scholarly journals An Integrated Hydrogeological and Remote Sensing Modeling Approach to Evaluate the Climate Change and Over-Irrigation Impact on Groundwater Depletion in North Jordan

2021 ◽  
Vol 54 (2B) ◽  
pp. 12-27
Author(s):  
Marwan Al-Raggad
Keyword(s):  
Remote Sensing ◽  
Agricultural Practices ◽  
Groundwater Depletion ◽  
Crop Water ◽  
Groundwater Abstraction ◽  
Water Requirements ◽  
Groundwater Levels ◽  
Multi Method Approach ◽  
Method Approach ◽  
Groundwater Wells

Groundwater is an essential source of freshwater for the severely water-deprived country of Jordan. Thus, understanding abstracted amounts of the ground water is essential for sustaining this resource. More than 50% of the annual abstracted groundwater is used for irrigation, indicating the need to correctly estimate this usage and minimize the uncertainties. Thus, this study aims to assess actual groundwater abstraction in North Jordan by implementing a new geographic information system–remote sensing multi-method approach. The results are promising and show that the announced GW abstraction volumes provided by the Water Authority of Jordan and the Ministry of Water and Irrigation are not particularly accurate, especially for areas where extensive agricultural practices are present. This fact may explain the discrepancies between official reports on declining groundwater levels and the results of several studies that assessed North Jordan groundwater abstraction. This study showed that irrigation is a crucial factor that affects this discrepancy and that the crop water requirements are generally higher than what is reported by the governmental sector. The results showed a 31 MCM discrepancy between the official recorded groundwater abstraction volumes and the actual (crop-based) water consumption. Increasing the irrigation efficiency by 20% will aid in sustaining the groundwater in the study area, maintaining the current groundwater wells and save the farmers money.

scholarly journals Water Management Using Drones and Satellites in Agriculture

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 874 ◽  
Author(s):  
Javier J. Cancela ◽  
Xesús P. González ◽  
Mar Vilanova ◽  
José M. Mirás-Avalos
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Water Status ◽  
Irrigation Management ◽  
Irrigation Efficiency ◽  
Agricultural Systems ◽  
Special Issue ◽  
Crop Water ◽  
Water Requirements ◽  
Remote Sensing Techniques

This document intends to be a presentation of the Special Issue “Water Management Using Drones and Satellites in Agriculture”. The objective of this Special Issue is to provide an overview of recent advances in the methodology of using remote sensing techniques for managing water in agricultural systems. Its eight peer-reviewed articles focus on three topics: new equipment for characterizing water bodies, development of satellite-based technologies for determining crop water requirements in order to enhance irrigation efficiency, and monitoring crop water status through proximal and remote sensing. Overall, these contributions explore new solutions for improving irrigation management and an efficient assessment of crop water needs, being of great value for both researchers and advisors.

scholarly journals Remote Sensing for Crop Water Management: from Experiments to User-Driven Services

2016 ◽  
Author(s):  
Alfonso Calera ◽  
Isidro Campos ◽  
Anna Osann ◽  
Guido D´Urso ◽  
Massimo Menenti
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
Meteorological Data ◽  
Irrigation Scheduling ◽  
Web Gis ◽  
Optical Remote Sensing ◽  
Crop Water ◽  
Biophysical Parameters ◽  
Water Requirements ◽  
Crop Water Requirements

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e. professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies. This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.

Multi-method approach for high resolution 3D data based process analyses of compound rock slides

2021 ◽  
Author(s):  
Christine Fey ◽  
Klaus Voit ◽  
Volker Wichmann ◽  
Christian Zangerl ◽  
Volkmar Mair
Keyword(s):  
Remote Sensing ◽  
Point Cloud ◽  
Point Clouds ◽  
Distance Measurement ◽  
Image Correlation ◽  
Original Surface ◽  
3D Point Clouds ◽  
Multi Method Approach ◽  
Method Approach ◽  
Measurement Approach

<p>The use of high resolution 3D point clouds and digital terrain models (DTM) from laserscanning or photogrammetry becomes more and more state of the art in landslide studies. Based on a multi-temporal terrestrial laserscanning (TLS) dataset of the deep-seated compound rockslide Laatsch, South Tyrol, we present a multi-method approach to characterize processes such as sliding, falling, toppling, and flows. Sliding is the predominant process of the Laatsch rockslide, accompanied by secondary processes such as rockfall, debris flows and erosion. The presented methods are applicable to all kind of 3D point clouds and not limited to TLS data. For remote sensing-based landslide analyses a distinction between two classes of surface processes is necessary: i) processes where the original surface is destroyed and no correlations between the shape and texture of the pre- and post-failure surfaces can be found (falls, rapid flows, rapid slides) and ii) processes where the surface is displaced without major surface changes (slow slides, slow flows and toppling). For processes where the original surface is destroyed, the distance between the pre- and post-failure terrain surface is measured with the aim to delineate the scarp and depositional area, and to quantify the failure volume as well as the scarp thickness. With DTMs of differences (DoD), the distance is measured along the plumb line. DoDs can be used to quickly and reliably assess the volume and extent of fall processes on flat to moderate slopes. For steep or even overhanging terrain, a 3D distance measurement approach must be used, where the distance is measured along the local surface normal. After 3D distance measurement, the volume of steep scarp areas can be calculated by first rotating, the point cloud into the horizontal plane (by making use of the average surface normal) and by interpolating the rotated 3D distance measurement values into a grid. Summing up the distances and multiplying with the cell area of the grid yields the scrap rupture volume. Remote sensing-based analyses of sliding and toppling processes are more complex compared to fall processes because the displaced surface patch must be detected in both surveys. Displacement analyses based on image correlation of ambient occlusion shaded relief images, together with DTMs of both epochs, are used to analyse the displacement of the entire rockslide area. The result is a map with displacement vectors. Disadvantages of image correlation are the coarse spatial resolution and the inability, as it is a 2.5D approach, to deal with steep slope parts. To analyse the displacement and toppling of steep rock walls a combination of the 3D distance measurement approach and an iterative closest point (ICP) based approach is applied. The 3D distance measurement values are clustered and used for a segmentation of the point cloud. In a next step, the ICP is applied on each of the resulting segments. This approach can deal with 3D displacements. The results are still sensitive towards the geometric contrast within the segments and not fully automated yet.</p>

