Socio-Hydrological Modelling: The Influence of Reservoir Management and Societal Responses on Flood Impacts
Abstract
:1. Introduction
- How do changes in water management policies influence flood risk and societal flood mitigation strategies?
- How do different possible future flow scenarios influence flood impacts?
2. Socio-Hydrological Model
2.1. Hypothetical Systems
2.2. Reservoir Management Module
2.3. Flooding Module
2.4. Assumptions
3. Sensitivity Analysis
3.1. Experimental Setup
3.2. Results
4. Model Application
4.1. Case Study
4.2. Model Calibration and Setup
4.3. Future Flow Scenarios
- Scenario 1—Baseline: Hydrological extremes “as today”. Floods and droughts occur with the same magnitude and frequency as in the reference period. This scenario was generated by repeating the original inflow data every 31 years.
- Scenario 2—Bigger Floods: Drought events “as today”, whereas flood peaks are exacerbated. A threshold to consider a flood event was set to 2000 m3/s. Inflow data exceeding the threshold in each time slice were multiplied by a factor equal to 1.2. This scenario can be representative of extreme rainfall events that become more extreme.
- Scenario 3—Shorter Droughts: Floods “as today”, whereas droughts duration is shorter. It was generated by adding artificial flood levels interrupting the Millennium Drought. This scenario can be representative of extreme rainfall events that become more frequent, or in other words, a scenario characterised by decreasing drought duration.
- Scenario 4—Bigger Floods & Shorter Droughts: Flood events increase in magnitude and droughts duration is shorter. This scenario is the combination of scenarios 1 and 2, in which all the inflow data above 2000 m3/s were amplified by a factor of 1.2. It can be considered as a scenario in which extreme rainfall events become more extreme in magnitude and frequency.
4.4. Results
5. Discussion and Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Wallemacq, P.; House, R. Economic Losses, Poverty & Disasters: 1998–2017; Centre for Research on the Epidemiology of Disasters (CRED): Brussels, Belgium, 2018. [Google Scholar]
- United Nations International Strategy for Disaster Reduction (UN/ISDR). Living with Risk: A Global Review of Disaster Reduction Initiatives; UN/ISDR: Geneva, Switzerland, 2004. [Google Scholar]
- Ye, B.; Yang, D.; Kane, D.L. Changes in Lena River streamflow hydrology: Human impacts versus natural variations. Water Resour. Res. 2003, 39. [Google Scholar] [CrossRef]
- Van den Honert, R.C.; McAneney, J. The 2011 Brisbane Floods: Causes, Impacts and Implications. Water 2011, 3, 1149–1173. [Google Scholar]
- Bohensky, E.L.; Leitch, A.M. Framing the flood: A media analysis of themes of resilience in the 2011 Brisbane flood. Reg. Environ. Chang. 2014, 14, 475–488. [Google Scholar]
- Cook, M. Vacating the Floodplain: Urban Property, Engineering, and Floods in Brisbane (1974–2011). Conserv. Soc. 2017, 15, 344. [Google Scholar]
- McKinnon, S. Remembering and forgetting 1974: The 2011 Brisbane floods and memories of an earlier disaster. Geogr. Res. 2019, 57, 204–214. [Google Scholar]
