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Velia Bigi
Interuniversity Department of Regional and Urban Studies and Planning (DIST), Politecnico di Torino & Università di Torino, 10125 Torino, Italy

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Journal article
Published: 09 April 2021 in Climate
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Climate analyses at a local scale are an essential tool in the field of sustainable development. The evolution of reanalysis datasets and their greater reliability contribute to overcoming the scarcity of observed data in the southern areas of the world. The purpose of this study is to compute the reference monthly values and ranges of maximum and minimum temperatures for the eight main inhabited villages of North Horr Sub-County, in northern Kenya. The official ten-day dataset derived from the Kenyan Meteorological Department (KMD), the monthly datasets derived from the ERA-Interim reanalysis (ERA), the Observational-Reanalysis Hybrid (ORH) and the Climate Limited Area Mode driven by HadG-EM2-ES (HAD) are assessed on a local scale using the most common statistical indices to determine which is more reliable in representing monthly maximum and minimum temperatures. Overall, ORH datasets showed lower biases and errors in representing local temperatures. Through an innovative methodology, a new set of monthly mean temperature values and ranges derived from ORH datasets are calculated for each location in the study area, in order to guarantee to locals an historical benchmark to compare present observations. The findings of this research provide insights for environmental risk management, supporting local populations in reducing their vulnerability.

ACS Style

Giovanni Siciliano; Velia Bigi; Ingrid Vigna; Elena Comino; Maurizio Rosso; Elena Cristofori; Alessandro Demarchi; Alessandro Pezzoli. Comparison of Multiple Maximum and Minimum Temperature Datasets at Local Level: The Case Study of North Horr Sub-County, Kenya. Climate 2021, 9, 62 .

AMA Style

Giovanni Siciliano, Velia Bigi, Ingrid Vigna, Elena Comino, Maurizio Rosso, Elena Cristofori, Alessandro Demarchi, Alessandro Pezzoli. Comparison of Multiple Maximum and Minimum Temperature Datasets at Local Level: The Case Study of North Horr Sub-County, Kenya. Climate. 2021; 9 (4):62.

Chicago/Turabian Style

Giovanni Siciliano; Velia Bigi; Ingrid Vigna; Elena Comino; Maurizio Rosso; Elena Cristofori; Alessandro Demarchi; Alessandro Pezzoli. 2021. "Comparison of Multiple Maximum and Minimum Temperature Datasets at Local Level: The Case Study of North Horr Sub-County, Kenya." Climate 9, no. 4: 62.

Review
Published: 09 January 2021 in Climate
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Despite indicators-based assessment models for flood vulnerability being a well-established methodology, a specific set of indicators that are universally or widely accepted has not been recognized yet. This work aims to review previous studies in the field of vulnerability analysis in order to overcome this knowledge gap identifying the most accepted sub-indicators of exposure, sensitivity and adaptive capacity. Moreover, this review aims to clarify the use of the terms of vulnerability and risk in vulnerability assessment. Throughout a three-phase process, a matrix containing all the sub-indicators encountered during the review process was constructed. Then, based on an adaptation of the Pareto diagram, a set of the most relevant sub-indicators was identified. According to the citation count of each sub-indicator, indeed, 33 sub-indicators were chosen to represent the most universally or widely accepted sub-indicators.

ACS Style

Velia Bigi; Elena Comino; Magda Fontana; Alessandro Pezzoli; Maurizio Rosso. Flood Vulnerability Analysis in Urban Context: A Socioeconomic Sub-Indicators Overview. Climate 2021, 9, 12 .

AMA Style

Velia Bigi, Elena Comino, Magda Fontana, Alessandro Pezzoli, Maurizio Rosso. Flood Vulnerability Analysis in Urban Context: A Socioeconomic Sub-Indicators Overview. Climate. 2021; 9 (1):12.

Chicago/Turabian Style

Velia Bigi; Elena Comino; Magda Fontana; Alessandro Pezzoli; Maurizio Rosso. 2021. "Flood Vulnerability Analysis in Urban Context: A Socioeconomic Sub-Indicators Overview." Climate 9, no. 1: 12.

Journal article
Published: 27 July 2020 in Sustainability
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In Kenyan rural areas belonging to the Arid and Semi-Arid Lands (ASALs), water quantity and water quality are major issues for the local population. In North Horr Sub-County water quality is threatened by nitrate contamination due to fecal matter pollution. This research, hence, aims at assessing the vulnerability of open shallow water sources to nitrate contamination due to fecal intrusion following flooding events and nitrate percolation in groundwater. The present research, indeed, provides, on one hand, new insights into the analysis of the vulnerability in a scant data context; on the other hand, it assesses the adaptation measures contained in the local development plan. Applying the reference definition of the Intergovernmental Panel on Climate Change (IPCC), the results demonstrate that the open shallow water sources in the northern part of the sub-county are more vulnerable to nitrate contamination. Furthermore, the consistency of the results proves the suitability of the methodology selected. Understanding the vulnerability at the local scale is key to planning risk-reduction strategies as well to increasing the local population’s knowledge about flood-related risks and water quality.

ACS Style

Velia Bigi; Alessandro Pezzoli; Elena Comino; Maurizio Rosso. A Vulnerability Assessment in Scant Data Context: The Case of North Horr Sub-County. Sustainability 2020, 12, 6024 .

AMA Style

Velia Bigi, Alessandro Pezzoli, Elena Comino, Maurizio Rosso. A Vulnerability Assessment in Scant Data Context: The Case of North Horr Sub-County. Sustainability. 2020; 12 (15):6024.

Chicago/Turabian Style

Velia Bigi; Alessandro Pezzoli; Elena Comino; Maurizio Rosso. 2020. "A Vulnerability Assessment in Scant Data Context: The Case of North Horr Sub-County." Sustainability 12, no. 15: 6024.

