scholarly journals Quantifying National-Scale Changes in Agricultural Land Exposure to Fluvial Flooding

2021 ◽  
Vol 13 (22) ◽  
pp. 12495
Author(s):  
Heather Craig ◽  
Ryan Paulik ◽  
Utkur Djanibekov ◽  
Patrick Walsh ◽  
Alec Wild ◽  
...  
Keyword(s):  
Agricultural Land ◽  
Flood Hazard ◽  
Dairy Farming ◽  
Flood Impacts ◽  
Flood Exposure ◽  
Management Plans ◽  
Risk Areas ◽  
Production Value ◽  
Spatio Temporal ◽  
National Trends

This study quantifies the exposure of agricultural land in Aotearoa-New Zealand’s (A-NZ) flood hazard zones (FHZs). We developed a spatio-temporal flood exposure framework to quantify the extent of the area and yearly earnings before income and tax (EBIT) for arable, forestry, horticulture, sheep and beef, and dairy land in FHZs between 1990 and 2016. In 1990, ~1.57 million hectares of agricultural land were exposed, decreasing slightly to ~1.50 million hectares by 2016. However, there was a change in the lower-value types of agricultural land uses being exposed, such as for sheep and beef farming and forestry, toward dairy farming (from ~364,000 hectares in FHZs in 2008 to ~471,000 hectares in 2016). Dairy farming is more intensively staffed with larger amounts of fixed assets, making them less resilient to flood impacts. Despite this, conversion to dairy farming even within the identified FHZs has been driven by the increasing profitability of the enterprise. As a result of both the production value change and land area increases, the dairy EBIT values within FHZs rose rapidly from NZD 382 million to NZD 1.25 billion between 2008 and 2012, creating significantly more economic exposure for A-NZ. This trend is particularly evident in the Southland, Canterbury, and Waikato regions. Similarly, in the Marlborough, Tasman, and Hawke’s Bay regions, there was an increase in high-value horticultural land—predominantly viticulture—in FHZs (a increase of NZD 321 million in annual EBIT for exposed horticulture across the three regions). Identifying sub-national trends in agricultural flood exposure allows for a detailed analysis of the likely impacts in high-risk areas, which can inform emergency management plans and mitigative actions that diminish the economic impacts from flood events.

scholarly journals Spatio-temporal dynamics of flood exposure in Shenzhen from present to future

2021 ◽  
pp. 239980832199154
Author(s):  
Gizem Mestav Sarica ◽  
Tinger Zhu ◽  
Wei Jian ◽  
Edmond Yat-Man Lo ◽  
Tso-Chien Pan
Keyword(s):  
Pearl River Delta ◽  
Temporal Dynamics ◽  
Flood Hazard ◽  
River Delta ◽  
Pearl River ◽  
Rapid Urbanization ◽  
The Pearl River Delta ◽  
Flood Exposure ◽  
Spatio Temporal ◽  
The Pearl River

The Pearl River Delta metropolitan region is one of the most densely urbanized megapolises worldwide with high exposure to weather-related disasters such as storms, storm surges and river floods. Shenzhen megacity has been the fastest growing city in the Pearl River Delta region with a significant increase of resident population from 0.32 million in 1980 to 13.03 million in 2018. Being a flood-prone city, Shenzhen’s rapid urbanization has further exacerbated potential flood losses and forthcoming risk. Thus, evaluating the changes in its exposure from present to future is essential for flood risk assessment, mitigation and management purposes. The main objective of this study is to present a methodology to assess the spatio-temporal dynamics of flood exposure from present to future using high-resolution and open-source data with a particular focus on the built-up area. To achieve this, the SLEUTH model, a cellular automata-based urban growth model, was employed for predicting the built-up area in Shenzhen in 2030. An almost threefold increase was observed in total built-up area from 421 km2 in 1995 to 1166 km2 in 2030, with the 2016 built-up area being 858 km2. Built-up areas, both present (2016) and projected (2030), were then used as the land cover input for flood hazard assessment based on a fuzzy comprehensive evaluation model, which classified the flood hazard into five levels. The analysis indicates that the built-up area subjected to the two highest flood hazard levels will increase by almost 88% (212 km2) from present to future. The approach presented here can be leveraged by policymakers to identify critical areas that should be prioritized for flood mitigation and protection actions to minimize potential losses.

