil moisture

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The enhanced integration of proven techniques to quantify the uncertainty of forecasting extreme flood events based on numerical weather prediction models

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Weather and Climate Extremes 2025年 48卷

作者： Tanhapour, Mitra Soltani, Jaber Shakibian, Hadi Malekmohammadi, Bahram Hlavcova, Kamila Kohnova, Silvia Valent, Peter Department of Water Engineering Faculty of Agricultural Technology University College of Agriculture & Natural Resources University of Tehran Tehran *** Iran Department of Land and Water Resources Management Faculty of Civil Engineering Slovak University of Technology Bratislava 81005 Slovakia Department of Computer Engineering Faculty of Engineering Alzahra University Tehran *** Iran Department of Environmental Planning and Management Graduate Faculty of Environment University of Tehran Tehran *** Iran Institute of Hydraulic Engineering and Water Resources Management TU Wien Vienna 1040 Austria

Skillful forecasting of reservoir inflow is one of the main prerequisites for determining reservoir operation and management policies. This research incorporates proven techniques in a novel way to develop a comprehensive framework for forecasting event-based inflow floods with sub-daily time steps (6-h intervals), considering the uncertainty of Numerical Weather Prediction (NWP) models. Accordingly, raw precipitation forecasts were extracted for six extreme flood events in the Dez River basin, Iran. A Multi-Model Ensemble (MME) system was developed using the Group Method of Data Handling (GMDH) and Weighted Average-Weighted Least Square Regression (WA-WLSR) models to post-process raw precipitation forecasts. We thereupon proposed an approach that combined the Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrological model with the Long-Short Term Memory (LSTM) network (HBV-LSTM model) to enhance flood forecasting. Moreover, a comparative analysis was performed between the modeling approaches, i.e., probabilistic inflow forecasting and deterministic inflow forecasting. The results revealed that the forecasting skill of the MME model built using the WA-WLSR model was higher than that of the GMDH model. Accordingly, the highest Continuous Ranked Probability Skill Scores (CRPSS) of 0.61 and 0.67 were achieved by the GMDH and WA-WLSR models, respectively, based on a precipitation threshold of 10 mm. Additionally, both the HBV-LSTM model and the LSTM network outperformed the individual HBV model in producing inflow flood hydrographs. Based on the best flood forecasting approach, i.e., the HBV-LSTM model, the NSE exceeded 0.95, and the NRMSE remained below 0.09 for various flood events. The outcomes indicated a variability of 2–10 % in the relative peak error using the HBV-LSTM approach for different flood events. Our findings provide valuable insights for determining the key elements of reservoir operations and enhancing management strategies under flood conditions. ©

关键词： Bias-correction deep learning Extreme flood events Multi-model ensemble system Numerical weather prediction models

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Antioxidant system alterations and oxidative stress caused by polyfluoroalkyl substances (PFAS) in exposed biota: a review

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Science of the Total Environment 2025年 977卷 179395页

作者： Soares, Lorena Oliveira Souza de Araujo, Gabriel Farias Gomes, Thais Braga Júnior, Sidney Fernandes Sales Cuprys, Agnieszka Katarzyna Soares, Raquel Moraes Saggioro, Enrico Mendes Laboratory of Environmental Health Assessment and Promotion Oswaldo Cruz Institute Oswaldo Cruz Foundation Av. Brasil 4365 RJ Rio de Janeiro21045-900 Brazil Post-Graduate Program in Public Health and Environment Sergio Arouca National School of Public Health Oswaldo Cruz Foundation Av. Leopoldo Bulhões 1480 RJ Rio de Janeiro21041-210 Brazil Faculty of Science and Technology Norwegian University of Life Sciences P.O. Box 5003 Ås1432 Norway Post-Graduate Program in Environmental Technology and Water Resources Department of Civil and Environmental Engineering – FT University of Brasília Darcy Ribeiro Campus Via L3 Norte DF Brasília70910-900 Brazil

Contamination of aquatic and terrestrial organisms by Perfluoroalkyl substances (PFAS), emerging contaminants, is widespread, as these compounds are present in water, soil, air, and food, owing to their environmental persistence. PFAS exposure induces biochemical process alterations associated with the disruption of the antioxidant defense system in several species. This review aims to discuss how PFAS-induced antioxidant system alterations lead to changes in biochemical processes in different organisms exposed to these pollutants. This disruption, then leads to an imbalance in antioxidant defense systems, contributing to the formation of reactive oxidative species (ROS), which, in turn, can be exacerbate oxidative stress, induce cellular damage, enhance lipid peroxidation, destabilize lysosomal membranes, and cause genotoxic effects, ultimately compromising DNA integrity. In acute tests, PFAS have led to mortality, growth inhibition, diminished behavioral and locomotor abilities, and reproductive impairment. PFAS-induced effects differ with varying species or types of substances, and further bioaccumulation through food chains exacerbates environmental contamination, carrying considerable risks. These findings demonstrate the complex and enduring impact of PFAS on environmental health, emphasizing the importance of this review in corroborating studies on sub-lethal toxicity in exposed organisms and how these effects reflect on the environment. © 2025 Elsevier B.V.

关键词： Biotic

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Occurrence of fecal indicator bacteria and microbial source tracking markers along the Texas Gulf Coast adjoining two barrier islands

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Science of the Total Environment 2025年 975卷 179323页

作者： Dhar, Dipti Anik Vadde, Kiran Kumar Narimani, Roya Murgulet, Dorina Felix, J. David Matta, Akanksha Pinchback, Jason Kapoor, Vikram School of Civil & Environmental Engineering Construction Management University of Texas at San Antonio San AntonioTX78249 United States Department of Physical and Environmental Sciences Center for Water Supply Studies Texas A&M University-Corpus Christi Corpus ChristiTX78412 United States Department of Chemistry University of Texas at San Antonio San AntonioTX78249 United States Water Resources Program Texas General Land Office AustinTX78701 United States

This study investigates the occurrence and sources of fecal contamination along the Texas Gulf Coast, focusing on two barrier islands: Sargent Beach and Matagorda Peninsula. Surface water samples from six sites were collected over 19 months and analyzed for fecal indicator bacteria (FIB) and microbial source tracking (MST) markers, including human (HF183), canine (BacCan), avian (GFD), and enterococci (Entero1) markers. Culturable enterococci were detected in all samples, often exceeding safety thresholds, indicating widespread fecal contamination. Statistical analyses revealed significant differences in marker concentrations among sites (ANOVA, p © 2025 Elsevier B.V.

关键词： Waste management

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