Remote sensing of crop water requirements in orange orchards using high-spatial-resolution sensors

2004 ◽  
Author(s):  
Salvatore Barbagallo ◽  
Simona Consoli ◽  
Guido D'Urso ◽  
Rosaria Giorgio Gaggia ◽  
Attilio Toscano
Keyword(s):  
Remote Sensing ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Crop Water ◽  
Water Requirements ◽  
Crop Water Requirements

Evaluating crop water requirements and actual crop water use with center pivot irrigation system in Inner Mongolia of China

2020 ◽  
Author(s):  
Peejush Pani ◽  
Li Jia ◽  
Massimo Menenti ◽  
Guangcheng Hu ◽  
Chaolei Zheng ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Water Use ◽  
Inner Mongolia ◽  
Crop Water ◽  
Water Requirements ◽  
Water Losses ◽  
Crop Water Use ◽  
Crop Water Requirements ◽  
Center Pivot

<p>This paper proposes a new approach to estimate and map separately gross and net water requirements and actual crop water use by applying multi–spectral satellite data. Remote sensing information is witnessing a boom in the availability of high-resolution multi-spectral data with frequent revisit time, paving the path for improved assessment of precision agriculture and minimizing the wastage of irrigation water. In this study, we have tried to integrate multi-source remote sensing information with farmer’s irrigation practices to evaluate the water use and losses at farm-scale for center pivot irrigation systems (CPIS) in Inner Mongolia autonomous region of China. The region is practicing modernized irrigation methods to efficiently use groundwater. Crop gross water requirements are estimated by evaluating separately the net crop water requirements (CWR) and the water losses inherently from a CPIS, i.e. droplet evaporation to the air directly before they fell on the crop canopy during irrigation application (<em>E<sub>A</sub></em>) and canopy interception loss (<em>I<sub>c</sub></em>). The crop water requirement is estimated according to the FAO-56 method based on the Penman-Monteith equation. Actual crop water use is evaluated by estimating separately soil evaporation (<em>E<sub>S</sub></em>) and plant transpiration (<em>E<sub>T</sub></em>) by applying the ETMonitor model. High-resolution multi–spectral data acquired by Sentinel-2 MSI and Landsat-8 OLI together with meteorological forcing data and soil moisture retrievals were used to construct daily estimates of crop water requirements and actual use. Finally, the performance of irrigation scenarios was assessed by applying a performance indicator (IP), as the ratio between gross water requirement and the volume of irrigation applied, where values closer to unity referring to optimum utilization and minimum loss. Measurements of actual evapotranspiration by eddy covariance system were applied to evaluate the actual evapotranspiration estimates by the ETMonitor. Field experiments were also carried out to validate the estimated irrigation losses, i.e. <em>E<sub>A</sub></em> and <em>I<sub>C</sub></em>. The estimates were in good agreement with the ground observations, i.e. an R<sup>2</sup> of 0.64 – 0.80 for actual water use and 0.66 – 0.97 for water losses. The RMSE was 0.6 – 1.2 mm/day for actual daily water use and 0.64 – 1.55 mm water losses for each irrigation, respectively. The IP was estimated as 1.6 for the performance of CPIS as per the above definition. Overall, the study shows that CPIS has under-performed in minimizing water losses in the study area with losses of 25.4% per season of the total volume of water applied for wheat, and 23.7% per season for potato. This implies that the amount of water applied was largely insufficient to meet the gross water requirements, i.e. including losses.</p>

scholarly journals Quantifying Vertical Deformation in the Tigris–Euphrates Basin Due to the Groundwater Abstraction: Insights from GRACE and Sentinel-1 Satellites

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1658 ◽  
Author(s):  
Ashraf Rateb ◽  
Chung-Yen Kuo
Keyword(s):  
Groundwater Depletion ◽  
Groundwater Abstraction ◽  
Groundwater Levels ◽  
In Situ Data ◽  
Depletion Rate ◽  
Small Baseline Subset ◽  
Small Baseline ◽  
Remote Sensing Techniques ◽  
Sbas Insar ◽  
Gravity Recovery

This study explores the occurrences of land subsidence in response to dropping groundwater levels in the central part of the Tigris–Euphrates basin. We estimated the groundwater depletion related to human and climate drivers between 2003 and 2017 based on estimates from the Gravity Recovery and Climate Experiment (GRACE) and two global hydrological models (NOAH-3.3 and WGHM-2.2d). The cumulative displacement was calculated using Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) for 96 interferograms, which were generated by 31 images acquired by the Sentinel-1 satellite. The results show that the basin is experiencing a decline in groundwater storage at a rate of −7.56 km3/year with a total loss of 106.81 km3. This depletion rate has led to inelastic compaction and has resulted in subsidence near the city of Baghdad at a rate of −10 mm/year. The measured coherence phase between the two signals is ~0.67, and the depletion precedes the subsidence by ~1.5 months. The new data from GRACE-Follow on, Sentinel-1, and the piezometric water level could help to constrain the rate of depletion and displacements in the basin. Combining these remote sensing techniques provides an independent tool for water management in areas where in-situ data are scarce.

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