scholarly journals Assessing the factors governing the ability to predict late-spring flooding in cold-region mountain basins

2020 ◽  
Vol 24 (4) ◽  
pp. 2141-2165 ◽  
Author(s):  
Vincent Vionnet ◽  
Vincent Fortin ◽  
Etienne Gaborit ◽  
Guy Roy ◽  
Maria Abrahamowicz ◽  
...  
Keyword(s):  
Soil Texture ◽  
Peak Flow ◽  
River Basins ◽  
Late Spring ◽  
Atmospheric Forcing ◽  
Cold Region ◽  
Flooding Event ◽  
Southern Alberta ◽  
Precipitation Analysis ◽  
Headwater Basins

Abstract. From 19 to 22 June 2013, intense rainfall and concurrent snowmelt led to devastating floods in the Canadian Rockies, foothills and downstream areas of southern Alberta and southeastern British Columbia, Canada. Such an event is typical of late-spring floods in cold-region mountain headwater, combining intense precipitation with rapid melting of late-lying snowpack, and represents a challenge for hydrological forecasting systems. This study investigated the factors governing the ability to predict such an event. Three sources of uncertainty, other than the hydrological model processes and parameters, were considered: (i) the resolution of the atmospheric forcings, (ii) the snow and soil moisture initial conditions (ICs) and (iii) the representation of the soil texture. The Global Environmental Multiscale hydrological modeling platform (GEM-Hydro), running at a 1 km grid spacing, was used to simulate hydrometeorological conditions in the main headwater basins of southern Alberta during this event. The GEM atmospheric model and the Canadian Precipitation Analysis (CaPA) system were combined to generate atmospheric forcing at 10, 2.5 and 1 km over southern Alberta. Gridded estimates of snow water equivalent (SWE) from the Snow Data Assimilation System (SNODAS) were used to replace the model SWE at peak snow accumulation and generate alternative snow and soil moisture ICs before the event. Two global soil texture datasets were also used. Overall 12 simulations of the flooding event were carried out. Results show that the resolution of the atmospheric forcing affected primarily the flood volume and peak flow in all river basins due to a more accurate estimation of intensity and total amount of precipitation during the flooding event provided by CaPA analysis at convection-permitting scales (2.5 and 1 km). Basin-averaged snowmelt also changed with the resolution due to changes in near-surface wind and resulting turbulent fluxes contributing to snowmelt. Snow ICs were the main sources of uncertainty for half of the headwater basins. Finally, the soil texture had less impact and only affected peak flow magnitude and timing for some stations. These results highlight the need to combine atmospheric forcing at convection-permitting scales with high-quality snow ICs to provide accurate streamflow predictions during late-spring floods in cold-region mountain river basins. The predictive improvement by inclusion of high-elevation weather stations in the precipitation analysis and the need for accurate mountain snow information suggest the necessity of integrated observation and prediction systems for forecasting extreme events in mountain river basins.

scholarly journals High-resolution hydrometeorological modelling of the June 2013 flood in southern Alberta, Canada

2019 ◽  
Author(s):  
Vincent Vionnet ◽  
Vincent Fortin ◽  
Etienne Gaborit ◽  
Guy Roy ◽  
Maria Abrahamowicz ◽  
...  
Keyword(s):  
Snow Water Equivalent ◽  
Peak Flow ◽  
Extreme Event ◽  
Accurate Estimation ◽  
Western Canada ◽  
Hydrological Forecasting ◽  
Southern Alberta ◽  
Precipitation Estimation ◽  
Snow Conditions ◽  
High Elevations

