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Vulnerability Analysis in an Early Warning System for Drought

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Vulnerability Analysis in an Early Warning System for Drought Politecnico di Torino Porto Institutional Repository [Doctoral thesis] Vulnerability analysis in an Early Warning System for drought Original Citation: Angeluccetti I. (2014). Vulnerability analysis in an Early Warning System for drought. PhD thesis Availability: This version is available at : http://porto.polito.it/2543940/ since: May 2014 Published version: DOI:10.6092/polito/porto/2543940 Terms of use: This article is made available under terms and conditions applicable to Open Access Policy Arti- cle ("Creative Commons: Attribution 3.0") , as described at http://porto.polito.it/terms_and_ conditions.html Porto, the institutional repository of the Politecnico di Torino, is provided by the University Library and the IT-Services. The aim is to enable open access to all the world. Please share with us how this access benefits you. Your story matters. (Article begins on next page) POLITECNICO DI TORINO Doctorate school PhD in Environment and Territory - Environmental Protection and Management XXVI cycle Final Dissertation Vulnerability analysis in an Early Warning System for drought Angeluccetti Irene Tutor: Co-tutor: Prof. Piero Boccardo Ing. Francesca Perez April 2014 Table of contents ABSTRACT .................................................................................................................................. 4 ACKNOWLEDGMENTS .............................................................................................................. 5 1 INTRODUCTION ................................................................................................................ 6 2 THE DROUGHT THREAT .................................................................................................... 8 2.1 Drought general concepts and definitions .................................................................. 9 2.1.1 American Meteorological Society definition ....................................................... 9 2.1.2 UNCDD definition .................................................................................................. 9 2.1.3 NDMC definition .................................................................................................... 9 2.2 Hazard, vulnerability and risk general concepts ..................................................... 11 2.2.1 UN/ISDR definitions ............................................................................................. 12 2.2.2 Vulnerability and resilience .................................................................................. 12 2.3 The emergency management ................................................................................. 13 2.4 Early warning systems ............................................................................................. 14 2.5 Drought and food security ...................................................................................... 18 2.6 ITHACA vegetation anomaly monitoring system .................................................. 20 2.6.1 Data input and methodology ............................................................................. 20 2.6.2 Derived products ................................................................................................. 24 3 LITERATURE REVIEW ...................................................................................................... 26 4 DATA AND METHODS ......................................................................................................33 4.1 Data inventory ..........................................................................................................33 4.2 Conceptual model ................................................................................................... 39 4.2.1 Applied methodology ......................................................................................... 39 4.2.2 Agricultural vulnerability ..................................................................................... 41 4.2.2.1 Soil suitability for crop production - Step 1 ................................................ 42 4.2.2.2 Global Map of Irrigation Areas - Step 2 ...................................................... 44 4.2.2.3 Crop Diversity Index - Step 3 ...................................................................... 45 4.2.3 Risk surface ......................................................................................................... 47 4.2.3.1 Accessibility – Risk surface I ....................................................................... 48 4.2.3.2 Market analysis ........................................................................................... 49 4.2.3.3 Gravity models – Risk surface II .................................................................. 52 4.2.3.4 Gravity models with market flows – Risk surface III ................................. 56 4.2.4 Weighted hazard ................................................................................................. 56 4.2.5 Final alert maps .................................................................................................... 57 4.3 Case studies ............................................................................................................. 58 4.3.1 Niger ..................................................................................................................... 58 4.3.1.1 Sahel and Niger Early Warning Systems .................................................... 60 4.3.1.2 Applied model, input and intermediate results .........................................64 4.3.2 Mozambique ........................................................................................................ 76 4.3.2.1 Applied model, input and intermediate results ......................................... 78 4.4 Evaluation phase...................................................................................................... 82 4.4.1 Qualitative evaluation ......................................................................................... 83 4.4.2 Quantitative evaluation ....................................................................................... 85 5 RESULTS .......................................................................................................................... 90 5.1 Qualitative evaluation ............................................................................................ 90 5.2 Quantitative evaluation ......................................................................................... 103 5.3 Discussion .............................................................................................................. 109 CONCLUSIONS AND FURTHER DEVELOPMENTS ................................................................. 113 ANNEXES ................................................................................................................................. 117 Annex I - Matlab script for CDI ........................................................................................... 118 Annex II - CountrySTAT raw data ...................................................................................... 120 Annex III - Developed tools ............................................................................................... 126 BIBLIOGRAPHY ...................................................................................................................... 139 3 ABSTRACT Early Warning Systems (EWS) for drought are often based on risk models that do not, or marginally, take into account the vulnerability factor. The multifaceted nature of drought (hydrological, meteorological, and agricultural) is source of coexistence for different ways to measure this phenomenon and its effects. The mentioned issue, together with the complexity of impacts generated by this hazard, causes the current underdevelopment of drought EWS compared to other hazards. In Least Developed Countries, where drought events causes the highest numbers of affected people, the importance of correct monitoring and forecasting is considered essential. Existing early warning and monitoring systems for drought, produced at different geographic levels, provide only in a few cases an actual spatial model that tries to describe the cause-effect link between where the hazard is detected and where impacts occur. Integrate vulnerability information in such systems would permit to better estimate affected zones and livelihoods, improving the effectiveness of produced hazard- related datasets and maps. In fact, the need of simplification and, in general, of a direct applicability of scientific outputs is still a matter of concern for field experts and early warning products end-users. Even if the surplus of hazard related information produced on the occasion of catastrophic events has, in some cases, led to the creation of specific data-sharing platforms, the conveyed meaning and usefulness of each product has not yet been addressed. The present work is an attempt to fill this gap which is still an open issue for the scientific community as well as for the humanitarian aid world. The present study aims at conceiving a simplified vulnerability model to embed into an existing EWS for drought, which is based on the monitoring of vegetation phenological parameters, produced using free satellite derived datasets. The proposed vulnerability model includes (i) a pure agricultural vulnerability and (ii) a systemic vulnerability. The first considers the agricultural potential of terrains, the diversity of cultivated
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