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Ezio Todini, born in Lucca, Italy, is a Italian hydrologist and civil engineer. He spent most of his early life and youth in Cairo, Egypt. In 1969 he was awarded the degree of Doctor in Hydraulic Engineering by the University of Pisa and joined the then just inaugurated IBM Pisa Scientific Centre in 1971. In 1973 he became Professor of Applied Hydromechanics at the University of Pisa. In 1979 he was appointed Professor of Water Resources Planning at the University of Florence. Since 1980 he has held the chair of Hydrology at the University of Bologna. He retired as Professor in 2010. In 2009 he was the founding president of the Italian Hydrological Society. Currently he has research collaborations with several Universities and serves as Water Resources Expert for International bodies and in particular for the World Bank.

Career

Ezio Todini is a leading scientist in the development of hydrological modeling approaches for water resources management and planning. Since the mid 70’s he pioneered the systems approach to hydrology and crafted a direction which guided hydrologic sciences into a new level of distributed hydrologic modelling, uncertainty quantification, and optimal parameter estimation via Kalman filtering. His Mutually Interactive State Parameter (MISP) algorithm....^[1] based on an approach conceptually similar to the Gibbs sampler ^[2], introduced a novel methodology to the joint estimation of state and parameters in Kalman Filters, and served not only the hydrologic community at large but other fields of communications ^[3]^[4] and environmental sciences ^[5].

In Hydraulics, Todini largely contributed to the enhancement of design and simulation methods for flow in looped water distribution networks (WDN). In this context he authored the Global Gradient Algorithm for the analysis of WDN ^[6]. The algorithm is at the core of the worldwide used WDN analysis freeware EPANET ^[7]. Moreover, in 2000 he introduced the Resilience Index ^[8], as the basis for implementing multi objective Pareto design to WDN.

Todini initiated his research career dealing with hydrological models. Initially he proposed a Quadratic Programming alternative to the constrained estimation of Unit Hydrographs as an alternative to the Linear Programming approach proposed by Eagleson ^[9]. The work was based on the seminal work of Norbert Wiener and Norman Levinson ^[10]. This gave rise to the Constrained Linear Systems (CLS) model, which favorably compared to the existing well know hydrological models at the WMO Intercomparison conceptual models used in hydrological forecasting ^[11].

He also developed the ARNO hydrological model ^[12]^[13]. ARNO was the first soil moisture accounting model to be included into a General Circulation Models (GCM) such as ECHAM GCM (Hamburg Climate Model) ^[14]. As distributed precipitation evolved, Todini developed the land surface model TOPKAPI ^[15]^[16]. The model is structured around grids that capture soil and precipitation variably. He used Bayesian inference to determine flood risk based on long-term TOPKAPI simulations. The use of Bayesian inference in hydrological modelling allowed to separate out parameter and input uncertainty in operational river flow forecasting ^[17]^[18]

A major contribution to hydrology is the explanation for mass losses in flow computations on mild river bed slopes using the Muskingum-Cunge routing method and the proposition of a corrective approach for making the method mass conservative^[19]

Another important contribution are his works on the quantification of forecasting uncertainty using multiple streamflow models through meta-Gaussian correlation-based ensemble averaging, an approach known as Model-Conditional Processor (MCP)^[20]^[21]^[22]

A major component of Todini’s work has been the continuous transfer of the developed scientific approaches into operational tools to be used in the solution of real-world problems. The hydrological models, the flood routing models and the uncertainty post processors were thus integrated into operational real time flood forecasting packages installed on several rivers all around the world, such as the Po, the Arno and the Tiber in Italy, the Han Jang, the Yellow river, and the Fuchun river in China, the Duero, the Tajo, the Jucar and the Segura rivers in Spain.

He also contributed to the reference Handbook of Applied Hydrology^[23] ^[24]

Between 1984 and 1991 E. Todini served as Vice-president of the International Association of Hydrological Sciences (IAHS).

Between 2009 and 2016 he served as President the Società Idrologica Italiana - Italian Hydrological Society. From 2017 he has become the Honorary President of SII-IHS.

