scholarly journals Determining the Optimal Spatial Distribution of Weather Station Networks for Hydrological Modeling Purposes Using RCM Datasets: An Experimental Approach

2014 ◽  
Vol 15 (1) ◽  
pp. 517-526 ◽  
Author(s):  
Richard Arsenault ◽  
François Brissette
Keyword(s):  
River Basin ◽  
Optimization Algorithm ◽  
Water Resource Management ◽  
Hydrological Modeling ◽  
Climate Model ◽  
Meteorological Data ◽  
High Density ◽  
Limiting Factor ◽  
Weather Station ◽  
Weather Stations

Abstract In many hydrological studies, the main limiting factor in model performance is the low meteorological data quality. In some cases, no meteorological records even exist. Installing weather stations becomes a necessity in these areas when water resource management becomes an issue. The objective of this study is to propose a new experimental and exploratory method for determining the optimal density of a weather station network when being used for long-term hydrological modeling. Data from the Canadian Regional Climate Model at 15-km resolution (CRCM15) were used to create a virtual network of stations with long and complete series of meteorological data over the Toulnustouc River basin in central Québec, Canada. The weather stations to be fed to HSAMI, Hydro-Québec's lumped rainfall–runoff hydrological model, were selected in order to minimize the number of stations while maintaining the best hydrological performance possible using a multi-objective optimization algorithm. It was shown that the number of stations making up the network on the Toulnustouc River basin should be at least two but not higher than four. If the stations are positioned optimally, there is little to no gain to be made with a denser network. The optimization algorithm clearly identified that combinations of two or three stations can result in better hydrological performance than if a high-density network was fed to the model. Thus, the major conclusion of this study is that if weather stations are positioned at optimal locations, a very few number of them are required to model runoff with as good as or better performance than when a high-density network is used.

scholarly journals ESTIMATING CONTRIBUTION OF WATER FLOW COMPONENTS TO KAMENG RIVER BASIN USING HYDROLOGICAL MODELLING

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 431-436
Author(s):  
S. Arora ◽  
A. V. Kulkarni ◽  
P. Ghosh ◽  
S. K. Satheesh
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Water Resource Management ◽  
Hydrological Cycle ◽  
Meteorological Data ◽  
Clean Energy ◽  
Coefficient Of Determination ◽  
Melt Water ◽  
Resilient Infrastructure ◽  
Discharge Profile

Abstract. The Himalayas, also known as third pole of the Earth feed some of the major rivers of the world viz. Ganga, Indus, Brahmaputra etc. The accurate assessment of water resources in eastern Himalayas is very important for respective policy makers. The detailed assessment of water resources and hydrological cycle component are very critical for attaining United Nations sustainable development goals (SDGs) such as affordable and clean energy, clean water and sanitation and building resilient infrastructure This study focuses on Kameng river basin, estimating the melt water & its contribution to the total discharge of the river. A 3-layer VIC model coupled with energy balance algorithm is used to estimate the patterns of melt and discharge profile in the region. Net contribution of melt water to the river were estimated to be about 18% during peak melt season in upper catchments. With advancement in technology, acquiring meteorological data via remote sensing has become more accurate & of high resolution. This data is one of the major inputs of the model. With accurate forecasting of these parameters, multipurpose hydropower projects in these regions can plan well in advance thus playing a major role in Integrated Water Resource Management. In current study the coefficient of determination & Nash-Sutcliffe efficiency were calculated to be 0.82 & 0.71 respectively. With increasing population in the region, any substantial change in the streamflow will have consequences unknown as of now, thus making this study a necessity & need of hour.

scholarly journals The spatiotemporal characteristics of the distribution of radiation frosts over the territory of the North-West region of Russia

2018 ◽  
Vol 3 ◽  
pp. 36-41
Author(s):  
Kononenko O.V.
Keyword(s):  
Crop Production ◽  
Limiting Factor ◽  
Leningrad Region ◽  
Agricultural Crop ◽  
Weather Station ◽  
North West ◽  
The North ◽  
West Region ◽  
Pskov Region ◽  
Weather Stations

