Article
Environmental Sciences
Zhan Tian, Ziwei Yu, Yifan Li, Qian Ke, Junguo Liu, Hongyan Luo, Yingdong Tang
Summary: This study proposed a data-driven approach to quantify the effects of different types of rainfall on river pollution and applied it in a case study of Shiyan River in Shenzhen, China. The results showed that dry period, average rainfall intensity, maximum rainfall in 10 min, total amount of rainfall, and initial runoff intensity are the most important factors affecting river pollution.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2022)
Article
Environmental Sciences
Rafael Magallanes-Quintanar, Carlos E. Galvan-Tejada, Jorge Galvan-Tejada, Santiago de Jesus Mendez-Gallegos, Antonio Garcia-Dominguez, Hamurabi Gamboa-Rosales
Summary: Humanity is dealing with environmental challenges caused by the occurrence and intensity increase of droughts. The use of predictive models, such as Artificial Neural Networks, can be a valuable tool in assessing water scarcity and identifying droughts. This research successfully predicted the monthly Standardized Precipitation Index in four regions of north-central Mexico using Artificial Neural Networks.
Article
Engineering, Civil
Thien Huy Truong Nguyen, Bree Bennett, Michael Leonard
Summary: Stochastic rainfall models are important for evaluating hydrological risks, but there are discrepancies between rainfall metrics and flow metrics. The performance of different models varies depending on the strictness of the flow-based comparison and the region analyzed.
JOURNAL OF HYDROLOGY
(2023)
Article
Engineering, Civil
Conor Tyson, Qianqiu Longyang, Bethany T. Neilson, Ruijie Zeng, Tianfang Xu
Summary: In the mountainous Western U.S., accurately simulating streamflow in snow-dominated, karst basins is important for water resources management. To overcome the challenges of high spatiotemporal variability and scarcity of climate stations, a physically based snow model is used to simulate snow processes, and deep learning is employed to simulate streamflow using the calculated snowmelt and potential evapotranspiration rates.
JOURNAL OF HYDROLOGY
(2023)
Article
Environmental Sciences
Chase B. Bergeson, Katherine L. Martin, Barbara Doll, Bethany B. Cutts
Summary: As urbanization continues and precipitation patterns become more extreme, stormwater management problems are expanding. Due to the disturbance and compaction of urban soils, rainfall-runoff models designed for non-urban soils may underestimate rainfall run-off, making accurate stormwater management difficult. This study quantifies soil infiltration rates across an urban watershed and compares them to estimates from commonly used rainfall-runoff models, finding that urban soils have higher infiltration capacities than expected. However, stormwater management remains a challenge in this urban watershed.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2022)
Article
Green & Sustainable Science & Technology
Abhinav Kumar Singh, Pankaj Kumar, Rawshan Ali, Nadhir Al-Ansari, Dinesh Kumar Vishwakarma, Kuldeep Singh Kushwaha, Kanhu Charan Panda, Atish Sagar, Ehsan Mirzania, Ahmed Elbeltagi, Alban Kuriqi, Salim Heddam
Summary: This study uses data-driven models for rainfall-runoff prediction in the Gola watershed and evaluates the performance of four heuristic methods. The results show that the RF model outperforms the other models and has higher accuracy.
Article
Multidisciplinary Sciences
Lifeng Yuan, Kenneth J. Forshay
Summary: Accurate streamflow prediction is crucial for hydraulic project design, nonpoint source pollution estimation, and water resources planning and management. A seasonal Support Vector Regression (SVR) model coupled with the Soil and Water Assessment Tool (SWAT) model was developed for monthly streamflow prediction in the Illinois River watershed (IRW). The hybrid SWAT-SVR model showed less deviation and better performance compared to SWAT-CUP simulations, with more accurate predictions during the wet season and satisfactory results for medium flows between 5 m(3) s(-1) and 30 m(3) s(-1) at a spatial scale of 500 to 3000 km(2).
Article
Environmental Sciences
Padala Raja Shekar, Aneesh Mathew, P. S. P. Arun, Varun P. Gopi
Summary: This study used the Soil and Water Assessment Tool (SWAT) model and eight artificial intelligence (AI) models to simulate monthly streamflow in the Murredu River basin. The LSTM model performed exceptionally well in modeling the rainfall-runoff relationship, while the other models also produced satisfactory results. Selecting the most efficient model, like the LSTM, can contribute significantly to the effective management and planning of water resources in the Murredu watershed.
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2023)
Article
Engineering, Civil
Gerhard Schoener, Mark C. Stone, Charles Thomas
Summary: In dryland watersheds, infiltration excess overland flow is the dominant mechanism for runoff generation. Rainfall-runoff models partition precipitation into loss and excess precipitation components, with many using simple loss models due to the complexity and uncertainty of more sophisticated models at larger spatial scales.
JOURNAL OF HYDROLOGY
(2021)
Article
Computer Science, Artificial Intelligence
K. Aditya Shastry, H. A. Sanjay
Summary: Crop yield prediction is crucial in agriculture, but many developing countries still rely on manual methods which are inefficient and error-prone. To address this issue, a hybrid prediction strategy is proposed, incorporating weighted principal component analysis and artificial neural network to enhance the accuracy of crop yield prediction.
APPLIED SOFT COMPUTING
(2021)
Article
Engineering, Civil
Yerel Morales, Marvin Querales, Harvey Rosas, Hector Allende-Cid, Rodrigo Salas
Summary: The study introduces a Self-Identification Neuro-Fuzzy Inference Model (SINFIM) to model the relationship between rainfall and runoff in Chilean watersheds, with experimental results showing promising performance in predicting runoff. The model's efficiency is higher compared to other forecasting models and shows potential for accurately predicting peak runoff values from rainfall events without predefining time series lags or fuzzy rules.
