scholarly journals Evaluation of precipitation forecasts from NOAA global forecast system in hydropower operation

2010 ◽  
Vol 13 (1) ◽  
pp. 81-95 ◽  
Author(s):  
Huicheng Zhou ◽  
Guolei Tang ◽  
Ningning Li ◽  
Feng Wang ◽  
Yajun Wang ◽  
...  
Keyword(s):  
River Basin ◽  
Hydrological Model ◽  
Hydropower Station ◽  
Forecast Errors ◽  
Global Forecast System ◽  
Forecast System ◽  
Medium Range ◽  
Hydropower Operation ◽  
Yalong River ◽  
Yalong River Basin

Forecasts of 10-day average inflow into the Ertan hydropower station of the Yalong river basin are needed for seasonal hydropower operation. Medium-range inflow forecasts have usually been obtained by Auto-Regressive-Moving-Average (ARMA) models, which do not utilize any precipitation forecasts. This paper presents a simple GFS-QPFs-based rainfall - runoff model (GRR) using the 10-day accumulated Quantitative Precipitation Forecasts from the Global Forecast System (GFS-QPFs) run at the American National Oceanic and Atmospheric Administration (NOAA). In this study, 10-day accumulated GFS-QPFs over the Yalong river basin are verified by first using a three-category contingency table. Then this paper presents the results from a proposed hydrological model using 10-day accumulated GFS-QPFs. Results show that inflow forecast errors can be reduced considerably, compared with those from the currently used ARMA model by both quantitative and qualitative analysis. Finally, simulations of medium-range hydropower operation are also presented using the historical data and forecasts of 10-day average inflows into the Ertan dam during May to September 2006 to evaluate the efficiency of the proposed hydrological model using the GFS-QPFs. The simulations demonstrate that the use of GFS-QPFs has improved reservoir inflow predictions and hydropower operation of the Ertan hydropower station in the Yalong river basin during the wet season.

Distribution features of landslides in the Yalong River Basin, Southwest China

2021 ◽  
Vol 80 (7) ◽  
Author(s):  
Gang Jin ◽  
Yunsheng Wang ◽  
Wenbin Wu ◽  
Tai Guo ◽  
Jialu Xu
Keyword(s):  
River Basin ◽  
Southwest China ◽  
Distribution Features ◽  
Yalong River ◽  
Yalong River Basin

Evaluation of Global Forecast System (GFS) Medium-Range Precipitation Forecasts in the Nile River Basin

2021 ◽  
Author(s):  
Haowen Yue ◽  
Mekonnen Gebremichael ◽  
Vahid Nourani
Keyword(s):  
Temporal Dynamics ◽  
Disease Outbreaks ◽  
Rain Gauge ◽  
Global Forecast System ◽  
Forecast System ◽  
Forecast Performance ◽  
Weather Forecasts ◽  
Rain Gauges ◽  
Basin Scale ◽  
Medium Range

Abstract Reliable weather forecasts are valuable in a number of applications, such as, agriculture, hydropower, and weather-related disease outbreaks. Global weather forecasts are widely used, but detailed evaluation over specific regions is paramount for users and operational centers to enhance the usability of forecasts and improve their accuracy. This study presents evaluation of the Global Forecast System (GFS) medium-range (1 day – 15 day) precipitation forecasts in the nine sub-basins of the Nile basin using NASA’s Integrated Multi-satellitE Retrievals (IMERG) “Final Run” satellite-gauge merged rainfall observations. The GFS products are available at a temporal resolution of 3-6 hours, spatial resolution of 0.25°, and its version-15 products are available since 12 June 2019. GFS forecasts are evaluated at a temporal scale of 1-15 days, spatial scale of 0.25° to all the way to the sub-basin scale, and for a period of one year (15 June 2019 – 15 June 2020). The results show that performance of the 1-day lead daily basin-averaged GFS forecast performance, as measured through the modified Kling-Gupta Efficiency (KGE), is poor (0 < KGE < 0.5) for most of the sub-basins. The factors contributing to the low performance are: (1) large overestimation bias in watersheds located in wet climate regimes in the northern hemispheres (Millennium watershed, Upper Atbara & Setit watershed, and Khashm El Gibra watershed), and (2) lower ability in capturing the temporal dynamics of watershed-averaged rainfall that have smaller watershed areas (Roseires at 14,110 sq. km and Sennar at 13,895 sq. km). GFS has better bias for watersheds located in the dry parts of the northern hemisphere or wet parts of the southern hemisphere, and better ability in capturing the temporal dynamics of watershed-average rainfall for large watershed areas. IMERG Early has better bias than GFS forecast for the Millennium watershed but still comparable and worse bias for the Upper Atbara & Setit, and Khashm El Gibra watersheds. The variation in the performance of the IMERG Early could be partly explained by the number of rain gauges used in the reference IMERG Final product, as 16 rain gauges were used for the Millennium watershed but only one rain gauge over each Upper Atbara & Setit, and Khashm El Gibra watershed. A simple climatological bias-correction of IMERG Early reduces in the bias in IMERG Early over most watersheds, but not all watersheds. We recommend exploring methods to increase the performance of GFS forecasts, including post-processing techniques through the use of both near-real-time and research-version satellite rainfall products.