To plan agrotechnical measures in changing climate it is necessary to track the dynamics of spatial and temporal changes in agrometeorological factors. Late spring and early autumn frosts are a limiting factor for agricultural crop production. In general, such frosts are of the radiation type. To study the spatial and temporal characteristics of the radiation frosts distribution in the North-West region of Russia, data of daily observations of the standard meteorological network from 1966 to 2015 were used. The change over the time in the average number of days with radiation frosts was calculated for two 25-year periods: from 1966 to 1990 and from 1991 to 2015. Two zones of multidirectional change of the average number of days with radiation frosts in the period from 1991 to 2015 were revealed. The decrease in the average number of days with radiation frosts during this period was recorded at the weather stations of Vologda and Leningrad (except for the weather station Belogorka) and the meteorological station Velikie Luky (Pskov region). At the same time all the weather stations of this zone (with the exception of the Vyborg weather station) are characterized by the higher number of days with radiation frosts then the weather station of the other zone. The increase in the average number of days with radiation frosts during this period was noted at the weather stations of the Pskov, Novgorod, Kaliningrad regions and the weather station Belogorka (Leningrad region).

scholarly journals Future irrigation water requirements in the Ijuí River basin, RS

2018 ◽  
Vol 22 (1) ◽  
pp. 57-62
Author(s):  
Kayoma K. da Silva ◽  
Tirzah M. Siqueira ◽  
Katiucia N. Adam ◽  
Andréa S. Castro ◽  
Luciara B. Corrêa ◽  
...  
Keyword(s):  
River Basin ◽  
Irrigation Water ◽  
Water Demand ◽  
Climate Model ◽  
Meteorological Data ◽  
Regional Climate ◽  
Baseline Period ◽  
Water Requirements ◽  
Temperature And Precipitation ◽  
Water Demands

ABSTRACT Changes in temperature and precipitation intensity and frequency have influenced the water demand for irrigation. Regions that have agriculture-based economies, as in the Ijuí River basin, are often affected by periods of drought or excessive rainfall, which is harmful for agricultural productivity. This study aimed to evaluate future irrigation water demands of four crops in this basin (bean, corn, wheat and soybean), comparing them with a baseline period. Meteorological data forecasts were obtained from the regional climate model ETA 40 CTRL for the climatic scenario A1B, for the baseline (1961-1990) and future (2011-2100) periods. The one-dimensional SWAP model was used to estimate the water demand for irrigation. The results showed that, in the future, irrigation water requirements will be smaller for all crops. In the short term (2011-2040), water demands were similar to those for the baseline period, but from the middle of the century onwards (2041-2100), greater reductions were observed.

scholarly journals The Use of Reanalyses and Gridded Observations as Weather Input Data for a Hydrological Model: Comparison of Performances of Simulated River Flows Based on the Density of Weather Stations

2017 ◽  
Vol 18 (2) ◽  
pp. 497-513 ◽  
Author(s):  
Gilles R. C. Essou ◽  
François Brissette ◽  
Philippe Lucas-Picher
Keyword(s):  
Hydrological Modeling ◽  
Strong Impact ◽  
Weather Station ◽  
River Flows ◽  
Mountainous Regions ◽  
Rough Approximation ◽  
Weather Stations ◽  
Precipitation And Temperature ◽  
Station Density ◽  
Better Than

Abstract Precipitation forcing is critical for hydrological modeling as it has a strong impact on the accuracy of simulated river flows. In general, precipitation data used in hydrological modeling are provided by weather stations. However, in regions with sparse weather station coverage, the spatial interpolation of the individual weather stations provides a rough approximation of the real precipitation fields. In such regions, precipitation from interpolated weather stations is generally considered unreliable for hydrological modeling. Precipitation estimates from reanalyses could represent an interesting alternative in regions where the weather station density is low. This article compares the performances of river flows simulated by a watershed model using precipitation and temperature estimates from reanalyses and gridded observations. The comparison was carried out based on the density of surface weather stations for 316 Canadian watersheds located in three climatic regions. Three state-of-the-art atmospheric reanalyses—ERA-Interim, CFSR, and MERRA—and one gridded observations database over Canada—Natural Resources Canada (NRCan)—were used. Results showed that the Nash–Sutcliffe values of simulated river flows using precipitation and temperature data from CFSR and NRCan were generally equivalent regardless of the weather station density. ERA-Interim and MERRA performed significantly better than NRCan for watersheds with weather station densities of less than 1 station per 1000 km2 in the mountainous region. Overall, these results indicate that for hydrological modeling in regions with high spatial variability of precipitation such as mountainous regions, reanalyses perform better than gridded observations when the weather station density is low.

scholarly journals Analyzing the impacts of climate and land use changes on the water quality in the 3S river basin

