scholarly journals Retraction notice to “Hydrological modeling using SWAT model and geoinformatic techniques” [Egypt. J. Remote Sensing Space Sci. 17 (2) (2014) 197–207]

2015 ◽  
Vol 18 (2) ◽  
pp. 311
Author(s):  
S.S. Panhalkar
Keyword(s):  
Remote Sensing ◽  
Hydrological Modeling ◽  
Swat Model ◽  
Retraction Notice

scholarly journals Hydrological modeling using the SWAT model based on two types of data from the watershed of Beni Haroun dam, Algeria

2019 ◽  
Vol 43 (1) ◽  
pp. 76-89 ◽  
Author(s):  
Zakaria Kateb ◽  
Hamid Bouchelkia ◽  
Abdelhalim Benmansour ◽  
Fadila Belarbi
Keyword(s):  
Remote Sensing ◽  
Hydrological Modeling ◽  
Assessment Tool ◽  
Hydrological Cycle ◽  
Swat Model ◽  
Soil Mapping ◽  
Digital Soil Mapping ◽  
Validation Period ◽  
Calibration Period ◽  
Water Assessment

AbstractThe dam of Beni Haroun is the largest in Algeria, and its transfer structures feed seven provinces (wilayas) in the eastern part of Algeria. Due to its importance in the region, it has now become urgent to study its watershed as well as all the parameters that can influence the water and solid intakes that come into the dam. The Soil and Water Assessment Tool (SWAT) model is used to quantify the water yields and identify the vulnerable spots using two scenarios. The first one uses worldwide data (GlobCover and HWSD), and the second one employs remote sensing and digital soil mapping in order to determine the most suitable data to obtain the best results. The SWAT model can be used to reproduce the hydrological cycle within the watershed. Concerning the first scenario, during the calibration period, R2 was found between 0.45 and 0.69, and the Nash–Sutcliffe efficiency (NSE) coefficient was within the interval from 0.63 to 0.80; in the validation period, R2 lied between 0.47 and 0.59, and the NSE coefficient ranged from 0.58 to 0.64. As for the second scenario, during the calibration period, R2 was between 0.60 and 0.66, and the NSE coefficient was between 0.55 and 0.75; however, during the validation period, R2 was in the interval from 0.56 to 0.70, and the NSE coefficient within the range 0.64–0.70. These findings indicate that the data obtained using remote sensing and digital soil mapping provide a better representation of the watershed and give a better hydrological modelling.

scholarly journals Hydrologic Responses to Land Use Change in the Loess Plateau: Case Study in the Upper Fenhe River Watershed

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Zhixiang Lu ◽  
Songbing Zou ◽  
Zuodong Qin ◽  
Yonggang Yang ◽  
Honglang Xiao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Loess Plateau ◽  
Hydrological Modeling ◽  
Swat Model ◽  
Water Yield ◽  
The Loess Plateau ◽  
River Watershed ◽  
Lulc Changes ◽  
Basin Scale

We applied an integrated approach to investigate the impacts of land use and land cover (LULC) changes on hydrology at different scales in the Loess Plateau of China. Hydrological modeling was conducted for the LULC maps from remote sensing images at two times in the Upper Fenhe River watershed using the SWAT model. The main LULC changes in this watershed from 1995 to 2010 were the transformation of farmland into forests, grassland, and built-up land. The simulation results showed that forested land contributed more than any other LULC class to water yield, but built-up land had most impact due to small initial loss and infiltration. At basin scale, a comparison of the simulated hydrological components of two LULC maps showed that there were slight increases in average annual potential evapotranspiration, actual evapotranspiration, and water yield, but soil water decreased, between the two intervals. In subbasins, obvious LULC changes did not have clear impacts on hydrology, and the impacts may be affected by precipitation conditions. By linking a hydrological model to remote sensing image analysis, our approach of quantifying the impacts of LULC changes on hydrology at different scales provide quantitative information for stakeholders in making decisions for land and water resource management.

scholarly journals Analysing the Impact of Climate Change on Hydrological Ecosystem Services in Laguna del Sauce (Uruguay) Using the SWAT Model and Remote Sensing Data

2021 ◽  
Vol 13 (10) ◽  
pp. 2014
Author(s):  
Celina Aznarez ◽  
Patricia Jimeno-Sáez ◽  
Adrián López-Ballesteros ◽  
Juan Pablo Pacheco ◽  
Javier Senent-Aparicio
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Ecosystem Services ◽  
Water Resources ◽  
Swat Model ◽  
Remote Sensing Data ◽  
Erosion Control ◽  
Sensing Data ◽  
Extreme Precipitation Events ◽  
The Impact

