Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

The projected frequent occurrences of extreme flood events will cause significant losses to crops and will threaten food security. To reduce the potential risk and provide support for agricultural flood management, prevention, and mitigation, it is important to account for flood damage to crop production and to understand the relationship between flood characteristics and crop losses. A quantitative and effective evaluation tool is therefore essential to explore what and how flood characteristics will affect the associated crop loss, based on accurately understanding the spatiotemporal dynamics of flood evolution and crop growth. Current evaluation methods are generally integrally or qualitatively based on statistic data or ex-post survey with less diagnosis into the process and dynamics of historical flood events. Therefore, a quantitative and spatial evaluation framework is presented in this study that integrates remote sensing imagery and hydraulic model simulation to facilitate the identification of historical flood characteristics that influence crop losses. Remote sensing imagery can capture the spatial variation of crop yields and yield losses from floods on a grid scale over large areas; however, it is incapable of providing spatial information regarding flood progress. Two-dimensional hydraulic model can simulate the dynamics of surface runoff and accomplish spatial and temporal quantification of flood characteristics on a grid scale over watersheds, i.e., flow velocity and flood duration. The methodological framework developed herein includes the following: (a) Vegetation indices for the critical period of crop growth from mid-high temporal and spatial remote sensing imagery in association with agricultural statistics data were used to develop empirical models to monitor the crop yield and evaluate yield losses from flood; (b) The two-dimensional hydraulic model coupled with the SCS-CN hydrologic model was employed to simulate the flood evolution process, with the SCS-CN model as a rainfall-runoff generator and the two-dimensional hydraulic model implementing the routing scheme for surface runoff; and (c) The spatial combination between crop yield losses and flood dynamics on a grid scale can be used to investigate the relationship between the intensity of flood characteristics and associated loss extent. The modeling framework was applied for a 50-year return period flood that occurred in Jilin province, Northeast China, which caused large agricultural losses in August, 2013. The modeling results indicated that (a) the flow velocity was the most influential factor that caused spring corn, rice and soybean yield losses from extreme storm event in the mountainous regions; (b) the power function archived the best results that fit the velocity-loss relationship for mountainous areas; and (c) integrated remote sensing imagery and two-dimensional hydraulic modeling approach are helpful for evaluating the influence of historical flood event on crop production and investigating the relationship between flood characteristics and crop yield losses

Efficiency of coupled invasive weed optimization-adaptive neuro fuzzy inference system method to assess physical habitats in streams

This study presents a coupled invasive weed optimization-adaptive neuro fuzzy inference system method to simulate physical habitat in streams. We implement proposed method in Lar national park in Iran as one of the habitats of Brown trout in southern Caspian Sea basin. Five indices consisting of root mean square error (RMSE), mean absolute error (MAE), reliability index, vulnerability index and Nash–Sutcliffe model efficiency coefficient (NSE) are utilized to compare observed fish habitats and simulated fish habitats. Based on results, measurement indices demonstrate model is robust to assess physical habitats in rivers. RMSE and MAE are 0.09 and 0.08 respectively. Besides, NSE is 0.78 that indicates robustness of model. Moreover, it is necessary to apply developed habitat model in a practical habitat simulation. We utilize two-dimensional hydraulic model in steady state to simulate depth and velocity distribution. Based on qualitative comparison between results of model and observation, coupled invasive weed optimization-adaptive neuro fuzzy inference system method is robust and reliable to simulate physical habitats. We recommend utilizing proposed model for physical habitat simulation in streams for future studies

Utility of different data types for calibrating flood inundation models within a GLUE framework

International audienceTo translate a point hydrograph forecast into products for use by environmental agencies and civil protection authorities, a hydraulic model is necessary. Typical one- and two-dimensional hydraulic models are able to predict dynamically varying inundation extent, water depth and velocity for river and floodplain reaches up to 100 km in length. However, because of uncertainties over appropriate surface friction parameters, calibration of hydraulic models against observed data is a necessity. The value of different types of data is explored in constraining the predictions of a simple two-dimensional hydraulic model, LISFLOOD-FP. For the January 1995 flooding on the River Meuse, The Netherlands, a flow observation data set has been assembled for the 35-km reach between Borgharen and Maaseik, consisting of Synthetic Aperture Radar and air photo images of inundation extent, downstream stage and discharge hydrographs, two stage hydrographs internal to the model domain and 84 point observations of maximum free surface elevation. The data set thus contains examples of all the types of data that potentially can be used to calibrate flood inundation models. 500 realisations of the model have been conducted with different friction parameterisations and the performance of each realisation has been evaluated against each observed data set. Implementation of the Generalised Likelihood Uncertainty Estimation (GLUE) methodology is then used to determine the value of each data set in constraining the model predictions as well as the reduction in parameter uncertainty resulting from the updating of generalised likelihoods based on multiple data sources

