Relevant bibliographies by topics / Soil loss estimation

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Soil loss estimation'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Soil loss estimation"

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Nortcliff, Stephen. "Soil loss estimation." Progress in Physical Geography: Earth and Environment 10, no. 2 (1986): 249–55. http://dx.doi.org/10.1177/030913338601000207.

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Kalita, Nilotpal, and Niranjan Bhattacharjee. "Estimation of Soil Loss in the Nanoi River Basin using Geospatial Techniques." Indian Journal Of Science And Technology 17, no. 18 (2024): 1845–53. http://dx.doi.org/10.17485/ijst/v17i18.1382.

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Objectives: The main purpose of this research is to identify severe soil loss areas in the Nanoi river basin of Assam, India to suggest appropriate soil management planning in the river basin. Methods: The Revised Universal Soil Loss Equation (RUSLE) integrates geospatial technologies to assess overall soil loss in the Nanoi river basin which provides a faster and more accurate estimation. It is possible to understand soil erosion patterns more thoroughly using RUSLE which makes sustainable soil management easier. Findings: According to the RUSLE equation, the Nanoi river basin experiences an
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Nouwakpo, Sayjro K., Mark A. Weltz, Awadis Arslan, Colleen H. Green, and Osama Z. Al-Hamdan. "Process-Based Modeling of Infiltration, Soil Loss, and Dissolved Solids on Saline and Sodic Soils." Transactions of the ASABE 61, no. 3 (2018): 1033–48. http://dx.doi.org/10.13031/trans.12705.

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Abstract. The Colorado River is a central socio-economic resource of the western U.S. but is vulnerable to excessive salt load. To improve knowledge of the surface processes controlling salt loading, a series of rainfall simulation experiments were conducted in saline rangelands of the upper Colorado River basin (UCRB). In this study, data from these rainfall simulation experiments were used to develop predictive equations for the process-based Rangeland Hydrology and Erosion Model (RHEM). Runoff and soil loss prediction performances were assessed with the Nash-Sutcliffe efficiency (NSE), the
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Nilotpal, Kalita, and Bhattacharjee Niranjan. "Estimation of Soil Loss in the Nanoi River Basin using Geospatial Techniques." Indian Journal of Science and Technology 17, no. 18 (2024): 1845–53. https://doi.org/10.17485/IJST/v17i18.1382.

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Abstract <strong>Objectives:</strong>&nbsp;The main purpose of this research is to identify severe soil loss areas in the Nanoi river basin of Assam, India to suggest appropriate soil management planning in the river basin.&nbsp;<strong>Methods:</strong>&nbsp;The Revised Universal Soil Loss Equation (RUSLE) integrates geospatial technologies to assess overall soil loss in the Nanoi river basin which provides a faster and more accurate estimation. It is possible to understand soil erosion patterns more thoroughly using RUSLE which makes sustainable soil management easier.&nbsp;<strong>Findings:
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Chandramohan, T., and Dilip G. Durbude. "Estimation of soil erosion potential using Universal Soil Loss Equation." Journal of the Indian Society of Remote Sensing 30, no. 4 (2002): 181–90. http://dx.doi.org/10.1007/bf03000361.

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KuroTamuno Peace, Jackson,, and Okwere, Chiziandu Enyinda. "Modelling and Estimation of Average Annual Soil Loss in Ika South Local Government Area of Delta State, Nigeria." Journal of Geography, Environment and Earth Science International 29, no. 1 (2025): 45–59. https://doi.org/10.9734/jgeesi/2025/v29i1854.

