Modeling riparian soil nitrogen removal based on a modified SWAT model coupled with remote sensing data

2009 ◽  
Author(s):  
Xuelei Wang ◽  
Shengtian Yang ◽  
Chris M. Mannaerts ◽  
Hongjuan Zeng ◽  
Donghai Zheng
Keyword(s):  
Remote Sensing ◽  
Nitrogen Removal ◽  
Soil Nitrogen ◽  
Swat Model ◽  
Remote Sensing Data ◽  
Sensing Data

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 Relationship between Remote Sensing Data, Plant Biomass and Soil Nitrogen Dynamics in Intensively Managed Grasslands under Controlled Conditions

Sensors ◽  
2017 ◽  
Vol 17 (7) ◽  
pp. 1483 ◽  
Author(s):  
Christoph Knoblauch ◽  
Conor Watson ◽  
Clara Berendonk ◽  
Rolf Becker ◽  
Nicole Wrage-Mönnig ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Nitrogen ◽  
Plant Biomass ◽  
Remote Sensing Data ◽  
Nitrogen Dynamics ◽  
Sensing Data ◽  
Soil Nitrogen Dynamics ◽  
Controlled Conditions ◽  
Intensively Managed

Representation of crop phenology and associated management practices in the SWAT+ model using global datasets for large scale hydrological applications

2021 ◽  
Author(s):  
Albert Nkwasa ◽  
Celray James Chawanda ◽  
Ann van Griensven ◽  
Jonas Jägermeyr
Keyword(s):  
Remote Sensing ◽  
Management Practices ◽  
Swat Model ◽  
Remote Sensing Data ◽  
Hydrological Models ◽  
Multiple Cropping ◽  
Crop Phenology ◽  
Sensing Data ◽  
Cropping Seasons ◽  
Global Datasets

<p>Even though cropland cultivation covers over 40% of the planet’s ice free land surface, most regional and global hydrological models either ignore the representation of cropland or consider crop cultivation in a simplistic way or in abstract terms without any management practices. Yet, the water balance of cultivated areas is strongly influenced by applied management practices (e.g. planting, irrigation, fertilization, harvesting). For instance, the SWAT+ model represents agricultural land by default in a generic way where the timing of the cropping season is driven by accumulated heat units. However, this approach does not work for tropical and sub-tropical regions such as the sub-Saharan Africa where crop growth dynamics are mainly controlled by rainfall rather than temperature.</p><p>In this study, we present an approach on how to reasonably incorporate crop phenology using decision tables and global datasets of rainfed and irrigated croplands with the associated cropping calendar and fertilizer applications in a SWAT+ model for North Eastern Africa. We evaluate the influence of the crop phenology representation on simulations of Leaf Area Index (LAI) and Evapotranspiration (ET) using LAI remote sensing data derived from Proba-V satellite and WaPOR ET data respectively. Results show that a representation of crop phenology using global datasets leads to improved temporal patterns of LAI and ET simulations especially for regions with a single cropping cycle.  However, for regions with multiple cropping seasons, global phenology datasets need to be complemented with local data or remote sensing data to capture additional cropping seasons. We conclude that regional and global hydrological models can benefit from improved representations of crop phenology and the associated management practices. Future work regarding the incorporation of multiple cropping seasons in global phenology data is needed to better represent cropping cycles in global hydrological models.</p>

Assessment of the national market demand for high-resolution remote sensing data

2002 ◽  
Vol 8 (1) ◽  
pp. 15-22
Author(s):  
V.N. Astapenko ◽  
◽  
Ye.I. Bushuev ◽  
V.P. Zubko ◽  
V.I. Ivanov ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Remote Sensing Data ◽  
Market Demand ◽  
Sensing Data ◽  
National Market

A procedure for integrated assessment of landscape fire risk using remote sensing data

2011 ◽  
Vol 17 (6) ◽  
pp. 30-44
Author(s):  
Yu.V. Kostyuchenko ◽  
◽  
M.V. Yushchenko ◽  
I.M. Kopachevskyi ◽  
S. Levynsky ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Integrated Assessment ◽  
Remote Sensing Data ◽  
Fire Risk ◽  
Sensing Data
Sign in / Sign up

Export Citation Format

Share Document