scholarly journals Effects of Land-Related Policies on Deforestation in a Protected Area: The Case Study of Rema-Kalenga Wildlife Sanctuary, Bangladesh

Conservation ◽  
2021 ◽  
Vol 1 (3) ◽  
pp. 168-181
Author(s):  
Mohammad Ismail Hossain ◽  
Shinya Numata
Keyword(s):  
Land Use ◽  
Agricultural Land ◽  
Interactive Effect ◽  
Forest Policy ◽  
Land Policy ◽  
Wildlife Sanctuary ◽  
Landsat Images ◽  
Change Analysis ◽  
Management Plans ◽  
Total Forest Area

In protected areas (PAs) in Bangladesh, as policies shift from net deforestation, conservation initiatives and various management plans have been implemented to reduce deforestation and include public participation at multiple levels. However, the interactive effect of land-related policies on deforestation in PAs is poorly understood. In this study, land-use change analysis using geographic information system data was performed to investigate how policies affected land use and land cover change in Rema-Kalenga Wildlife Sanctuary (RKWS), particularly the National Forest Policy (1979~), National Land Policy (2001~), and Agricultural Land Policy (1999~), using a series of Landsat images captured at different times. Our analyses showed that the total forest area increased in the 1994–2005 period when a plantation program was implemented, and also that many forest areas were replaced with noncommercial agricultural land areas in the 2005–2013 and 2013–2018 periods, when land zoning and co-management programs were implemented under different land-related policies. Commercial and non-commercial agricultural land expansions were the main drivers of deforestation, suggesting that several programs under the different land-related policies could have had synergetic effects on deforestation even in PAs. Our findings emphasize the importance of considering the undesirable effects of land-related policies in Pas, and the need to support the community for forest conservation.

scholarly journals Spatio-temporal epidemiology of the tuberculosis incidence rate in Iran 2008 to 2018

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Behzad Kiani ◽  
Amene Raouf Rahmati ◽  
Robert Bergquist ◽  
Soheil Hashtarkhani ◽  
Neda Firouraghi ◽  
...  
Keyword(s):  
High Risk ◽  
Incidence Rate ◽  
Policy Development ◽  
Temporal Pattern ◽  
Temporal Analysis ◽  
High Rate ◽  
Spatial Scan Statistic ◽  
Cross Sectional ◽  
Risk Areas ◽  
Spatio Temporal

Abstract Background Effective reduction of tuberculosis (TB) requires information on the distribution of TB incidence rate across time and location. This study aims to identify the spatio-temporal pattern of TB incidence rate in Iran between 2008 and 2018. Methods This cross-sectional study was conducted on aggregated TB data (50,500 patients) at the provincial level provided by the Ministry of Health in Iran between 2008 and 2018. The Anselin Local Moran’s I and Getis-Ord Gi* were performed to identify the spatial variations of the disease. Furthermore, spatial scan statistic was employed for purely temporal and spatio-temporal analyses. In all instances, the null hypothesis of no clusters was rejected at p ≤ 0.05. Results The overall incidence rate of TB decreased from 13.46 per 100,000 (95% CI: 13.19–13.73) in 2008 to 10.88 per 100,000 (95% CI: 10.65–11.11) in 2018. The highest incidence rate of TB was observed in southeast and northeast of Iran for the whole study period. Additionally, spatial cluster analysis discovered Khuzestan Province, in the West of the country, having significantly higher rates than neighbouring provinces in terms of both total TB and smear-positive pulmonary TB (SPPTB). Purely temporal analysis showed that high-rate and low-rate clusters were predominantly distributed in the time periods 2010–2014 and 2017–2018. Spatio-temporal results showed that the statistically significant clusters were mainly distributed from centre to the east during the study period. Some high-trend TB and SPPTB statistically significant clusters were found. Conclusion The results provided an overview of the latest TB spatio-temporal status In Iran and identified decreasing trends of TB in the 2008–2018 period. Despite the decreasing incidence rate, there is still need for screening, and targeting of preventive interventions, especially in high-risk areas. Knowledge of the spatio-temporal pattern of TB can be useful for policy development as the information regarding the high-risk areas would contribute to the selection of areas needed to be targeted for the expansion of health facilities.

