scholarly journals Assessment of soil erosion using two spatial approaches: RUSLE and SWAT Model

2021 ◽  
Vol 234 ◽  
pp. 00082
Author(s):  
Soufiane Taia ◽  
Lamia Erraioui ◽  
Noella Claire Mbrenga ◽  
Jamal Chao ◽  
Bouabid El Mansouri ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Degradation ◽  
Swat Model ◽  
Remote Sensing Data ◽  
Climatic Data ◽  
Scale Analysis ◽  
Gis Tools ◽  
Major Factors ◽  
Specific Degradation ◽  
Priority Action

In this paper, we attempted to review the erosion in the Ouergha watershed by applying two spatial approaches. The Ouergha watershed has an area of around 7300 km² representing approximately 18.2% of the Sebou basin of which it is the main tributary. In order to develop the erosion map using the SWAT model, it was important to prepare a large spatial database describing basin proprieties, furthermore, the daily hydro-climatic data. This model integrates MUSLE equation for the estimation of specific degradation. In addition, the estimation of erosion through SWAT was consolidated by constructing an erosion mapping through RUSLE method. This method was applied following an approach based on the use of remote sensing data and GIS tools to produce the major factors involved in the erosive process and their integration into RUSLE. The results obtained, in cartographic form, make it possible to target areas that require priority action for a larger-scale analysis, with a view to finding appropriate solutions to fight against erosion and protect the natural environment. Soil degradation in the Ouergha watershed is around 27 ton/ha/year (SWAT_MUSLE) and 25 ton/ha/year (RUSLE). Average sediment yield was estimated for Al Wahda dam of 10.4 Million tons.

scholarly journals Evaluation Des Risques D’érosion Hydrique Et Cartographie Des Zones Vulnérables Par La Méthode RUSLE Couplée Aux SIG Et À La Télédétection Dans Le Bassin Versant d’Agoudal En Amont De La Vallée d’Imilchil (Haut Atlas Central, Maroc)

2021 ◽  
Vol 17 (21) ◽  
pp. 66
Author(s):  
Youssef ◽  
El-Arbi Ait Yacine ◽  
Brahim Benzougagh ◽  
Laila Nassiri ◽  
Jamal Ibijbijen
Keyword(s):  
Remote Sensing ◽  
Arable Land ◽  
Ecological Factors ◽  
Remote Sensing Data ◽  
Water Erosion ◽  
Climatic Data ◽  
Degradation Rates ◽  
Systèmes D’Information ◽  
Specific Degradation ◽  
Bassin Versant

Le sous-bassin versant (SBV) d’Agoudal est la partie amont de la vallée d’Imilchil relevant de la province de Midelt et la région de Draa-Tafilalet au Sud-Est du Maroc. Il s’étale sur la tranche altitudinale asylvatique du Haut Atlas central, allant de 2400 à plus de 3150 m. Ce sont des écosystèmes fragiles dont les sols sont peu arables et peu protégés, à haut risques d’érosion. Ils sont dans un stade très avancé de dégradation, sous l’effet de l’action de l’Homme, des facteurs écologiques, aggravés par les changements climatiques. L’objectif principal de cette recherche est d’évaluer le degré de sensibilité de la zone d’étude vis-à-vis de l’érosion hydrique et de cartographier les zones vulnérables prioritaires pour d’éventuelles interventions d’atténuation. La méthode utilisée s’est basée sur l’Équation Universelle Révisée des Pertes en sols (RUSLE) en intégrant les différents facteurs causaux de ladite équation dans le Systèmes d’Information Géographique (SIG) et en se servant des données officielles (cartes géologiques et topographiques de la zone d’études, données climatiques, les études sur l’érosion réalisées par les départements étatiques concernés) et la télédétection, validées par les réalités de terrain. Les résultats dégagés montrent que la quasi-totalité de ce bassin est soumis à une forte dégradation des sols ; en effet près de 66% de la superficie de la zone d’étude est couverte par les classes de dégradation spécifique de 50 à 400 t/ha/an et 18.9% affiche des taux faibles à moyens allant de 7,4 à 32,17 t/ha/an. Seulement 1,4% du SVB est soumise à des taux de dégradation spécifique inférieurs à 7,4 t/ha/an. La valeur moyenne du taux d’érosion est de 255t/h/an, avec un écart type de près 285 t/an/ha, dû l’hétérogénéité des caractéristiques du milieu et de ses conditions. Ces chiffres attestent que cette région est soumise aux hauts risques d’érosion. Ce phénomène ajouté aux inondations récurrentes, constituent la principale menace qui met en péril l’agriculture vivrière de cette zone, ce qui donne le signal d’alarme pour intervention de mitigation urgente. The Agoudal sub-basin is the upstream part of the Assif Melloul watershed in the Imilchil valley belonging to the province of Midelt and the region of Draa-Tafilalet in south-eastern Morocco. It is located on the Asylvatic altitudinal slice of the Central High Atlas, ranging from 2400 to more than 3150 m. These are fragile ecosystems with poor arable land that are poorly protected, with a high risk of erosion. They are in fact in their advanced stage of degradation due to human activities and ecological factors aggravated by climate change. This paper focuses on assessing the degree of sensitivity of this area to water erosion, and it aims to map priority vulnerable areas for any future mitigation intervention. The method was based on the Revised Universal Soil Loss Equation (RUSLE) by integrating the causal factors of this equation in Geographic Information Systems (GIS) and by using remote sensing data validated based on official data (geological maps and topography of the study area, climatic data, studies on erosion carried out by the state departments concerned) and remote sensing (validated by the realities on the ground). The results show that almost all the watershed is subject to severe soil degradation due to water erosion. In fact, nearly 66% of its area is covered by specific degradation classes of 50 to 400 t / ha / year, and 18.9% of the area displays low and medium erosion rates. Only 1.4% of the study area is subject to specific degradation rates less than 7.4 t / ha / year. The average erosion rate is 255 t / h / year, with a standard deviation of 285 t / year / ha, mainly due to the heterogeneity of the characteristics and its conditions. These figures show that this region is subject to high risks of erosion. This phenomenon, along with recurrent floods, constitutes the main threat that is endangering subsistence agriculture, which gives the alarm signal for urgent mitigation intervention.

