“…Heavy and abundant rainfall usually accompany the rainy season with annual rainfall ranging from 1400 mm in the northern part to about 2500 mm in the Southern part ( Fagbohun et al., 2017 ). The state has major surface waters which include springs, lakes, streams, and major rivers such as the southward-flowing Niger River that drains into the Atlantic Ocean, and the Anambra River that drains into the Niger River ( Egboka and Okoyeh, 2019 ; Okoyeh et al., 2014 ). The State has an annual average temperature that ranges from 20.78 °C to 30.24 °C, with a relative humidity that ranges from 34% annual minimum during the dry season to 89% maximum during the rainy season ( Chukwuma et al., 2021 ).…”
Flooding is a major environmental problem facing Anambra State of Nigeria, which also threatens food security in the state. To address this issue, continual flood vulnerability mapping exploring more efficient methods is needed to facilitate flood risk management in the state. The advantages of employing spatial information technologies such as Remote Sensing (RS) and Geographic Information System (GIS) in flood vulnerability mapping has been widely documented; the limitations of employing GIS alone in effective vulnerability analysis have also been documented by researchers. To overcome these limitations, this study adopted the use of GIS and the integration of Interval Value Fuzzy Rough Number (IVFRN), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Analytical Network Process (ANP) method in vulnerability assessment of flood hazard. The result of the study shows that the state is very vulnerable to flood with 73% of the total area of the state lying between Very High and Medium vulnerable zones. The most vulnerable Local Government Area (LGA) in the State is Anambra West with 95% of the total area of the LGA lying between Very High and Medium vulnerable zones. Furthermore, the obtained values ofR ÀD show that Rainfall Intensity factor is the major cause of flood in the study area with the highest positive value of 1.55 and Soil factor is the major effect with the highest negative value of -0.93. The IVFRN-DEMATEL-ANP assessment model was validated using AUC-ROC method; an AUC value of 0.946 was obtained, this indicates that the model has excellent prediction accuracy. This study was able to establish the feasibility of integrating the IVFRN, DEMATEL and ANP methods in flood vulnerability assessment. It is recommended that the provision of adequate drainage systems should be prioritized to areas of high flood vulnerability index; to help mitigate flood hazards in the State. Also, strategic planning of infrastructures and emergency routes for moving people and key assets from vulnerable areas especially during the rainy season should be geospatialbased and systematic.
“…Heavy and abundant rainfall usually accompany the rainy season with annual rainfall ranging from 1400 mm in the northern part to about 2500 mm in the Southern part ( Fagbohun et al., 2017 ). The state has major surface waters which include springs, lakes, streams, and major rivers such as the southward-flowing Niger River that drains into the Atlantic Ocean, and the Anambra River that drains into the Niger River ( Egboka and Okoyeh, 2019 ; Okoyeh et al., 2014 ). The State has an annual average temperature that ranges from 20.78 °C to 30.24 °C, with a relative humidity that ranges from 34% annual minimum during the dry season to 89% maximum during the rainy season ( Chukwuma et al., 2021 ).…”
Flooding is a major environmental problem facing Anambra State of Nigeria, which also threatens food security in the state. To address this issue, continual flood vulnerability mapping exploring more efficient methods is needed to facilitate flood risk management in the state. The advantages of employing spatial information technologies such as Remote Sensing (RS) and Geographic Information System (GIS) in flood vulnerability mapping has been widely documented; the limitations of employing GIS alone in effective vulnerability analysis have also been documented by researchers. To overcome these limitations, this study adopted the use of GIS and the integration of Interval Value Fuzzy Rough Number (IVFRN), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Analytical Network Process (ANP) method in vulnerability assessment of flood hazard. The result of the study shows that the state is very vulnerable to flood with 73% of the total area of the state lying between Very High and Medium vulnerable zones. The most vulnerable Local Government Area (LGA) in the State is Anambra West with 95% of the total area of the LGA lying between Very High and Medium vulnerable zones. Furthermore, the obtained values ofR ÀD show that Rainfall Intensity factor is the major cause of flood in the study area with the highest positive value of 1.55 and Soil factor is the major effect with the highest negative value of -0.93. The IVFRN-DEMATEL-ANP assessment model was validated using AUC-ROC method; an AUC value of 0.946 was obtained, this indicates that the model has excellent prediction accuracy. This study was able to establish the feasibility of integrating the IVFRN, DEMATEL and ANP methods in flood vulnerability assessment. It is recommended that the provision of adequate drainage systems should be prioritized to areas of high flood vulnerability index; to help mitigate flood hazards in the State. Also, strategic planning of infrastructures and emergency routes for moving people and key assets from vulnerable areas especially during the rainy season should be geospatialbased and systematic.