Currently he acts as Honorary President of the Italian Hydrological Society

References

^ Todini, E. (1978). Chao-Lin, Chiu (ed.). "Mutually Interactive State/Parameter Estimation (MISP)". Application of Kalman Filter to Hydrology, Hydraulics and Water Resources. Univ. of Pittsburgh, Pennsylvania.
^ Geman, S.; Geman, D. (1984). "Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images". IEEE Transactions on Pattern Analysis and Machine Intelligence. 6 (6): 721–741. doi:10.1109/TPAMI.1984.4767596. PMID 22499653.
^ Najim, M. (2006). Modélisation, estimation et filtrage optimal en traitement du signal (in French). Paris: Lavoisier. p. 414. ISBN 2-7462-1499-7.
^ Labarre, D.; Grivel, E.; Berthomieu, Y.; Todini, E.; Najim, M. (2006). "Consistent estimation of autoregressive parameters from noisy observations based on two interacting Kalman filters". Signal Processing. 86 (10): 2863–2876. {{cite journal}}: |doi-access= requires |doi= (help); Invalid |doi-access=10.1016/j.sigpro.2005.12.001 (help)
^ Poli, I.; Jones, D. (1994). "A Neural Net Model for Prediction". Journal of the American Statistical Association. 89 (425): 117–121. doi:10.2307/2291206.
^ Todini, E.; Pilati, A. (1988). Coulbeck, B.; Orr, C.H. (eds.). "A gradient Algorithm for the analysis of pipe networks". Computer Application in Water Supply, Volume 1 (System analysis and simulation). John Wiley and Sons, London: 1–20.
^ https://www.epa.gov/water-research/epanet
^ Todini, E. (2000). "Looped water distribution networks design using a resilience index based heuristic approach". Urban Water. 2: 115–122. doi:10.1016/S1462-0758(00)00049-2.
^ Eagleson, P.J.; Mejia-R, R.; March, F. (1966). "Computation of optimum realizable unit hydrographs". Water Resour. Res. 24 (4): 755–764. doi:10.1029/WR002i004p00755.
^ Levinson, N. (1964). "The Wiener RMS (Root Mean Square) Error Criterion in Filter Design and Prediction - Appendix B". In Wiener, N. (ed.). Extrapolation, Interpolation, and Smoothing of Stationary Time Series: With Engineering Applications. The MIT Press. Cambridge, Mass.
^ Sittner, W.T. (1976). "WMO Project on Intercomparison of Conceptual Models Used in Hydrological Forecasting". Hydrological Sciences Journal. 21 (1): 203–213. doi:10.1080/02626667609491617.
^ Beven, K. (2012). Rainfall-Runoff Modellling – A Primer. Oxford: Wiley-Blackwell, Oxford. , 488 Pages. ISBN 978-0-470-71459-1.
^ Todini, E. (1996). "The ARNO rainfall-runoff model". Journal of Hydrology. 175: 339–382. doi:10.1016/S0022-1694(96)80016-3.
^ Dümenil, L.; Todini, E. (1992). O' Kane, J.P. (ed.). "A rainfall-runoff scheme for use in the Hamburg climate model". Advances in Theoretical Hydrology - A tribute to James Dooge. Elsevier Science, Amsterdam: 129–157.
^ Ciarapica, L.; Todini, E. (2002). "TOPKAPI: a model for the representation of the rainfall-runoff process at different scales". Hydrological Processes. 16 (2): 207–229. doi:10.1002/hyp.342.
^ Liu, Z.; Todini, E. (2004). "Towards a comprehensive physically based rainfall-runoff model". Hydrology and Earth Sys. Sci. 6 (5): 859–881. doi:10.5194/hess-6-859-2002.{{cite journal}}: CS1 maint: unflagged free DOI (link)
^ Todini, E. (2009). Baveye, P.; Mysiak, J.; Laba, M. (eds.). "Role and Treatment of Uncertainty in Real Time Flood Forecasting". Uncertainties in Environmental Modelling and Consequences for Policy Making. Nato Science for Peace and Security Series. C. Environmental Security. Dordrecht, The Netherlands: Springer. doi:10.1007/978-90-481-2636-1. ISBN 978-90-481-2636-1.
^ Mantovan, P.; Todini, E. (2006). "Hydrological forecasting uncertainty assessment: Incoherence of the GLUE methodology". Journal of Hydrology. 330: 368–381. doi:10.1016/j.jhydrol.2006.04.046.
^ Todini, E. (2007). "A mass conservative and water storage consistent variable parameter Muskingum-Cunge approach". Hydrol. Earth Sys. Sci. 11: 645–1659. doi:10.5194/hess-11-1645-2007.{{cite journal}}: CS1 maint: unflagged free DOI (link)
^ Todini, E. (2008). "A model conditional processor to assess predictive uncertainty in flood forecasting". Intl. J. River Basin Management. 6 (2): 123–137. doi:10.1080/15715124.2008.9635342.
^ Coccia, G.; Todini, E. (2011). "Recent developments in predictive uncertainty assessment based on the Model Conditional Processor approach". Hydrol. Earth Sys. Sci. 15: 3253–3274. doi:10.5194/hess-15-3253-2011.{{cite journal}}: CS1 maint: unflagged free DOI (link)
^ Todini, E. (2013). "From HUP to MCP: Analogies and extended performances". J. of Hydrol. 477: 33–42. doi:10.1016/j.jhydrol.2012.10.037.
^ Todini, E.; Biondi, D. (2017). "Calibration, parameter estimation, uncertainty, data assimilation, sensitivity analysis, and validation. Chapter 22". In Singh, V.P. (ed.). Handbook of Applied Hydrology. New York: McGraw-Hill Education. pp. 1–19.
^ Todini, E. (2017). "Predictive uncertainty assessment and decision making. Chapter 26". In Singh, V.P. (ed.). Handbook of Applied Hydrology. New York: McGraw-Hill Education.