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Soil-related phenomenon and the Sustainable Development Goals (SDGs) particularly SDG-15 are strictly tied. A healthy soil ecosystem encourages the existence of life on Earth and for agricultural purposes. One of the key factors that is contributing to unhealthy soil ecosystems is soil erosion. The research involves the assessment and modelling of soil erosion using the Revised Universal Soil Loss Equation (RUSLE II) with the sole aim of ascertaining the annual Soil loss within the study area, this will be a veritable tool in estimating soil loss in farming systems and in supporting the achiev
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Noor, Hamze, Seyed Khalagh Mirnia, Somaye Fazli, Mohamad bagher Raisi, and Mahdi Vafakhah. "Application of MUSLE for the prediction of phosphorus losses." Water Science and Technology 62, no. 4 (2010): 809–15. http://dx.doi.org/10.2166/wst.2010.092.

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Soil erosion in forestlands affects not only land productivity but also the water body down stream. The Universal Soil Loss Equation (USLE) has been applied broadly for the prediction of soil loss from upland fields. However, there are few reports concerning the prediction of nutrient (P) losses based on the USLE and its versions. The present study was conducted to evaluate the applicability of the deterministic model Modified Universal Soil Loss Equation (MUSLE) to estimation of phosphorus losses in the Kojor forest watershed, northern Iran. The model was tested and calibrated using accurate
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M, MUTHAMIL SELVAN, SUBRAMANIAN K, RAJENDRAN V, and RANGASAMY K. "Estimation of runoff and soil loss for a hilly watershed." Madras Agricultural Journal 88, june (2001): 284–86. http://dx.doi.org/10.29321/maj.10.a00339.

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Estimation and analysis of rainfall-runoff-discharge data for a watershed would be of great use. for optimum planning and managing the watershed. Universal Soil Loss Equation (USLE) was used to estimate the annual soil loss from a hilly watershed in the Nilgiris. A set of linear regression models were developed by relating (1) rainfall and runoff, (2) rainfall and soil loss and they can be used for prediction of the runoff and soil loss for the watershed. Packages of soil and water conservation measures were recommendd for the watershed as the present rinoff and soil loss wre found to be enorm
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Ratul, Das, Gogoi Barnali, and Kumar Jaiswal Monoj. "Soil loss assessment in Sadiya Region, Assam, India using remote sensing and GIS." Indian Journal of Science and Technology 13, no. 23 (2020): 2319–27. https://doi.org/10.17485/IJST/v13i23.588.

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Abstract <strong>Objectives:</strong>&nbsp;This study focuses on identifying areas of intense soil erosion in Sadiya, a subdivision of Tinsukia district of Assam in India to facilitate appropriate implementation of soil management and conservation schemes in an administrative unit.&nbsp;<strong>Methods:</strong>&nbsp;A comprehensive methodology of Remote Sensing (RS) and Geographical Information System (GIS) is implemented with an empirical model called the Revised Universal Soil Loss Equation (RUSLE). RUSLE is the best model to assess soil loss creating different raster layers in GIS.&nbsp;<s
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Schnitzer, S., F. Seitz, A. Eicker, A. Güntner, M. Wattenbach, and A. Menzel. "Estimation of soil loss by water erosion in the Chinese Loess Plateau using Universal Soil Loss Equation and GRACE." Geophysical Journal International 193, no. 3 (2013): 1283–90. http://dx.doi.org/10.1093/gji/ggt023.

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Dissertations / Theses on the topic "Soil loss estimation"

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Sourlamtas, Konstantinos. "Soil Erosion estimation for the Göta Älv river using remote sensing, GIS and the Revised Universal Soil Loss Equation (RUSLE) model." Thesis, Stockholms universitet, Institutionen för naturgeografi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-175412.

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According to previous studies, the study area of Göta Älv river has high risk of landslides along the river banks due to the water flow. Soil erosion can affect the increase of the landslides in an area with unstable soils caused by the increase rainfall. The Swedish climate is getting more vulnerable thus there is a potential increased risk in erosion and landslides due to unpredictable rainfall intensity. This study aims to calculate soil erosion for the Göta Älv river using the Revised Universal Soil Loss Equation (RUSLE) where a comparison of data from remote sensing and meteorological and
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Rosa, Joel Zubek. "Diagnóstico de processos erosivos em solos agrícolas mediante análise de modelos numéricos do terreno." Universidade Estadual de Ponta Grossa, 2018. http://tede2.uepg.br/jspui/handle/prefix/2689.