Assessing how climate change will affect hydrological ecosystem services (HES) provision is necessary for long-term planning and requires local comprehensive climate information. In this study, we used SWAT to evaluate the impacts on four HES, natural hazard protection, erosion control regulation and water supply and flow regulation for the Laguna del Sauce catchment in Uruguay. We used downscaled CMIP-5 global climate models for Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 projections. We calibrated and validated our SWAT model for the periods 2005–2009 and 2010–2013 based on remote sensed ET data. Monthly NSE and R2 values for calibration and validation were 0.74, 0.64 and 0.79, 0.84, respectively. Our results suggest that climate change will likely negatively affect the water resources of the Laguna del Sauce catchment, especially in the RCP 8.5 scenario. In all RCP scenarios, the catchment is likely to experience a wetting trend, higher temperatures, seasonality shifts and an increase in extreme precipitation events, particularly in frequency and magnitude. This will likely affect water quality provision through runoff and sediment yield inputs, reducing the erosion control HES and likely aggravating eutrophication. Although the amount of water will increase, changes to the hydrological cycle might jeopardize the stability of freshwater supplies and HES on which many people in the south-eastern region of Uruguay depend. Despite streamflow monitoring capacities need to be enhanced to reduce the uncertainty of model results, our findings provide valuable insights for water resources planning in the study area. Hence, water management and monitoring capacities need to be enhanced to reduce the potential negative climate change impacts on HES. The methodological approach presented here, based on satellite ET data can be replicated and adapted to any other place in the world since we employed open-access software and remote sensing data for all the phases of hydrological modelling and HES provision assessment.

scholarly journals Extensive Evaluation of a Continental-Scale High-Resolution Hydrological Model Using Remote Sensing and Ground-Based Observations

2021 ◽  
Vol 13 (7) ◽  
pp. 1247
Author(s):  
Bowen Zhu ◽  
Xianhong Xie ◽  
Chuiyu Lu ◽  
Tianjie Lei ◽  
Yibing Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Hydrological Modeling ◽  
Infiltration Capacity ◽  
Modeling Framework ◽  
Large Domain ◽  
Continental Scale ◽  
Extensive Evaluation ◽  
Mean Differences ◽  
Fine Resolution

Extreme hydrologic events are getting more frequent under a changing climate, and a reliable hydrological modeling framework is important to understand their mechanism. However, existing hydrological modeling frameworks are mostly constrained to a relatively coarse resolution, unrealistic input information, and insufficient evaluations, especially for the large domain, and they are, therefore, unable to address and reconstruct many of the water-related issues (e.g., flooding and drought). In this study, a 0.0625-degree (~6 km) resolution variable infiltration capacity (VIC) model developed for China from 1970 to 2016 was extensively evaluated against remote sensing and ground-based observations. A unique feature in this modeling framework is the incorporation of new remotely sensed vegetation and soil parameter dataset. To our knowledge, this constitutes the first application of VIC with such a long-term and fine resolution over a large domain, and more importantly, with a holistic system-evaluation leveraging the best available earth data. The evaluations using in-situ observations of streamflow, evapotranspiration (ET), and soil moisture (SM) indicate a great improvement. The simulations are also consistent with satellite remote sensing products of ET and SM, because the mean differences between the VIC ET and the remote sensing ET range from −2 to 2 mm/day, and the differences for SM of the top thin layer range from −2 to 3 mm. Therefore, this continental-scale hydrological modeling framework is reliable and accurate, which can be used for various applications including extreme hydrological event detections.

scholarly journals A Review of SWAT Model Application in Africa

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1313
Author(s):  
George Akoko ◽  
Tu Hoang Le ◽  
Takashi Gomi ◽  
Tasuku Kato
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Water Resources ◽  
Hydrological Modeling ◽  
Assessment Tool ◽  
Swat Model ◽  
Data Availability ◽  
Mitigation Measures ◽  
Model Parameterization ◽  
Basin Scale

