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Hydrology
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The Application of Remote Sensing in Hydrology
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The Application of Remote Sensing in Hydrology

A special issue of Hydrology (ISSN 2306-5338). This special issue belongs to the section "Hydrological Measurements and Instrumentation".

Deadline for manuscript submissions: closed (15 May 2022) | Viewed by 16591

Special Issue Editor

Prof. Dr. Jarosław Chormański

E-Mail Website
Guest Editor
Department of Remote Sensing and Environmental Assessment, Warsaw University of Life Sciences (WULS) Nowoursynowska 166, 02-787 Warszawa, Poland
Interests: remote sensing for hydrology and hydrological modeling; remote sensing for urban hydrology and urban ecosystem services; hydro-ecological processes monitoring and modeling; wetlands applications; aquatic remote sensing; water stress detection

Special Issue Information

Dear Colleagues,

The tremendous growth of digital technology in the last decades has greatly changed the way humans can analyse, interpret and monitor our environment. A new generation of Remote Sensing technologies has been developed with higher spatial and spectral resolution, covering ever larger areas, offering a wealth of novel opportunities in different fields of application. Hydrology is a complex science that in the past century has witnessed a tremendous growth, benefiting at the same time the new developments in the field of Remote Sensing. Several hydrological variables can nowadays be computed and monitored through the use of Remote Sensing information and future satellite missions have even been designed specifically for hydrological purposes (e.g. NASA SWOT Mission) by providing systematic hydrological observations at high spatial and temporal resolution.

Despite this growth, there still remain many concerns in the field, especially for what concerns data processing and analysis. We are interested in papers facing new advances in Remote Sensing data analysis and algorithms, such as Machine Learning/Artificial Intelligence, with a particular interest on how Hyperspectral and LiDAR data collected from multi-scale platforms (e.g. satellite, airborne, or UAV), could help enhance the characterization of important hydrological variables. Papers focusing on the exploitation of such data in the context of soil moisture, surface water extent and floods monitoring, water level monitoring, snow cover monitoring, hydrological fluxes monitoring and modelling (rainfall, runoff, evapotranspiration, interception), improving water balance calculation, investigation of ecohydrological processes, hydromorphology assessment, hydrological catchment models parametrisation with applications to catchments, rivers and lakes are very welcome. However, other sources of Remote Sensing data are also accepted (such as satellite-based multispectral or radar information).

Dr. Jarosław Chormański
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Hydrology is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Multi-sensor and multi-scale remote sensing
  • Hyperspectral and LiDAR
  • UAV, airborne and satellite-based data
  • Soil moisture, surface water extent and level monitoring
  • Hydrological fluxes monitoring
  • Urban Greeness

Published Papers (5 papers)