[1] Todini, E. (1978). Chao-Lin, Chiu (ed.). "Mutually Interactive State/Parameter Estimation (MISP)". Application of Kalman Filter to Hydrology, Hydraulics and Water Resources. Univ. of Pittsburgh, Pennsylvania.

[2] Geman, S.; Geman, D. (1984). "Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images". IEEE Transactions on Pattern Analysis and Machine Intelligence. 6 (6): 721–741. doi:10.1109/TPAMI.1984.4767596. PMID 22499653.

[3] Najim, M. (2006). Modélisation, estimation et filtrage optimal en traitement du signal (in French). Paris: Lavoisier. p. 414. ISBN 2-7462-1499-7.

[4] Labarre, D.; Grivel, E.; Berthomieu, Y.; Todini, E.; Najim, M. (2006). "Consistent estimation of autoregressive parameters from noisy observations based on two interacting Kalman filters". Signal Processing. 86 (10): 2863–2876. {{cite journal}}: |doi-access= requires |doi= (help); Invalid |doi-access=10.1016/j.sigpro.2005.12.001 (help)

[5] Poli, I.; Jones, D. (1994). "A Neural Net Model for Prediction". Journal of the American Statistical Association. 89 (425): 117–121. doi:10.2307/2291206.

[6] Todini, E.; Pilati, A. (1988). Coulbeck, B.; Orr, C.H. (eds.). "A gradient Algorithm for the analysis of pipe networks". Computer Application in Water Supply, Volume 1 (System analysis and simulation). John Wiley and Sons, London: 1–20.

[7] ttps://www.epa.gov/water-research/epanet

[8] Todini, E. (2000). "Looped water distribution networks design using a resilience index based heuristic approach". Urban Water. 2: 115–122. doi:10.1016/S1462-0758(00)00049-2.

[9] Eagleson, P.J.; Mejia-R, R.; March, F. (1966). "Computation of optimum realizable unit hydrographs". Water Resour. Res. 24 (4): 755–764. doi:10.1029/WR002i004p00755.

[10] Levinson, N. (1964). "The Wiener RMS (Root Mean Square) Error Criterion in Filter Design and Prediction - Appendix B". In Wiener, N. (ed.). Extrapolation, Interpolation, and Smoothing of Stationary Time Series: With Engineering Applications. The MIT Press. Cambridge, Mass.

[11] Sittner, W.T. (1976). "WMO Project on Intercomparison of Conceptual Models Used in Hydrological Forecasting". Hydrological Sciences Journal. 21 (1): 203–213. doi:10.1080/02626667609491617.

[12] Beven, K. (2012). Rainfall-Runoff Modellling – A Primer. Oxford: Wiley-Blackwell, Oxford. , 488 Pages. ISBN 978-0-470-71459-1.

[13] Todini, E. (1996). "The ARNO rainfall-runoff model". Journal of Hydrology. 175: 339–382. doi:10.1016/S0022-1694(96)80016-3.

[14] Dümenil, L.; Todini, E. (1992). O' Kane, J.P. (ed.). "A rainfall-runoff scheme for use in the Hamburg climate model". Advances in Theoretical Hydrology - A tribute to James Dooge. Elsevier Science, Amsterdam: 129–157.

[15] Ciarapica, L.; Todini, E. (2002). "TOPKAPI: a model for the representation of the rainfall-runoff process at different scales". Hydrological Processes. 16 (2): 207–229. doi:10.1002/hyp.342.

[16] Liu, Z.; Todini, E. (2004). "Towards a comprehensive physically based rainfall-runoff model". Hydrology and Earth Sys. Sci. 6 (5): 859–881. doi:10.5194/hess-6-859-2002.{{cite journal}}: CS1 maint: unflagged free DOI (link)

[17] Todini, E. (2009). Baveye, P.; Mysiak, J.; Laba, M. (eds.). "Role and Treatment of Uncertainty in Real Time Flood Forecasting". Uncertainties in Environmental Modelling and Consequences for Policy Making. Nato Science for Peace and Security Series. C. Environmental Security. Dordrecht, The Netherlands: Springer. doi:10.1007/978-90-481-2636-1. ISBN 978-90-481-2636-1.

[18] Mantovan, P.; Todini, E. (2006). "Hydrological forecasting uncertainty assessment: Incoherence of the GLUE methodology". Journal of Hydrology. 330: 368–381. doi:10.1016/j.jhydrol.2006.04.046.

