scholarly journals Can MCDA guide transdisciplinary endeavors? A framework applied to co-developing a flood forecasting system in West Africa

2021 ◽  
Author(s):  
Judit Lienert ◽  
Jafet Andersson ◽  
Daniel Hofmann ◽  
Francisco Silva Pinto ◽  
Martijn Kuller
Keyword(s):  
West Africa ◽  
Expert Knowledge ◽  
System Development ◽  
Stakeholder Analysis ◽  
Flood Forecasting ◽  
Sensitivity Analyses ◽  
Problem Structuring ◽  
Horizon 2020 ◽  
Stakeholder Preferences ◽  
Forecasting System

Abstract. Climate change is projected to increase flood risks in West Africa. The EU Horizon 2020 project FANFAR co-designed a pre-operational flood forecasting and alert system for West Africa in four workshops with 50–60 stakeholders from 17 countries, adopting a Multi-Criteria Decision Analysis (MCDA) process. Firstly, we aimed to find a robust configuration of the FANFAR system. We document empirical evidence of MCDA, including stakeholder analysis, jointly creating 10 objectives, and 11 FANFAR system configurations. Stakeholders found it most important that the system produces accurate, clear, and accessible flood risk information, well before floods. Monte Carlo simulation and sensitivity analyses helped identifying three configurations that were robust despite uncertainty of expert predictions and different stakeholder preferences, elicited in group sessions. Secondly, we investigated if problem structuring helps focus early technical system development. Although partly achieved, full MCDA was necessary to provide convincingly robust configurations. Thirdly, we critically analyzed MCDA based on literature from sustainability science and transdisciplinary research. Our proposed framework consists of three steps: co-design (joint problem framing), co-production (doing research), and co-dissemination and evaluation of integrated knowledge. MCDA met many requirements, but not all. In step 1, participatory MCDA with problem structuring provides a consistent methodology, and can identify stakeholders and shared objectives to foster joint understanding. MCDA successfully contributes to step 2 by combining interdisciplinary expert knowledge, integrating conflicting stakeholder preferences, handling uncertainty, and providing unambiguous, shared results. Many elements of step 3 are not met by MCDA. We discuss this framework and using MCDA for transdisciplinary hydrology research that engages with stakeholders and society.

Co-designing a flood forecasting and alert system in West Africa with decision-making methods: the transdisciplinary project FANFAR

2020 ◽  
Author(s):  
Judit Lienert ◽  
Jafet Andersson ◽  
Francisco Silva Pinto
Keyword(s):  
West Africa ◽  
Weighted Average ◽  
Flood Forecasting ◽  
West African ◽  
Problem Structuring Methods ◽  
Alert System ◽  
Problem Structuring ◽  
Worst Case ◽  
Ict System ◽  
Design Workshop

<p>Floods are a serious concern in West Africa, and their severity will likely increase with climate change. The European Union-financed, inter- and transdisciplinary project FANFAR (https://fanfar.eu/) aims at providing an operational flood forecast and alert pilot system for West Africa, based on an open-source hydrological model employed in a cloud-based Information and Communications Technology (ICT) environment. To achieve this, an existing pilot ICT system is co-designed and co-adapted to meet needs and preferences of West African users. Four workshops are carried out in West Africa from 2018 to 2020, each with around 40 representatives from hydrological and emergency management agencies from 17 West African countries.</p><p>To better understand the stakeholders’ needs and preferences, and to prioritize the development of the FANFAR ICT flood forecasting and alert system, we use Multi-Criteria Decision Analysis (MCDA). This MCDA framework guides through a stepwise procedure to develop the FANFAR ICT system such that it best fulfils those objectives that are fundamentally important to stakeholders. The first steps of MCDA are problem structuring; starting with a stakeholder analysis to identify the most important participants for the co-design workshops. In the first co-design workshop (Niamey, Niger, 2018), we then used different problem structuring methods (PSMs) to brainstorm which objectives are fundamentally important to West African stakeholders, and which options (ICT system configurations) might achieve these objectives. To generate objectives, we used online and pen-and-paper surveys, group brainstorming, and plenary discussions. To generate options, we used a strategy generation table and the brainwriting-635 method. Between workshops, the FANFAR consortium post-processed the objectives and options. We also interviewed experts to predict how well an option achieves each objective; including the uncertainty, which is later propagated to the MCDA results with Monte Carlo simulation.</p><p>The refined objectives were again discussed in plenary sessions in co-design workshop 2 (Accra, Ghana, 2019), and we elicited the participants’ preferences in small group sessions. Weight elicitation captures the trade-offs stakeholders are willing to make regarding achieving objectives, if not all objectives can be fully fulfilled. We used the card procedure to elicit weights (Simos revised procedure), and the popular swing method. As additional preference information for the MCDA modelling, we elicited the shape of the most-important marginal value functions, which “translate” the objectives’ measurement-units to a neutral value between 0 (objective is not achieved) and 1 (fully achieved). To give one example: for the objective “high accuracy of information”, the best case is “100% accuracy”, translated to the value v=1; the worst case “0% accuracy” translates to v=0. Furthermore, we asked whether stakeholders agree with the implications of the commonly used (linear) additive aggregation model in MCDA (weighted average).</p><p>We will present and discuss main results of the MCDA-modeling. Our main aim is to give some insights into the participatory co-design process employed in FANFAR, and recommendations for other projects. We will discuss the problem structuring and preference elicitation methods, and how well they worked in this interesting West African context.</p>