scholarly journals Assessing the Impact of Reservoir Parameters on Runoff in the Yalong River Basin using the SWAT Model

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 643 ◽  
Author(s):  
Xuan Liu ◽  
Mingxiang Yang ◽  
Xianyong Meng ◽  
Fan Wen ◽  
Guangdong Sun
Keyword(s):  
River Basin ◽  
Flood Control ◽  
Hydrological Cycle ◽  
Swat Model ◽  
Relative Location ◽  
Reservoir Capacity ◽  
Joint Operation ◽  
The Impact ◽  
Yalong River ◽  
Yalong River Basin

The construction and operation of cascade reservoirs has changed the natural hydrological cycle in the Yalong River Basin, and reduced the accuracy of hydrological forecasting. The impact of cascade reservoir operation on the runoff of the Yalong River Basin is assessed, providing a theoretical reference for the construction and joint operation of reservoirs. In this paper, eight scenarios were set up, by changing the reservoir capacity, operating location, and relative location in the case of two reservoirs. The aim of this study is to explore the impact of the capacity and location of a single reservoir on runoff processes, and the effect of the relative location in the case of joint operation of reservoirs. The results show that: (1) the reservoir has a delay and reduction effect on the flood during the flood season, and has a replenishment effect on the runoff during the dry season; (2) the impact of the reservoir on runoff processes and changes in runoff distribution during the year increases with the reservoir capacity; (3) the mitigation of flooding is more obvious at the river basin outlet control station when the reservoir is further downstream; (4) an arrangement with the smaller reservoir located upstream and the larger reservoir located downstream can maximize the benefits of the reservoirs in flood control.

scholarly journals Cumulative Environmental Effects of Hydropower Stations Based on the Water Footprint Method—Yalong River Basin, China

2019 ◽  
Vol 11 (21) ◽  
pp. 5958 ◽  
Author(s):  
Yu ◽  
Jia ◽  
Wu ◽  
Wu ◽  
Xu ◽  
...  
Keyword(s):  
River Basin ◽  
Environmental Effects ◽  
Water Scarcity ◽  
Water Footprint ◽  
Environmental Flow ◽  
Blue Water ◽  
Development And Utilization ◽  
Hydropower Stations ◽  
Yalong River ◽  
Yalong River Basin

The construction of hydropower stations is not without controversy as they have a certain degree of impact on the ecological environment. Moreover, the water footprint and its cumulative effects on the environment (The relationship between the degree of hydropower development and utilization in the basin and the environment) of the development and utilization of cascade hydropower stations are incompletely understood. In this paper, we calculate the evaporated water footprint (EWF, water evaporated from reservoirs) and the product water footprint of hydropower stations (PWF, water consumption per unit of electricity production), and the blue water scarcity (BWS, the ratio of the total blue water footprint to blue water availability) based on data from 19 selected hydropower stations in the Yalong River Basin, China. Results show that: (a) the EWFs in established, ongoing, proposed, and planning phases of 19 hydropower stations are 243, 123, 59, and 42 Mm3, respectively; (b) the PWF of 19 hydropower stations varies between 0.01 and 4.49 m3GJ−1, and the average PWF is 1.20 m3GJ−1. These values are quite small when compared with hydropower stations in other basins in the world, and the difference in PWF among different hydropower stations is mainly derived from energy efficiency factor; (c) all the BWS in the Yalong River Basin are below 100% (low blue water scarcity), in which the total blue water footprint is less than 20% of the natural flow, and environmental flow requirements are met. From the perspective of the water footprint method, the cumulative environmental effects of hydropower development and utilization in the Yalong River Basin will not affect the local environmental flow requirements.

