scholarly journals The Characteristics of Mountainous Runoff in Shiyang River Basin and Its Spatial Correlation with the Large-Scale Moisture Field

2017 ◽  
Vol 06 (02) ◽  
pp. 166-175
Author(s):  
迎 侯
Keyword(s):  
Spatial Correlation ◽  
River Basin ◽  
Large Scale ◽  
Shiyang River Basin ◽  
Moisture Field

scholarly journals Using the Global Hydrodynamic Model and GRACE Follow-On Data to Access the 2020 Catastrophic Flood in Yangtze River Basin

2021 ◽  
Vol 13 (15) ◽  
pp. 3023
Author(s):  
Jinghua Xiong ◽  
Shenglian Guo ◽  
Jiabo Yin ◽  
Lei Gu ◽  
Feng Xiong
Keyword(s):  
River Basin ◽  
Hydrodynamic Model ◽  
Yangtze River ◽  
Large Scale ◽  
Yangtze River Basin ◽  
The Yangtze River ◽  
Ecosystem Monitoring ◽  
Catastrophic Flood ◽  
Basin Scale ◽  
The Yangtze River Basin

Flooding is one of the most widespread and frequent weather-related hazards that has devastating impacts on the society and ecosystem. Monitoring flooding is a vital issue for water resources management, socioeconomic sustainable development, and maintaining life safety. By integrating multiple precipitation, evapotranspiration, and GRACE-Follow On (GRAFO) terrestrial water storage anomaly (TWSA) datasets, this study uses the water balance principle coupled with the CaMa-Flood hydrodynamic model to access the spatiotemporal discharge variations in the Yangtze River basin during the 2020 catastrophic flood. The results show that: (1) TWSA bias dominates the overall uncertainty in runoff at the basin scale, which is spatially governed by uncertainty in TWSA and precipitation; (2) spatially, a field significance at the 5% level is discovered for the correlations between GRAFO-based runoff and GLDAS results. The GRAFO-derived discharge series has a high correlation coefficient with either in situ observations and hydrological simulations for the Yangtze River basin, at the 0.01 significance level; (3) the GRAFO-derived discharge observes the flood peaks in July and August and the recession process in October 2020. Our developed approach provides an alternative way of monitoring large-scale extreme hydrological events with the latest GRAFO release and CaMa-Flood model.

scholarly journals A New Tool to Estimate Inundation Depths by Spatial Interpolation (RAPIDE): Design, Application and Impact on Quantitative Assessment of Flood Damages

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1805 ◽  
Author(s):  
Anna Scorzini ◽  
Alessio Radice ◽  
Daniela Molinari
Keyword(s):  
River Basin ◽  
Water Depth ◽  
Spatial Interpolation ◽  
Large Scale ◽  
Quantitative Estimation ◽  
Digital Terrain Model ◽  
Water Levels ◽  
Flood Depth ◽  
Inundation Depth ◽  
Basin Scale

Rapid tools for the prediction of the spatial distribution of flood depths within inundated areas are necessary when the implementation of complex hydrodynamic models is not possible due to time constraints or lack of data. For example, similar tools may be extremely useful to obtain first estimates of flood losses in the aftermath of an event, or for large-scale river basin planning. This paper presents RAPIDE, a new GIS-based tool for the estimation of the water depth distribution that relies only on the perimeter of the inundation and a digital terrain model. RAPIDE is based on a spatial interpolation of water levels, starting from the hypothesis that the perimeter of the flooded area is the locus of points having null water depth. The interpolation is improved by (i) the use of auxiliary lines, perpendicular to the river reach, along which additional control points are placed and (ii) the possibility to introduce a mask for filtering interpolation points near critical areas. The reliability of RAPIDE is tested for the 2002 flood in Lodi (northern Italy), by comparing the inundation depth maps obtained by the rapid tool to those from 2D hydraulic modelling. The change of the results, related to the use of either method, affects the quantitative estimation of direct damages very limitedly. The results, therefore, show that RAPIDE can provide accurate flood depth predictions, with errors that are fully compatible with its use for river-basin scale flood risk assessments and civil protection purposes.

