Economic and commercial analysis of reusing dam reservoir sediments
Author
Abstract
Suggested Citation
DOI: 10.1016/j.ecolecon.2022.107668
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Chojnacka, K. & Witek-Krowiak, A. & Moustakas, K. & Skrzypczak, D. & Mikula, K. & Loizidou, M., 2020. "A transition from conventional irrigation to fertigation with reclaimed wastewater: Prospects and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
- Kieslich, Marcus & Salles, Jean-Michel, 2021.
"Implementation context and science-policy interfaces: Implications for the economic valuation of ecosystem services,"
Ecological Economics, Elsevier, vol. 179(C).
- Marcus Kieslich & Jean-Michel A Salles, 2021. "Implementation context and science-policy interfaces: Implications for the economic valuation of ecosystem services," Post-Print hal-02964325, HAL.
- Sheehan, C. & Harrington, J. & Murphy, J.D., 2010. "A technical assessment of topsoil production from dredged material," Resources, Conservation & Recycling, Elsevier, vol. 54(12), pages 1377-1385.
- De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
- Gezahegn Weldu Woldemariam & Anteneh Derribew Iguala & Solomon Tekalign & Ramireddy Uttama Reddy, 2018. "Spatial Modeling of Soil Erosion Risk and Its Implication for Conservation Planning: the Case of the Gobele Watershed, East Hararghe Zone, Ethiopia," Land, MDPI, vol. 7(1), pages 1-25, February.
- Giancarlo Renella, 2021. "Recycling and Reuse of Sediments in Agriculture: Where Is the Problem?," Sustainability, MDPI, vol. 13(4), pages 1-12, February.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Mazhar Hussain & Daniel Levacher & Nathalie Leblanc & Hafida Zmamou & Irini Djeran-Maigre & Andry Razakamanantsoa, 2023. "Testing the Feasibility of Usumacinta River Sediments as a Renewable Resource for Landscaping and Agronomy," Sustainability, MDPI, vol. 15(22), pages 1-11, November.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Nahapetyan Yervand, 2019. "The benefits of the Velvet Revolution in Armenia: Estimation of the short-term economic gains using deep neural networks," Central European Economic Journal, Sciendo, vol. 6(53), pages 286-303, January.
- Hayashi, Masayoshi, 2014.
"Forecasting welfare caseloads: The case of the Japanese public assistance program,"
Socio-Economic Planning Sciences, Elsevier, vol. 48(2), pages 105-114.
- Masayoshi Hayashi, 2012. "Forecasting Welfare Caseloads: The Case of the Japanese Public Assistance Program," CIRJE F-Series CIRJE-F-846, CIRJE, Faculty of Economics, University of Tokyo.
- Bolinches, Antonio & Blanco-Gutiérrez, Irene & Zubelzu, Sergio & Esteve, Paloma & Gómez-Ramos, Almudena, 2022. "A method for the prioritization of water reuse projects in agriculture irrigation," Agricultural Water Management, Elsevier, vol. 263(C).
- Kourentzes, Nikolaos & Petropoulos, Fotios & Trapero, Juan R., 2014. "Improving forecasting by estimating time series structural components across multiple frequencies," International Journal of Forecasting, Elsevier, vol. 30(2), pages 291-302.
- Man Li & Tao Ye & Peijun Shi & Jian Fang, 2015. "Impacts of the global economic crisis and Tohoku earthquake on Sino–Japan trade: a comparative perspective," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(1), pages 541-556, January.
- Caglar, Abdullah Emre & Daştan, Muhammet & Avci, Salih Bortecine, 2024. "Persistence of disaggregate energy RD&D expenditures in top-five economies: Evidence from artificial neural network approach," Applied Energy, Elsevier, vol. 365(C).
- Anna Staszewska-Bystrova & Peter Winker, 2016. "Improved bootstrap prediction intervals for SETAR models," Statistical Papers, Springer, vol. 57(1), pages 89-98, March.