2019 ◽  
Vol 2 (2) ◽  
pp. 125-131
Author(s):  
Loi Thi Pham ◽  
Khoi Nguyen Dao
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Land Use ◽  
Water Resources ◽  
Land Use Change ◽  
River Basin ◽  
Water Resource Management ◽  
Hydrological Modeling ◽  
Swat Model ◽  
The Impact

Assessing water resources under the influence of environmental change have gained attentions of scientists. The objective of this study was to analyze the impacts of land use change and climate change on water resources in terms quantity and quality in the 3S basin in the period 1981–2008 by using hydrological modeling (SWAT model). The results showed that streamflow and water quality (TSS, T-N, and T-P) tend to increase under individual and combined effects of climate change and land use change. In addition, the impact of land use change on the flow was smaller than the climate change impact. However, water balance components and water quality were equally affected by two factors of climate change and land use change. In general, the results of this study could serve as a reference for water resource management and planning in the river basin.

scholarly journals Bias correction techniques for meteorological data of A2 scenario climate model output in Chao Phraya River Basin of Thailand

2014 ◽  
Vol 8 (1) ◽  
pp. 71-76 ◽  
Author(s):  
Somchai Baimoung ◽  
Taikan Oki ◽  
Boonlert Archevarahuprok ◽  
Aphantree Yuttaphan ◽  
Manoon Pangpom
Keyword(s):  
River Basin ◽  
Bias Correction ◽  
Climate Model ◽  
Meteorological Data ◽  
Model Output ◽  
Climate Model Output ◽  
Chao Phraya River

scholarly journals Water supply failure probability under influence of climate change—Balsillas river basin case study

2020 ◽  
Author(s):  
Darwin Mena Rentería ◽  
Eydy Michell Espinosa ◽  
Paula Carolina Soler ◽  
Miguel Cañón Ramos ◽  
Freddy Santiago Duarte ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Supply ◽  
Water Resource Management ◽  
Agricultural Sector ◽  
Hydrological Modeling ◽  
Climate Model ◽  
Global Climate Model ◽  
Climate Change Scenarios ◽  
Modeling Tools ◽  
Basin Scale

This project assesses the risk of water supply failure for the agricultural sector under climate change conditions by implementing hydrological models that support decision-making for satisfying consumptive demands in times of scarcity. This project was developed using hydrological modeling tools such as the HydroBID software and the SIMGES and SIMRISK water resource management models of AQUATOOL DSS. The flow series for a current scenario were obtained for different climate change scenarios from a Global Climate Model (GCM) and the Coordinated Regional Experiment on Climate Reduction (CORDEX) by downscaling the results from the global scale to basin-scale using a statistical method based on chaos theory. These projections show that under conditions of climate change, the agricultural sector of the Balsillas basin will not suffer significant impacts since they will be able to satisfy most demand points.

scholarly journals The China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) Application in China: A Case Study in Heihe River Basin

2017 ◽  
Author(s):  
Xian-yong Meng ◽  
Hao Wang ◽  
Si-yu Cai ◽  
Xue-song Zhang ◽  
Guo-yong Leng ◽  
...  
Keyword(s):  
River Basin ◽  
Large Scale ◽  
Hydrologic Modeling ◽  
Hydrological Modeling ◽  
Assessment Tool ◽  
Swat Model ◽  
Heihe River Basin ◽  
Heihe River ◽  
Climate Data ◽  
Weather Stations

Large-scale hydrological modeling in China is challenging given the sparse meteorological stations and large uncertainties associated with atmospheric forcing data.Here we introduce the development and use of the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) in the Heihe River Basin(HRB) for improving hydrologic modeling, by leveraging the datasets from the China Meteorological Administration Land Data Assimilation System (CLDAS)(including climate data from nearly 40000 area encryption stations, 2700 national automatic weather stations, FengYun (FY) 2 satellite and radar stations). CMADS uses the Space Time Multiscale Analysis System (STMAS) to fuse data based on ECWMF ambient field and ensure data accuracy. In addition, compared with CLDAS, CMADS includes relative humidity and climate data of varied resolutions to drive hydrological models such as the Soil and Water Assessment Tool (SWAT) model. Here, we compared climate data from CMADS, Climate Forecast System Reanalysis (CFSR) and traditional weather station (TWS) climate forcing data and evaluatedtheir applicability for driving large scale hydrologic modeling with SWAT. In general, CMADS has higher accuracy than CFRS when evaluated against observations at TWS; CMADS also provides spatially continuous climate field to drive distributed hydrologic models, which is an important advantage over TWS climate data, particular in regions with sparse weather stations. Therefore, SWAT model simulations driven with CMADS and TWS achieved similar performances in terms of monthly and daily stream flow simulations, and both of them outperformed CFRS. For example, for the three hydrological stations (Ying Luoxia, Qilian Mountain, and ZhaMasheke) in the HRB at the monthly and daily Nash-Sutcliffe efficiency ranges of 0.75-0.95 and 0.58-0.78, respectively, which are much higher than corresponding efficiency statistics achieved with CFSR (monthly: 0.32-0.49 and daily: 0.26 – 0.45). The CMADS dataset is available free of charge and is expected to a valuable addition to the existing climate reanalysis datasets for deriving distributed hydrologic modeling in China and other countries in East Asia.