The soil and water assessment tool (SWAT) is a well-known hydrological modeling tool that has been applied in various hydrologic and environmental simulations. A total of 206 studies over a 15-year period (2005–2019) were identified from various peer-reviewed scientific journals listed on the SWAT website database, which is supported by the Centre for Agricultural and Rural Development (CARD). These studies were categorized into five areas, namely applications considering: water resources and streamflow, erosion and sedimentation, land-use management and agricultural-related contexts, climate-change contexts, and model parameterization and dataset inputs. Water resources studies were applied to understand hydrological processes and responses in various river basins. Land-use and agriculture-related context studies mainly analyzed impacts and mitigation measures on the environment and provided insights into better environmental management. Erosion and sedimentation studies using the SWAT model were done to quantify sediment yield and evaluate soil conservation measures. Climate-change context studies mainly demonstrated streamflow sensitivity to weather changes. The model parameterization studies highlighted parameter selection in streamflow analysis, model improvements, and basin scale calibrations. Dataset inputs mainly compared simulations with rain-gauge and global rainfall data sources. The challenges and advantages of the SWAT model’s applications, which range from data availability and prediction uncertainties to the model’s capability in various applications, are highlighted. Discussions on considerations for future simulations such as data sharing, and potential for better future analysis are also highlighted. Increased efforts in local data availability and a multidimensional approach in future simulations are recommended.

scholarly journals Evapotranspiration from Remote Sensing to Improve the Swat Model in Eastern Amazonia

2015 ◽  
Vol 22 (4) ◽  
pp. 456-464 ◽  
Author(s):  
Adriano Marlison Leão de Sousa ◽  
Maria Isabel Vitorino ◽  
Nilza Maria dos Reis Castro ◽  
Marcel do Nascimento Botelho ◽  
Paulo Jorge Oliveira Ponte de Souza
Keyword(s):  
Hydrological Modeling ◽  
Swat Model ◽  
Assessment Tools ◽  
Flow Data ◽  
Remote Sensors ◽  
Araguaia River ◽  
Moderate Resolution ◽  
Model Adjustment ◽  
Daily Scale ◽  
Moderate Resolution Imaging Spectroradiometer

ABSTRACT In this study, we estimated the evapotranspiration from orbital images - MODIS (Moderate Resolution Imaging Spectroradiometer) for assimilation in the hydrological modeling of the SWAT (Soil Water Assessment Tools) model. The data used include the period between October 2003 and December 2006 of the sub-basin of the Lajeado River, located in the Tocantins-Araguaia River basin in Tocantins state. Overall, the results of the use of heat flows estimated by remote sensors in the SWAT model can be considered satisfactory. The values of the COE (coefficient of efficiency of Nash-Sutcliffe) ranged from -0.40 to 0.91 in the comparison with the daily flow data and from 0.17 to 0.77 with the monthly flow data, with the assimilation of evapotranspiration from orbital images. These results indicate benefit to the model adjustment due to improvement in the data assimilated of approximately 0.91 in the COE on daily scale and 0.60 in the CEO on monthly scale.

scholarly journals Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data

2015 ◽  
Vol 19 (1) ◽  
pp. 507-532 ◽  
Author(s):  
P. Karimi ◽  
W. G. M. Bastiaanssen
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Water Resource Management ◽  
Hydrological Modeling ◽  
Remote Sensing Data ◽  
Actual Evapotranspiration ◽  
Primary Concern ◽  
Suitable Alternative ◽  
Sensing Data ◽  
Water Accounting

Abstract. The scarcity of water encourages scientists to develop new analytical tools to enhance water resource management. Water accounting and distributed hydrological models are examples of such tools. Water accounting needs accurate input data for adequate descriptions of water distribution and water depletion in river basins. Ground-based observatories are decreasing, and not generally accessible. Remote sensing data is a suitable alternative to measure the required input variables. This paper reviews the reliability of remote sensing algorithms to accurately determine the spatial distribution of actual evapotranspiration, rainfall and land use. For our validation we used only those papers that covered study periods of seasonal to annual cycles because the accumulated water balance is the primary concern. Review papers covering shorter periods only (days, weeks) were not included in our review. Our review shows that by using remote sensing, the absolute values of evapotranspiration can be estimated with an overall accuracy of 95% (SD 5%) and rainfall with an overall absolute accuracy of 82% (SD 15%). Land use can be identified with an overall accuracy of 85% (SD 7%). Hence, more scientific work is needed to improve the spatial mapping of rainfall and land use using multiple space-borne sensors. While not always perfect at all spatial and temporal scales, seasonally accumulated actual evapotranspiration maps can be used with confidence in water accounting and hydrological modeling.

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