scholarly journals Flood risk mapping and crop-water loss modeling using water footprint analysis in agricultural watershed, northern Iran

2020 ◽  
Author(s):  
Maziar Mohammadi ◽  
Hamid Darabi ◽  
Fahimeh Mirchooli ◽  
Alireza Bakhshaee ◽  
Ali Torabi Haghighi
Keyword(s):  
Flood Risk ◽  
Agricultural Land ◽  
Spatial Information ◽  
Water Footprint ◽  
Critical Factor ◽  
Flood Damage ◽  
Agricultural Watershed ◽  
Northern Iran ◽  
Conditioning Factors ◽  
Very High

Abstract Spatial information on flood risk and flood-related crop losses is important in flood mitigation and risk management in agricultural watersheds. In this study, loss of water bound in agricultural products following damage by flooding was calculated using water footprint and agricultural statistics, using the Talar watershed, northern Iran, as a case. The main conditioning factors on flood risk (flow accumulation, slope, land use, rainfall intensity, geology, and elevation) were rated and combined in GIS, and a flood risk map classified into five risk classes (very low to very high) was created. Using average crop yield per hectare, the amount of rice and wheat products under flood risk was calculated for the watershed. Finally, the spatial relationships between agricultural land uses (rice and wheat) and flood risk areas were evaluated using geographically weighted regression (GWR) in terms of local R2 at sub-watershed scale. The results showed that elevation was the most critical factor for flood risk. GWR results indicated that local R2 between rice farms and flood risk decreased gradually from north to south in the watershed, while no pattern was detected for wheat farms. Potential production of rice and wheat in very high flood risk zones was estimated to be 7972 and 18,860 tons, on an area of 822 ha and 7218 ha, respectively. Loss of these crops to flooding meant that approximately 34.04 and 12.10 million m3 water used for production of wheat and rice, respectively, were lost. These findings can help managers, policymakers, and watershed stakeholders achieve better crop management and flood damage reduction.

scholarly journals Use of Very High-Resolution Optical Data for Landslide Mapping and Susceptibility Analysis along the Karnali Highway, Nepal

2019 ◽  
Vol 11 (19) ◽  
pp. 2284 ◽  
Author(s):  
Pukar Amatya ◽  
Dalia Kirschbaum ◽  
Thomas Stanley
Keyword(s):  
High Resolution ◽  
Agricultural Land ◽  
Spatial Information ◽  
Area Under The Curve ◽  
Optical Data ◽  
Susceptibility Map ◽  
Good Prediction ◽  
Landslide Occurrence ◽  
The Road ◽  
Very High

The Karnali highway is a vital transport link and the only primary roadway that connects the remote Karnali region to the lowlands in Mid-Western Nepal. Every year there are reports of landslides blocking the road, making this area largely inaccessible. However, little effort has focused on systematically identifying landslides and landslide-prone areas along this highway. In this study, landslides were mapped with an object-based approach from very high-resolution optical satellite imagery obtained by the DigitalGlobe constellation in 2012 and PlanetScope in 2018. Landslides ranging from 10 to 30,496 m2 were detected within a 3 km buffer along the highway. Most of the landslides were located at lower elevations (between 500–1500 m) and on steep south-facing slopes. Landslides tended to cluster closer to the highway, near drainage channels and away from faults. Landslides were also most prevalent within the Kuncha Formation geologic class, and the forested and agricultural land cover classes. A susceptibility map was then created using a logistic regression methodology to highlight patterns in landslide activity. The landslide susceptibility map showed a good prediction rate with an area under the curve (AUC) of 0.90. A total of 33% of the study arealies in high/very high susceptibility zones. The map highlighted the lower elevated areas between Bangesimal and Manma towns with the Kuncha Formation geologic class as being the most hazardous. The banks of the Karnali River, its tributaries and areas near the highway were also highly susceptible to landslides. The results highlight the potential of very high-resolution optical imagery for documenting detailed spatial information on landslide occurrence, which enables susceptibility assessment in remote and data scarce regions such as the Karnali highway.

