scholarly journals The Impact of Reforestation Induced Land Cover Change (1990–2017) on Flood Peak Discharge Using HEC-HMS Hydrological Model and Satellite Observations: A Study in Two Mountain Basins, China

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1347 ◽  
Author(s):  
Crispin Kabeja ◽  
Rui Li ◽  
Jianping Guo ◽  
Digne Edmond Rwabuhungu Rwatangabo ◽  
Marc Manyifika ◽  
...  
Keyword(s):  
Land Cover ◽  
Agricultural Land ◽  
Flash Flood ◽  
Peak Discharge ◽  
Substantial Impact ◽  
Flood Peak ◽  
Mountainous Regions ◽  
Hydrological Responses ◽  
Basin Scale ◽  
The Impact

Understanding the effect of land use and land cover (LULC) type change on watershed hydrological response is essential for adopting applicable measures to control floods. In China, the Grain to Green Program (GTGP) and the Natural Forest Conservation Program (NFCP) have had a substantial impact on LULC. We investigate the effect of these conservation efforts on flood peak discharge in two mountainous catchments. We used a series of Landsat images ranging from 1990 to 2016/2017 to evaluate the LULC changes. Further to this, the hydrological responses at the basin and sub-basin scale were generated by the Hydrologic Modeling System (HEC-HMS) under four LULC scenarios. Between 1990 and 2016/2017, both catchments experienced an increase in forest and urban land by 18% and 2% in Yanhe and by 16% and 8% in Guangyuan, respectively. In contrast, the agricultural land decreased by approximately 30% in Yanhe and 24% in Guangyuan, respectively. The changes in land cover resulted in decrease in flood peak discharge ranging from 14% in Yanhe to 6% in Guangyuan. These findings provide a better understanding on the impact of reforestation induced LULC change on spatial patterns of typical hydrological responses of mountainous catchment and could help to mitigate flash flood hazards in other mountainous regions.

Towards Predicting Flood Event Peak Discharge in Ungauged Basins by Learning Universal Hydrological Behaviors with Machine Learning

2021 ◽  
Author(s):  
Akhil Sanjay Potdar ◽  
Pierre-Emmanuel Kirstetter ◽  
Devon Woods ◽  
Manabendra Saharia
Keyword(s):  
Machine Learning ◽  
Spatial Variability ◽  
Spatial Organization ◽  
Flash Flood ◽  
Rainfall Variability ◽  
Peak Discharge ◽  
Machine Learning Techniques ◽  
Major Influence ◽  
Flood Peak ◽  
Basin Scale

AbstractIn the hydrological sciences, the outstanding challenge of regional modeling requires to capture common and event-specific hydrologic behaviors driven by rainfall spatial variability and catchment physiography during floods. The overall objective of this study is to develop robust understanding and predictive capability of how rainfall spatial variability influences flood peak discharge relative to basin physiography. A machine learning approach is used on a high-resolution dataset of rainfall and flooding events spanning 10 years, with rainfall events and basins of widely varying characteristics selected across the continental United States. It overcomes major limitations in prior studies that were based on limited observations or hydrological model simulations. This study explores first-order dependencies in the relationships between peak discharge, rainfall variability, and basin physiography, and it sheds light on these complex interactions using a multi-dimensional statistical modeling approach. Amongst different machine learning techniques, XGBoost is used to determine the significant physiographical and rainfall characteristics that influence peak discharge through variable importance analysis. A parsimonious model with low bias and variance is created which can be deployed in the future for flash flood forecasting. The results confirm that although the spatial organization of rainfall within a basin has a major influence on basin response, basin physiography is the primary driver of peak discharge. These findings have unprecedented spatial and temporal representativeness in terms of flood characterization across basins. An improved understanding of sub-basin scale rainfall spatial variability will aid in robust flash flood characterization as well as with identifying basins which could most benefit from distributed hydrologic modeling.

scholarly journals Erratum: Kabeja, C., et al. The Impact of Reforestation Induced Land Cover Change (1990–2017) on Flood Peak Discharge Using HEC-HMS Hydrological Model and Satellite Observations: A Study in Two Mountain Basins, China. Water 2020, 12, 1347

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 676
Author(s):  
Crispin Kabeja ◽  
Rui Li ◽  
Jianping Guo ◽  
Digne Edmond Rwabuhungu Rwatangabo ◽  
Marc Manyifika ◽  
...  
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Hydrological Model ◽  
Satellite Observations ◽  
Peak Discharge ◽  
Flood Peak ◽  
Mountain Basins ◽  
The Impact

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scholarly journals Unmanned Aerial Systems-Aided Post-Flood Peak Discharge Estimation in Ephemeral Streams