[19] Todini, E. (2007). "A mass conservative and water storage consistent variable parameter Muskingum-Cunge approach". Hydrol. Earth Sys. Sci. 11: 645–1659. doi:10.5194/hess-11-1645-2007.{{cite journal}}: CS1 maint: unflagged free DOI (link)

[20] Todini, E. (2008). "A model conditional processor to assess predictive uncertainty in flood forecasting". Intl. J. River Basin Management. 6 (2): 123–137. doi:10.1080/15715124.2008.9635342.

[21] Coccia, G.; Todini, E. (2011). "Recent developments in predictive uncertainty assessment based on the Model Conditional Processor approach". Hydrol. Earth Sys. Sci. 15: 3253–3274. doi:10.5194/hess-15-3253-2011.{{cite journal}}: CS1 maint: unflagged free DOI (link)

[22] Todini, E. (2013). "From HUP to MCP: Analogies and extended performances". J. of Hydrol. 477: 33–42. doi:10.1016/j.jhydrol.2012.10.037.

[23] Todini, E.; Biondi, D. (2017). "Calibration, parameter estimation, uncertainty, data assimilation, sensitivity analysis, and validation. Chapter 22". In Singh, V.P. (ed.). Handbook of Applied Hydrology. New York: McGraw-Hill Education. pp. 1–19.

[24] Todini, E. (2017). "Predictive uncertainty assessment and decision making. Chapter 26". In Singh, V.P. (ed.). Handbook of Applied Hydrology. New York: McGraw-Hill Education.