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.

Groundwater potential zonation for basaltic watersheds using satellite remote sensing data and GIS techniques

2009 ◽  
Vol 1 (1) ◽  
Author(s):  
Biswajeet Pradhan
Keyword(s):  
Remote Sensing ◽  
Process Model ◽  
Remote Sensing Data ◽  
Groundwater Potential ◽  
Remotely Sensed Data ◽  
Drainage Pattern ◽  
Ancillary Data ◽  
Sensing Data ◽  
Gis Techniques ◽  
Gis Tools

AbstractThis paper summarizes the findings of groundwater potential zonation mapping at the Bharangi River basin, Thane district, Maharastra, India, using Satty’s Analytical Hierarchal Process model with the aid of GIS tools and remote sensing data. To meet the objectives, remotely sensed data were used in extracting lineaments, faults and drainage pattern which influence the groundwater sources to the aquifer. The digitally processed satellite images were subsequently combined in a GIS with ancillary data such as topographical (slope, drainage), geological (litho types and lineaments), hydrogeomorphology and constructed into a spatial database using GIS and image processing tools. In this study, six thematic layers were used for groundwater potential analysis. Each thematic layer’s weight was determined, and groundwater potential indices were calculated using groundwater conditions. The present study has demonstrated the capabilities of remote sensing and GIS techniques in the demarcation of different groundwater potential zones for hard rock basaltic basin.

scholarly journals Evaluation of Soil Degradation Based on High Resolution Remote Sensing Data

2005 ◽  
pp. 145-148
Author(s):  
Péter Burai ◽  
János Tamás
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Soil Salinity ◽  
Strong Correlation ◽  
Soil Degradation ◽  
Vegetation Index ◽  
Near Infrared ◽  
Salt Content ◽  
Remote Sensing Data ◽  
Test Site

Soil salinity is the main problem of soil degradation in the Grate Plain with cultivated area of 20% affected. Its influence is accelerated on the water managed and irrigated lands. Remote sensing can significantly contribute to detecting temporal changes of salt-related surface features. We have chosen a farm where intensive crop cultivation takes place as a test site as soil degradation can be intensive as a result of land use and irrigation. In order to evaluate soil salt content and biomass analysis, we gathered detailed data from an 100x250 m area. We analyzed the salinity property of the samples. In our research we used a TETRACAM ADC multispectral camera to take high resolution images (0,2-0,5 m) of low altitude (300-500 m). A Normalized Vegetation Index was computed from near infrared (750-950 nm) and red (620-750 nm) bands. This data was compared with the samples of investigated area. Analyzing the images, we evaluated image reliability, and the connection between the bands and the soil properties (pH, salt content). A strong correlation observed between NDVI and soil salinity (EC) makes the multispectral images suitable for construction of salinity map. A further strong correlation was determined between NDVI and yield.

scholarly journals Use of Geoinformatics Techniques for the Assessment and Mapping of Soil Salinity: Concepts and Applications