scholarly journals Zakour Forest fire risk map assessment in the commune of Mamounia (Mascara, Algeria)

2021 ◽  
Vol 63 (1) ◽  
pp. 21-35
Author(s):  
Djamel Anteur ◽  
Abdelkrim Benaradj ◽  
Youcef Fekir ◽  
Djillali Baghdadi
Keyword(s):  
Decision Making ◽  
Forest Fires ◽  
Human Activities ◽  
Forest Ecosystems ◽  
Agricultural Land ◽  
Fire Risk ◽  
Risk Map ◽  
Management Plans ◽  
The City ◽  
Forest Fire Risk

Abstract The great forest of Zakour is located north of the commune of Mamounia (department of Mascara). It is considered the lung of the city of Mascara, covers an area of 126.8 ha. It is a forest that is subject to several natural and human constraints. Among them, the fires are a major danger because of their impacts on forest ecosystems. The purpose of this work is to develop a fire risk map of the Zakour Forest through the contribution of geomatics according to natural and anthropogenic conditions (human activities, agglomeration, agricultural land) while integrating information from ground on the physiognomy of the vegetation. For this, the creation of a clearer fire risk map to delimit the zones potentially sensitive to forest fires in the forest area of Zakour. This then allows good implementation of detection management plans, for better prevention and decision-making assistance in protecting and fighting forest fires.

scholarly journals ASSESSMENT OF VULNERABILITY IN AGRICULTURAL LAND IN FLOOD PRONE AREAS AND APPLICATION OF MOBILE SMART PHONE IN PROVIDING FLOOD HAZARD INFORMATION IN LAM RIVER BASIN (VIETNAM)

2021 ◽  
Vol 13 (2) ◽  
pp. 254-264
Author(s):  
Nguyen DUNG ◽  
◽  
Dang MINH ◽  
Bui AN ◽  
Nguyen NGA ◽  
...  
Keyword(s):  
River Basin ◽  
Agricultural Land ◽  
Flood Hazard ◽  
Smart Phone ◽  
Flood Management ◽  
Drainage Density ◽  
Slope Length ◽  
Risk Levels ◽  
High Hazard ◽  
Very High

Floods are considered to be one of the most costly natural hazards in the Lam river basin causing infrastructure damages as well as devastating the affected area and relatively high death toll. So prevention is necessary for shielding lives and properties. The flood management on the Lam River basin has been considering for many years to minimize damages caused by flooding. The flood hazard zoning map is one of the indispensable tools to provide information about hazard and risk levels in a particular area and to perform the necessary preventive and preparedness procedures. The multicriteria decision analysis based on geographic information systems is used to build a flood hazard map of the study area. The analytic hierarchy process is applied to extract the weights of six criteria affecting the areas where are prone to flooding hazards, including rainfall, slope, relative slope length, soil, land cover, and drainage density. The results showed in 91.32 % (20103.83 km2) of the basin located in the moderate hazard zones to very high hazard zones. Accordingly, this study also determined 4 vulnerability levels to agricultural land including low, medium, high, and very high. About 94% of the total area of agricultural land in the basin are classified into moderate to the very high hazard of flood vulnerability. The paper presents a method that allows flood risk areas in the Lam River basin to receive information about flood risks on a smartphone, making them more aware.