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@@ Line 3: / Line 3: @@
 [[File:Todini Petra.jpg|thumb|Ezio Todini in Petra, Jordan, 2022]]<!-- Do not remove this line! -->
-'''Ezio Todini''', born in [[Lucca, Italy]], is a Italian hydrologist and civil engineer. He spent most of his early life and youth in Cairo, Egypt. In 1969 he was awarded the degree of Doctor in Hydraulic Engineering by the University of Pisa and joined the then just inaugurated IBM Pisa Scientific Centre in 1970. In 1973 he became Professor of Applied Hydromechanics at the University of Pisa. In 1979 he was appointed Professor of  Water Resources Planning at the University of Florence. Since 1980 he has held the chair of Hydrology at the University of Bologna. He retired as Professor in 2010. In 2009 he was the founding president of the Italian Hydrological Society. Currently he has research collaborations with several Universities and serves as Water Resources Expert for International bodies and in particular for the World Bank.
+'''Ezio Todini''', born in [[Lucca, Italy]], is a Italian hydrologist and civil engineer. He spent most of his early life and youth in Cairo, Egypt. In 1969 he was awarded the degree of Doctor in Hydraulic Engineering by the University of Pisa and joined the then just inaugurated IBM Pisa Scientific Centre in 1971. In 1973 he became Professor of Applied Hydromechanics at the University of Pisa. In 1979 he was appointed Professor of  Water Resources Planning at the University of Florence. Since 1980 he has held the chair of Hydrology at the University of Bologna. He retired as Professor in 2010. In 2009 he was the founding president of the [https://www.sii-ihs.it/ Italian Hydrological Society]. Currently he has research collaborations with several Universities and serves as Water Resources Expert for International bodies and in particular for the World Bank.
 == Career ==
-Ezio Todini is a leading scientist in the development of hydrological modeling approaches for water resources management and planning.  Since the mid 70’s he pioneered the systems approach to hydrology and crafted a direction which guided hydrologic sciences into a new level of distributed hydrologic modelling, uncertainty quantification, and optimal parameter estimation via [[Kalman filtering]]. His Mutually Interactive State Parameter (MISP) algorithm....<ref>{{Cite journal |last=Todini |first=E. |year=1978 |editor-last=Chao-Lin |editor-first=Chiu |title=Mutually Interactive State/Parameter Estimation (MISP) |journal=Application of Kalman Filter to Hydrology, Hydraulics and Water Resources |publisher=Univ. of Pittsburgh, Pennsylvania}}</ref> based on an approach conceptually similar to the Gibbs sampler <ref>{{Cite journal |last=Geman |first=S. |last2=Geman |first2=D. |year=1984 |title=Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images. |journal=IEEE Transactions on Pattern Analysis and Machine Intelligence. |volume=6 |issue=6 |pages=721–741 |doi=10.1109/TPAMI.1984.4767596 |pmid=22499653}}</ref>, introduced a novel methodology to the joint estimation of state and parameters in Kalman Filters, and served not only the hydrologic community at large but other fields of communications <ref>{{Cite book |last=Najim |first=M. |title=Modélisation, estimation et filtrage optimal en traitement du signal |publisher=Lavoisier |year=2006 |isbn=2-7462-1499-7 |location=Paris |pages=414 |language=French}}</ref><ref>{{Cite journal |last=Labarre |first=D. |last2=Grivel |first2=E. |last3=Berthomieu |first3=Y. |last4=Todini |first4=E. |last5=Najim |first5=M. |year=2006 |title=Consistent estimation of autoregressive parameters from noisy observations based on two interacting Kalman filters |journal=Signal Processing |volume=86 |issue=10 |pages=2863-2876}}</ref> and environmental sciences <ref>{{Cite journal |last=Poli |first=I. |last2=Jones |first2=D. |year=1994 |title=A Neural Net Model for Prediction |journal=Journal of the American Statistical Association |volume=89 |issue=425 |pages=117-121 |doi=10.2307/2291206}}</ref>.
+Ezio Todini is a leading scientist in the development of hydrological modeling approaches for water resources management and planning.  Since the mid 70’s he pioneered the systems approach to hydrology and crafted a direction which guided hydrologic sciences into a new level of distributed hydrologic modelling, uncertainty quantification, and optimal parameter estimation via [[Kalman filtering]]. His Mutually Interactive State Parameter (MISP) algorithm....<ref>{{Cite journal |last=Todini |first=E. |year=1978 |editor-last=Chao-Lin |editor-first=Chiu |title=Mutually Interactive State/Parameter Estimation (MISP) |journal=Application of Kalman Filter to Hydrology, Hydraulics and Water Resources |publisher=Univ. of Pittsburgh, Pennsylvania}}</ref> based on an approach conceptually similar to the Gibbs sampler <ref>{{Cite journal |last=Geman |first=S. |last2=Geman |first2=D. |year=1984 |title=Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images. |journal=IEEE Transactions on Pattern Analysis and Machine Intelligence. |volume=6 |issue=6 |pages=721–741 |doi=10.1109/TPAMI.1984.4767596 |pmid=22499653}}</ref>, introduced a novel methodology to the joint estimation of state and parameters in Kalman Filters, and served not only the hydrologic community at large but other fields of communications <ref>{{Cite book |last=Najim |first=M. |title=Modélisation, estimation et filtrage optimal en traitement du signal |publisher=Lavoisier |year=2006 |isbn=2-7462-1499-7 |location=Paris |pages=414 |language=French}}</ref><ref>{{Cite journal |last=Labarre |first=D. |last2=Grivel |first2=E. |last3=Berthomieu |first3=Y. |last4=Todini |first4=E. |last5=Najim |first5=M. |year=2006 |title=Consistent estimation of autoregressive parameters from noisy observations based on two interacting Kalman filters |journal=Signal Processing |volume=86 |issue=10 |pages=2863-2876 |doi-access=10.1016/j.sigpro.2005.12.001}}</ref> and environmental sciences <ref>{{Cite journal |last=Poli |first=I. |last2=Jones |first2=D. |year=1994 |title=A Neural Net Model for Prediction |journal=Journal of the American Statistical Association |volume=89 |issue=425 |pages=117-121 |doi=10.2307/2291206}}</ref>.