scholarly journals Flood forecasting system development and availability of water related spatial data

2012 ◽  
Vol 56 (04) ◽  
pp. 769-785 ◽  
Author(s):  
Nejc Pogačnik ◽  
Sašo Petan ◽  
Mojca Sušnik ◽  
Janez Polajnar
Keyword(s):  
Spatial Data ◽  
System Development ◽  
Flood Forecasting ◽  
Forecasting System

scholarly journals Using Multi-Criteria Decision Analysis for transdisciplinary co-design of the FANFAR flood forecasting and alert system in West Africa

2021 ◽  
Author(s):  
Judit Lienert ◽  
Jafet Andersson ◽  
Daniel Hofmann ◽  
Francisco Silva Pinto ◽  
Martijn Kuller
Keyword(s):  
West Africa ◽  
Decision Analysis ◽  
System Performance ◽  
Flood Forecasting ◽  
West African ◽  
Problem Structuring Methods ◽  
Alert System ◽  
Multi Criteria Decision Analysis ◽  
Stakeholder Preferences ◽  
System Configurations

Abstract. Climate change is projected to increase flood risks in West Africa. The EU Horizon 2020 project FANFAR co-designed a pre-operational flood forecasting and alert system for West Africa in three lively workshops with 50–60 stakeholders, adopting a transdisciplinary framework from Multi-Criteria Decision Analysis (MCDA). We aimed to (i) exemplify MCDA as a structured transdisciplinary process; (ii) prioritize suitable FANFAR system configurations; and (iii) document and discuss empirical evidence. We used various interactive problem structuring methods in stakeholder sessions to generate 10 objectives and design 11 FANFAR system configurations. The non-additive MCDA model combined expert predictions about system performance with stakeholder preferences elicited in group sessions. All groups preferred a system producing accurate, clear, and accessible flood risk information that reaches recipients well before floods. To receive this, most groups would trade off higher operation and maintenance costs, development time, and implementing several languages. We accounted for uncertainty in expert predictions with Monte Carlo simulation. Sensitivity analyses tested the results’ robustness for changing MCDA aggregation models and diverging stakeholder preferences. Despite many uncertainties, three FANFAR system configurations achieved 63–70 % of the ideal case over all objectives in all stakeholder groups, and outperformed other options in cost-benefit visualizations. Stakeholders designed these best options to work reliably under difficult West African conditions rather than incorporating many advanced features. The current FANFAR system combines important features increasing system performance. Most respondents of a small online survey are satisfied, and willing to use the system in future. We discuss our learning drawing from design principles of transdisciplinary research. We attempted to over-come “unbalanced ownership” and “insufficient legitimacy” by including key West African institutions as consortium partners and carrying out co-design workshops with mandated representatives from 17 countries. MCDA overcomes challenges such as “lack of technical integration”, or “vagueness and ambiguity of results”. Whether FANFAR will have a “societal impact” depends on long term financing and system uptake by West African institutions after termination of EU sponsoring. We hope that our promising results will have a “scientific impact” and motivate further stakeholder engagement in hydrology research.