Trends of Diabetes Mortality in Iran at National and Sub-national levels from 1990 to 2015 and its association with socioeconomic factors

2020 ◽  
Author(s):  
Niloofar Peykari ◽  
Sahar Saeedi Moghaddam ◽  
Nazila Rezaei ◽  
Anita Mansouri ◽  
Shohreh Naderimagham ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Socioeconomic Factors ◽  
National Level ◽  
Gaussian Process Regression ◽  
Mortality Trends ◽  
Registration System ◽  
Diabetes Mortality ◽  
Spatio Temporal ◽  
The Difference ◽  
National Trends

Abstract Background Following global commitments to prevent and control non-communicable diseases, we sought to estimate national and sub-national trends in diabetes mortality in Iran and to assess its association with socioeconomic factors.Methods To assess the correlation between diabetes mortality and socioeconomic factors we used data obtained from the Death Registration System (DRS), the spatio-temporal model and Gaussian Process Regression (GPR) levels and the diabetes mortality trends, which were estimated by sex, age and year at national and sub-national levels from 1990 to 2015.Results Between the years 1990 and 2015, the age-standardized diabetes mortality rate (per 100,000) increased from 3.40 (95% UI: 2.33 to 4.99) to 7.72 (95% UI: 5.51 to 10.78) in males and from 4.66 (95% UI: 3.23 to 6.76) to 10.38 (95% UI: 7.54 to 14.23) in females. In 1990, the difference between the highest age-standardized diabetes mortality rate among males was 3.88 times greater than the lowest (5.97 vs. 1.54) and in 2015 this difference was 3.96 times greater (14.65 vs. 3.70). This provincial difference was higher among females and was 5.13 times greater in 1990 (8.41 vs. 1.64) and 5.04 times greater in 2015 (19.87 vs. 3.94). The rate of diabetes mortality rose with urbanization, yet declined with an increase in wealth and years of schooling as the main socio-economic factors.Conclusion The rising trend of diabetes mortality rate at national level and the sub-national disparities associated with socioeconomic status in Iran warrant the implementation of specific interventions recommended by the ‘25 by 25’ goal.

Using a model-of-models approach and remote sensing technologies to improve flood disaster alerting

2020 ◽  
Author(s):  
Guy J.-P. Schumann ◽  
Margaret Glasscoe ◽  
Douglas Bausch ◽  
Marlon Pierce ◽  
Jun Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Open Access ◽  
Structural Damage ◽  
Flood Hazard ◽  
Remote Sensing Data ◽  
Observation Data ◽  
Flood Impacts ◽  
Coordination System ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Almost All

<p>Floods are happening regularly in almost all places of the world and impact people, societies and economies, causing widespread devastation that can be hard to recover from. Yet, accurately predicting and alerting for floods is challenging, primarily since flood events are very local in nature and processes causing a flood can be very complex. In an era of open-access geospatial data proliferation as well as data and model interoperability, it makes sense to leverage on existing data and models, many of which are underutilized by decision-making applications. Thus, the objective of the project is to develop an open-access rapid alerting and severity assessment component for global flooding based on existing models and observation data sources. We do this within the DisasterAWARE platform of the Pacific Disaster Center (PDC).</p><p>This paper will outline the proposed concept of model-of-models that will leverage existing flood-hazard modeling capabilities, illustrating products that we will leverage, such as: GLOFAS (Global Flood Forecasting Feeds) probabilistic hydrologic data, IMERG (The Integrated Multi-satellitE Retrievals for GPM) observed precipitation grids, GDACS (Global Disaster Alerting Coordination System) anomaly points, GFMS (Global Flood Monitoring System) depth above baseline grids, the NASA MODIS (Moderate Resolution Imaging Spectroradiometer) and Dartmouth Observatory flood maps, as well as new models as they are developed. We will further combine the flood hazard data with existing exposure data to estimate property loss using a probabilistic fragility approach. With the use of an end-to-end deep learning framework, structural damage will be detected using different remote sensing data. The approach will further incorporate other, non-routinely-generated remotely-sensed products for ground-truthing for areas and events where and when such products are available.</p><p>The existing resilience and capacity of communities to rapidly respond to and recover from flood impacts will be incorporated into the severity determination on an administrative area and watershed risk basis. This model-of-models approach will leverage major efforts, improve reliability and reduce false triggers by ensuring two or more models agree.</p>