2020 ◽  
Vol 12 (24) ◽  
pp. 4183
Author(s):  
Emmanouil Andreadakis ◽  
Michalis Diakakis ◽  
Emmanuel Vassilakis ◽  
Georgios Deligiannakis ◽  
Antonis Antoniadis ◽  
...  
Keyword(s):  
Flash Flood ◽  
Traditional Approach ◽  
Peak Discharge ◽  
Unmanned Aerial Systems ◽  
Monitoring Networks ◽  
Response Dynamics ◽  
Hydrologic Modelling ◽  
Flood Peak ◽  
Field Evidence ◽  
Aerial Systems

The spatial and temporal scale of flash flood occurrence provides limited opportunities for observations and measurements using conventional monitoring networks, turning the focus to event-based, post-disaster studies. Post-flood surveys exploit field evidence to make indirect discharge estimations, aiming to improve our understanding of hydrological response dynamics under extreme meteorological forcing. However, discharge estimations are associated with demanding fieldwork aiming to record in small timeframes delicate data and data prone-to-be-lost and achieve the desired accuracy in measurements to minimize various uncertainties of the process. In this work, we explore the potential of unmanned aerial systems (UAS) technology, in combination with the Structure for Motion (SfM) and optical granulometry techniques in peak discharge estimations. We compare the results of the UAS-aided discharge estimations to estimates derived from differential Global Navigation Satellite System (d-GNSS) surveys and hydrologic modelling. The application in the catchment of the Soures torrent in Greece, after a catastrophic flood, shows that the UAS-aided method determined peak discharge with accuracy, providing very similar values compared to the ones estimated by the established traditional approach. The technique proved to be particularly effective, providing flexibility in terms of resources and timing, although there are certain limitations to its applicability, related mostly to the optical granulometry as well as the condition of the channel. The application highlighted important advantages and certain weaknesses of these emerging tools in indirect discharge estimations, which we discuss in detail.

scholarly journals Benefits and limitations of data assimilation for discharge forecasting using an event-based rainfall–runoff model

2013 ◽  
Vol 13 (3) ◽  
pp. 583-596 ◽  
Author(s):  
M. Coustau ◽  
S. Ricci ◽  
V. Borrell-Estupina ◽  
C. Bouvier ◽  
O. Thual
Keyword(s):  
Data Assimilation ◽  
Hydrological Model ◽  
Peak Discharge ◽  
State Variables ◽  
Rainfall Runoff ◽  
Discharge Data ◽  
Southern France ◽  
Flood Peak ◽  
Event Based ◽  
The Impact

Abstract. Mediterranean catchments in southern France are threatened by potentially devastating fast floods which are difficult to anticipate. In order to improve the skill of rainfall-runoff models in predicting such flash floods, hydrologists use data assimilation techniques to provide real-time updates of the model using observational data. This approach seeks to reduce the uncertainties present in different components of the hydrological model (forcing, parameters or state variables) in order to minimize the error in simulated discharges. This article presents a data assimilation procedure, the best linear unbiased estimator (BLUE), used with the goal of improving the peak discharge predictions generated by an event-based hydrological model Soil Conservation Service lag and route (SCS-LR). For a given prediction date, selected model inputs are corrected by assimilating discharge data observed at the basin outlet. This study is conducted on the Lez Mediterranean basin in southern France. The key objectives of this article are (i) to select the parameter(s) which allow for the most efficient and reliable correction of the simulated discharges, (ii) to demonstrate the impact of the correction of the initial condition upon simulated discharges, and (iii) to identify and understand conditions in which this technique fails to improve the forecast skill. The correction of the initial moisture deficit of the soil reservoir proves to be the most efficient control parameter for adjusting the peak discharge. Using data assimilation, this correction leads to an average of 12% improvement in the flood peak magnitude forecast in 75% of cases. The investigation of the other 25% of cases points out a number of precautions for the appropriate use of this data assimilation procedure.

scholarly journals Hydrological Responses to Land Use Land Cover Changes in the Fincha’a Watershed, Ethiopia

Land ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 916
Author(s):  
Urgessa Kenea ◽  
Dereje Adeba ◽  
Motuma Shiferaw Regasa ◽  
Michael Nones
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Local Governments ◽  
Swat Model ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
Hydrological Response ◽  
African Countries ◽  
Hydrological Responses ◽  
Basin Scale