scholarly journals A pan-African medium-range ensemble flood forecast system

2015 ◽  
Vol 19 (8) ◽  
pp. 3365-3385 ◽  
Author(s):  
V. Thiemig ◽  
B. Bisselink ◽  
F. Pappenberger ◽  
J. Thielen
Keyword(s):  
Large Scale ◽  
Practical Implication ◽  
River Basins ◽  
Flood Forecasting ◽  
Small Scale ◽  
Flood Forecast ◽  
Flood Events ◽  
Forecast System ◽  
Pan African ◽  
Forecasting System

Abstract. The African Flood Forecasting System (AFFS) is a probabilistic flood forecast system for medium- to large-scale African river basins, with lead times of up to 15 days. The key components are the hydrological model LISFLOOD, the African GIS database, the meteorological ensemble predictions by the ECMWF (European Centre for Medium-Ranged Weather Forecasts) and critical hydrological thresholds. In this paper, the predictive capability is investigated in a hindcast mode, by reproducing hydrological predictions for the year 2003 when important floods were observed. Results were verified by ground measurements of 36 sub-catchments as well as by reports of various flood archives. Results showed that AFFS detected around 70 % of the reported flood events correctly. In particular, the system showed good performance in predicting riverine flood events of long duration (> 1 week) and large affected areas (> 10 000 km2) well in advance, whereas AFFS showed limitations for small-scale and short duration flood events. The case study for the flood event in March 2003 in the Sabi Basin (Zimbabwe) illustrated the good performance of AFFS in forecasting timing and severity of the floods, gave an example of the clear and concise output products, and showed that the system is capable of producing flood warnings even in ungauged river basins. Hence, from a technical perspective, AFFS shows a large potential as an operational pan-African flood forecasting system, although issues related to the practical implication will still need to be investigated.

Development of a Real-Time Flood Forecasting System by Hydraulic Flood Routing

2001 ◽  
Author(s):  
Joo Heon Lee ◽  
Do Hun Lee ◽  
Sang Man Jeong ◽  
Eun Tae Lee
Keyword(s):  
Real Time ◽  
Flood Forecasting ◽  
Flood Routing ◽  
Forecasting System

Measuring the skill of an operational ice jam flood forecasting system

2021 ◽  
Vol 52 ◽  
pp. 102001
Author(s):  
Brandon S. Williams ◽  
Apurba Das ◽  
Peter Johnston ◽  
Bin Luo ◽  
Karl-Erich Lindenschmidt
Keyword(s):  
Flood Forecasting ◽  
Ice Jam ◽  
Forecasting System

scholarly journals A Robust Skewed Boxplot for Detecting Outliers in Rainfall Observations in Real-Time Flood Forecasting

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Chao Zhao ◽  
Jinyan Yang
Keyword(s):  
Real Time ◽  
Exponential Function ◽  
Flood Forecasting ◽  
Interquartile Range ◽  
Skewed Data ◽  
Symmetric Distributions ◽  
Contaminated Data ◽  
Forecasting System

The standard boxplot is one of the most popular nonparametric tools for detecting outliers in univariate datasets. For Gaussian or symmetric distributions, the chance of data occurring outside of the standard boxplot fence is only 0.7%. However, for skewed data, such as telemetric rain observations in a real-time flood forecasting system, the probability is significantly higher. To overcome this problem, a medcouple (MC) that is robust to resisting outliers and sensitive to detecting skewness was introduced to construct a new robust skewed boxplot fence. Three types of boxplot fences related to MC were analyzed and compared, and the exponential function boxplot fence was selected. Operating on uncontaminated as well as simulated contaminated data, the results showed that the proposed method could produce a lower swamping rate and higher accuracy than the standard boxplot and semi-interquartile range boxplot. The outcomes of this study demonstrated that it is reasonable to use the new robust skewed boxplot method to detect outliers in skewed rain distributions.

Sign in / Sign up

Export Citation Format

Share Document