scholarly journals Analysis of evapotranspiration and biomass in pastures with degradation indicatives in the Upper Tocantins River Basin, in Brazilian Savanna

Revista CERES ◽  
2016 ◽  
Vol 63 (6) ◽  
pp. 754-760 ◽  
Author(s):  
Ricardo Guimarães Andrade ◽  
Antônio Heriberto de Castro Teixeira ◽  
Janice Freitas Leivas ◽  
Sandra Furlan Nogueira
Keyword(s):  
River Basin ◽  
Large Scale ◽  
Meteorological Data ◽  
Simple Algorithm ◽  
Production Potential ◽  
Pasture Degradation ◽  
Ndvi Time Series ◽  
Tocantins River ◽  
Remote Sensing Techniques ◽  
Degraded Pastures

ABSTRACT The objective of this study was to apply the Simple Algorithm For Evapotranspiration Retrieving (SAFER) with MODIS images together with meteorological data to analyze evapotranspiration (ET) and biomass production (BIO) according to indicative classes of pasture degradation in Upper Tocantins River Basin. Indicative classes of degraded pastures were obtained from the NDVI time-series (2002-2012). To estimate ET and BIO in each class, MODIS images and data from meteorological stations of the year 2012 were used. The results show that compared to not-degraded pastures, ET and BIO were different in pastures with moderate to strong degradation, mainly during water stress period. Therefore, changes in energy balance partition may occur according to the degradation levels, considering that those indicatives of degradation processes were identified in 24% of the planted pasture areas. In this context, ET and BIO estimates using remote sensing techniques can be a reliable indicator of forage availability, and large-scale aspects related to the degradation of pastures. It is expected that this knowledge may contribute to initiatives of public policies aimed at controlling the loss of production potential of pasture areas in the Upper Tocantins River Basin in the state of Goiás, Brazil.

scholarly journals Optimal Water Allocation Based on Water Rights Transaction Models with Administered and Market-Based Systems: A Case Study of Shiyang River Basin, China

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 577 ◽  
Author(s):  
Lizhen Wang ◽  
Yong Zhao ◽  
Yuefei Huang ◽  
Jianhua Wang ◽  
Haihong Li ◽  
...  
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Water Allocation ◽  
Water Rights ◽  
Water Saving ◽  
Allocation Model ◽  
Transaction Model ◽  
Shiyang River Basin ◽  
The Impact ◽  
Optimal Water Allocation

Water-rights trade has proved to be an effective method for coping with water shortages through the transfer of water resources between users. The water allocation system is classified into two categories based on information transparency and water rights transaction goals: administered system (AS) and market-based system (MS). A multi-agent and multi-objective optimal allocation model, built on a complex adaptive system, was introduced to direct the distribution of water resources under an AS in the Shiyang River Basin; it was compared with a market-based water rights transaction model using the bulletin-board approach. Ideal economic agent equations played a dominant role in both models. The government and different water users were conceptualized as agents with different behaviors and goals in water allocation. The impact of water-saving cost on optimal water allocation was also considered. The results showed that an agent’s water-saving behavior was incentivized by high transaction prices in the water market. Under the MS, the highest bid in the quotation set had a dominant influence on how trade was conducted. A higher transaction price will, thus, result in a better benefit ratio, and a lower one will result in inactivity in terms of water rights trade. This will significantly impact the economic benefit to the basin.

scholarly journals Cloud obstruction and snow cover in Alpine areas from MODIS products

2014 ◽  
Vol 18 (11) ◽  
pp. 4579-4600 ◽  
Author(s):  
P. Da Ronco ◽  
C. De Michele
Keyword(s):  
Snow Cover ◽  
River Basin ◽  
Cloud Cover ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Practical Interest ◽  
Computational Effort ◽  
Po River ◽  
Average Value ◽  
Po River Basin

