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Hydrology
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Technological Advances in Hydroclimatic Observations
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Technological Advances in Hydroclimatic Observations

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

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 11333

Special Issue Editors

Prof. Dr. Ionut Minea

E-Mail Website
Guest Editor
Faculty of Geography and Geology, University of Alexandru Ioan Cuza, Iasi, Romania
Interests: hydrology; hydrological risks; water resources management; hydrogeology; rivers; hydrological modelling
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Martina Zeleňáková

E-Mail Website
Guest Editor
Faculty of Civil Engineering, Technical University of Košice, Vysokoskolska 4, 042 00 Kosice, Slovakia
Interests: water management; water structures; hydrology; rainwater management; environmental impact assessment; environmental risks
Special Issues, Collections and Topics in MDPI journals
Dr. Ivan Radevski

E-Mail Website
Guest Editor
Faculty of Natural Sciences and Mathematics, Institute of Geography, Ss. Cyril and Methodius University, Arhimedova 3, 1000 Skopje, North Macedonia
Interests: water resources management; hydrological risks; rivers; environment; spatial analysis; water resources engineering; hydrological modelling

Special Issue Information

Dear Colleagues,

This Special Issue will expand the researches about technological advances made in the field of hydroclimatic observations. Floods and droughts, sea level rising, variation in groundwater level associated with increasing or decreasing trends of climatic elements (precipitation, temperatures, humidity) these are some phenomena associated with climate change that is manifesting at a global level. All required the identification of some technical solutions regarding the modalities of observation and analysis of the hydroclimatic parameters. This implies improvement and updating of traditional techniques or identifying new solutions which can be used in hydroclimatic observations. At the same time, analysis models based on the interpretation of satellite images and remote sensing have been developed. This Special Issue will try to gather the researches carried out on the observational techniques of the hydroclimatic elements and to identify the new development directions in the field. The results will reveal the most significant contributions to theoretical development and scientific advancement relating to hydroclimatic observations.

Prof. Dr. Ionut Minea
Dr. Martina Zelenakova
Dr. Ivan Radevki
Guest Editors

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

  • hydroclimatic observations
  • techniques
  • new approaches
  • applications
  • modelling

Published Papers (4 papers)