Land use land cover (LULC) changes are highly pronounced in African countries, as they are characterized by an agriculture-based economy and a rapidly growing population. Understanding how land use/cover changes (LULCC) influence watershed hydrology will enable local governments and policymakers to formulate and implement effective and appropriate response strategies to minimize the undesirable effects of future land use/cover change or modification and sustain the local socio-economic situation. The hydrological response of the Ethiopia Fincha’a watershed to LULCC that happened during 25 years was investigated, comparing the situation in three reference years: 1994, 2004, and 2018. The information was derived from Landsat sensors, respectively Landsat 5 TM, Landsat 7 ETM, and Landsat 8 OLI/TIRS. The various LULC classes were derived via ArcGIS using a supervised classification system, and the accuracy assessment was done using confusion matrixes. For all the years investigated, the overall accuracies and the kappa coefficients were higher than 80%, with 2018 as the more accurate year. The analysis of LULCC revealed that forest decreased by 20.0% between the years 1994–2004, and it decreased by 11.8% in the following period 2004–2018. Such decline in areas covered by forest is correlated to an expansion of cultivated land by 16.4% and 10.81%, respectively. After having evaluated the LULCC at the basin scale, the watershed was divided into 18 sub-watersheds, which contained 176 hydrologic response units (HRUs), having a specific LULC. Accounting for such a detailed subdivision of the Fincha’a watershed, the SWAT model was firstly calibrated and validated on past data, and then applied to infer information on the hydrological response of each HRU on LULCC. The modelling results pointed out a general increase of average water flow, both during dry and wet periods, as a consequence of a shift of land coverage from forest and grass towards settlements and build-up areas. The present analysis pointed out the need of accounting for past and future LULCC in modelling the hydrological responses of rivers at the watershed scale.

Effects of channel engineering on flood dynamics along the middle and lower Rhône over the last two centuries.

2021 ◽  
Author(s):  
Mathieu Lucas ◽  
Michel Lang ◽  
Jérôme Le Coz ◽  
Benjamin Renard ◽  
Hervé Piegay
Keyword(s):  
Peak Discharge ◽  
Anthropogenic Pressures ◽  
Flood Peak ◽  
Area Of Interest ◽  
Channel Engineering ◽  
Indirect Consequence ◽  
Channel Patterns ◽  
Flood Dynamics ◽  
The Impact ◽  
Flood Waves

<p>The Rhône River has undergone many anthropogenic transformations to improve his navigability and produce hydroelectricity since the mid-19th century. From the longitudinal dikes of the 1850’s to the hydroelectric diversion schemes of the 1950’s and 1960’s, these structures had a direct impact on the channel geometry along the 300km of river course between Lyon (France) and the Mediterranean Sea. An indirect consequence could be a change in the flood dynamics along the channel course, caused by the simplification of the channel patterns and the floodplain accretion. This communication aims to assess the potential changes in the flood propagation along the middle and lower Rhône valley throughout a century of anthropogenic reconfigurations of the channel. The possible impact of these human pressures on the inundation risk and the attenuation of the flood peak discharge is also discussed. Through the use of digitized hydrometric data recorded since 1840 on multiple stream gauges of the Rhône river, a variety of floods of the same type and magnitude are selected. The oceanic flood types (as described by Pardé, 1925) that take their origin from heavy rainfalls upstream of the area of interest are preferred. Thus, complex flood waves due to floods from the lower Rhône valley tributaries are avoided, to keep the analysis as simple as possible. The flood travel time and the peak discharge attenuation of the selected events are compared over the years of channel transformations, permitting us to estimate the impact of anthropogenic pressures on the flood dynamics.</p>

Landscape Influences on Stream Habitats and Biological Assemblages

2006 ◽  
Keyword(s):  
Land Cover ◽  
Ictalurus Punctatus ◽  
Environmental Variables ◽  
Agricultural Land ◽  
Fish Assemblages ◽  
Spatial Scales ◽  
Species Abundance ◽  
Ecological Condition ◽  
Basin Scale ◽  
Assemblage Metrics

<em>Abstract.</em>—We analyzed data from 38 sites on 31 large rivers in Wisconsin to characterize the influence of environmental variables at the basin, reach, and site scales on fish assemblages. Electrofishing and site habitat data were collected for a distance of 1.6 km per site. Environmental variables included conductivity, substrate, and fish cover at the site scale; distance to impoundments, dams, and length of riverine habitat at the reach scale; and land cover, climate, and geology at the basin scale. Of the 77 fish species found, 39 occurred in more than 10% of the sites and were retained for analyses of fish abundance and biomass. Redundancy analysis (RDA) was used to relate species abundance, biomass, and 16 assemblage metrics to environmental variables at the three spatial scales. The site and basin scales defined fishes along a gradient from high conductivity, fine substrate, and agricultural land cover to low conductivity, rocky substrate, and forested land cover. For abundance and biomass, the strongest assemblage pattern contrasted northern hog sucker <em>Hypentelium nigricans</em>, blackside darter <em>Percina maculata</em>, and logperch <em>P. caprodes </em>with common carp <em>Cyprinus carpio</em>, channel catfish <em>Ictalurus punctatus</em>, and sauger <em>Sander canadensis</em>. The <em>H. nigricans </em>group, along with high values of index of biotic integrity and some assemblage metrics (percent lithophilic spawners, percent round-bodied suckers), corresponded with the forested end of the ecological gradient, whereas the <em>C. carpio </em>group and percent anomalies corresponded with the agricultural end. Natural environmental conditions, including bedrock geology type, bedrock depth, surficial geology texture, basin area, and precipitation, also influenced the fish assemblage. Partial RDA procedures partitioned the explained variation among spatial scales and their interactions. We found that widespread land cover alterations at the basin scale were most strongly related to fish assemblages across our study area. Understanding the influence of environmental variables among multiple spatial scales on fish assemblages can improve our ability to assess the ecological condition of large river systems and subsequently target the appropriate scale for management or restoration efforts.