Abstract. From June 19 to June 22, 2013, intense rainfall and concurrent snowmelt led to devastating floods in the Canadian Rockies, foothills and downstream areas of southern Alberta and southeastern British Columbia. The complexity of the topography in the mountain headwaters, presence of snow at high elevations and other factors challenged hydrological forecasting of this extreme event. In this study, the ability of the Global Environmental Multi-scale hydrological modelling platform (GEM-Hydro), running at a 1-km grid spacing, to simulate hydrometeorological conditions in several Alberta rivers during this event is assessed. Four quantitative precipitation estimation (QPE) products were generated using the Canadian Precipitation Analysis (CaPA) system by varying (i) station density and (ii) horizontal resolutions (10, 2.5 and 1 km) of the GEM precipitation background. CaPA at 2.5 and 1 km including all available stations in the headwaters provided the most accurate estimation of intensity and total amount of precipitation during the flooding event. Using these products to drive GEM-Hydro, it is shown that QPE accuracy dominates the ability to predict flood volumes. Initial snow conditions also represent a large additional source of uncertainty. Default GEM-Hydro simulations starting with almost no snowpack at high-elevations led to a systematic underestimation of flood volume and peak flow. Gridded estimates of snow water equivalent from the Snow Data Assimilation System (SNODAS) were also considered. They led to contrasting abilities to simulate flood discharge volumes and a consistent overestimation in the headwater catchments, illustrating the strong need for a reference snow product in the mountains of Western Canada. Finally, GEM-Hydro did not predict peak flow timing and hydrograph shape well. Model sensitivity tests show that it could be improved by adjusting the Manning coefficients, suggesting the need to revisit the routing parameters. There may be a need to include water management effects on flood hydrographs as well. These results will guide the development of GEM-Hydro as a hydrological forecasting system in Western Canada.

PEAK FLOW REQUIREMENTS FOR SPRINKLER IRRIGATION OF ORCHARDS AS AFFECTED BY SOIL TEXTURE AND PEAK EVAPOTRANSPIRATION

1969 ◽  
Vol 49 (1) ◽  
pp. 39-45
Author(s):  
J. C. Wilcox
Keyword(s):  
Steady Flow ◽  
Soil Texture ◽  
Irrigation Water ◽  
Peak Flow ◽  
Unit Area ◽  
Correlation Coefficients ◽  
Sprinkler Irrigation ◽  
Water Holding Capacity ◽  
Irrigation Interval ◽  
Water Holding

A scheduling procedure was used in 17 orchards, from 1962 to 1965 inclusive, to determine the peak flow of irrigation water required per unit area of land. Irrigation was by the sprinkler method, with portable pipe settings of 12 hours. Peak flow was determined on a steady-flow basis during periods of peak evapotranspiration. Evapotranspiration (ET) was determined by use of evaporimeters. The texture and the water-holding capacity of the soil were also determined. Highly significant coefficients of correlation were obtained between the peak flow required and each of percent sand, average ET per day during the period of peak ET, depth of water applied at each irrigation, length of irrigation interval and various other factors. High correlation coefficients were also obtained among the factors studied. Regression of percent sand and peak ET on peak flow accounted for 90.6% of the variations in peak flow; regression of depth per application and length of irrigation interval accounted for 84.1%. It is suggested that peak flow was affected directly by the depth of water applied at each irrigation and by the length of the "safe" irrigation interval, and indirectly by other factors.

scholarly journals Flood Mitigation in the Transboundary Chenab River Basin: A Basin-Wise Approach from Flood Forecasting to Management

2021 ◽  
Vol 13 (19) ◽  
pp. 3916
Author(s):  
Sikandar Ali ◽  
Muhammad Jehanzeb Masud Cheema ◽  
Muhammad Mohsin Waqas ◽  
Muhammad Waseem ◽  
Megersa Kebede Leta ◽  
...  
Keyword(s):  
River Basin ◽  
Peak Flow ◽  
Flow Simulation ◽  
River Basins ◽  
Flood Forecasting ◽  
Flood Mitigation ◽  
Economic Losses ◽  
The World ◽  
Chenab River ◽  
Inundation Modeling