“…Geologically, the state has five predominant formations, including the Imo Formation (Imo shale and Ebenebe sandstone) (Paleocene), the Nsukka Formation (Maastrichtian–Danian), the Ogwashi-Asaba Formation (Oligocene–Miocene), the Ameki Formation (Nanka sandstone and Nsugbe sandstone) (Eocene), and the Benin Formation (Pliocene-Recent) (Anizoba et al 2020 ). Hydrologically, the state has surface water sources from springs, streams, lakes, and other major rivers, such as the Anambra River, which serves as a tributary to the Niger River, and the Niger River that connects to the Atlantic Ocean (Egboka and Okoyeh 2019 ). Fig.…”
This study evaluated the susceptibility to groundwater pollution using a modified DRASTIC model. A novel hybrid multi-criteria decision-making (MCDM) model integrating Interval Rough Numbers (IRN), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Analytical Network Process (ANP) was used to investigate the interrelationships between critical hydrogeologic factors (and determine their relative weights) via a novel vulnerability index based on the DRASTIC model. The flexibility of GIS in handling spatial data was employed to delineate thematic map layers of the hydrogeologic factors and to improve the DRASTIC model. The hybrid MCDM model results show that net recharge (a key hydrogeologic factor) had the highest priority with a weight of 0.1986. In contrast, the topography factor had the least priority, with a weight of 0.0497. A case study validated the hybrid model using Anambra State, Nigeria. The resultant vulnerability map shows that 12.98% of the study area falls into a very high vulnerability class, 31.90% falls into a high vulnerability, 23.52% falls into the average vulnerability, 21.75% falls into a low vulnerability, and 9.85% falls into very low vulnerability classes, respectively. In addition, nitrate concentration was used to evaluate the degree of groundwater pollution. Based on observed nitrate concentration, the modified DRASTIC model was validated and compared to the traditional DRASTIC model; interestingly, the spatial model of the modified DRASTIC model performed better. This study is thus critical for environmental monitoring and implementing appropriate management interventions to protect groundwater resources against indiscriminate sources of pollution.
“…In Anambra state, Nigeria, environmental education and sustainable construction are needed to rewrite the wrongs of natural and anthropogenic activities with effects in high temperatures, dust storms, excessive aridity, flooding, soil and gully erosion, landslides, pollution and contamination, desertification etc. (Egboka and Okoyeh, 2019).…”
Green building technology (GBT) implies products of environmental sciences and technology infusion integrated in constructions to achieve an end product of green or sustainable building. This study examined Lecturersâ perception of GBT as a driver for the teaching and learning of sustainable construction and environmental education in Anambra state, Nigeria. Structured questionnaire survey of 64 lecturers teaching constructions and environmental science inclined courses provided the data for the analysis. Findings revealed that active players for environmental transformation are required in the areas of engineering, technology, environmental science, architecture, and education. Also, although 100% of the respondents were aware of sustainable development goals, 92.2% need more orientation on GBT required to achieve sustainability in construction industry. The respondents have interest in GBT (89.1%), but actions such as reading researches (37.5%) and publishing in GBT (23.4) were very low. The implication of the findings indicates that poor attention to sustainable constructions and environmental education in Anambra state is proportional to the perception of higher institution lecturers towards GBT.
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