-In Hydraulics, Todini largely contributed to the enhancement of design and simulation methods for flow in looped water distribution networks (WDN). In this context he authored the Global Gradient Algortihm for the analysis of WDN <ref>{{Cite journal |last=Todini |first=E. |last2=Pilati |first2=A. |year=1988 |editor-last=Coulbeck |editor-first=B. |editor2-last=Orr |editor2-first=C.H. |title=A gradient Algorithm for the analysis of pipe networks |journal=Computer Application in Water Supply, Volume 1 (System analysis and simulation) |publisher=John Wiley and Sons, London |pages=1-20}}</ref>. The algorithm is at the core of the worldwide used WDN analysis freeware EPANET <ref>https://www.epa.gov/water-research/epanet</ref>. Moreover, in 2000 he introduced the Resilience Index <ref>{{Cite journal |last=Todini |first=E. |year=2000 |title=Looped water distribution networks design using a resilience index based heuristic approach |journal=Urban Water |volume=2 |pages=115-122}}</ref>, as the basis for implementing multi objective Pareto design to WDN.
+In Hydraulics, Todini largely contributed to the enhancement of design and simulation methods for flow in looped water distribution networks (WDN). In this context he authored the Global Gradient Algorithm for the analysis of WDN <ref>{{Cite journal |last=Todini |first=E. |last2=Pilati |first2=A. |year=1988 |editor-last=Coulbeck |editor-first=B. |editor2-last=Orr |editor2-first=C.H. |title=A gradient Algorithm for the analysis of pipe networks |journal=Computer Application in Water Supply, Volume 1 (System analysis and simulation) |publisher=John Wiley and Sons, London |pages=1-20}}</ref>. The algorithm is at the core of the worldwide used WDN analysis freeware EPANET <ref>https://www.epa.gov/water-research/epanet</ref>. Moreover, in 2000 he introduced the Resilience Index <ref>{{Cite journal |last=Todini |first=E. |year=2000 |title=Looped water distribution networks design using a resilience index based heuristic approach |journal=Urban Water |volume=2 |pages=115-122 |doi=10.1016/S1462-0758(00)00049-2}}</ref>, as the basis for implementing multi objective Pareto design to WDN.
-Todini initiated his research career dealing with hydrological models. Initially he proposed a Quadratic Programming alternative to the constrained estimation of Unit Hydrographs as an alternative to the Linear Programming approach proposed by Eagleson <ref>{{Cite journal |last=Eagleson |first=P.J. |year=1966 |title=Computation of optimum realizable unit hydrographs |journal=Water Resour. Res. |volume=24 |issue=4 |pages=755–764}}</ref>. The work was based on the seminal work of Norbert Wiener and Norman Levinson <ref>{{Cite book |last=Wiener |first=N. |title=Extrapolation, Interpolation, and Smoothing of Stationary Time Series: With Engineering Applications. |publisher=The MIT Press. Cambridge, Mass. |year=1964 |editor-last=Wiener |editor-first=N. |chapter=The Wiener RMS (Root Mean Square) Error Criterion in Filter Design and Prediction - Appendix B}}</ref>. This gave rise to the Constrained Linear Systems (CLS) model, which favorably compared to the existing well know hydrological models at the WMO Intercomparison conceptual models used in hydrological forecasting <ref>{{Cite journal |last=Sittner |first=W.T. |year=1976 |title=WMO Project on Intercomparison of Conceptual Models Used in Hydrological Forecasting |journal=Hydrological Sciences Journal |volume=21 |issue=1 |pages=203-213 |doi=10.1080/02626667609491617}}</ref>.
+Todini initiated his research career dealing with hydrological models. Initially he proposed a Quadratic Programming alternative to the constrained estimation of Unit Hydrographs as an alternative to the Linear Programming approach proposed by Eagleson <ref>{{Cite journal |last=Eagleson |first=P.J. |last2=Mejia-R |first2=R. |last3=March |first3=F. |year=1966 |title=Computation of optimum realizable unit hydrographs |journal=Water Resour. Res. |volume=24 |issue=4 |pages=755–764 |doi=10.1029/WR002i004p00755}}</ref>. The work was based on the seminal work of Norbert Wiener and Norman Levinson <ref>{{Cite book |last=Levinson |first=N. |title=Extrapolation, Interpolation, and Smoothing of Stationary Time Series: With Engineering Applications. |publisher=The MIT Press. Cambridge, Mass. |year=1964 |editor-last=Wiener |editor-first=N. |chapter=The Wiener RMS (Root Mean Square) Error Criterion in Filter Design and Prediction - Appendix B}}</ref>. This gave rise to the Constrained Linear Systems (CLS) model, which favorably compared to the existing well know hydrological models at the WMO Intercomparison conceptual models used in hydrological forecasting <ref>{{Cite journal |last=Sittner |first=W.T. |year=1976 |title=WMO Project on Intercomparison of Conceptual Models Used in Hydrological Forecasting |journal=Hydrological Sciences Journal |volume=21 |issue=1 |pages=203-213 |doi=10.1080/02626667609491617}}</ref>.