Abstract. Snow cover maps provide information of great practical interest for hydrologic purposes: when combined with point values of snow water equivalent (SWE), they enable estimation of the regional snow resource. In this context, Earth observation satellites are an interesting tool for evaluating large scale snow distribution and extension. MODIS (MODerate resolution Imaging Spectroradiometer on board Terra and Aqua satellites) daily Snow Covered Area product has been widely tested and proved to be appropriate for hydrologic applications. However, within a daily map the presence of cloud cover can hide the ground, thus obstructing snow detection. Here, we consider MODIS binary products for daily snow mapping over the Po River basin. Ten years (2003–2012) of MOD10A1 and MYD10A1 snow maps have been analysed and processed with the support of a 500 m resolution Digital Elevation Model (DEM). We first investigate the issue of cloud obstruction, highlighting its dependence on altitude and season. Snow maps seem to suffer the influence of overcast conditions mainly in mountain and during the melting period. Thus, cloud cover highly influences those areas where snow detection is regarded with more interest. In spring, the average percentages of area lying beneath clouds are in the order of 70%, for altitudes over 1000 m a.s.l. Then, starting from previous studies, we propose a cloud removal procedure and we apply it to a wide area, characterized by high geomorphological heterogeneity such as the Po River basin. In conceiving the new procedure, our first target was to preserve the daily temporal resolution of the product. Regional snow and land lines were estimated for detecting snow cover dependence on elevation. In cases when there was not enough information on the same day within the cloud-free areas, we used temporal filters with the aim of reproducing the micro-cycles which characterize the transition altitudes, where snow does not stand continually over the entire winter. In the validation stage, the proposed procedure was compared against others, showing improvements in the performance for our case study. The accuracy is assessed by applying the procedure to clear-sky maps masked with additional cloud cover. The average value is higher than 95% considering 40 days chosen over all seasons. The procedure also has advantages in terms of input data and computational effort requirements.

scholarly journals Investigation of Atmospheric Rivers Impacting the Pigeon River Basin of the Southern Appalachian Mountains

2018 ◽  
Vol 33 (1) ◽  
pp. 283-299 ◽  
Author(s):  
Douglas K. Miller ◽  
David Hotz ◽  
Jessica Winton ◽  
Lukas Stewart
Keyword(s):  
North Carolina ◽  
River Basin ◽  
Large Scale ◽  
Large Fraction ◽  
Appalachian Mountains ◽  
Warm Season ◽  
Atmospheric Rivers ◽  
Southern Appalachian Mountains ◽  
Low Level ◽  
Southern Appalachian

Abstract Rainfall observations in the Pigeon River basin of the southern Appalachian Mountains over a 5-yr period (2009–14) are examined to investigate the synoptic patterns responsible for downstream flooding events as observed near Knoxville, Tennessee, and Asheville, North Carolina. The study is designed to address the hypothesis that atmospheric rivers (ARs) are primarily responsible for the highest accumulation periods observed by the gauge network and that these periods correspond to events having a societal hazard (flooding). The upper 2.5% (extreme) and middle 33% (normal) rainfall events flagged using the gauge network observations showed that half of the heaviest rainfall cases were associated with an AR. Of those extreme events having an AR influence, over 73% had a societal hazard defined as minor-to-major flooding at the USGS river gauge located in Newport, Tennessee, or flooding observations for locations near the Tennessee and North Carolina border reported in the Storm Data publication. Composites of extreme AR-influenced events revealed a synoptic pattern consisting of a highly amplified slow-moving positively tilted trough, suggestive of the anticyclonic Rossby wave breaking scenario that sometimes precedes hydrological events of high impact. Composites of extreme non-AR events indicated a large-scale weather pattern typical of a warm season scenario in which an anomalous low-level cyclone, cut off far from the primary upper-tropospheric jet, was located in the southeastern United States. AR events without a societal hazard represented a large fraction (75%–88%) of all ARs detected during the study period. Synoptic-scale weather patterns of these events were fast moving and had weak low-level atmospheric dynamics.

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