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Submitted by Angela Maria de Oliveira (amolivei@uepg.br) on 2018-11-26T20:27:20Z No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Joel Zubek.pdf: 7864320 bytes, checksum: f2e6f06e6ec1c27abd616c5e845d97f8 (MD5)<br>Made available in DSpace on 2018-11-26T20:27:20Z (GMT). No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Joel Zubek.pdf: 7864320 bytes, checksum: f2e6f06e6ec1c27abd616c5e845d97f8 (MD5) Previous issue date: 2018-08-10<br>Entre os principais problemas relacionados à conservação ambiental em
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Barros, Enicléia Nunes de Sousa. "Estimativa da erosão hídrica nas bacias hidrográficas dos rios Lontra e Manuel Alves Pequeno, TO." Universidade Federal do Tocantins, 2017. http://hdl.handle.net/11612/418.

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A erosão hídrica constitui um dos principais processos de degradação do solo, com impactos que vão desde a redução da produtividade até a diminuição dos recursos naturais existentes. Nesse sentido, o presente trabalho objetivou avaliar o efeito das alterações no uso do solo, de 1990 a 2007, aplicando o modelo RUSLE para estimar espacialmente o comportamento da erosão do solo para as bacias hidrográficas dos rios Lontra e Manuel Alves Pequeno-TO. A erosão hídrica na bacia do rio Lontra, no ano de 2007, variou de “suave” (51,3%), na região central da bacia, onde o relevo é plano e o uso do solo
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Oliveira, Júlio Storion de. "Avaliação de modelos de elevação na estimativa de perda de solo em ambiente SIG." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/11/11143/tde-31052012-075705/.

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O presente trabalho avaliou a utilização de imagens ASTER GDEM e SRTM em substituição a cartas planialtmétricas em escala 1:10000 e 1:50000 como fonte de dados altimétricos para predição de perda de solo em microbacia hidrográfica. Para tanto as imagens com os dados de topografia e demais informações foram incorporadas ao banco de dados do SPRING. Como requisito para estimar perda de solo pela Equação Universal da Perda de Solo, estabeleceu-se o uso atual da terra na microbacia hidrográfica do Ceveiro, situada no município de Piracicaba, SP. Foi constatado que a microbacia é utilizada em sua m
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Klopfenstein, Andrew A. "An Empirical Model for Estimating Corn Yield Loss from Compaction Events with Tires vs. Tracks High Axle Loads." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1461316924.

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Zhou, Hong. "Integration of Analytical Models for Estimating Sediment Supply and Evaluation of Channel Stability." Ohio University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1456273575.

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Basso, Bruna Tauana. "Estimativa de erosão utilizando a Equação Universal de Perdas de Solos (EUPS): o caso do alto curso do rio Chopim." Universidade Estadual do Oeste do Paraná, 2018. http://tede.unioeste.br/handle/tede/4041.

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Submitted by Fabielle Cheuczuk (fabielle.cheuczuk@unioeste.br) on 2018-11-29T18:04:45Z No. of bitstreams: 2 Versão Final.pdf: 3865354 bytes, checksum: c057a961a6b88478a6890a7fc6df2932 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Made available in DSpace on 2018-11-29T18:04:45Z (GMT). No. of bitstreams: 2 Versão Final.pdf: 3865354 bytes, checksum: c057a961a6b88478a6890a7fc6df2932 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-09-04<br>Conselho Nacional de Pesquisa e Desenvolvimento Científico e Te
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Jaramillo, Fernando. "Estimating and modeling soil loss and sediment yield in the Maracas-St. Joseph River catchment with empirical models (RUSLE and MUSLE) and a physically based model (EROSION 3D)." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=18412.