- Döpke, Jörg & Fritsche, Ulrich & Müller, Karsten, 2019. "Has macroeconomic forecasting changed after the Great Recession? Panel-based evidence on forecast accuracy and forecaster behavior from Germany," Journal of Macroeconomics, Elsevier, vol. 62(C).
- Goodwin, Paul & Önkal, Dilek & Thomson, Mary, 2010. "Do forecasts expressed as prediction intervals improve production planning decisions?," European Journal of Operational Research, Elsevier, vol. 205(1), pages 195-201, August.
- Nowotarski, Jakub & Weron, Rafał, 2018.
"Recent advances in electricity price forecasting: A review of probabilistic forecasting,"
Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
- Jakub Nowotarski & Rafal Weron, 2016. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," HSC Research Reports HSC/16/07, Hugo Steinhaus Center, Wroclaw University of Technology.
- Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Paul Doukhan & Gabriel Lang & Anne Leucht & Michael H. Neumann, 2015.
"Recent developments in bootstrap methods for dependent data,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 290-314, May.
- Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Michael Wolf & Dan Wunderli, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 352-376, May.
- Charles, Amelie & Darne, Olivier & Kim, Jae, 2016.
"Stock Return Predictability: Evaluation based on Prediction Intervals,"
MPRA Paper
70143, University Library of Munich, Germany.
- Amélie Charles & Olivier Darné & Jae H. Kim, 2016. "Stock Return Predictability: Evaluation based on prediction intervals," Working Papers hal-01295037, HAL.
- Schneider, Matthew J. & Gupta, Sachin, 2016. "Forecasting sales of new and existing products using consumer reviews: A random projections approach," International Journal of Forecasting, Elsevier, vol. 32(2), pages 243-256.
- Vidhi Vig & Anmol Kaur, 2022. "Time series forecasting and mathematical modeling of COVID-19 pandemic in India: a developing country struggling to cope up," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(6), pages 2920-2933, December.
- Mergani A. Khairalla & Xu Ning & Nashat T. AL-Jallad & Musaab O. El-Faroug, 2018. "Short-Term Forecasting for Energy Consumption through Stacking Heterogeneous Ensemble Learning Model," Energies, MDPI, vol. 11(6), pages 1-21, June.
- Kate Murray & Andrea Rossi & Diego Carraro & Andrea Visentin, 2023. "On Forecasting Cryptocurrency Prices: A Comparison of Machine Learning, Deep Learning, and Ensembles," Forecasting, MDPI, vol. 5(1), pages 1-14, January.
- Salas-Molina, Francisco & Martin, Francisco J. & Rodríguez-Aguilar, Juan A. & Serrà, Joan & Arcos, Josep Ll., 2017.
"Empowering cash managers to achieve cost savings by improving predictive accuracy,"
International Journal of Forecasting, Elsevier, vol. 33(2), pages 403-415.
- Francisco Salas-Molina & Francisco J. Martin & Juan A. Rodr'iguez-Aguilar & Joan Serr`a & Josep Ll. Arcos, 2016. "Empowering cash managers to achieve cost savings by improving predictive accuracy," Papers 1605.04219, arXiv.org.
- Longbing Cao, 2021. "AI in Finance: Challenges, Techniques and Opportunities," Papers 2107.09051, arXiv.org.
- Stetco, Adrian & Dinmohammadi, Fateme & Zhao, Xingyu & Robu, Valentin & Flynn, David & Barnes, Mike & Keane, John & Nenadic, Goran, 2019. "Machine learning methods for wind turbine condition monitoring: A review," Renewable Energy, Elsevier, vol. 133(C), pages 620-635.
- Riezebos, Jan & Zhu, Stuart X., 2020. "Inventory control with seasonality of lead times," Omega, Elsevier, vol. 92(C).
More about this item
Keywords
Reservoir sedimentation; Sediment reuse; Fertilizer; Cost-benefit analysis;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecolec:v:204:y:2023:i:pb:s0921800922003299. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolecon .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.