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Research

17 pages, 4809 KiB  
Article
Evaluating Magnitude Agreement and Occurrence Consistency of CHIRPS Product with Ground-Based Observations over Medium-Sized River Basins in Nepal
by Surabhi Upadhyay, Priya Silwal, Rajaram Prajapati, Rocky Talchabhadel, Sandesh Shrestha, Sudeep Duwal and Hanik Lakhe
Hydrology 2022, 9(8), 146; https://doi.org/10.3390/hydrology9080146 - 16 Aug 2022
Cited by 4 | Viewed by 2758
Abstract
High spatio-temporal resolution and accurate long-term rainfall estimates are critical in sustainable water resource planning and management, assessment of climate variability and extremes, and hydro-meteorology-related water system decisions. The recent advent of improved higher-resolution open-access satellite-based rainfall products has emerged as a viable [...] Read more.
High spatio-temporal resolution and accurate long-term rainfall estimates are critical in sustainable water resource planning and management, assessment of climate variability and extremes, and hydro-meteorology-related water system decisions. The recent advent of improved higher-resolution open-access satellite-based rainfall products has emerged as a viable complementary to ground-based observations that can often not capture the rainfall variability on a spatial scale. In a developing country such as Nepal, where the rain-gauge monitoring network is sparse and unevenly distributed, satellite rainfall estimates are crucial. However, substantial errors associated with such satellite rainfall estimates pose a challenge to their application, particularly in complex orographic regions such as Nepal. Therefore, these precipitation products must be validated before practical usage to check their accuracy and occurrence consistency. This study aims to assess the reliability of the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) product against ground-based observations from 1986 to 2015 in five medium-sized river basins in Nepal, namely, Babai, Bagmati, Kamala, Kankai, and the West Rapti river basin. A set of continuous evaluation metrics (correlation coefficient, root mean square error, relative bias, and Kling-Gupta efficiency) were used in analyzing the accuracy of CHIRPS and categorical metrics (probability of detection, critical success index, false alarm ratio, and frequency bias index). The Probability of Detection and Critical Success Index values were found to be considerably low (<0.4 on average), while the false alarm ratio was significant (>0.4 on average). It was found that CHIRPS showed better performance in seasonal and monthly time scales with high correlation and indicated greater consistency in non-monsoon seasons. Rainfall amount (less than 10 mm and greater than 150 mm) and rainfall frequency was underestimated by CHIRPS in all basins, while the overestimated rainfall was between 10 and 100 mm in all basins except Kamala. Additionally, CHIRPS overestimated dry days and maximum consecutive dry days in the study area. Our study suggests that CHIRPS rainfall products cannot supplant the ground-based observations but complement rain-gauge networks. However, the reliability of this product in capturing local extreme events (such as floods and droughts) seems less prominent. A high-quality rain gauge network is essential to enhance the accuracy of satellite estimations. Full article
(This article belongs to the Special Issue The Application of Remote Sensing in Hydrology)
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12 pages, 6128 KiB  
Article
Decrease in the Water Level of Lake Prespa (North Macedonia) Studied by Remote Sensing Methodology: Relation with Hydrology and Agriculture
by Juan Soria and Nadezda Apostolova
Hydrology 2022, 9(6), 99; https://doi.org/10.3390/hydrology9060099 - 5 Jun 2022
Cited by 1 | Viewed by 3369
Abstract
The Ohrid-Prespa lake system is the oldest and most diverse permanent lake system in Europe, dating from the Pliocene era and aged at over 4Ma. Its smaller component is Lake Macro Prespa (thereafter called Prespa), shared by North Macedonia, Albania, and Greece. Lake [...] Read more.
The Ohrid-Prespa lake system is the oldest and most diverse permanent lake system in Europe, dating from the Pliocene era and aged at over 4Ma. Its smaller component is Lake Macro Prespa (thereafter called Prespa), shared by North Macedonia, Albania, and Greece. Lake Prespa’s depth was reported as 14 m mean and 48 m maximum before its major water level decline. The lake is highly sensitive to external impacts, including climate change, and has been suffering major water loss for decades. A lake-level decline of almost 10 m was documented between 1950 and 2009 due to restricted precipitation and increased water abstraction for irrigation. This study describes the changes in the surface size of Prespa Lake and the vegetation/land use in the surrounding area in the period 1984–2020 using satellite images (remote sensing, Landsat 5 & 8 images by United States Geological Survey). The lake lost 18.87 km2 of surface in this period (6.9% of its size, dropping from 273.38 km2 to 254.51 km2). Water loss was greater in the period 1987–1993 and 1998–2004. The Analysis of Normalized Difference Vegetation Index (NDVI) in the area (app. 4950 km2) surrounding Lake Prespa revealed an increase in the mean NDVI values over the period studied (1984–2020), pointing to a general increase in vegetation. Areas with NDVI > 0.13 increased from 78% in 1984 to 86% in 2020, while those with the highest vegetation intensity (NDVI > 0.45) increased by 40%. These changes in vegetation may be related to the water loss of the lake. Full article
(This article belongs to the Special Issue The Application of Remote Sensing in Hydrology)
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21 pages, 3303 KiB  
Article
Long-Term Hydrological Regime Monitoring of a Mediterranean Agro-Ecological Wetland Using Landsat Imagery: Correlation with the Water Renewal Rate of a Shallow Lake
by Lucía Vera-Herrera, Juan Soria, Javier Pérez and Susana Romo
Hydrology 2021, 8(4), 172; https://doi.org/10.3390/hydrology8040172 - 20 Nov 2021
Cited by 5 | Viewed by 2603
Abstract
The Natural Park of Albufera (Valencia, Spain) is one of the Spanish Mediterranean wetlands where rice is cultivated intensively. The hydrology of the Albufera Lake, located in the center, combines natural contributions with complex human management. The aim of our study was to [...] Read more.