- Koutsoyiannis, D.; Zarkadoulas, N.; Angelakis, A.N.; Tchobanoglous, G. Urban Water Management in Ancient Greece: Legacies and Lessons. J. Water Resour. Plan. Manag. 2008, 134, 45–54. [Google Scholar]
- Viglione, A.; Di Baldassarre, G.; Brandimarte, L.; Kuil, L.; Carr, G.; Salinas, J.L.; Scolobig, A.; Blöschl, G. Insights from socio-hydrology modelling on dealing with flood risk – Roles of collective memory, risk-taking attitude and trust. J. Hydrol. 2014, 518, 71–82. [Google Scholar]
- White, G. Human Adjustment to Floods—A Geographical Approach to the Flood Problem in the United States; Research Paper No. 29; University of Chicago: Chicago, IL, USA, 1945. [Google Scholar]
- Haer, T.; Husby, T.G.; Botzen, W.J.W.; Aerts, J.C.J.H. The safe development paradox: An agent-based model for flood risk under climate change in the European Union. Glob. Environ. Chang. 2020, 60, 102009. [Google Scholar] [CrossRef]
- Kreibich, H.; Di Baldassarre, G.; Vorogushyn, S.; Aerts, J.C.J.H.; Apel, H.; Aronica, G.T.; Arnbjerg-Nielsen, K.; Bouwer, L.M.; Bubeck, P.; Caloiero, T.; et al. Adaptation to flood risk: Results of international paired flood event studies. Earth’s Future 2017, 5, 953–965. [Google Scholar] [CrossRef] [Green Version]
- Mård, J.; Di Baldassarre, G.; Mazzoleni, M. Nighttime light data reveal how flood protection shapes human proximity to rivers. Sci. Adv. 2018, 4, eaar5779. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sivapalan, M.; Savenije, H.H.G.; Blöschl, G. Socio-hydrology: A new science of people and water. Hydrol. Process. 2012, 26, 1270–1276. [Google Scholar] [CrossRef]
- Di Baldassarre, G.; Viglione, A.; Carr, G.; Kuil, L.; Salinas, J.; Blöschl, G. Socio-hydrology: Conceptualising human-flood interactions. Hydrol. Earth Syst. Sci. 2013, 17, 3295–3303. [Google Scholar] [CrossRef] [Green Version]
- Di Baldassarre, G.; Viglione, A.; Carr, G.; Kuil, L.; Yan, K.; Brandimarte, L.; Blöschl, G. Debates—Perspectives on socio-hydrology: Capturing feedbacks between physical and social processes. Water Resour. Res. 2015, 51, 4770–4781. [Google Scholar] [CrossRef]
- Ciullo, A.; Viglione, A.; Castellarin, A.; Crisci, M.; Di Baldassarre, G. Socio-hydrological modelling of flood-risk dynamics: Comparing the resilience of green and technological systems. Hydrol. Sci. J. 2017, 62, 880–891. [Google Scholar] [CrossRef] [Green Version]
- Girons Lopez, M.; Di Baldassarre, G.; Seibert, J. Impact of social preparedness on flood early warning systems. Water Resour. Res. 2017, 53, 522–534. [Google Scholar] [CrossRef] [Green Version]
- Aerts, J.C.J.H.; Botzen, W.J.; Clarke, K.C.; Cutter, S.L.; Hall, J.W.; Merz, B.; Michel-Kerjan, E.; Mysiak, J.; Surminski, S.; Kunreuther, H. Integrating human behaviour dynamics into flood disaster risk assessment. Nat. Clim. Chang. 2018, 8, 193–199. [Google Scholar] [CrossRef] [Green Version]
- Di Baldassarre, G.; Martinez, F.; Kalantari, Z.; Viglione, A. Drought and flood in the Anthropocene: Feedback mechanisms in reservoir operation. Earth Syst. Dyn. 2017, 8, 1–9. [Google Scholar] [CrossRef] [Green Version]
- Blair, P.; Buytaert, W. Socio-hydrological modelling: A review asking “why, what and how?”. Hydrol. Earth Syst. Sci. 2016, 20, 443–478. [Google Scholar] [CrossRef] [Green Version]