Application of scenario technique in flood risk management

2007 ◽  
Vol 56 (4) ◽  
pp. 87-95 ◽  
Author(s):  
A. Winterscheid
Keyword(s):  
Risk Management ◽  
Flood Risk ◽  
Flood Control ◽  
Flood Damage ◽  
Flood Risk Management ◽  
Policy Framework ◽  
Limited Perspective ◽  
Integrated Flood Risk Management ◽  
Scenario Technique ◽  
Management Cycle

It is now commonly accepted that the management of flood risks has to be fulfilled within an integrated framework. About two decades ago flood risk was managed from a limited perspective predominantly by means of structural measures aimed at flood control. In contrast integrated flood risk management incorporates the complete management cycle consisting of the phases prevention, protection and preparedness. In theory it is a well described concept. In the stage of implementation, however, there is often a lack of support although a consistent policy framework exists. Consequently, the degree of implementation must be rated as inadequate in many cases. In particular this refers to the elements which focus on preparedness and prevention. The study to which this paper refers emphasises the means and potentials of scenario technique to foster the implementation of potentially appropriate measures and new societal arrangements when applied in the framework of integrated flood risk management. A literature review is carried out to reveal the state-of-the-art and the specific problem framework within which scenario technique is generally being applied. Subsequently, it is demonstrated that scenario technique is transferable to a policy making process in flood risk management that is integrated, sustainable and interactive. The study concludes with a recommendation for three applications in which the implementation of measures of flood damage prevention and preparedness is supported by scenario technique.

scholarly journals Integrated Framework for Detecting the Areas Prone to Flooding Generated by Flash-Floods in Small River Catchments

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 758 ◽  
Author(s):  
Romulus Costache ◽  
Alina Barbulescu ◽  
Quoc Bao Pham
Keyword(s):  
Analytical Hierarchy Process ◽  
Process Model ◽  
Buffer Zone ◽  
Training Sample ◽  
Flash Floods ◽  
Operating Characteristics ◽  
Conditioning Factors ◽  
Flood Susceptibility ◽  
Hierarchy Process ◽  
Very High

In the present study, the susceptibility to flash-floods and flooding was studied across the Izvorul Dorului River basin in Romania. In the first phase, three ensemble models were used to determine the susceptibility to flash-floods. These models were generated by a combination of three statistical bivariate methods, namely frequency ratio (FR), weights of evidence (WOE), and statistical index (SI), with fuzzy analytical hierarchy process (FAHP). The result obtained from the application of the FAHP-WOE model had the best performance highlighted by an Area Under Curve—Receiver Operating Characteristics Curve (AUC-ROC) value of 0.837 for the training sample and another of 0.79 for the validation sample. Furthermore, the results offered by FAHP-WOE were weighted on the river network level using the flow accumulation method, through which the valleys with a medium, high, and very high torrential susceptibility were identified. Based on these valleys’ locations, the susceptibility to floods was estimated. Thus, in the first stage, a buffer zone of 200 m was delimited around the identified valleys along which the floods could occur. Once the buffer zone was established, ten flood conditioning factors were used to determine the flood susceptibility through the analytical hierarchy process model. Approximately 25% of the total delimited area had a high and very high flood susceptibility.

scholarly journals Incorporating Landslide Spatial Information and Correlated Features among Conditioning Factors for Landslide Susceptibility Mapping

2021 ◽  
Vol 13 (11) ◽  
pp. 2166
Author(s):  
Xin Yang ◽  
Rui Liu ◽  
Mei Yang ◽  
Jingjue Chen ◽  
Tianqiang Liu ◽  
...  
Keyword(s):  
Land Use ◽  
Hybrid Model ◽  
Landslide Susceptibility ◽  
Spatial Information ◽  
Landslide Susceptibility Mapping ◽  
Ratio Method ◽  
Support Vector ◽  
Susceptibility Map ◽  
Conditioning Factors ◽  
Proposed Model

This study proposed a new hybrid model based on the convolutional neural network (CNN) for making effective use of historical datasets and producing a reliable landslide susceptibility map. The proposed model consists of two parts; one is the extraction of landslide spatial information using two-dimensional CNN and pixel windows, and the other is to capture the correlated features among the conditioning factors using one-dimensional convolutional operations. To evaluate the validity of the proposed model, two pure CNN models and the previously used methods of random forest and a support vector machine were selected as the benchmark models. A total of 621 earthquake-triggered landslides in Ludian County, China and 14 conditioning factors derived from the topography, geological, hydrological, geophysical, land use and land cover data were used to generate a geospatial dataset. The conditioning factors were then selected and analyzed by a multicollinearity analysis and the frequency ratio method. Finally, the trained model calculated the landslide probability of each pixel in the study area and produced the resultant susceptibility map. The results indicated that the hybrid model benefitted from the features extraction capability of the CNN and achieved high-performance results in terms of the area under the receiver operating characteristic curve (AUC) and statistical indices. Moreover, the proposed model had 6.2% and 3.7% more improvement than the two pure CNN models in terms of the AUC, respectively. Therefore, the proposed model is capable of accurately mapping landslide susceptibility and providing a promising method for hazard mitigation and land use planning. Additionally, it is recommended to be applied to other areas of the world.