scholarly journals Streamflow prediction in ungauged basins: benchmarking the efficiency of deep learning

2020 ◽  
Vol 163 ◽  
pp. 01001
Author(s):  
Georgy Ayzel ◽  
Liubov Kurochkina ◽  
Eduard Kazakov ◽  
Sergei Zhuravlev
Keyword(s):  
Deep Learning ◽  
Hydrological Model ◽  
State Of The Art ◽  
Flash Flood ◽  
Early Warning Systems ◽  
Model Parameters ◽  
Ungauged Basins ◽  
Streamflow Prediction ◽  
Basin Scale ◽  
The Impact

Streamflow prediction is a vital public service that helps to establish flash-flood early warning systems or assess the impact of projected climate change on water management. However, the availability of streamflow observations limits the utilization of the state-of-the-art streamflow prediction techniques to the basins where hydrometric gauging stations exist. Since the most river basins in the world are ungauged, the development of the specialized techniques for the reliable streamflow prediction in ungauged basins (PUB) is of crucial importance. In recent years, the emerging field of deep learning provides a myriad of new models that can breathe new life into the stagnating PUB methods. In the presented study, we benchmark the streamflow prediction efficiency of Long Short-Term Memory (LSTM) networks against the standard technique of GR4J hydrological model parameters regionalization (HMREG) at 200 basins in Northwest Russia. Results show that the LSTM-based regional hydrological model significantly outperforms the HMREG scheme in terms of median Nash-Sutcliffe efficiency (NSE), which is 0.73 and 0.61 for LSTM and HMREG, respectively. Moreover, LSTM demonstrates the comparable median NSE with that for basin-scale calibration of GR4J (0.75). Therefore, this study underlines the high utilization potential of deep learning for the PUB by demonstrating the new state-of-the-art performance in this field.

scholarly journals The Use of Selected Landscape Metrics to Evaluate the Transformation of the Rural Landscape as a Result of the Development of the Mining Function—A Case Study of the Puchaczów Commune

2021 ◽  
Vol 13 (21) ◽  
pp. 12279
Author(s):  
Sylwia Barwicka ◽  
Małgorzata Milecka
Keyword(s):  
Comparative Analysis ◽  
Land Cover ◽  
Landscape Metrics ◽  
Rural Areas ◽  
Agricultural Land ◽  
Diversity Index ◽  
Rural Landscape ◽  
Hard Coal ◽  
Landscape Indicators ◽  
The Impact

Landscape metrics have been used for years in research on the evolution of landscapes. They are also important in the process of monitoring changes taking place in the functional and spatial structure of rural areas. The main aim of this article is to assess the transformation of the rural landscape of the Puchaczów commune, which is based on a comparative analysis of selected landscape metrics. In the Puchaczów commune, due to the availability of raw materials, a mining industry has developed, which has a decisive influence on the development of the region. The study included schemes of the commune’s land cover from four periods: the pre-war period, the 1960s and the 1970s (i.e., shortly before the construction of the hard coal mine), 1990–2000, and 2020. Then, for the given time frames, with the help of the FRAGSTATS version 4.2 program, the following landscape indicators were calculated: the percentage of the landscape coverage by particular land cover units, the number of patches, the mean class area, the Shannon diversity index, and the Simpson diversity index. A comparative analysis of landscape metrics showed that the landscape of the Puchaczów commune was constantly transformed in the years 1937–2020. Despite the decrease in the area of agricultural land, agricultural production remains the dominant function of the commune. The percentage of industrial areas is the smallest, but the metric values do not reflect the enormous environmental impact of the mine. A broader description of the changes taking place in the landscape of the Puchaczów commune can therefore be obtained only by combining research with the use of landscape metrics and analyses of the impact of land cover units on the environment.

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