Beyond Floodplain Analysis: A Modeler’s Experience Using HEC-RAS 2D for Spillway Assessments and Designs

HEC-RAS 5.0 (2D) has been increasingly used by the dam safety community for performing dam breach and other hydraulic analyses since its debut in 2015. While this two-dimensional hydraulic modeling software has wide applications in dam breach analysis and urban flood simulation, its ability to analyze complex multidirectional flow problems can also be used as a design tool for spillways, overtopping protection, and other hydraulic structures. In this manuscript, the authors discussed their experience using HEC-RAS and other two-dimensional hydraulic models to design and assess various hydraulic structures. This includes: 1) sizing spillway outlet channels and assessing the hydraulic adequacy of training dikes, especially where non-linear or super-elevated flow conditions are anticipated; 2) using depth, velocity, and shear stress outputs to design erosion/overtopping protection for vegetated spillways, lined channels, and earthen embankments; 3) designing temporary diversions to facilitate construction within rivers, reservoirs, or other waterways; and 4) identifying and assessing potential failure modes (e.g. erosion and headcutting of vegetated spillways). Insights are shared to help the audience understand when a two-dimensional modeling approach is effective and appropriate

Two-dimensional modelling of flow conditions generated by piled piers and turbulence-based erosion risk assessment

Water Qualit

Response of Sandhill Crane (\u3ci\u3eGrus canadensis\u3c/i\u3e Riverine Roosting Habitat to Changes in Stage and Sandbar Morphology

Over the past century, flow regulation and vegetation encroachment have reduced active channel widths along the central Platte River, Nebraska. During the last two decades, an annual program of in-channel vegetation management has been implemented to stabilize or expand active channel widths. Vegetation management practices are intended to enhance riverine habitats which include nocturnal roosting habitat for sandhill cranes. Evaluating the success of other management treatments such as streamflow modification requires an understanding of how flow shapes the sandbars in the river and how sandbar morphology interacts with flow to create crane habitat. These linkages were investigated along a 1-km managed river reach by comparing the spatial pattern of riverine roosts and emergent sandbars identified with aerial infrared imagery to variables computed with a two-dimensional hydraulic model. Nocturnal observations made multiple years showed that the area and patterns of riverine roosts and emergent sandbars and the densities of cranes within roosts changed with stage. Despite sandbar vegetation management, low flows were concentrated into incised channels rather than spread out over broad sandbars. The flow model was used to compute hydraulic variables for identical streamflows through two sandbar morphologies; one following a period of relatively high flow and the other following the low-flow period. Compared with the simulation using the morphology from the antecedent high flow, the simulation using the morphology from the antecedent low flow produced a smaller quantity of available wetted area. These remote-sensing observations and hydraulic simulations illustrate the importance of considering flow history when designing streamflows to manage in-channel habitat for cranes

Selection of Elevation Models for Flood Inundation Map Generation in Small Urban Stream: Case Study of Anyang Stream

To reduce flood damages, the Ministry of Environment in Korea has provided a flood inundation map so that people can expediently identify flood-prone areas. However, the current flood inundation maps have been produced based on the DEM which makes it difficult to represent realistic situations due to the lack of reproduction of land surface conditions. This study aims to provide more accurate and detailed flood inundation maps for flooding events due to river overflow in small urban areas. In this study, flood inundation analysis is performed using the river analysis system, HEC-RAS 2D, with the DSM and the DEM of urban areas in the Anyang Stream Basin, Korea to examine the differences in terms of terrain data and flooded area. Finally, for urban areas with dense buildings and congested road networks, the flood inundation analysis based on DSM can represent a more realistic flood situation and create an appropriate flood inundation map