scholarly journals The added value of system robustness analysis for flood risk management illustrated by a case on the IJssel River

2015 ◽  
Vol 15 (2) ◽  
pp. 213-223 ◽  
Author(s):  
M. J. P. Mens ◽  
F. Klijn
Keyword(s):  
Risk Management ◽  
Flood Risk ◽  
Robustness Analysis ◽  
Decision Criterion ◽  
Flood Damage ◽  
Flood Risk Management ◽  
Added Value ◽  
Common Basis ◽  
System Robustness ◽  
System Configurations

Abstract. Decision makers in fluvial flood risk management increasingly acknowledge that they have to prepare for extreme events. Flood risk is the most common basis on which to compare flood risk-reducing strategies. To take uncertainties into account the criteria of robustness and flexibility are advocated as well. This paper discusses the added value of robustness as an additional decision criterion compared to single-value flood risk only. We do so by quantifying flood risk and system robustness for alternative system configurations of the IJssel River valley in the Netherlands. We found that robustness analysis has added value in three respects: (1) it does not require assumptions on current and future flood probabilities, since flood consequences are shown as a function of discharge; (2) it shows the sensitivity of the system to varying discharges; and (3) it supports a discussion on the acceptability of flood damage. We conclude that robustness analysis is a valuable addition to flood risk analysis in support of long-term decision-making on flood risk management.

scholarly journals Raising risk preparedness by flood risk communication

2015 ◽  
Vol 15 (7) ◽  
pp. 1577-1595 ◽  
Author(s):  
E. Maidl ◽  
M. Buchecker
Keyword(s):  
Risk Communication ◽  
Flood Risk ◽  
Information Needs ◽  
Flood Hazard ◽  
Flood Damage ◽  
Communication Strategy ◽  
Special Focus ◽  
Risk Awareness ◽  
Local Authorities ◽  
Risk Preparedness

Abstract. During the last decade, most European countries have produced hazard maps of natural hazards, but little is known about how to communicate these maps most efficiently to the public. In October 2011, Zurich's local authorities informed owners of buildings located in the urban flood hazard zone about potential flood damage, the probability of flood events and protection measures. The campaign was based on the assumptions that informing citizens increases their risk awareness and that citizens who are aware of risks are more likely to undertake actions to protect themselves and their property. This study is intended as a contribution to better understand the factors that influence flood risk preparedness, with a special focus on the effects of such a one-way risk communication strategy. We conducted a standardized mail survey of 1500 property owners in the hazard zones in Zurich (response rate main survey: 34 %). The questionnaire included items to measure respondents' risk awareness, risk preparedness, flood experience, information-seeking behaviour, knowledge about flood risk, evaluation of the information material, risk acceptance, attachment to the property and trust in local authorities. Data about the type of property and socio-demographic variables were also collected. Multivariate data analysis revealed that the average level of risk awareness and preparedness was low, but the results confirmed that the campaign had a statistically significant effect on the level of preparedness. The main influencing factors on the intention to prepare for a flood were the extent to which respondents evaluated the information material positively as well as their risk awareness. Respondents who had never taken any previous interest in floods were less likely to read the material. For future campaigns, we therefore recommend repeated communication that is tailored to the information needs of the target population.

scholarly journals A Implementação da Telemedicina em Cabo Verde: Fatores Influenciadores

2017 ◽  
Vol 30 (4) ◽  
pp. 255 ◽  
Author(s):  
Artur Correia ◽  
Vanda Azevedo ◽  
Luís Velez Lapão
Keyword(s):  
Information And Communication Technologies ◽  
Success Factors ◽  
New Technology ◽  
Policy Instruments ◽  
Critical Factor ◽  
Communication Technologies ◽  
Cape Verde ◽  
Structured Interviews ◽  
Conditioning Factors ◽  
Information And Communication

Introduction: Telemedicine is the provision of health services, where distance is a critical factor, using information and communication technologies. Cape Verde has bet on using this tool to increase access of the population of its islands to specialized care.Material and Methods: Qualitative study, covering the period between 2013 and 2014. It uses document analysis, semi-structured interviews and focus groups to collect data and analysis of content for their analysis. The participant population includes doctors, nurses and professionals from some institutions related to telemedicine.Results: The priorities of the National Telemedicine Program are set, the cores and reference centers are operational, with trained personnel and equipment installed. Several other policy instruments and conditioning factors and facilitators of the program have been identified.Discussion: Telemedicine is contributing to the reduction of inequalities in access to health, in Cape Verde. However, the full adoption of a service based on a new technology depends on conditioning factors and facilitators, and several success factors of telemedicine, identified in the literature, are not observed and in conjunction with other existing weaknesses affect the overall development of the National Telemedicine Program. However the strengths and capabilities are highlighted opportunities to act.Conclusion: Despite the progress, some telemedicine success factors highlighted on the literature are not seen in the country.