- Loucks, D.P.; van Beek, E.; Loucks, D.P.; van Beek, E. Water Resources Planning and Management: An Overview. In Water Resource Systems Planning and Management: An Introduction to Methods, Models, and Applications; Springer International Publishing: Cham, Switzerland, 2017; pp. 1–49. [Google Scholar] [CrossRef] [Green Version]
- Di Baldassarre, G.; Yan, K.; Ferdous, M.R.; Brandimarte, L. The interplay between human population dynamics and flooding in Bangladesh: A spatial analysis. Proc. IAHS 2014, 364, 188–191. [Google Scholar] [CrossRef] [Green Version]
- Baan, P.J.A.; Klijn, F. Flood risk perception and implications for flood risk management in the Netherlands. Int. J. River Basin Manag. 2004, 2, 113–122. [Google Scholar] [CrossRef] [Green Version]
- Ridolfi, E.; Wanders, N.; Baldassarre, G.D. Human impacts and responses to hydrological extremes: Large scale modeling over Europe to unravel the role of reservoir operations. Geophys. Res. Abstr. 2019, 21, 1. [Google Scholar]
- Penning-Orwsell, E.; Viavattene, C.; Pardoe, J.; Chatterton, J.; Parker, D.; Morris, J. The Benefits of Flood and Coastal Risk Management: A Handbook of Techniques—2010 (The Multi-Coloured Manual); Flood Hazard Research Centre, Middlesex University: London, UK, 2010. [Google Scholar]
- Heine, R.A.; Pinter, N. Levee effects upon flood levels: An empirical assessment. Hydrol. Process. 2012, 26, 3225–3240. [Google Scholar] [CrossRef]
- Me-Bar, Y.; Valdez, F., Jr. Recovery time after a disaster and the ancient Maya. J. Archaeol. Sci. 2004, 31, 1311–1324. [Google Scholar] [CrossRef]
- Brisbane City Council. Benchmarking Brisbane 2018. Available online: https://www.brisbane.qld.gov.au/sites/default/files/20180607-benchmarking-brisbane-report.pdf (accessed on 20 August 2019).
- Scolobig, A.; De Marchi, B.; Borga, M. The missing link between flood risk awareness and preparedness: Findings from case studies in an Alpine Region. Nat. Hazards 2012, 63, 499–520. [Google Scholar] [CrossRef]
- Da Deppo, L.; Datei, C.; Salandin, P. Sistemazione dei Corsi D’acqua; Libreria Cortina: Padova, Italy, 1997; ISBN 88-7784-171-0. [Google Scholar]
- Di Baldassarre, G.; Kooy, M.; Kemerink, J.S.; Brandimarte, L. Towards understanding the dynamic behaviour of floodplains as human-water systems. Hydrol. Earth Syst. Sci. 2013, 17, 3235–3244. [Google Scholar] [CrossRef] [Green Version]
- Smith, I.; McAlpine, C. Estimating future changes in flood risk: Case study of the Brisbane River, Australia. Clim. Risk Manag. 2014, 6, 6–17. [Google Scholar] [CrossRef] [Green Version]
- Franks, S.W.; Kuczera, G. Flood frequency analysis: Evidence and implications of secular climate variability, New South Wales. Water Resour. Res. 2002, 38, 20–21. [Google Scholar] [CrossRef]
- Micevski, T.; Franks, S.W.; Kuczera, G. Multidecadal variability in coastal eastern Australian flood data. J. Hydrol. 2006, 327, 219–225. [Google Scholar] [CrossRef]
- Seqwater. Manual of Operational Procedures for Flood Mitigation at Wivenhoe Dam and Somerset Dam. 2016. Available online: https://www.seqwater.com.au/s3fs-public/PDF%20Documents/Flood%20reports%20and%20manuals/22%2011%202016%20Manual%20WivSom%20-%20Rev14%20-%20Final.pdf (accessed on 4 July 2019).