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Research

19 pages, 4825 KiB  
Article
Development of a Regional Gridded Runoff Dataset Using Long Short-Term Memory (LSTM) Networks
by Georgy Ayzel, Liubov Kurochkina, Dmitriy Abramov and Sergei Zhuravlev
Hydrology 2021, 8(1), 6; https://doi.org/10.3390/hydrology8010006 - 08 Jan 2021
Cited by 14 | Viewed by 2727
Abstract
Gridded datasets provide spatially and temporally consistent runoff estimates that serve as reliable sources for assessing water resources from regional to global scales. This study presents LSTM-REG, a regional gridded runoff dataset for northwest Russia based on Long Short-Term Memory (LSTM) networks. LSTM-REG [...] Read more.
Gridded datasets provide spatially and temporally consistent runoff estimates that serve as reliable sources for assessing water resources from regional to global scales. This study presents LSTM-REG, a regional gridded runoff dataset for northwest Russia based on Long Short-Term Memory (LSTM) networks. LSTM-REG covers the period from 1980 to 2016 at a 0.5° spatial and daily temporal resolution. LSTM-REG has been extensively validated and benchmarked against GR4J-REG, a gridded runoff dataset based on a parsimonious regionalization scheme and the GR4J hydrological model. While both datasets provide runoff estimates with reliable prediction efficiency, LSTM-REG outperforms GR4J-REG for most basins in the independent evaluation set. Thus, the results demonstrate a higher generalization capacity of LSTM-REG than GR4J-REG, which can be attributed to the higher efficiency of the proposed LSTM-based regionalization scheme. The developed datasets are freely available in open repositories to foster further regional hydrology research in northwest Russia. Full article
(This article belongs to the Special Issue Technological Advances in Hydroclimatic Observations)
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17 pages, 1598 KiB  
Article
Assessing the Robustness of Pan Evaporation Models for Estimating Reference Crop Evapotranspiration during Recalibration at Local Conditions
by Konstantinos Babakos, Dimitris Papamichail, Panagiotis Tziachris, Vassilios Pisinaras, Kleoniki Demertzi and Vassilis Aschonitis
Hydrology 2020, 7(3), 62; https://doi.org/10.3390/hydrology7030062 - 01 Sep 2020
Cited by 5 | Viewed by 2584
Abstract
A classic method for assessing the reference crop evapotranspiration (ETo) is the pan evaporation (Epan) method that uses Epan measurements and pan coefficient (kp) models, which can be functions of relative humidity (RH), wind speed (u [...] Read more.
A classic method for assessing the reference crop evapotranspiration (ETo) is the pan evaporation (Epan) method that uses Epan measurements and pan coefficient (kp) models, which can be functions of relative humidity (RH), wind speed (u2), and temperature (T). The aim of this study is to present a methodology for evaluating the robustness of regression coefficients associated to climate parameters (RH, u2, and T) in pan method models during recalibration at local conditions. Two years of daily data from April to October (warm season) of meteorological parameters, Epan measurements from class A pan evaporimeter and ETo estimated by ASCE-standardized method for the climatic conditions of Thessaloniki (Greece, semi-arid environment), were used. The regression coefficients of six general nonlinear (NLR) regression Epan models were analyzed through recalibration using a technique called “random cross-validation nonlinear regression RCV-NLR” that produced 1000 random splits of the initial dataset into calibration and validation sets using a constant proportion (70% and 30%, respectively). The variance of the regression coefficients was analyzed based on the 95% interval of the highest posterior density distribution. NLR models that included coefficients with a 95% HPD interval that fluctuates in both positive and negative values were considered nonrobust. The machine-learning technique of random forests (RF) was also used to build a RF model that includes Epan, u2, RH, and T parameters. This model was used as a benchmark for evaluating the predictive accuracy of NLR models but, also, for assessing the relative importance of the predictor climate variables if they were all included in one NLR model. The findings of this study indicated that locally calibrated NLR functions that use only the Epan parameter presented better results, while the inclusion of additional climate parameters was redundant and led to underfitting. Full article
(This article belongs to the Special Issue Technological Advances in Hydroclimatic Observations)
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46 pages, 26057 KiB  
Article
GEO-CWB: GIS-Based Algorithms for Parametrising the Responses of Catchment Dynamic Water Balance Regarding Climate and Land Use Changes
by Salem S. Gharbia, Laurence Gill, Paul Johnston and Francesco Pilla
Hydrology 2020, 7(3), 39; https://doi.org/10.3390/hydrology7030039 - 13 Jul 2020
Cited by 4 | Viewed by 2945
Abstract
Parametrising the spatially distributed dynamic catchment water balance is a critical factor in studying the hydrological system responses to climate and land use changes. This study presents the development of a geographic information system (GIS)-based set of algorithms (geographical spatially distributed water balance [...] Read more.
Parametrising the spatially distributed dynamic catchment water balance is a critical factor in studying the hydrological system responses to climate and land use changes. This study presents the development of a geographic information system (GIS)-based set of algorithms (geographical spatially distributed water balance model (GEO-CWB)), which is developed from integrating physical, statistical, and machine learning models. The GEO-CWB tool has been developed to simulate and predict future spatially distributed dynamic water balance using GIS environment at the catchment scale in response to the future changes in climate variables and land use through a user-friendly interface. The tool helps in bridging the gap in quantifying the high-resolution dynamic water balance components for the large catchments by reducing the computational costs. Also, this paper presents the application and validation of GEO-CWB on the Shannon catchment in Ireland as an example of a large and complicated hydrological system. It can be concluded that climate and land use changes have significant effects on the spatial and temporal patterns of the different water balance components of the catchment. Full article
(This article belongs to the Special Issue Technological Advances in Hydroclimatic Observations)
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14 pages, 3284 KiB  
Article
Temporal Analysis of Daily and 10 Minutes of Rainfall of Poprad Station in Eastern Slovakia
by Adam Repel, Vinayakam Jothiprakash, Martina Zeleňáková, Helena Hlavatá and Ionut Minea
Hydrology 2020, 7(2), 32; https://doi.org/10.3390/hydrology7020032 - 11 Jun 2020
Cited by 4 | Viewed by 2371
Abstract
The aim of this paper is the application of temporal analysis of daily and 10 min of rainfall data from Poprad station, located in Eastern Slovakia. There are two types of data used in the analysis, firstly, a daily time step data, manually [...] Read more.
The aim of this paper is the application of temporal analysis of daily and 10 min of rainfall data from Poprad station, located in Eastern Slovakia. There are two types of data used in the analysis, firstly, a daily time step data, manually collected between the years 1951 and 2018 and secondly, 10 min of data, automatically collected between the years 2000 and 2018. For proper comparability, the automatically collected data has been recalculated to the daily form. After a comparison of the sets of data, manually collected daily data has been used in further analysis. The main analysis can be divided into two sections. The first section consists of basic statistics (mean, standard deviation, etc.) and the second section of descriptive statistics, where the subjects of examination were trend, stationarity, homogeneity, periodicity and noise. The results of the basic statistics outlined trend behavior in the data meaning that the annual total rainfall for the period 1951–2018 is slightly increasing but the further investigation supported by the methods of descriptive statistics refuted this thesis. The number of rainy days is decreasing but maximum rainfall intensity is increasing year by year, indicating that total rainfall is happening in lesser and lesser days, with an increase in the number of 0 rainfall days. The results demonstrated no presence of the trend or only a weak trend in daily time step, but a significant increasing trend in annual rainfall. Tests of stationarity proved that the data are stationary and, therefore, suitable for any hydrologic analysis. The tests of homogeneity showed no breakpoints in the data. The interesting result was demonstrated by the periodicity test, which showed exactly a 365.25 days’ period, while 0.25 indicates a leap year. As a summary for the Poprad station, there is no tendency of increasing of daily average rainfall, but slight increasing trend of total annual rainfall, the summer season has the highest ratio on total precipitation per year, September and October are the months with the highest numbers of days without rain. Full article
(This article belongs to the Special Issue Technological Advances in Hydroclimatic Observations)
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