-He also developed the ARNO hydrological model <ref>{{Cite book |last=Beven |first=K. |title=Rainfall-Runoff Modellling – A Primer. |publisher=Wiley-Blackwell, Oxford. , 488 Pages. |year=2012 |isbn=978-0-470-71459-1 |location=Oxford}}</ref><ref>{{Cite journal |last=Todini |first=E. |year=1996 |title=The ARNO rainfall-runoff model |journal=Journal of Hydrology |volume=175 |pages=339-382}}</ref>.  ARNO was the first soil moisture accounting model to be included into a General Circulation Models (GCM) such as  ECHAM GCM (Hamburg Climate Model) <ref>{{Cite journal |last=Dümenil |first=L. |last2=Todini |first2=E. |year=1992 |editor-last=Kane |editor-first=J.P. |title=A rainfall-runoff scheme for use in the Hamburg climate model |journal=Advances in Theoretical Hydrology - A tribute to James Dooge. |publisher=Elsevier Science, Amsterdam |pages=129-157}}</ref>. As distributed precipitation evolved, Todini developed the land surface model TOPKAPI <ref>{{Cite journal |last=Ciarapica |first=L. |last2=Todini |first2=E. |year=2002 |title=TOPKAPI: a model for the representation of the rainfall-runoff process at different scales. |journal=Hydrological Processes |volume=16 |issue=2 |pages=207-229}}</ref><ref>{{Cite journal |last=Liu |first=Z. |last2=Todini |first2=E. |year=2004 |title=Towards a comprehensive physically based rainfall-runoff model |journal=Hydrology and Earth Sys. Sci. |volume=6 |issue=5 |pages=859–881}}</ref>. The model is structured around grids that capture soil and precipitation variably. He used Bayesian inference to determine flood risk based on long-term TOPKAPI simulations. The use of Bayesian inference in hydrological modelling allowed to separate out parameter and input uncertainty in operational river flow forecasting <ref>{{Cite book |last=Todini |first=E. |title=Uncertainties in Environmental Modelling and Consequences for Policy Making. Nato Science for Peace and Security Series. C. Environmental Security. |publisher=Springer, Dordrecht, The Netherlands |year=2009 |editor-last=Baveye P.; Mysiak J.; Laba M. |chapter=Role and Treatment of Uncertainty in Real Time Flood Forecasting.}}</ref><ref>{{Cite journal |last=Mantovan |first=P. |last2=Todini |first2=E. |year=2006 |title=Hydrological forecasting uncertainty assessment: Incoherence of the GLUE methodology |journal=Journal of Hydrology |volume=330 |pages=368-381}}</ref>
+He also developed the ARNO hydrological model <ref>{{Cite book |last=Beven |first=K. |title=Rainfall-Runoff Modellling – A Primer. |publisher=Wiley-Blackwell, Oxford. , 488 Pages. |year=2012 |isbn=978-0-470-71459-1 |location=Oxford}}</ref><ref>{{Cite journal |last=Todini |first=E. |year=1996 |title=The ARNO rainfall-runoff model |journal=Journal of Hydrology |volume=175 |pages=339-382 |doi=10.1016/S0022-1694(96)80016-3}}</ref>.  ARNO was the first soil moisture accounting model to be included into a General Circulation Models (GCM) such as  ECHAM GCM (Hamburg Climate Model) <ref>{{Cite journal |last=Dümenil |first=L. |last2=Todini |first2=E. |year=1992 |editor-last=O' Kane |editor-first=J.P. |title=A rainfall-runoff scheme for use in the Hamburg climate model |journal=Advances in Theoretical Hydrology - A tribute to James Dooge. |publisher=Elsevier Science, Amsterdam |pages=129-157}}</ref>. As distributed precipitation evolved, Todini developed the land surface model TOPKAPI <ref>{{Cite journal |last=Ciarapica |first=L. |last2=Todini |first2=E. |year=2002 |title=TOPKAPI: a model for the representation of the rainfall-runoff process at different scales. |journal=Hydrological Processes |volume=16 |issue=2 |pages=207-229 |doi=10.1002/hyp.342}}</ref><ref>{{Cite journal |last=Liu |first=Z. |last2=Todini |first2=E. |year=2004 |title=Towards a comprehensive physically based rainfall-runoff model |journal=Hydrology and Earth Sys. Sci. |volume=6 |issue=5 |pages=859–881 |doi=10.5194/hess-6-859-2002}}</ref>. The model is structured around grids that capture soil and precipitation variably. He used Bayesian inference to determine flood risk based on long-term TOPKAPI simulations. The use of Bayesian inference in hydrological modelling allowed to separate out parameter and input uncertainty in operational river flow forecasting <ref>{{Cite journal |last=Todini |first=E. |year=2009 |editor-last=Baveye |editor-first=P. |editor2-last=Mysiak |editor2-first=J. |editor3-last=Laba |editor3-first=M. |title=Role and Treatment of Uncertainty in Real Time Flood Forecasting. |journal=Uncertainties in Environmental Modelling and Consequences for Policy Making. Nato Science for Peace and Security Series. C. Environmental Security. |location=Dordrecht, The Netherlands |publisher=Springer |doi=10.1007/978-90-481-2636-1 |isbn=978-90-481-2636-1}}</ref><ref>{{Cite journal |last=Mantovan |first=P. |last2=Todini |first2=E. |year=2006 |title=Hydrological forecasting uncertainty assessment: Incoherence of the GLUE methodology |journal=Journal of Hydrology |volume=330 |pages=368-381 |doi=10.1016/j.jhydrol.2006.04.046}}</ref>
-A major contribution to hydrology is the explanation for mass losses in flow computations on mild river bed slopes using the Muskingum-Cunge routing method and the proposition of a corrective approach for making the method mass conservative<ref>{{Cite journal |last=Todini |first=E. |year=2007 |title=A mass conservative and water storage consistent variable parameter Muskingum-Cunge approach |journal=Hydrol. Earth Sys. Sci. |volume=11 |pages=645-1659}}</ref>