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In Trinidad the implications of high sediment concentrations in the rivers are becoming a major concern. Three models were used to estimate sediment loads from soil loss due to rainfall in the 41 km2 St. Joseph River Catchment. The models were the empirically-based RUSLE and MUSLE for annual and single event loading predictions, respectively and the physically based, Erosion 3D, for single event loading predictions. A hydrologic network was constructed that included an on-line Optical Backscatter sensor (OBS), and a water quality sampler. RUSLE overpredicted the measured sediment yield for th
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Pen, Show-Chih, and 彭壽奇. "Estimation of Soil Loss in Watershed." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/87071035443469226634.

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碩士<br>國立交通大學<br>土木工程系<br>89<br>The existed reservoirs in Taiwan are mostly constructed at the middle and upper reaches of the rivers. Frequently due to the steep topography and frail geology or due to improper cultivation and deforestation, they have resulted in serious erosion to the top-soil. The river water carries abundant of sand to the reservoir; subsequently, the latter’s capacity is reducing day by day, which is very disadvantageous to the operation of reservoir. According to the measured results to the sand-depositing volume of reservoir in the past years, the average deposit volume o
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陳文欽. "Estimation of Slopeland Soil Loss in Erhjen Creek Watershed." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/65588036761507003636.

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碩士<br>國立中興大學<br>水土保持學系<br>88<br>Due to steep topography, weak geology, heavy rainfall in the typhoon season, tremendous soil loss disaster usually occurs in Taiwan especially at the mudstone areas. Geographic Information System (GIS), Remote Sensing (RS), and Global Positioning System (GPS) coupled with Universal Soil Loss Equation (USLE) were used to estimate watershed soil loss in Erhjen Creek located at mudstone areas. Watershed topographic and hydrologic information of interest was also extracted automatically from Digital Terrain Model (DTM) in this study for the references of slopeland p
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Books on the topic "Soil loss estimation"

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Kasran, Baharuddin. A guide for estimating surface soil loss using the modified soil loss equation (MSLE) on forest land. Forest Research Institute Malaysia, 1999.

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O'Brien, Rachel. Estimation of groundwater recharge in the Palouse loess using environmental tritium. State of Washington Water Research Center, 1993.

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Kiggundu, Lawrence. Distribution of rainfall erosivity in Swaziland: For use in the universal soil loss equation (USLE) and the soil loss estimator for southern Africa (SLEMSA) to estimate soil loss due to sheet and rill erosion. Social Science Research Unit and Research and Publications, University of Swaziland, 1986.

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O'Brien, Rachel. Estimation of groundwater recharge in the Palouse loess using environmental tritium. 1992.

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Book chapters on the topic "Soil loss estimation"

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Renard, Kenneth G., Leonard J. Lane, George R. Foster, and John M. Laflen. "Soil Loss Estimation." In Soil Erosion, Conservation, and Rehabilitation. CRC Press, 2023. http://dx.doi.org/10.1201/9781003418177-9.

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Singh, Rajendra. "Soil Loss Estimation." In Soil and Water Conservation Structures Design. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8665-9_3.

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Schulte, E. E., and B. G. Hopkins. "Estimation of Soil Organic Matter by Weight Loss-On-Ignition." In Soil Organic Matter: Analysis and Interpretation. Soil Science Society of America, 2015. http://dx.doi.org/10.2136/sssaspecpub46.c3.

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Supriya, S., and A. S. Ravikumar. "Estimation of Soil Loss Using RS and GIS Techniques." In Lecture Notes in Civil Engineering. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0304-5_35.

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Thapa, Pawan. "Soil Erosion Estimation Using Revised Universal Soil Loss Equation (RUSLE) Model and GIS." In GIScience for the Sustainable Management of Water Resources. Apple Academic Press, 2022. http://dx.doi.org/10.1201/9781003284512-16.

