scholarly journals Estimation of the Water Balance of a Small Tropical Andean Catchment

La Granja ◽  
2019 ◽  
Vol 29 (1) ◽  
pp. 56-69
Author(s):  
Paola Jackeline Duque-Sarango ◽  
Ronald Cajamarca-Rivadeneira ◽  
Beverley C. Wemple ◽  
Manuel E. Delgado-Fernández
Keyword(s):  
Time Series ◽  
Water Balance ◽  
Soil Analysis ◽  
Field Capacity ◽  
Digital Elevation ◽  
Double Mass ◽  
Temperature Reference ◽  
Elevation Model ◽  
Precipitation And Temperature

The present study seeks to estimate the water balance that results as a product of the variation of precipitation and temperature over the Chaquilcay microcatchment, a natural system that intercepts with the surface of the Aguarongo Protected Forest in Gualaceo, Ecuador. Four meteorological stations of the National Institute of Meteorology and Hydrology (INAMHI) were studied, which are divided into climatological and pluviometric, with time series of over 30 years, (1982-2015 period). In order to quantify the contributions and losses of water, statistical analyzes of the time series and surveys of in situ information were carried out. The methods used are linear regression, streak test and double mass curve. To fill and validate the series of precipitation and temperature, reference temperatures of the isothermal raster of Ecuador were included in the pluviometric stations. Additionally, a digital elevation model (MDE) was used to predict the amount of sunshine, and the Thornthwaite evapotranspiration method (1948) was applied from the obtained data. The results show acceptance of the meteorological records, while in the soil analysis we obtained the following data: Humidity, 62.38%; organic matter, 21.29%; field capacity, 18.71 mm and a flow of 1.89 m³ / s during the month of May. Finally, the water balance indicates 843.7 mm of annual precipitation, a storage difference of 18.71 mm representing 2.22% of total precipitation, an surplus of 144.5 mm, and actual evapotranspiration of 680.5 mm, with 17.13% and 80.65%, respectively.

scholarly journals Soil Moisture Estimation Using Citizen Observatory Data, Microwave Satellite Imagery, and Environmental Covariates

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2160
Author(s):  
Daniel Kibirige ◽  
Endre Dobos
Keyword(s):  
Soil Moisture ◽  
Expert Knowledge ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Regression Kriging ◽  
Environmental Covariates ◽  
Observatory Data ◽  
Digital Elevation ◽  
Elevation Model

Soil moisture (SM) is a key variable in the climate system and a key parameter in earth surface processes. This study aimed to test the citizen observatory (CO) data to develop a method to estimate surface SM distribution using Sentinel-1B C-band Synthetic Aperture Radar (SAR) and Landsat 8 data; acquired between January 2019 and June 2019. An agricultural region of Tard in western Hungary was chosen as the study area. In situ soil moisture measurements in the uppermost 10 cm were carried out in 36 test fields simultaneously with SAR data acquisition. The effects of environmental covariates and the backscattering coefficient on SM were analyzed to perform SM estimation procedures. Three approaches were developed and compared for a continuous four-month period, using multiple regression analysis, regression-kriging and cokriging with the digital elevation model (DEM), and Sentinel-1B C-band and Landsat 8 images. CO data were evaluated over the landscape by expert knowledge and found to be representative of the major SM distribution processes but also presenting some indifferent short-range variability that was difficult to explain at this scale. The proposed models were evaluated using statistical metrics: The coefficient of determination (R2) and root mean square error (RMSE). Multiple linear regression provides more realistic spatial patterns over the landscape, even in a data-poor environment. Regression kriging was found to be a potential tool to refine the results, while ordinary cokriging was found to be less effective. The obtained results showed that CO data complemented with Sentinel-1B SAR, Landsat 8, and terrain data has the potential to estimate and map soil moisture content.

scholarly journals Contribution of glacier melt to stream runoff: if the climatically extreme summer of 2003 had happened in 1979…

2007 ◽  
Vol 46 ◽  
pp. 303-308 ◽  
Author(s):  
Gernot R. Koboltschnig ◽  
Wolfgang Schöner ◽  
Massimiliano Zappa ◽  
Hubert Holzmann
Keyword(s):  
Water Balance ◽  
Catchment Area ◽  
Meteorological Data ◽  
Snow Accumulation ◽  
Balance Model ◽  
High Temporal Resolution ◽  
Ice Melt ◽  
Digital Elevation ◽  
Dry Conditions ◽  
Elevation Model