Spatio-temporal dynamics in the flood exposure due to land use changes in the Alpine Lech Valley in Tyrol (Austria)

2012 ◽  
Vol 68 (3) ◽  
pp. 1243-1270 ◽  
Author(s):  
Holger Cammerer ◽  
Annegret H. Thieken ◽  
Peter H. Verburg
Keyword(s):  
Land Use ◽  
Temporal Dynamics ◽  
Land Use Changes ◽  
Flood Exposure ◽  
Spatio Temporal

scholarly journals Flood risk perception and adaptation capacity: a contribution to the socio-hydrology debate

2017 ◽  
Vol 21 (6) ◽  
pp. 3183-3198 ◽  
Author(s):  
Sven Fuchs ◽  
Konstantinos Karagiorgos ◽  
Kyriaki Kitikidou ◽  
Fotios Maris ◽  
Spyridon Paparrizos ◽  
...  
Keyword(s):  
Risk Management ◽  
Flood Risk ◽  
Public Perception ◽  
Flood Hazard ◽  
Social Dimension ◽  
Environment Interaction ◽  
Human Environment ◽  
Adaptation Capacity ◽  
Management Plans ◽  
Key Issues

Abstract. Dealing with flood hazard and risk requires approaches rooted in both natural and social sciences, which provided the nexus for the ongoing debate on socio-hydrology. Various combinations of non-structural and structural flood risk reduction options are available to communities. Focusing on flood risk and the information associated with it, developing risk management plans is required but often overlooks public perception of a threat. The perception of risk varies in many different ways, especially between the authorities and the affected public. It is because of this disconnection that many risk management plans concerning floods have failed in the past. This paper examines the private adaptation capacity and willingness with respect to flooding in two different catchments in Greece prone to multiple flood events during the last 20 years. Two studies (East Attica and Evros) were carried out, comprised of a survey questionnaire of 155 and 157 individuals, from a peri-urban (East Attica) and a rural (Evros) area, respectively, and they focused on those vulnerable to periodic (rural area) and flash floods (peri-urban area). Based on the comparisons drawn from these responses, and identifying key issues to be addressed when flood risk management plans are implemented, improvements are being recommended for the social dimension surrounding such implementation. As such, the paper contributes to the ongoing discussion on human–environment interaction in socio-hydrology.

scholarly journals Arabian Sea Tropical Cyclones: A Spatio-Temporal Analysis in Support of Natural Hazard Risk Appraisal in Oman

2021 ◽  
Author(s):  
Suad Al-Manji ◽  
Gordon Mitchell ◽  
Amna Al Ruheili
Keyword(s):  
High Risk ◽  
Tropical Cyclones ◽  
Natural Hazard ◽  
Temporal Distribution ◽  
Storm Surges ◽  
Temporal Analysis ◽  
The North ◽  
Risk Areas ◽  
Spatio Temporal ◽  
Extreme Winds

Tropical cyclones [TCs] are a common natural hazard that have significantly impacted Oman. Over the period 1881–2019, 41 TC systems made landfall in Oman, each associated with extreme winds, storm surges and significant flash floods, often resulting in loss of life and substantial damage to infrastructure. TCs affect Omani coastal areas from Muscat in the north to Salalah in the south. However, developing a better understanding of the high-risk regions is needed, and is of particular interest in disaster risk reduction institutions in Oman. This study aims to find and map TC tracks and their spatio-temporal distribution to landfall in Oman to identify the high-risk areas. The analysis uses Kernel Density Estimation [KDE] and Linear Direction Mean [LDM] methods to better identify the spatio-temporal distribution of TC tracks and their landfall in Oman. The study reveals clear seasonal and monthly patterns. This knowledge will help to improve disaster planning for the high-risk areas.

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