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Pal, Subodh Chandra, and Rabin Chakrabortty. "Soil Loss Estimation Using Different Empirical and Semi-empirical Models." In Climate Change Impact on Soil Erosion in Sub-tropical Environment. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15721-9_5.

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Sarma, Arnab. "Estimation of Soil Loss and Sediment Yield Using Universal Soil Loss Equation in Jiadhal Basin of Dhemaji District, Assam." In Advances in Hydrology and Climate Change. Apple Academic Press, 2022. http://dx.doi.org/10.1201/9781003282365-14.

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Halder, Sudipa, Malabika Biswas Roy, Shuvoshri Bhattacharya, Souvik Mondal, and Pankaj Kumar Roy. "Soil Loss Estimation for Sustainable Watershed Conservation in Semi-arid Bengal Basin." In Lecture Notes in Civil Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6412-7_31.

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Bhandari, Ujjwal, and Uttam Mukhopadhyay. "Estimation of Soil Erosion Using Revised Universal Soil Loss Equation (RUSLE) Model in Subarnarekha River Basin, India." In Geography of the Physical Environment. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04532-5_19.

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Safi, Md, and Dipankar Oraw. "Soil Loss Estimation Using Rainfall Erosivity and Soil Erodibility of RUSLE Model in the Jayanti River Basin (Jharkhand)." In Fluvial Systems in the Anthropocene. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11181-5_21.

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Conference papers on the topic "Soil loss estimation"

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Vinci, Alessandra, Raffaella Brigante, and Lorenzo Vergni. "Soil Loss Estimation Under Different Soil Management Using a Multispectral UAV." In 2024 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor). IEEE, 2024. https://doi.org/10.1109/metroagrifor63043.2024.10948822.

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Mazzella, Joseph, Thomas Hayden, Haralampos Tsaprailis, and Len Krissa. "Estimating Wall Loss Risk Distributions Using Machine Learning and Geospatial Analytics." In CORROSION 2020. NACE International, 2020. https://doi.org/10.5006/c2020-14640.

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Abstract Estimating corrosion growth rates for underground pipelines is a challenging problem. There are confounding variables with complex interaction effects that may result in unexpected outcomes. For instance, the relationship between soil conditions and AC interference is highly non-linear and challenging to model. This work expands upon prior work using a suite of machine learning tools to estimate corrosion rates. However, instead of estimating a single corrosion growth rate for a single girth weld address (GWA), this work estimates a distribution of potential corrosion growth rates. Mo
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Tziolas, Nikolaos, Nikiforos Samarinas, Ioannis Tsividis, and George Zalidis. "Evaluating the effectiveness of improved digital soil maps, generated through a hybrid CNN-XGBoost approach, for estimating soil loss due to water erosion." In Tenth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2024), edited by Silas C. Michaelides, Diofantos G. Hadjimitsis, Chris Danezis, et al. SPIE, 2024. http://dx.doi.org/10.1117/12.3037235.

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Dimen, Levente. "SOIL LOSS ESTIMATION USING GIS TECHNOLOGY." In 13th SGEM GeoConference on INFORMATICS, GEOINFORMATICS AND REMOTE SENSING. Stef92 Technology, 2013. http://dx.doi.org/10.5593/sgem2013/bb2.v1/s11.038.

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Ansal, Atilla, Asli Kurtulus, and Gökce Tönük. "Earthquake Loss Estimation Tool for Urban Areas." In Geotechnical Earthquake Engineering and Soil Dynamics Congress IV. American Society of Civil Engineers, 2008. http://dx.doi.org/10.1061/40975(318)34.

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Baise, Laurie G., and Vahid Rashidian. "A Geospatial Approach to Liquefaction Assessment for Rapid Response and Loss Estimation." In Geotechnical Earthquake Engineering and Soil Dynamics V. American Society of Civil Engineers, 2018. http://dx.doi.org/10.1061/9780784481462.001.

