Floods and food security: A method to estimate the effect of inundation on crops availability

Pacetti, Tommaso; Caporali, Enrica; Rulli, Maria Cristina

doi:10.1016/j.advwatres.2017.06.019

Cited by 56 publications

(47 citation statements)

References 21 publications

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“…Many studies used three to four depth classes and associated potential damage in crop loss assessment [47,[60][61][62]. Waisurasingha et al [30] and Pacetti et al [63] used 80 and 100 cm flood-depth threshold to determine crop damage. The depth-damage curve allows a continuous loss assessment at any flood depth, whereas loss assessment using depth categories or thresholds generalizes loss within the range of depth categories.…”

Section: Flood-intensity-based Crop Loss Assessmentmentioning

confidence: 99%

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A Systematic Review on Case Studies of Remote-Sensing-Based Flood Crop Loss Assessment

Rahman

2020

Agriculture

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This article reviews case studies which have used remote sensing data for different aspects of flood crop loss assessment. The review systematically finds a total of 62 empirical case studies from the past three decades. The number of case studies has recently been increased because of increased availability of remote sensing data. In the past, flood crop loss assessment was very generalized and time-intensive because of the dependency on the survey-based data collection. Remote sensing data availability makes rapid flood loss assessment possible. This study groups flood crop loss assessment approaches into three broad categories: flood-intensity-based approach, crop-condition-based approach, and a hybrid approach of the two. Flood crop damage assessment is more precise when both flood information and crop condition are incorporated in damage assessment models. This review discusses the strengths and weaknesses of different loss assessment approaches. Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat are the dominant sources of optical remote sensing data for flood crop loss assessment. Remote-sensing-based vegetation indices (VIs) have significantly been utilized for crop damage assessments in recent years. Many case studies also relied on microwave remote sensing data, because of the inability of optical remote sensing to see through clouds. Recent free-of-charge availability of synthetic-aperture radar (SAR) data from Sentinel-1 will advance flood crop damage assessment. Data for the validation of loss assessment models are scarce. Recent advancements of data archiving and distribution through web technologies will be helpful for loss assessment and validation.

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Section: Flood-intensity-based Crop Loss Assessmentmentioning

confidence: 99%

“…Local-scaled studies often utilized fine spatial resolution images to get a detailed assessment at a parcel level. Case studies are also conducted at the national level in some countries like Bangladesh, Pakistan, and Cambodia [32,63,64].…”

Section: Spatiotemporal Distribution Of Case Study Researchmentioning

confidence: 99%

A Systematic Review on Case Studies of Remote-Sensing-Based Flood Crop Loss Assessment

Rahman

2020

Agriculture

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“…In future, we will further to explore the application of this data in the flood process of other lakes and rivers in the study area. Moreover, as a disaster event, floods can also be used to explore the impact of floods on some things, such as economic losses and crop damage [34]. Remote sensing data with high temporal resolution can be used as basic data for determining the extent of floods for disaster result analysis.…”

Section: Flood Analysis Using the Productsmentioning

confidence: 99%

Dynamic Change Analysis of Surface Water in the Yangtze River Basin Based on MODIS Products

et al. 2018

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The use of remote sensing to monitor surface water bodies has gradually matured. Long-term serial water change analysis and floods monitoring are currently research hotspots of remote sensing hydrology. However, these studies are also faced with some problems, such as coarse temporal or spatial resolution of some remote sensing data. In general, flood monitoring requires high temporal resolution, and small-scale surface water extraction requires high spatial resolution. The machine learning method has been proven to be effective against long-term serial surface water extraction, such as random forests (RFs). MODIS data are well suited for large-scale surface water dynamic analysis and flood monitoring because of its short return cycle and medium spatial resolution. In this paper, the Yangtze River Basin (YRB) in China was selected as the study area, and two MODIS products (MOD09A1 and MOD13Q1) and RF method were used to extract the surface water from 2000 to 2016. Considering the disadvantages of temporal or spatial resolution of these two MODIS products, this study also presents a data fusion method to combine them and get higher spatiotemporal resolution water results. Finally, 762 surface water maps from 2000 to 2016 are obtained, whose temporal and spatial resolution is every eight days and 250 m, respectively. In addition, water extent variation is analyzed and compared to observed precipitation data. The main conclusions are as follows: (1) this constructed approach for long-term serial surface water extraction based on the RF classifier is feasible, and a good fusion method is used to obtain the surface water body with higher spatiotemporal resolution; (2) the maximum area of the surface water extent is 48.53 × 10 3 km 2 , and seasonal and permanent water areas are 20.51 × 10 3 km 2 and 28.01 × 10 3 km 2 , respectively; (3) surface water area is increasing in the YRB, such that seasonal water area decreased by 3450 km 2 , and the permanent water area increased by 3565 km 2 in 2001-2015; (4) precipitation is the main factor causing variation in the surface water bodies, and they both show an increasing trend in 2000-2016. As such, the approach is worth referring to other remote sensing applications, and these products are very both valuable for water resource management and flood monitoring in the study area.

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“…Climate change is placing a stronger pressure on the resource farmers depend on, increasing the risks associated with disasters. The impacts of disasters are greater in developing countries than in developed countries (Lolemtum et al, 2017;Marfai et al, 2008;Pacetti et al, 2017). Disasters have affected more than 1.9 billion people and caused over USD 494 billion in estimated damage in developing countries from 2003 to 2013 (FAO, 2015).…”

Section: Introductionmentioning

confidence: 99%

The Impacts of Flood and Drought on Food Security in Central Java

Pratiwi

Ramadhani

Nurrochmad

et al. 2020

Journal of the Civil Engineering Forum

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To achieve food security, water must be available at the right place, at the right time, in the right quantity, and be of the right quality. Water-related disasters will negatively affect agricultural areas and crop production, which can threaten food security. Nevertheless, flood and drought strike Central Java, one of the rice production centres in Indonesia, every year, and climate change has been worsening the condition because extreme events occur more frequently. This study reviews the impacts of flood and drought on paddy fields in Central Java from 2014 to 2018. A set of historical documents, including reports on flood and drought, rainfall records, and rice production, were collected from government institutions. Quantitative analysis was conducted using statistics and geographic information system tools. The results showed that the 2014 flood event reflected badly on 94,306 hectares (ha) paddy fields. Four severely affected regencies were Pati (25,460 ha), Demak (13,560 ha), Jepara (13,281 ha), and Kudus (12,203 ha). Meanwhile, drought in 2015 affected 82,324 ha paddy field. The areas severely damaged by drought were Blora (12,335 ha), Cilacap (11,503 ha), Grobogan (10,514 ha), and Pemalang (10,134 ha). Pearson’s correlation analysis results indicated that the correlation between annual rainfall and drought impact (r = −0.865, p = 0.058) is more significant than that between annual rainfall and drought impact (r = 0.794, p = 0.108). The stakeholders have adopted some strategies to minimise losses, such as establishing a 1,000 small water reservoirs program, preparing temporary pump irrigation, and providing agricultural insurance. Nevertheless, more efforts are still necessary to fight against food insecurity.

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Floods and food security: A method to estimate the effect of inundation on crops availability

Cited by 56 publications

References 21 publications

A Systematic Review on Case Studies of Remote-Sensing-Based Flood Crop Loss Assessment

A Systematic Review on Case Studies of Remote-Sensing-Based Flood Crop Loss Assessment

Dynamic Change Analysis of Surface Water in the Yangtze River Basin Based on MODIS Products

The Impacts of Flood and Drought on Food Security in Central Java

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