AbstractThis paper presents a comparative study at a small and highly glacierized catchment area in the Austrian Alps, where runoff under the extreme hot and dry conditions of summer 2003 was simulated based on two different glacier extents: the 2003 glacier extent and the 29% larger 1979 extent. Runoff was simulated applying the hydrological water balance model PREVAH at a high temporal resolution. For this purpose, the catchment area was subdivided into hydrological response units based on digital elevation model and land-cover data. The model was driven by meteorological data from the observatory at Hoher Sonnblick, situated at the highest point of the catchment area (3106ma.s.l.). We were interested in the effect the change in glacier extent would have on the annual and monthly water balance and the hydrograph of hourly discharges. Results of the 2003 and the hypothetical 1979 simulation show main differences in runoff for the period July–August depending on a higher ice-melt contribution. Due to the same meteorological input, both simulations calculate the same snow accumulation and snowmelt. Annual discharge in 1979 would have been 12% higher and hourly runoff up to 35% higher than in 2003.

scholarly journals A multi-level strategy for anticipating future glacier lake formation and associated hazard potentials

2010 ◽  
Vol 10 (2) ◽  
pp. 339-352 ◽  
Author(s):  
H. Frey ◽  
W. Haeberli ◽  
A. Linsbauer ◽  
C. Huggel ◽  
F. Paul
Keyword(s):  
Swiss Alps ◽  
Bed Topography ◽  
Aster Gdem ◽  
Digital Elevation ◽  
Lake Formation ◽  
Level 3 ◽  
Multi Level ◽  
Four Levels ◽  
Elevation Model

Abstract. In the course of glacier retreat, new glacier lakes can develop. As such lakes can be a source of natural hazards, strategies for predicting future glacier lake formation are important for an early planning of safety measures. In this article, a multi-level strategy for the identification of overdeepened parts of the glacier beds and, hence, sites with potential future lake formation, is presented. At the first two of the four levels of this strategy, glacier bed overdeepenings are estimated qualitatively and over large regions based on a digital elevation model (DEM) and digital glacier outlines. On level 3, more detailed and laborious models are applied for modeling the glacier bed topography over smaller regions; and on level 4, special situations must be investigated in-situ with detailed measurements such as geophysical soundings. The approaches of the strategy are validated using historical data from Trift Glacier, where a lake formed over the past decade. Scenarios of future glacier lakes are shown for the two test regions Aletsch and Bernina in the Swiss Alps. In the Bernina region, potential future lake outbursts are modeled, using a GIS-based hydrological flow routing model. As shown by a corresponding test, the ASTER GDEM and the SRTM DEM are both suitable to be used within the proposed strategy. Application of this strategy in other mountain regions of the world is therefore possible as well.

scholarly journals The 1513 Monte Crenone rock avalanche: numerical model and geomorphological analysis

2022 ◽  
Vol 77 (1) ◽  
pp. 21-37
Author(s):  
Alessandro De Pedrini ◽  
Christian Ambrosi ◽  
Cristian Scapozza
Keyword(s):  
Numerical Modelling ◽  
Rock Avalanche ◽  
Historical Reconstruction ◽  
Field Mapping ◽  
Digital Elevation ◽  
Lake Formation ◽  
Detachment Zone ◽  
Elevation Model ◽  
Geomorphological Analysis

Abstract. As a contribution to the knowledge of historical rockslides, this research focuses on the historical reconstruction, field mapping, and simulation of the expansion, through numerical modelling, of the 30 September 1513 Monte Crenone rock avalanche. Earth observation in 2-D and 3-D, as well as direct in situ field mapping, allowed the detachment zone and the perimeter and volume of the accumulation to be determined. Thanks to the reconstruction of the post-event digital elevation model based on historical topographic maps and the numerical modelling with the RAMMS::DEBRISFLOW software, the dynamics and runout of the rock avalanche were calibrated and reconstructed. The reconstruction of the runout model allowed confirmation of the historical data concerning this event, particularly the damming of the valley floor and the lake formation up to an elevation of 390 m a.s.l., which generated an enormous flood by dam breaching on 20 May 1515, known as the “Buzza di Biasca”.

scholarly journals Quaternary formations mapping in the region of Volta Grande do Rio Uruguai (Brazil)

2021 ◽  
Vol 41 ◽  
pp. e174174
Author(s):  
Sandra Cristina Deodoro ◽  
William Zanete Bertolini ◽  
Plinio da Costa Temba
Keyword(s):  
Particle Size Analysis ◽  
Size Analysis ◽  
Valley Bottom ◽  
Model Soil ◽  
Fluvial Dynamics ◽  
Digital Elevation ◽  
Topographic Attributes ◽  
History Of ◽  
Elevation Model