Integrating weather and climate predictions for seamless hydrologic ensemble forecasting: A case study in the Yalong River basin

2017 ◽  
Vol 547 ◽  
pp. 196-207 ◽  
Author(s):  
Aizhong Ye ◽  
Xiaoxue Deng ◽  
Feng Ma ◽  
Qingyun Duan ◽  
Zheng Zhou ◽  
...  
Keyword(s):  
River Basin ◽  
Ensemble Forecasting ◽  
Weather And Climate ◽  
Yalong River ◽  
Yalong River Basin

scholarly journals Empirical Correction of the NCEP Global Forecast System

2008 ◽  
Vol 136 (12) ◽  
pp. 5224-5233 ◽  
Author(s):  
Xiaosong Yang ◽  
Timothy DelSole ◽  
Hua-Lu Pan
Keyword(s):  
Mean Square Error ◽  
Least Squares Method ◽  
Forecast Model ◽  
Correction Method ◽  
Forecast Errors ◽  
Calibration Data ◽  
Mean Square ◽  
Global Forecast System ◽  
Forecast System ◽  
Empirical Correction

Abstract This paper examines the extent to which an empirical correction method can improve forecasts of the National Centers for Environmental Prediction (NCEP) operational Global Forecast System. The empirical correction is based on adding a forcing term to the prognostic equations equal to the negative of the climatological tendency errors. The tendency errors are estimated by a least squares method using 6-, 12-, 18-, and 24-h forecast errors. Tests on independent verification data show that the empirical correction significantly reduces temperature biases nearly everywhere at all lead times up to at least 5 days but does not significantly reduce biases in forecast winds and humidity. Decomposing mean-square error into bias and random components reveals that the reduction in total mean-square error arises solely from reduction in bias. Interestingly, the empirical correction increases the random error slightly, but this increase is argued to be an artifact of the change in variance in the forecasts. The empirical correction also is found to reduce the bias more than traditional “after the fact” corrections. The latter result might be a consequence of the very different sample sizes available for estimation, but this difference in sample size is unavoidable in operational situations in which limited calibration data are available for a given forecast model.

Impact of the Different Components of 4DVAR on the Global Forecast System of the Meteorological Service of Canada

2007 ◽  
Vol 135 (6) ◽  
pp. 2355-2364 ◽  
Author(s):  
Stéphane Laroche ◽  
Pierre Gauthier ◽  
Monique Tanguay ◽  
Simon Pellerin ◽  
Josée Morneau
Keyword(s):  
Data Assimilation ◽  
Positive Impact ◽  
Weather Forecast ◽  
Forecast Model ◽  
Variational Data Assimilation ◽  
Global Forecast System ◽  
Forecast System ◽  
Medium Range Weather Forecast ◽  
Medium Range ◽  
The Impact

Abstract A four-dimensional variational data assimilation (4DVAR) scheme has recently been implemented in the medium-range weather forecast system of the Meteorological Service of Canada (MSC). The new scheme is now composed of several additional and improved features as compared with the three-dimensional variational data assimilation (3DVAR): the first guess at the appropriate time from the full-resolution model trajectory is used to calculate the misfit to the observations; the tangent linear of the forecast model and its adjoint are employed to propagate the analysis increment and the gradient of the cost function over the 6-h assimilation window; a comprehensive set of simplified physical parameterizations is used during the final minimization process; and the number of frequently reported data, in particular satellite data, has substantially increased. The impact of these 4DVAR components on the forecast skill is reported in this article. This is achieved by comparing data assimilation configurations that range in complexity from the former 3DVAR with the implemented 4DVAR over a 1-month period. It is shown that the implementation of the tangent-linear model and its adjoint as well as the increased number of observations are the two features of the new 4DVAR that contribute the most to the forecast improvement. All the other components provide marginal though positive impact. 4DVAR does not improve the medium-range forecast of tropical storms in general and tends to amplify the existing, too early extratropical transition often observed in the MSC global forecast system with 3DVAR. It is shown that this recurrent problem is, however, more sensitive to the forecast model than the data assimilation scheme employed in this system. Finally, the impact of using a shorter cutoff time for the reception of observations, as the one used in the operational context for the 0000 and 1200 UTC forecasts, is more detrimental with 4DVAR. This result indicates that 4DVAR is more sensitive to observations at the end of the assimilation window than 3DVAR.

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