Rapid and reliable flood information is crucial for minimizing post-event catastrophes in the complex river basins of the world. The Chenab River basin is one of the complex river basins of the world, facing adverse hydrometeorological conditions with unpredictable hydrologic response. Resultantly, many vicinities along the river undergo destructive inundation, resulting in huge life and economic losses. In this study, Hydrologic Engineering Centre–Hydrologic Modeling System (HEC-HMS) and HEC–River Analysis System (HEC-RAS) models were used for flood forecasting and inundation modeling of the Chenab River basin. The HEC-HMS model was used for peak flow simulation of 2014 flood event using Global Precipitation Mission (GMP) Integrated Multisatellite Retrievals-Final (IMERG-F), Tropical Rainfall Measuring Mission_Real Time (TRMM_3B42RT), and Global Satellite Mapping of Precipitation_Near Real Time (GSMaP_NRT) precipitation products. The calibration and validation of the HEC-RAS model were carried out for flood events of 1992 and 2014, respectively. The comparison of observed and simulated flow at the outlet indicated that IMERG-F has good peak flow simulation results. The simulated inundation extent revealed an overall accuracy of more than 90% when compared with satellite imagery. The HEC-RAS model performed well at Manning’s n of 0.06 for the river and the floodplain. From the results, it can be concluded that remote sensing integrated with HEC-HMS and HEC-RAS models could be one of the workable solutions for flood forecasting, inundation modeling, and early warning. The concept of integrated flood management (IFM) has also been translated into practical implementation for joint Indo-Pak management for flood mitigation in the transboundary Chenab River basin.

scholarly journals Comparing the performances of WRF QPF and PERSIANN-CCS QPEs in karst flood simulations and forecasting with a new Karst-Liuxihe model

2019 ◽  
Author(s):  
Ji Li ◽  
Daoxian Yuan ◽  
Aihua Hong ◽  
Yongjun Jiang ◽  
Jiao Liu ◽  
...  
Keyword(s):  
Lead Time ◽  
Peak Flow ◽  
Coupled Model ◽  
River Basins ◽  
Flood Simulation ◽  
Flood Peak ◽  
Karst Areas ◽  
Karst River ◽  
Flood Simulations ◽  
Weather Models

Abstract. Long-term, available rainfall data are very important for karst flood simulations and forecasting. However, in karst areas, there is often a lack of effective precipitation available to build distributed hydrological models. Forecasting karst floods is highly challenging. Quantitative precipitation forecasts (QPF) and estimates (QPEs) could provide rational methods to acquire the available precipitation results for karst areas. Furthermore, coupling a physically-based hydrological model with the QPF and QPEs felicitously could largely enhance the performance and extend the lead time of floods forecasting in karst areas, the performance of coupling the Weather Research and Forecasting Quantitative Precipitation Forecast (WRF QPF) and Precipitation Estimations through Remotely Sensed Information based on the Artificial Neural Network-Cloud Classification System (PERSIANN-CCS QPEs) with a new fully distributed and physical hydrological model, the Karst-Liuxihe model in flood simulations and forecasting in karst area. This study served 2 main purposes: one purpose is to compare the performances of WRF QPF and PERSIANN-CCS QPEs for rainfall forecasting in karst river basins. The other purpose is to test the effective feasibility and application of the karst flood simulation and forecasting by coupling the 2 weather models with a new Karst-Liuxihe model. The new Karst-Liuxihe model improved the structure of the model by adding the karst mechanism based on the Liuxihe model as follows: (1) Refine the model structure and put forward the concept of karst hydrological response units (KHRUs) in the model. The KHRU, as the smallest unit of the Karst-Liuxihe model, is defined in this paper to be suitable for karst basins; (2) Increase the calculations of water movement rules in the epikarst zone and underground river, such as the division of slow flow and rapid flow in the epikarst zone and the exchange of water flow between the karst fissures and conduit systems; thus, the convergence of the underground runoff calculation method is improved to be suitable for karst water-bearing media; and (3) Add some necessary hydrogeological parameters in the coupled model to reflect the true conditions of rainfall-runoff in the karst underlying surface. Moreover, the flood detention and peak clipping effects due to the upstream karst depressions during flooding were considered and reasonably calculated in the coupled model. The flood detention effect can affect the peak flow time error simulated in the model and make the true peak flow appear later; the flood peak clipping effect can affect the flood peak flow relative errors and the simulation errors of floods volume. The consideration of these 2 factors in the model makes the flood simulations and forecasting effects more credible. The rainfall forecasting result show that the precipitation distribution of the 2 weather models was very similar compared with the observed rainfall result. However, the precipitation amounts forecasted by WRF QPF were larger than that measured by the rain gauges, while the quantities were smaller by the PERSIANN-CCS QPEs. A postprocessing algorithm was adopted in this paper to correct the rainfall results by the 2 weather models. The karst flood simulation and forecasting results showed that the flood peak flow simulations were better by coupling the Karst-Liuxihe model with the PERSIANN-CCS QPEs, and coupling the Karst-Liuxihe model with WRF QPF could extend the lead time of flood forecasting largely, as a maximum lead time of 96 hours can provide an adequate amount of time for flood warnings and emergency responses. The satisfying and rational karst flood simulation evaluation indices proved that coupling the 2 weather models with the new Karst-Liuxihe model could be effectively used for karst river basins, which provides great practical application prospects for karst flood simulations and forecasting. In addition, the postprocessing method used to revise the 2 weather models in this paper is feasible and effective, and this method can largely improve the coupled model application effectiveness and prospect in karst river basins.