The Natural Park of Albufera (Valencia, Spain) is one of the Spanish Mediterranean wetlands where rice is cultivated intensively. The hydrology of the Albufera Lake, located in the center, combines natural contributions with complex human management. The aim of our study was to develop a new methodology to accurately detect the volume of flood water in complex natural environments which experience significant seasonal changes due to climate and agriculture. The study included 132 Landsat images, covering a 15-year period. The algorithm was adjusted using the NDWI index and simultaneous measurements of water levels in the rice fields. The NDVI index was applied to monitor the cultivated area during the summer. Lake inflows and residence times were also evaluated to quantify how the hydrodynamic of the lake is conditioned by the agricultural management. The algorithm developed is confirmed as a useful ecological tool to monitor the flood cycle of the wetland, being able to detect even the lowest water levels. The flood dynamics are consistent over the fifteen years, being in line with the rice cultivation cycle. Water renewal in Albufera lake is altered with respect to that expected according to the rainfall recorded in the study area, so an improvement in the water management of the hydrological basin is required to optimize the runoff during the rainiest months. Full article
(This article belongs to the Special Issue The Application of Remote Sensing in Hydrology)
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22 pages, 2276 KiB  
Article
Validation of Three Daily Satellite Rainfall Products in a Humid Tropic Watershed, Brantas, Indonesia: Implications to Land Characteristics and Hydrological Modelling
by Bagus Setiabudi Wiwoho, Ike Sari Astuti, Imam Abdul Gani Alfarizi and Hetty Rahmawati Sucahyo
Hydrology 2021, 8(4), 154; https://doi.org/10.3390/hydrology8040154 - 14 Oct 2021
Cited by 14 | Viewed by 2286
Abstract
A total of three different satellite products, CHIRPS, GPM, and PERSIANN, with different spatial resolutions, were examined for their ability to estimate rainfall data at a pixel level, using 30-year-long observations from six locations. Quantitative and qualitative accuracy indicators, as well as R [...] Read more.
A total of three different satellite products, CHIRPS, GPM, and PERSIANN, with different spatial resolutions, were examined for their ability to estimate rainfall data at a pixel level, using 30-year-long observations from six locations. Quantitative and qualitative accuracy indicators, as well as R2 and NSE from hydrological estimates, were used as the performance measures. The results show that all of the satellite estimates are unsatisfactory, giving the NRMSE ranging from 6 to 30% at a daily level, with CC only 0.21–0.36. Limited number of gauges, coarse spatial data resolution, and physical terrain complexity were found to be linked with low accuracy. Accuracy was slightly better in dry seasons or low rain rate classes. The errors increased exponentially with the increase in rain rates. CHIPRS and PERSIANN tend to slightly underestimate at lower rain rates, but do show a consistently better performance, with an NRMSE of 6–12%. CHRIPS and PERSIANN also exhibit better estimates of monthly flow data and water balance components, namely runoff, groundwater, and water yield. GPM has a better ability for rainfall event detections, especially during high rainfall events or extremes (>40 mm/day). The errors of the satellite products are generally linked to slope, wind, elevation, and evapotranspiration. Hydrologic simulations using SWAT modelling and the three satellite rainfall products show that CHIRPS slightly has the daily best performance, with R2 of 0.59 and 0.62, and NSE = 0.54, and the monthly aggregated improved at a monthly level. The water balance components generated at an annual level, using three satellite products, show that CHIRPS outperformed with a ration closer to one, though with a tendency to overestimate up to 3–4× times the data generated from the rainfall gauges. The findings of this study are beneficial in supporting efforts for improving satellite rainfall products and water resource implications. Full article
(This article belongs to the Special Issue The Application of Remote Sensing in Hydrology)
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14 pages, 6209 KiB  
Article
High-Resolution Mapping of Tile Drainage in Agricultural Fields Using Unmanned Aerial System (UAS)-Based Radiometric Thermal and Optical Sensors
by Tewodros Tilahun and Wondwosen M. Seyoum
Hydrology 2021, 8(1), 2; https://doi.org/10.3390/hydrology8010002 - 28 Dec 2020
Cited by 11 | Viewed by 4291
Abstract
With the growing concerns of water quality related to tile drainage in agricultural lands, developing an efficient and cost-effective method of mapping tile drainage is essential. This research aimed to establish mapping of tile drainage systems in agricultural fields using optical and radiometric [...] Read more.
With the growing concerns of water quality related to tile drainage in agricultural lands, developing an efficient and cost-effective method of mapping tile drainage is essential. This research aimed to establish mapping of tile drainage systems in agricultural fields using optical and radiometric thermal sensors mounted on Unmanned Aerial System (UAS). The overarching hypothesis is that in a tile-drained land, spatial distribution of soil water content is affected by tile lines, therefore, contrasting soil temperature signals exist between areas along the tile lines and between the tile lines. Designated flights were conducted to assess the effectiveness of the UAS under various conditions such as rainfall, crop cover, crop maturity and time of the day. Image correction, mosaicking, image enhancements and map production were conducted using Agisoft and ENVI image analysis software. The results showed intermediate growth stage of soybean plants and rainfall helped delineating tile lines. In-situ soil temperature measurements revealed appropriate time of the day (14:00 to 18:00 h) for thermal image detection of the tile lines. The role of soil moisture and plant cover is not resolved, thus, further refinement of the approach considering these factors is necessary to develop efficient mapping techniques of tile drainage using UAS thermal and optical sensors. Full article
(This article belongs to the Special Issue The Application of Remote Sensing in Hydrology)
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