- Kemp, J.; Olley, J.M.; Ellison, T.; McMahon, J. River response to European settlement in the subtropical Brisbane River, Australia. Anthropocene 2015, 11, 48–60. [Google Scholar] [CrossRef]
- Di Baldassarre, G.; Wanders, N.; AghaKouchak, A.; Kuil, L.; Rangecroft, S.; Veldkamp, T.I.E.; Garcia, M.; van Oel, P.R.; Breinl, K.; Van Loon, A.F. Water shortages worsened by reservoir effects. Nat. Sustain. 2018, 1, 617–622. [Google Scholar] [CrossRef]
Initial Conditions | ||||
---|---|---|---|---|
Units | Description | Sensitivity Analysis | Brisbane Case Study | |
S | (m3) | Storage | 0.5·Smax | 0 |
Qout | (m3 s−1) | Human-modified outflow | 1 | 0 |
Mf | (-) | Flood memory | 0.1 | 0.01 |
Md | (-) | Drought memory | 0.1 | 0 |
Shape | (-) | Shape factor | 3000 | 135 |
Values | ||||
---|---|---|---|---|
Units | Description | Sensitivity Analysis | Brisbane Case Study | |
Smax | (m3) | Maximum reservoir storage | 2.8 × 1010 | 3 × 109 |
hmax | (m) | Reservoir maximum water level | 21 | 80 |
hspill | (m) | Spillway crest | 19 | 57 |
L | (m) | Spillway length | 100 | 60 |
kf | (-) | Storage coefficient to cope with flood | 1 | 1 |
kd | (-) | Storage coefficient to cope with drought | 0 | 0 |
μ | (year−1) | Memory decay rate | 0.01 0.15 0.20 | 0.06 |
β | (-) | Bias parameter | 0 1 10 | 3 |
Initial Conditions | ||||
---|---|---|---|---|
Units | Description | Sensitivity Analysis | Brisbane Case Study | |
F | (-) | Relative flood damage | 0 | 0 |
D | (-) | Population density | 0.1 | 0.2 |
H | (m) | Flood protection level | 0 | 0 |
Mpop | (-) | Societal memory of floods | 0 | 0.2 |
Values | ||||
---|---|---|---|---|
Units | Description | Sensitivity Analysis | Brisbane Case Study | |
αH | (m) | Parameter related to relationship between flood water levels to relative damage | 10 (Penning-Orwsell et al. [26]) | |
ξH | (-) | Proportion of flood level enhancement due to presence of levees | 0.2 (Heine & Pinter [27]) | |
ρD | (year−1) | Maximum relative growth rate | 0.03 (Me-Bar & Valdez Jr [28]) | 0.02 (Brisbane City Council [29]) |
αD | (-) | Ratio awareness | 5 (Scolobig et al. [30]) | |
εT | (-) | Safety factor for levee heightening | 1.1 (Da Deppo et al. [31]) | |
κT | (year−1) | Protection level decay rate | 2 × 10 −5 (Di Baldassarre et al. [15,32]) | |
μS | (year−1) | Memory loss rate | 0.06 (Di Baldassarre et al. [15,32]) | 0.12 (Di Baldassarre et al. [16]) |
FLOODS Magnitude | |||
---|---|---|---|
“As today” | Exacerbated | ||
DROUGHTS Duration | “As today” | BASELINE SCENARIO | BIGGER FLOODS SCENARIO |
Reduced | SHORTER DROUGHTS SCENARIO | BIGGER FLOODS & SHORTER DROUGHTS SCENARIO |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Albertini, C.; Mazzoleni, M.; Totaro, V.; Iacobellis, V.; Di Baldassarre, G. Socio-Hydrological Modelling: The Influence of Reservoir Management and Societal Responses on Flood Impacts. Water 2020, 12, 1384. https://doi.org/10.3390/w12051384
Albertini C, Mazzoleni M, Totaro V, Iacobellis V, Di Baldassarre G. Socio-Hydrological Modelling: The Influence of Reservoir Management and Societal Responses on Flood Impacts. Water. 2020; 12(5):1384. https://doi.org/10.3390/w12051384
Chicago/Turabian StyleAlbertini, Cinzia, Maurizio Mazzoleni, Vincenzo Totaro, Vito Iacobellis, and Giuliano Di Baldassarre. 2020. "Socio-Hydrological Modelling: The Influence of Reservoir Management and Societal Responses on Flood Impacts" Water 12, no. 5: 1384. https://doi.org/10.3390/w12051384