scholarly journals The uncertainties of synthetic unit hydrographs applied for basins with different runoff generation processes

RBRH ◽  
2021 ◽  
Vol 26 ◽  
Author(s):  
Andreia Pedroso ◽  
Michael Mannich
Keyword(s):  
Peak Flow ◽  
River Basins ◽  
Point Of View ◽  
Generation Process ◽  
Historical Records ◽  
Runoff Generation ◽  
Peak Flows ◽  
The Real ◽  
Unit Hydrographs ◽  
Maximum Flows

ABSTRACT Synthetic unit hydrographs (SUH) are useful tools for the estimation of maximum flows in basins lacking historical records of measurements. However, these methods have many uncertainties and do not always produce results consistent with reality. This study comparatively analyzed the uncertainty of the application of the Snyder, SCS, and Clark HUS methods, widely used, in relation to the observed hydrographs, in the Pequeno River and the Espingarda River basins, located in the State of Paraná, considered small from the point of view of the drainage area. The simulation was performed using the HEC-HMS 4.2.1 software considering a combination of parameters that produced the higher and lower peak flow, respectively named as conservative and bold approaches. It was verified that the SUH methods, in general, overestimated the peak flows for both basins under study. In addition, the results obtained showed that SUH are fundamentally conservative models so that a bold approach in estimating the parameters input leads to results with smaller errors in simulated peak flows. Even running the SUH with the real excess rainfall as input there is an overestimation of the peak flow. SCS SUH produced the highest peak flows and consequently the largest errors while Snyder’s SUH produced the smallest errors. The magnitude of the overestimation of the peak flow for the Pequeno River was up to 60 folds. Its geology features suggest a Dunnian runoff generation process, which explains the larger errors.

SOIL SALINITY STATUS AND ITS RELATION TO SOME OF THE SOIL AND LAND PROPERTIES OF THREE IRRIGATION DISTRICTS IN SOUTHERN ALBERTA

1985 ◽  
Vol 65 (1) ◽  
pp. 187-193 ◽  
Author(s):  
C. CHANG ◽  
G. C. KOZUB ◽  
D. C. MACKAY
Keyword(s):  
Water Supply ◽  
Water Table ◽  
Soil Salinity ◽  
Soil Texture ◽  
Clay Content ◽  
Salinity Level ◽  
Irrigation District ◽  
Irrigation Districts ◽  
Southern Alberta ◽  
Western Block