scholarly journals Equitable Allocation of Blue and Green Water Footprints Based on Land-Use Types: A Case Study of the Yangtze River Economic Belt

2018 ◽  
Vol 10 (10) ◽  
pp. 3556 ◽  
Author(s):  
Gang Liu ◽  
Lu Shi ◽  
Kevin Li
Keyword(s):  
Land Use ◽  
Water Resources ◽  
Agricultural Land ◽  
Optimal Allocation ◽  
Water Footprint ◽  
Agricultural Water ◽  
Land Area ◽  
Lexicographic Optimization ◽  
The Impact

This paper develops a lexicographic optimization model to allocate agricultural and non-agricultural water footprints by using the land area as the influencing factor. An index known as the water-footprint-land density (WFLD) index is then put forward to assess the impact and equity of the resulting allocation scheme. Subsequently, the proposed model is applied to a case study allocating water resources for the 11 provinces and municipalities in the Yangtze River Economic Belt (YREB). The objective is to achieve equitable spatial allocation of water resources from a water footprint perspective. Based on the statistical data in 2013, this approach starts with a proper accounting for water footprints in the 11 YREB provinces. We then determined an optimal allocation of water footprints by using the proposed lexicographic optimization approach from a land area angle. Lastly, we analyzed how different types of land uses contribute to allocation equity and we discuss policy changes to implement the optimal allocation schemes in the YREB. Analytical results show that: (1) the optimized agricultural and non-agricultural water footprints decrease from the current levels for each province across the YREB, but this decrease shows a heterogeneous pattern; (2) the WFLD of 11 YREB provinces all decline after optimization with the largest decline in Shanghai and the smallest decline in Sichuan; and (3) the impact of agricultural land on the allocation of agricultural water footprints is mainly reflected in the land use structure of three land types including arable land, forest land, and grassland. The different land use structures in the upstream, midstream, and downstream regions lead to the spatial heterogeneity of the optimized agricultural water footprints in the three YREB segments; (4) In addition to the non-agricultural land area, different regional industrial structures are the main reason for the spatial heterogeneity of the optimized non-agricultural water footprints. Our water-footprint-based optimal water resources allocation scheme helps alleviate the water resources shortage pressure and achieve coordinated and balanced development in the YREB.

scholarly journals Groundwater Augmentation through the Site Selection of Floodwater Spreading Using a Data Mining Approach (Case study: Mashhad Plain, Iran)

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1405 ◽  
Author(s):  
Seyed Naghibi ◽  
Mehdi Vafakhah ◽  
Hossein Hashemi ◽  
Biswajeet Pradhan ◽  
Seyed Alavi
Keyword(s):  
Data Mining ◽  
Regression Tree ◽  
Roc Curves ◽  
Flood Damage ◽  
Boosted Regression Trees ◽  
Classification And Regression Tree ◽  
Operating Characteristics ◽  
National Guidelines ◽  
Conditioning Factors ◽  
Suitability Maps

It is a well-known fact that sustainable development goals are difficult to achieve without a proper water resources management strategy. This study tries to implement some state-of-the-art statistical and data mining models i.e., weights-of-evidence (WoE), boosted regression trees (BRT), and classification and regression tree (CART) to identify suitable areas for artificial recharge through floodwater spreading (FWS). At first, suitable areas for the FWS project were identified in a basin in north-eastern Iran based on the national guidelines and a literature survey. Using the same methodology, an identical number of FWS unsuitable areas were also determined. Afterward, a set of different FWS conditioning factors were selected for modeling FWS suitability. The models were applied using 70% of the suitable and unsuitable locations and validated with the rest of the input data (i.e., 30%). Finally, a receiver operating characteristics (ROC) curve was plotted to compare the produced FWS suitability maps. The findings depicted acceptable performance of the BRT, CART, and WoE for FWS suitability mapping with an area under the ROC curves of 92, 87.5, and 81.6%, respectively. Among the considered variables, transmissivity, distance from rivers, aquifer thickness, and electrical conductivity were determined as the most important contributors in the modeling. FWS suitability maps produced by the proposed method in this study could be used as a guideline for water resource managers to control flood damage and obtain new sources of groundwater. This methodology could be easily replicated to produce FWS suitability maps in other regions with similar hydrogeological conditions.

Sign in / Sign up

Export Citation Format

Share Document