scholarly journals Assessing urban climate model results with crowd-sourced data

2021 ◽  
Author(s):  
Claudia Hahn ◽  
Sandro Oswald ◽  
Brigitta Hollosi ◽  
Robert Goler ◽  
Astrid Kainz ◽  
...  
Keyword(s):  
City Planning ◽  
Climate Models ◽  
Climate Model ◽  
Scale Effects ◽  
Urban Climate ◽  
Monitoring Network ◽  
Climate Change Impacts ◽  
Weather Station ◽  
Weather Stations ◽  
Good Agreement

<p>Climate change impacts are amplified in cities due to the urban heat island effect and the high population density. Information about the intra-urban temperature patterns is therefore crucial to support resilient city planning. Within the ACRP funded project LUCRETIA, the intra-urban temperature patterns in Vienna, Austria, are investigated using urban climate models (MUKLIMO_3, PALM-4U) and data from citizen weather stations.</p><p>While the density of conventional weather station networks is usually too low to capture the temperature patterns in cities and to assess urban climate model results, citizen weather stations provide a dense monitoring network, especially in cities. In Vienna, more than 1000 citizen weather stations from the company Netatmo are available for our study period in August 2018, after the quality control. First investigations showed, that air temperature measurements from citizen weather stations are in good agreement with measurements from conventional stations. The observed differences are attributed to the different locations of the stations and micro-scale effects. A preliminary comparison of citizen weather station data with urban climate model results from MUKLIMO_3 for Vienna revealed for some of the stations similar patterns as the comparison between conventional stations and model results: a reasonably good agreement during the day, after model initialization, and a temperature overestimation at night. Within LUCRETIA we are assessing in more detail the model results (MUKLIMO_3, PALM-4U) for a three day period in August 2018, thereby looking at the effect of the different land-use classes within the city. In addition, we will investigate whether similar spatial temperature patterns are identified when using urban climate models and data from citizen weather stations.</p>

scholarly journals Application and Flood Discharge Analysis with Hydrological Model (WEB-DHM) in Bago River Basin

2020 ◽  
Vol 15 (3) ◽  
pp. 344-352
Author(s):  
Sann Win Maung ◽  
Zin Mar Lar Tin San ◽  
Win Win Zin ◽  
Akiyuki Kawasaki ◽  
Kyu Kyu Thin ◽  
...  
Keyword(s):  
River Basin ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Monsoon Season ◽  
Meteorological Data ◽  
Historical Record ◽  
Japan Meteorological Agency ◽  
Distributed Hydrological Model ◽  
Flood Discharge ◽  
Storm Rainfall

Flooding has always been one of the major hazards in Myanmar, accounting for 11% of all disasters. The Bago River Basin is a floodprone area in Myanmar, where, during the last decade, many severe floods occurred during the monsoon season, usually in July and August. Most of these floods are caused by storm rainfall. The 2011 and 2018 floods form part of the historical record of Bago. The main objective of this research paper is to develop a new hydrological model (WEB-DHM) for the Bago River Basin using observed station data to represent floods in the study area. The Water and Energy Budget-based Distributed Hydrological Model (WEB-DHM) was used for hydrological modeling as determined for the discharge of floods. The HydroSHEDS digital elevation model is used for the discharge estimation and analysis of the WEB-DHM. The Japanese 55-year Reanalysis JRA-55 data, from the Japan Meteorological Agency (JMA), were used for the preparation of meteorological data for this model. The results of flood discharge from the hydrological modeling and the observed data of the past three years (2014, 2015 and 2016) are provided in this study.

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