A detailed soil salinity survey was carried out in three of the 13 irrigation districts in southern Alberta. About 30 quarter-sections in each district were randomly selected for soil sampling. The location, distance from water supply ditches, slope of the land, and depth to till and water table at each site were recorded. Soil texture and electrical conductivity of extracts of soil samples were determined in the laboratory. The extent of the area with a soil salinity level of 4 dS/m or more is 5% of the total surveyed land in the Western Block of the St. Mary River Irrigation District (WSMRID), 6% in the Lethbridge Northern Irrigation District (LNID) and 9% in the Taber Irrigation District (TID). These values are not as high as others have previously estimated. The salinity level of the soil at each site was found to vary with its location and distance from water supply ditches in the WSMRID and LNID, clay content in the 0- to 120-cm depth in the WSMRID and TID, and water table level in the TID. Key words: Soil texture, EC, SAR, pH

scholarly journals Peak river flows in cold regions – Drivers and modelling using GRACE satellite observations and temperature data

2016 ◽  
Author(s):  
Shusen Wang ◽  
Fuqun Zhou ◽  
Hazen A. J. Russell ◽  
Ran Huang ◽  
Yanjun Shen
Keyword(s):  
River Basin ◽  
River Flow ◽  
Peak Flow ◽  
Flood Forecasting ◽  
Temperature Data ◽  
Satellite Observations ◽  
Cold Region ◽  
Grace Satellite ◽  
Hydrometric Station ◽  
Mackenzie River

Abstract. The peak river flow for the Mackenzie River is modelled using GRACE satellite observations and temperature data, which advances the applications of space-based time-variable gravity measurements in cold region flood forecasting. The model estimates peak river flow by simulating peak surface runoff from snowmelt and the corresponding baseflow. The modelled results compared fairly well with the observed values at a downstream hydrometric station. The results also revealed an average 22-day travel time for the snowmelt water to reach the hydrometric station. The major driver for determining the peak flow was found to be the temperature variations. Compared with the Red River basin, the results showed that the Mackenzie River basin has relatively high water storage and water discharge capability, and low snowmelt efficiency per unit temperature. The study also provides a GRACE-based approach for basin-scale snowfall estimation, which is independent of in situ measurements and largely eliminates the limitations and uncertainties with traditional approaches. The model is relatively simple and only needs GRACE and temperature observations for peak flow or flood forecasting. The model can be readily applied to other cold region basins, and could be particularly useful for regions with minimal data.

scholarly journals Evaluation of satellite rainfall estimates over Ethiopian river basins

2010 ◽  
Vol 7 (5) ◽  
pp. 7669-7694 ◽  
Author(s):  
T. G. Romilly ◽  
M. Gebremichael
Keyword(s):  
High Resolution ◽  
Tropical Rainfall Measuring Mission ◽  
River Basins ◽  
Rain Gauges ◽  
Precipitation Estimation ◽  
Precipitation Estimates ◽  
Annual Total ◽  
Precipitation Analysis ◽  
Climate Prediction Center ◽  
Rainfall Estimates

Abstract. The objective of this study was to evaluate the accuracy of high resolution satellite-based rainfall estimates (SREs) across six river basins within Ethiopia during the major (Kiremt) and minor (Belg) rainy seasons for the years 2003 to 2007. The six regions, the Awash, Baro Akobo, Blue Nile, Genale Dawa, Rift Valley and Wabi Shebele River Basins surround the Ethiopian Highlands, which produces different topographical features, as well as spatial and temporal rainfall patterns. Precipitation estimates for the six regions were taken from three widely used high resolution SREs: the Climate Prediction Center morphing method (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Neural Networks (PERSIANN) and the real-time version of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42RT. All three SREs show the natural northwest-southeast precipitation gradient, but exhibit different spatial (mean annual total and number of rainy days) and temporal (monthly) totals. When compared to ground based rain gauges throughout the six regions, and for the years of interest, the performance of the three SREs were found to be season independent. The results varied for lower elevations, with CMORPH and TMPA 3B42RT performing better than PERSIANN in the southeast, while PERSIANN provided more accurate results in the northwest. At higher elevations, PERSIANN consistently underestimated while the performance of CMORPH and TMPA 3B42RT varied.

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