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Badulescu, Bianca. "ESTIMATION AND MODELLING OF UNCERTAINTY PROPAGATION IN SOIL LOSS ASSESSMENT USING RUSLE EQUATION." In 19th SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings. STEF92 Technology, 2019. http://dx.doi.org/10.5593/sgem2019/2.2/s11.099.

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Junakova, Natalia. "ESTIMATION OF SOIL LOSS BY WATER EROSION DEPENDING ON LAND USE MANAGEMENT USING GIS." In 14th SGEM GeoConference on ECOLOGY, ECONOMICS, EDUCATION AND LEGISLATION. Stef92 Technology, 2014. http://dx.doi.org/10.5593/sgem2014/b51/s20.039.

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Mi Seon Lee, Jong Yoon Park, Kyun In Jung, and Seong Joon Kim. "Estimation of Spatial Soil Loss using the Land Use Information of QuickBird Satellite Imagery." In 2008 Providence, Rhode Island, June 29 - July 2, 2008. American Society of Agricultural and Biological Engineers, 2008. http://dx.doi.org/10.13031/2013.25081.

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Patil, Manti, Radheshyam Patel, and Arnab Saha. "Sediment Yield and Soil Loss Estimation Using GIS Based Soil Erosion Model: A Case Study in the MAN Catchment, Madhya Pradesh, India." In The 4th International Electronic Conference on Atmospheric Sciences. MDPI, 2021. http://dx.doi.org/10.3390/ecas2021-10348.

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Reports on the topic "Soil loss estimation"

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Fourqurean, James, Johannes Krause, Juan González-Corredor, Tom Frankovich, and Justin Campbell. Caricas Partner's Practical Field and Laboratory Guide. Florida International University, 2024. http://dx.doi.org/10.25148/merc_fac.2024.32.

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This field and laboratory guide describes the field and laboratory methods used to characterize blue carbon in seagrass meadows. It was developed for the Caribbean Carbon Accounting in Seagrass project and describes the protocols and methods used by the network. In brief, at each project site, seagrass abundance, species composition, canopy height, and sediment type were assessed at sixteen 0.25 m2 quadrats placed at random locations within the site. Eight 20 cm diameter cores were taken to assess seagrass biomass, shoot density, and to provide the material for assessing seagrass carbon and nu
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Zhang, Renduo, and David Russo. Scale-dependency and spatial variability of soil hydraulic properties. United States Department of Agriculture, 2004. http://dx.doi.org/10.32747/2004.7587220.bard.

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Water resources assessment and protection requires quantitative descriptions of field-scale water flow and contaminant transport through the subsurface, which, in turn, require reliable information about soil hydraulic properties. However, much is still unknown concerning hydraulic properties and flow behavior in heterogeneous soils. Especially, relationships of hydraulic properties changing with measured scales are poorly understood. Soil hydraulic properties are usually measured at a small scale and used for quantifying flow and transport in large scales, which causes misleading results. The
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Robert Guertin, Jason, Naomie Chouinard, Chanel Beaudoin Cloutier, et al. Estimation du coût de l’hospitalisation index des patients admis dans une unité de soins des grands brûlés d’un centre hospitalier du Québec selon deux approches méthodologiques. CIRANO, 2024. http://dx.doi.org/10.54932/fxem6229.

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Les traumatismes de brûlures sévères sont reconnus comme étant parmi les plus sévères en termes de morbidités et de mortalité qu’un individu peut vivre. Étant donné la nature des hospitalisations et des soins requis, ces hospitalisations sont reconnues comme étant parmi les plus dispendieuses au sein du système de santé. Les analyses de coûts en santé permettent de quantifier la valeur monétaire des ressources utilisées lors d’un épisode de soins. Historiquement, au Québec, l’approche basée sur le niveau d’intensité relative des ressources utilisées (NIRRU) était l’approche la plus utilisée lo
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