2021 ◽  
Author(s):  
Olumuyiwa Idowu Ojo ◽  
Masengo Francois Ilunga
Keyword(s):  
Remote Sensing ◽  
Soil Salinity ◽  
Traditional Method ◽  
Soil Degradation ◽  
Remote Sensing Data ◽  
Field Work ◽  
Irrigated Agriculture ◽  
Salinity Data ◽  
Geoinformatics Techniques ◽  
Labour Time

Irrigated agriculture has a major impact on the environment, especially soil degradation. Soil salinity is a critical environmental problem, which has great impact on soil fertility and overall agricultural productivity. Since, soil salinity processes are highly dynamic, the methods of detecting soil salinity hazards should also be dynamic. Remote sensing data are modern tools that provide information on variation over time essential for environmental monitoring and change detection, as they also help in the reduction of conventional time-consuming and expensive field sampling methods, which is the traditional method of monitoring and assessment. This chapter thus reviewed the concepts and applications of remote sensing, GIS-assisted spatial analysis and modelling of the salinity issue in irrigation fields. Generally, compared to the labour, time and money invested in field work devoted to collecting soil salinity data and analysis, the availability and ease of acquiring satellite imagery data and analysis made this concept very attractive and efficient.

scholarly journals Derivation of Spatially Distributed Thermal Comfort Levels in Jordan as Investigated From Remote Sensing, GIS Tools and Computational Methods

2021 ◽  
Author(s):  
ibrahim M. oroud
Keyword(s):  
Remote Sensing ◽  
Thermal Comfort ◽  
Remote Sensing Data ◽  
Dead Sea ◽  
Discrete Point ◽  
Jordan Valley ◽  
Comfort Levels ◽  
Gis Tools ◽  
Wide Range ◽  
Elevation Data

Abstract Thermal comfort is usually calculated using discrete point measurements. This procedure is not suitable to study thermal comfort for inhabited areas with rugged terrains where climate gradient is high. The wide availability of remote sensing data and GIS tools have revolutionized data management, processing and visualization. The present paper implemented digital elevation data, GIS tools and a computational algorithm to generate spatially continuous maps of climatological elements which were employed to derive thermal comfort levels across Jordan. Results show detailed information of the spatial distribution of the degree of thermal comfort in winter and summer across the country which cannot be resolved using discrete point measurements. It is shown that the mountainous areas in the country, where most urban centers are situated, experience “slightly warm” to “warm” indoor apparent temperatures in summer. The Jordan Valley and the desert experience high indoor apparent temperatures in summer. Cold conditions prevail over most parts of the country, with the heating degree days ranging from 2100 in the southern mountains to values close to zero near the Dead Sea area. The presented procedure demonstrated that the very low levels of ambient vapor pressure is an important atmospheric forcing contributing to the widespread cold conditions prevailing over the desert areas in winter. The efficiency of direct evaporative cooling systems to achieve thermal comfort in the various parts of the country is investigated. The procedure presented can be used over regional scales with different levels of spatial resolutions for a wide range of climatological studies.

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>

scholarly journals An Evaluation of Satellite Remote Sensing Data Products for Land Surface Hydrology: Atmospheric Infrared Sounder*

2010 ◽  
Vol 11 (6) ◽  
pp. 1234-1262 ◽  
Author(s):  
Craig R. Ferguson ◽  
Eric F. Wood
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Specific Humidity ◽  
Retrieval Algorithm ◽  
Climatic Data ◽  
Atmospheric Infrared Sounder ◽  
Retrieval Models ◽  
Near Surface

Abstract The skill of instantaneous Atmospheric Infrared Sounder (AIRS) retrieved near-surface meteorology, including surface skin temperature (Ts), air temperature (Ta), specific humidity (q), and relative humidity (RH), as well as model-derived surface pressure (Psurf) and 10-m wind speed (w), is evaluated using collocated National Climatic Data Center (NCDC) in situ observations, offline data from the North American Land Data Assimilation System (NLDAS), and geostationary remote sensing (RS) data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI). Such data are needed for RS-based water cycle monitoring in areas without readily available in situ data. The study is conducted over the continental United States and Africa for a period of more than 6 years (2002–08). For both regions, it provides for the first time the geographic distribution of AIRS retrieval performance. Through conditional sampling, attribution of retrieval errors to scene atmospheric and surface conditions is performed. The findings support previous assertions that performance degrades with cloud fraction and that (positive) bias enhances with altitude. In general AIRS is biased warm and dry. In certain regions, strong AIRS–NCDC correlation suggests that bias-driven errors, which can be substantial, are correctable. The utility of the error characteristics for prescribing the input-induced uncertainty of RS retrieval models is demonstrated through two applications: a microwave soil moisture retrieval algorithm and the Penman–Monteith evapotranspiration model. An important side benefit of this study is the verification of NLDAS forcing.

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