+A major contribution to hydrology is the explanation for mass losses in flow computations on mild river bed slopes using the Muskingum-Cunge routing method and the proposition of a corrective approach for making the method mass conservative<ref>{{Cite journal |last=Todini |first=E. |year=2007 |title=A mass conservative and water storage consistent variable parameter Muskingum-Cunge approach |journal=Hydrol. Earth Sys. Sci. |volume=11 |pages=645-1659 |doi=10.5194/hess-11-1645-2007}}</ref>
-Another important contribution are his works on the quantification of forecasting uncertainty using multiple streamflow models through meta-Gaussian correlation-based ensemble averaging, an approach known as Model-Conditional Processor (MCP)<ref>{{Cite journal |last=Todini |first=E. |year=2008 |title=A model conditional processor to assess predictive uncertainty in flood forecasting |journal=Intl. J. River Basin Management |volume=6 |issue=2 |pages=123-137}}</ref><ref>{{Cite journal |last=Coccia |first=G. |last2=Todini |first2=E. |year=2011 |title=Recent developments in predictive uncertainty assessment based on the Model Conditional Processor approach |journal=Hydrol. Earth Sys. Sci |volume=15 |pages=3253-3274 |doi=10.5194/hess-15-3253-2011}}</ref><ref>{{Cite journal |last=Todini |first=E. |year=2013 |title=From HUP to MCP: Analogies and extended performances |journal=J. of Hydrol |volume=477 |pages=33-42}}</ref>
+Another important contribution are his works on the quantification of forecasting uncertainty using multiple [[streamflow]] models through meta-Gaussian correlation-based ensemble averaging, an approach known as Model-Conditional Processor (MCP)<ref>{{Cite journal |last=Todini |first=E. |year=2008 |title=A model conditional processor to assess predictive uncertainty in flood forecasting |journal=Intl. J. River Basin Management |volume=6 |issue=2 |pages=123-137 |doi=10.1080/15715124.2008.9635342}}</ref><ref>{{Cite journal |last=Coccia |first=G. |last2=Todini |first2=E. |year=2011 |title=Recent developments in predictive uncertainty assessment based on the Model Conditional Processor approach |journal=Hydrol. Earth Sys. Sci |volume=15 |pages=3253-3274 |doi=10.5194/hess-15-3253-2011}}</ref><ref>{{Cite journal |last=Todini |first=E. |year=2013 |title=From HUP to MCP: Analogies and extended performances |journal=J. of Hydrol |volume=477 |pages=33-42 |doi=10.1016/j.jhydrol.2012.10.037}}</ref>
-A major component of Todini’s work has been the continuous transfer of the developed scientific approaches into operational tools to be used in the solution of real-world problems. The hydrological models, the flood routing models and the uncertainty post processors were thus integrated into operational real time flood forecasting packages installed on several rivers all around the world, such as the Po, the Arno and the Tiber in Italy, the Han Jang, the Yellow river, and the Fuchun river in China, the Duero, the Tajo, the Jucar and the Segura in Spain.
+A major component of Todini’s work has been the continuous transfer of the developed scientific approaches into operational tools to be used in the solution of real-world problems. The hydrological models, the flood routing models and the uncertainty post processors were thus integrated into operational real time flood forecasting packages installed on several rivers all around the world, such as the Po, the Arno and the Tiber in Italy, the Han Jang, the Yellow river, and the Fuchun river in China, the Duero, the Tajo, the Jucar and the Segura rivers in Spain.
-He also contributed to the reference Handbook of Applied Hydrology<ref>{{Cite book |last=Todini |first=E. |title=Handbook of Applied Hydrology |last2=Biondi |first2=D. |publisher=McGraw-Hill Education |year=2017 |editor-last=Singh |editor-first=V.P. |location=New York |pages=1-19 |chapter=Calibration, parameter estimation, uncertainty, data assimilation, sensitivity analysis, and validation. Chapter 22}}</ref> <ref>{{Cite book |last=Todini |first=E. |title=Handbook of Applied Hydrology |publisher=McGraw-Hill Education |year=2017 |editor-last=Singh |editor-first=V.P. |location=New York |pages= |chapter=Predictive uncertainty assessment and decision making. Chapter 25}}</ref>
+He also contributed to the reference Handbook of Applied Hydrology<ref>{{Cite book |last=Todini |first=E. |title=Handbook of Applied Hydrology |last2=Biondi |first2=D. |publisher=McGraw-Hill Education |year=2017 |editor-last=Singh |editor-first=V.P. |location=New York |pages=1-19 |chapter=Calibration, parameter estimation, uncertainty, data assimilation, sensitivity analysis, and validation. Chapter 22}}</ref> <ref>{{Cite book |last=Todini |first=E. |title=Handbook of Applied Hydrology |publisher=McGraw-Hill Education |year=2017 |editor-last=Singh |editor-first=V.P. |location=New York |pages= |chapter=Predictive uncertainty assessment and decision making. Chapter 26}}</ref>
 Between 1984 and 1991 E. Todini served as Vice-president of the International Association of Hydrological Sciences ([https://iahs.info/ IAHS]).
-Between 2009 and 2016 he served as President the Società Idrologica Italiana - Italian Hydrological Society. From 2017 he has become the Honorary President of [https://www.sii-ihs.it/ SII-HIS].
+Between 2009 and 2016 he served as President the Società Idrologica Italiana - Italian Hydrological Society. From 2017 he has become the Honorary President of [https://www.sii-ihs.it/ SII-IHS].
 Currently he acts as Honorary President of the Italian Hydrological Society