Quaternary formations (detrital and weathered materials) are an important natural resource for different areas of scientific investigation, from understanding their relation to erosive processes and morphodynamic processes that create landforms or to understanding the history of the first human settlements (geoarcheology). Quaternary coverings can be formed in situ or be transported by external geologic agents. Regarding soils, Quaternary formations are related to landscape topography and are transformed according to the characteristics of this topography. Hence, classifying and mapping these soils is not always easy. The present article aims to map the Quaternary formations along a stretch of the Uruguay River basin  known as Volta Grande (SC/RS-Brazil), by using  topographic attributes derived from the SRTM GL1-Up Sampled digital elevation model, soil particle-size analysis, and a generated Multiresolution Index of Valley Bottom Flatness (MRVBF) index . The results of the analysis show that: (i) colluvium is the predominant Quaternary formation in the study area; (ii) there is a predominance of clay, corroborating previous studies of the region; (iii) the spatial distribution of the study area’s  Quaternary formations reflect local slope dynamics based on morphology and topographic position; and, (iv) the existence of colluvium-alluvium on the Uruguay River’s banks indicates that slope attributes contributed to the pedogeomorphological dynamics of the study area and not only fluvial dynamics. Based on the results, the methodology applied in this study might be useful for pedogeomorphological studies, notably in the analysis and mapping of Quaternary formations, despite some of its limitations.

scholarly journals CARTOGRAPHY OF MOROCCAN ARGAN TREE USING COMBINED OPTICAL AND SAR IMAGERY INTEGRATED WITH DIGITAL ELEVATION MODEL

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 211-217
Author(s):  
E. Elmoussaoui ◽  
A. Moumni ◽  
A. Lahrouni
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Digital Elevation Model ◽  
Optical Data ◽  
Support Vector ◽  
Ground Truth Data ◽  
Argan Tree ◽  
Digital Elevation ◽  
Elevation Model ◽  
Sentinel 2

Abstract. Forest tree species mapping became easier due to the global availability of high spatio-temporal resolution images acquired from multiple sensors. Such data can lead to better forest resources management. Machine-learning pixel based analysis was performed to multi-spectral Sentinel-2 and Synthetic Aperture Radar Sentinel-1 time series integrated with Digital Elevation Model acquired over Argan forest of Essaouira province, Morocco. The argan tree constitutes a fundamental resource for the populations of this arid area of Morocco. This research aims to use the potential of the combination of multi-sensor data to detect, map and identify argan tree from other forest species using three Machine Learning algorithms: Support Vector Machine (SVM), Maximum Likelihood (ML) and Artificial Neural Networks (ANN). The exploited datasets included Sentinel-1 (S1), Sentinel-2 (S2) time series, Shuttle Radar Topographic Missing Digital Elevation Model (DEM) layer and Ground truth data. We tested several sets of scenarios, including single S1 derived features, single S2 time series and combined S1 and S2 derived layers with DEM scene acquisition. The best results (overall accuracy OA and Kappa coefficient K) obtained from time series of optical data (NDVI): OA = 86.87%, K = 0.84, from time series of SAR data (VV+VH/VV): OA = 45.90%, K = 0.36, from the combination of optical and SAR time series (NDVI+VH+DEM): OA = 93.01%, K = 0.914, and from the fusion of optical time series and DEM layer (NDVI+DEM): OA = 93.25%, K = 0.91. These results indicate that single-sensor (S2) integrated with the DEM layer led us to obtain the highest classification results.

Sentinel-1 InSAR data by LiCSAR system

2021 ◽  
Author(s):  
Milan Lazecky ◽  
Yasser Maghsoudi Mehrani ◽  
Scott Watson ◽  
Yu Morishita ◽  
John Elliott ◽  
...  
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Atmospheric Correction ◽  
East African ◽  
Digital Elevation ◽  
African Rift ◽  
Earth Observation Satellites ◽  
Elevation Model ◽  
Data Coherence ◽  
Standard Frame

<p>Looking Into the Continents from Space with Synthetic Aperture Radar (LiCSAR) is a system built for large-scale interferometric processing of Sentinel-1 data. LiCSAR automatically produces geocoded wrapped and unwrapped interferograms combining every acquisition epoch with four preceding epochs, and complementary data (coherence, amplitude, line-of-sight unit vectors, digital elevation model, metadata, and atmospheric phase screen estimates by the Generic Atmospheric Correction Online Service, GACOS).</p><p>The LiCSAR products are generated in frame units where a standard frame covers ~220x250 km, at 0.001° resolution (WGS-84 coordinate system). Frames are continuously updated for tectonic and volcanic priority areas. In 2020, the LiCSAR system covered about 1,500 global frames in which we have processed over 89,000 Sentinel-1 acquisitions and generated over 300,000 interferograms. Among these, 470 frames cover 1,024 global volcanoes. We aim to cover the global seismic mask defined by the Committee on Earth Observation Satellites (CEOS), but focus initially on the Alpine-Himalayan belt and East African Rift.</p><p>We serve the products as open and freely accessible through our web portal: https://comet.nerc.ac.uk/comet-lics-portal and aim to provide them to shared infrastructures as the European Plate Observing System (EPOS). We also generate rapid response coseismic interferograms for earthquakes with moment magnitude (Mw)> 5.5  a few hours after the postseismic data become available, and we update frames covering active volcanoes twice per day.</p><p>Our products can be directly converted to displacement time series and velocities using  the LiCSBAS time series analysis software. We present solutions implemented in LiCSAR, and show several case studies that use LiCSAR and LiCSBAS products to measure tectonic and volcanic deformation.</p><p><img src="https://contentmanager.copernicus.org/fileStorageProxy.php?f=gnp.1c122b867cff59390830161/sdaolpUECMynit/12UGE&app=m&a=0&c=02895a62108de9393057db6a355e3b06&ct=x&pn=gnp.elif&d=1" alt=""></p>