JOURNAL OF HYDROLOGY
(2021)
Article
Geosciences, Multidisciplinary
Pingping Yang, Rui Li, Zaike Gu, Li Qin, Tao Song, Zhongxian Liu, Jiayong Gao, Jiang Yuan
Summary: Few studies have focused on long-term localized runoff and sediment yield in karst areas in southwest China. This study investigated the rainfall, runoff, and sediment yields in a small watershed and classified erosive rainfall events into three types based on duration, rainfall depth, and maximum intensity. The results showed that pattern B had the greatest impact on runoff and sediment yield in the watershed.
Article
Environmental Sciences
Dapeng Feng, Jiangtao Liu, Kathryn Lawson, Chaopeng Shen
Summary: This paper introduces a differentiable and learnable process-based model (delta model) that approaches the performance level of purely data-driven deep learning models (such as LSTM) in predicting hydrologic variables. Experimental results show that the delta model performs similarly to LSTM in simulating variables like streamflow and can also output other untrained variables, such as soil and groundwater storage.
WATER RESOURCES RESEARCH
(2022)
Article
Environmental Sciences
Nabila Siti Burnama, Faizal Immaddudin Wira Rohmat, Mohammad Farid, Arno Adi Kuntoro, Hadi Kardhana, Fauzan Ikhlas Wira Rohmat, Winda Wijayasari
Summary: This study presents a data-driven method for predicting flood inundation height across the Majalaya Watershed, by combining data from the HEC-RAS model, GSMaP satellite rainfall data, elevation, and other spatial data to build an artificial neural network model. The trained ANN model showed excellent validation performances and demonstrated the capability of predicting flood inundation height with unseen data, suggesting the potential of this approach in reducing flood risks.
Article
Water Resources
David C. Goodrich, Philip Heilman, Mark Nearing, Mary Nichols, Russ L. Scott, C. Jason Williams, Joel Biederman
Summary: The Walnut Gulch Experimental Watershed (WGEW) is a premier semiarid research watershed in the world, collecting a wide range of data and curated by the USDA-Agricultural Research Service's Southwest Watershed Research Center.
HYDROLOGICAL PROCESSES
(2021)
Article
Engineering, Environmental
Raj Cibin, Indrajeet Chaubey, Rebecca L. Muenich, Keith A. Cherkauer, Philip W. Gassman, Catherine L. Kling, Yiannis Panagopoulos
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
(2017)
Article
Engineering, Environmental
Catherine L. Kling, Indrajeet Chaubey, Raj Cibin, Philip W. Gassman, Yiannis Panagopoulos
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
(2017)
Article
Engineering, Environmental
Philip W. Gassman, Adriana M. Valcu-Lisman, Catherine L. Kling, Steven K. Mickelson, Yiannis Panagopoulos, Raj Cibin, Indrajeet Chaubey, Calvin F. Wolter, Keith E. Schilling
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
(2017)
Article
Engineering, Environmental
Ryan Bailey, Hendrik Rathjens, Katrin Bieger, Indrajeet Chaubey, Jeffrey Arnold
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
(2017)
Article
Environmental Sciences
Nithya Krishnan, Cibin Raj, I. Chaubey, K. P. Sudheer
ENVIRONMENTAL EARTH SCIENCES
(2018)
Article
Soil Science
Tingyu Hou, Timothy D. Berry, Sarmistha Singh, Madison N. Hughes, Yanan Tong, A. N. Thanos Papanicolaou, Kenneth M. Wacha, Christopher G. Wilson, Indrajeet Chaubey, Timothy R. Filley
Article
Environmental Sciences
P. V. Femeena, K. P. Sudheer, R. Cibin, I. Chaubey
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2018)
Article
Engineering, Civil
Vamsikrishna Vema, K. P. Sudheer, I. Chaubey
JOURNAL OF HYDROLOGY
(2018)
Article
Engineering, Civil
Yaoze Liu, Bernard A. Engel, Dennis C. Flanagan, Margaret W. Gitau, Sara K. McMillan, Indrajeet Chaubey, Shweta Singh
JOURNAL OF HYDROLOGY
(2018)
Article
Environmental Sciences
Qingyu Feng, Indrajeet Chaubey, Raj Cibin, Bernard Engel, K. P. Sudheer, Jeffrey Volenec, Nina Omani
LAND DEGRADATION & DEVELOPMENT
(2018)
Article
Environmental Sciences
Tian Guo, Raj Cibin, Indrajeet Chaubey, Margaret Gitau, Jeffrey G. Arnold, Raghavan Srinivasan, James R. Kiniry, Bernard A. Engel
SCIENCE OF THE TOTAL ENVIRONMENT
(2018)
Article
Engineering, Civil
Ping Li, Rebecca L. Muenich, Indrajeet Chaubey, Xiaomei Wei
WATER RESOURCES MANAGEMENT
(2019)
Article
Agronomy
Vamsikrishna Vema, K. P. Sudheer, I Chaubey
AGRICULTURAL WATER MANAGEMENT
(2019)
Review
Agricultural Engineering
Jasmine A. F. Kreig, Herbert Ssegane, Indrajeet Chaubey, Maria C. Negri, Henriette Jager
BIOMASS & BIOENERGY
(2019)
Article
Agricultural Engineering
R. Cibin, I. Chaubey, M. Helmers, K. P. Sudheer, M. J. White, J. G. Arnold
TRANSACTIONS OF THE ASABE
(2018)