Journal article
Published: 05 April 2020 in Sustainability
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Understanding ongoing trends at local level is fundamental in research on climate change. However, in the Global South it is hampered by a lack of data. The scarcity of land-based observed data can be overcome through satellite-derived datasets, although performance varies according to the region. The purpose of this study is to compute the normal monthly values of precipitation for the eight main inhabited areas of North Horr Sub-County, in northern Kenya. The official decadal precipitation dataset from the Kenyan Meteorological Department (KMD), the Global Precipitation Climatology Centre (GPCC) monthly dataset and the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) monthly dataset are compared with the historical observed data by means of the most common statistical indices. The GPCC showed the best fit for the study area. The Quantile Mapping correction is applied to combine the high resolution of the KMD dataset with the high performance of the GPCC set. A new and more reliable bias-corrected monthly precipitation time series for 1983–2014 results for each location. This dataset allows a detailed description of the precipitation distribution through the year, which can be applied in the climate change adaptation and tailored territorial planning.

ACS Style

Ingrid Vigna; Velia Bigi; Alessandro Pezzoli; Angelo Besana. Comparison and Bias-Correction of Satellite-Derived Precipitation Datasets at Local Level in Northern Kenya. Sustainability 2020, 12, 2896 .

AMA Style

Ingrid Vigna, Velia Bigi, Alessandro Pezzoli, Angelo Besana. Comparison and Bias-Correction of Satellite-Derived Precipitation Datasets at Local Level in Northern Kenya. Sustainability. 2020; 12 (7):2896.

Chicago/Turabian Style

Ingrid Vigna; Velia Bigi; Alessandro Pezzoli; Angelo Besana. 2020. "Comparison and Bias-Correction of Satellite-Derived Precipitation Datasets at Local Level in Northern Kenya." Sustainability 12, no. 7: 2896.

Journal article
Published: 25 February 2020 in Water
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In the last decades, the Sahelian area was hit by an increase of flood events, both in frequency and in magnitude. In order to prevent damages, an early warning system (EWS) has been planned for the Sirba River, the major tributary of the Middle Niger River Basin. The EWS uses the prior notification of Global Flood Awareness System (GloFAS) to realize adaptive measures in the exposed villages. This study analyzed the performances of GloFAS 1.0 and 2.0 at Garbey Kourou. The model verification was performed using continuous and categorical indices computed according to the historical flow series and the flow hazard thresholds. The unsatisfactory reliability of the original forecasts suggested the performing of an optimization to improve the model performances. Therefore, datasets were divided into two periods, 5 years for training and 5 years for validation, and an optimization was conducted applying a linear regression throughout the homogeneous periods of the wet season. The results show that the optimization improved the performances of GloFAS 1.0 and decreased the forecast deficit of GloFAS 2.0. Moreover, it highlighted the fundamental role played by the hazard thresholds in the model evaluation. The optimized GloFAS 2.0 demonstrated performance acceptable in order to be applied in an EWS.

ACS Style

Giulio Passerotti; Giovanni Massazza; Alessandro Pezzoli; Velia Bigi; Ervin Zsótér; Maurizio Rosso. Hydrological Model Application in the Sirba River: Early Warning System and GloFAS Improvements. Water 2020, 12, 620 .

AMA Style

Giulio Passerotti, Giovanni Massazza, Alessandro Pezzoli, Velia Bigi, Ervin Zsótér, Maurizio Rosso. Hydrological Model Application in the Sirba River: Early Warning System and GloFAS Improvements. Water. 2020; 12 (3):620.

Chicago/Turabian Style

Giulio Passerotti; Giovanni Massazza; Alessandro Pezzoli; Velia Bigi; Ervin Zsótér; Maurizio Rosso. 2020. "Hydrological Model Application in the Sirba River: Early Warning System and GloFAS Improvements." Water 12, no. 3: 620.

Journal article
Published: 05 September 2018 in Climate
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Despite the interest in detecting the extremes of climate in the West African Sahel, few studies have been specifically conducted on the Republic of Niger. This research focuses on past, present, and future precipitation trends for the city of Niamey through the combined assessment of WMO precipitation indices using RClimDex and the Standardized Precipitation Index. Past daily precipitation data were derived from a 60-year reconstructed meteorological dataset for the Niamey airport station for the period of 1950–2009 and validated through comparison with an observed time series at Niamey airport (1980–2012). Precipitation analysis confirms the literature’s findings, in particular, a decreasing trend in total precipitation over the period of 1950–2009, and a positive trend for data that spans over the period of 1980–2009, suggesting a precipitation recovery after the dry epoch (1968–1985), even if the deficit with the wettest years in the period of 1950–1968 has not been made up. Furthermore, WATCH-Forcing-Data-ERA-Interim projections, elaborated under RCP 4.5 and RCP 8.5 socio-economic conditions, show that precipitation will increase in the future. Therefore, the Nigerien population will benefit from increased rainfall, but will also have to cope with the exacerbation of both flood and drought risks due to a great interannual variability that can positively or negatively influence water availability.

ACS Style

Velia Bigi; Alessandro Pezzoli; Maurizio Rosso. Past and Future Precipitation Trend Analysis for the City of Niamey (Niger): An Overview. Climate 2018, 6, 73 .

AMA Style

Velia Bigi, Alessandro Pezzoli, Maurizio Rosso. Past and Future Precipitation Trend Analysis for the City of Niamey (Niger): An Overview. Climate. 2018; 6 (3):73.

Chicago/Turabian Style

Velia Bigi; Alessandro Pezzoli; Maurizio Rosso. 2018. "Past and Future Precipitation Trend Analysis for the City of Niamey (Niger): An Overview." Climate 6, no. 3: 73.