scholarly journals A GIS-Based Water Balance Approach Using a LiDAR-Derived DEM Captures Fine-Scale Vegetation Patterns

2019 ◽  
Vol 11 (20) ◽  
pp. 2385 ◽  
Author(s):  
James M. Dyer
Keyword(s):  
Water Balance ◽  
Vegetation Patterns ◽  
Fine Scale ◽  
Individual Tree ◽  
Annual Variations ◽  
Digital Elevation ◽  
Climatic Water Deficit ◽  
Elevation Model ◽  
Fine Resolution ◽  
Strong Control

Topography exerts strong control on microclimate, resulting in distinctive vegetation patterns in areas of moderate to high relief. Using the Thornthwaite approach to account for hydrologic cycle components, a GIS-based Water Balance Toolset is presented as a means to address fine-scale species–site relationships. For each pixel within a study area, the toolset assesses inter-annual variations in moisture demand (governed by temperature and radiation) and availability (precipitation, soil storage). These in turn enable computation of climatic water deficit, the amount by which available moisture fails to meet demand. Summer deficit computed by the model correlates highly with the Standardized Precipitation–Evapotranspiration Index (SPEI) for drought at several sites across the eastern U.S. Yet the strength of the approach is its ability to model fine-scale patterns. For a 25-ha study site in central Indiana, individual tree locations were linked to summer deficit under different historical conditions: using average monthly climatic variables for 1998–2017, and for the drought year of 2012. In addition, future baseline and drought-year projections were modeled based on downscaled GCM data for 2071–2100. Although small deficits are observed under average conditions (historical or future), strong patterns linked to topography emerge during drought years. The modeled moisture patterns capture vegetation distributions described for the region, with beech and maple preferentially occurring in low-deficit settings, and oak and hickory dominating more xeric positions. End-of-century projections suggest severe deficit, which should favor oak and hickory over more mesic species. Pockets of smaller deficit persist on the landscape, but only when a fine-resolution Light Detection and Ranging (LiDAR)-derived Digital Elevation Model (DEM) is used; a coarse-resolution DEM masks fine-scale variability and compresses the range of observed values. Identification of mesic habitat microrefugia has important implications for retreating species under altered climate. Using readily available data to evaluate fine-scale patterns of moisture demand and availability, the Water Balance Toolset provides a useful approach to explore species–environment linkages.

scholarly journals IGS-CMAES: A Two-Stage Optimization for Ground Deformation and DEM Error Estimation in Time Series InSAR Data

2021 ◽  
Vol 13 (13) ◽  
pp. 2615
Author(s):  
Xinyao Sun ◽  
Aaron Zimmer ◽  
Subhayan Mukherjee ◽  
Parwant Ghuman ◽  
Irene Cheng
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Optimization Problems ◽  
Ground Deformation ◽  
Series Data ◽  
Two Stage ◽  
Real Time Processing ◽  
Sensing Technology ◽  
Digital Elevation ◽  
Elevation Model

Interferometric synthetic aperture radar (InSAR) has become an increasingly recognized remote sensing technology for earth surface monitoring. Slow and subtle terrain displacements can be estimated using time-series InSAR (TSInSAR) data. However, a substantial increase in the availability of exclusive time series data necessitates the development of more efficient and effective algorithms. Research in these areas is usually carried out by solving complicated optimization problems, which is very computationally expensive and time-consuming. This work proposes a two-stage black-box optimization framework to jointly estimate the average ground deformation rate and terrain digital elevation model (DEM) error. The method performs an iterative grid search (IGS) to acquire coarse candidate solutions, and then a covariance matrix adaptive evolution strategy (CMAES) is adopted to obtain the final local results. The performance of our method is evaluated using both simulated and real datasets. Both quantitative and qualitative comparisons using different optimizers support the reliability and effectiveness of our work. The proposed IGS-CMAES achieves higher accuracy with a significantly fewer number of objective function evaluations than other established algorithms. It offers the possibility for wide-area monitoring, where high precision and real-time processing is essential.

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