Content uploaded by Aristoteles Tegos
Author content
All content in this area was uploaded by Aristoteles Tegos on Jan 28, 2020
Content may be subject to copyright.
A preview of the PDF is not available
State-of-the-art approach for potential evapotranspiration assessment
Abstract
The aim of the Ph.D thesis is the foundation of a new temperature-based model since simplified PET estimation proves very useful in absence of a complete data set. In this respect, the Parametric model is presented based on a simplified formulation of the well-established Penman-Monteith expression, which only requires mean daily or monthly temperature data. The model was applied at both global and local regions and the outcomes of this new approach are very encouraging, as indicated by the substantially high validation scores of the proposed approach across all examined data sets. In general, the parametric model outperforms well-established methods of the everyday practice. A second analysis which was examined as part of this thesis is related to which spatial techniques is the optimal in order to transform the point scale estimate in regional. A thorough analysis of different geostatistical model was carried out (Kriging, IDW, NN, BSS) and it can be concluded that the IDW even is the most simplify geostatistical model, it can be produce consistent spatial PET results.
Another part of the thesis was the development of an R function for testing the trend significance of time series. The function calculates the trend significance using a modified Mann- Kendall test, which takes into account the well-known physical behavior of the Hurst-Kolmogorov dynamics. The function is tested in 10 stations in Greece, with approximately 50 years of PET data with the use of a recent parametric model.
Finally, a number of hydrological, agronomist and climatologist applications are presented for lighting the robustness of the new Parametric approach in multidiscipline areas.
... In addition, the SPEI better characterizes medium-to long-term droughts, i.e., those occurring in 3-to 6-month periods, than the SPI (Fung et al., 2020;Li et al., 2020). Furthermore, the SPEI is more suitable for use in areas where there is a long-term increase in air temperature and it better illustrates hydrological drought compared to the SPI or Palmer Drought Severity Index -PDSI , 2019Ionita and Nagavciuc, 2021). ...
... Of the many models proposed for estimating ETo, Penman-Monteith's FAO-56 method has been shown to have the highest accuracy (Maeda et al., 2011;Fan and Thomas, 2013;Mattar et al., 2016). Although its main drawback is the extensive data required for input (air temperature, sunshine, relative humidity, wind), Penman-Monteith's FAO-56 method is highly flexible and provides accurate ETo results, even with insufficient data for some climatic elements (Sentelhas et al., 2010;Tegos et al., 2017;Tegos, 2019;Prȃvȃlie et al., 2019Prȃvȃlie et al., , 2020. It works well in different climate types and is widely recommended for calculating evapotranspiration (WMO, 2006;Łabędzki et al., 2011Maeda et al., 2011;Xystrakis and Matzarakis, 2011;Fan and Thomas, 2013;Beguería et al., 2014;Djaman et al., 2018;Yassen et al., 2020). ...
This paper characterizes temporal and spatial changes of humidity in Poland during April–September in 1981–2020 and its decades. For this purpose, absolute values of climatic water balance (PEI) and its standardized values (SPEI) were used, based on data from the Institute of Meteorology and Water Management – National Research Institute (IMWM‑NRI). The PEI component, potential evaporation, was calculated using the Penman-Monteith method. The average PEI totals were found to be negative across most of Poland, with the lowest values below −250 mm in the central part of the country. A particularly pronounced decrease in the PEI and the SPEI was noted during the decade 2011–2020. Temporal variability of the SPEI indicates that in the last two decades there has been a noticeable increase in moisture deficit. This is particularly noticeable from 2011–2020 when changes in the mean SPEI values were statistically significant (α=0.05$\alpha=\nobreak 0.05$). During the period 1981–2020, the 6‑month area-averaged PEI totals showed a negative trend (15 mm/decade). The minimum and maximum PEI values also showed negative trends. The rate of change of the minimum PEI values was almost 3 times higher than that of the maximum PEI values. The trends for the minimum PEI values are statistically significant (α=0.05$\alpha=\nobreak 0.05$). After the year 2000, a higher prevalence of negative SPEI was found, as well as its intensity in the decade 2011–2020. All negative SPEI categories show positive trends. In contrast, positive SPEI categories are characterized by little or no negative trends, as in the case of extremely wet conditions. Frequency trends for all SPEI categories are not statistically significant at α=0.05$\alpha=\nobreak 0.05$.SPEI changes in Poland confirm the observed, increasing trend of moisture deficit in central and southern Europe as a response to increasing air temperature and evapotranspiration.
... The application of the Penman-Monteith method is not possible where detailed meteorological data is not available. In such a case, Lang [74] compares three radiationbased methods (Makkink, Abtew, and Priestley-Taylor) and five temperature-based methods (Hargreaves-Samani, Thornthwaite, Hamon, Linacre, and Blaney-Criddle) with the Penman-Monteith method on a yearly and seasonal scale. The key finding was that radiation-based methods for PET estimation performed better than temperature-based methods among the selected methods in the study area. ...
Evapotranspiration (ET) is a major component of the water cycle and agricultural water balance. Estimation of water consumption over agricultural areas is important for agricultural water resources planning, management, and regulation. It leads to the establishment of a sustainable water balance, mitigates the impacts of water scarcity, as well as prevents the overusing and wasting of precious water resources. As evapotranspiration is a major consumptive use of irrigation water and rainwater on agricultural lands, improvements of water use efficiency and sustainable water management in agriculture must be based on the accurate estimation of ET. Applications of precision and digital agricultural technologies, the integration of advanced techniques including remote sensing and satellite technology, and usage of machine learning algorithms will be an advantage to enhance the accuracy of the ET estimation in agricultural water management. This paper reviews and summarizes the technical development of the available methodologies and explores the advanced techniques in the estimation of ET in agricultural water management and highlights the potential improvements to enhance the accuracy of the ET estimation to achieve precise agricultural water management.
Estimates of extreme water level return periods in river systems are crucial for hydraulic engineering design and planning. Recorded historical water level data of Taiwan’s rivers are not long enough for traditional frequency analyses when predicting extreme water levels for different return periods. In this study, the integration of a one-dimensional flash flood routing hydrodynamic model with the Monte Carlo simulation was developed to predict extreme water levels in the Danshuei River system of northern Taiwan. The numerical model was calibrated and verified with observed water levels using four typhoon events. The results indicated a reasonable agreement between the model simulation and observation data. Seven parameters, including the astronomical tide and surge height at the mouth of the Danshuei River and the river discharge at five gauge stations, were adopted to calculate the joint probability and generate stochastic scenarios via the Monte Carlo simulation. The validated hydrodynamic model driven by the stochastic scenarios was then used to simulate extreme water levels for further frequency analysis. The design water level was estimated using different probability distributions in the frequency analysis at five stations. The design high-water levels for a 200-year return period at Guandu Bridge, Taipei Bridge, Hsin-Hai Bridge, Da-Zhi Bridge, and Chung-Cheng Bridge were 2.90 m, 5.13 m, 6.38 m, 6.05 m, and 9.94 m, respectively. The estimated design water levels plus the freeboard are proposed and recommended for further engineering design and planning.
The use of FAO-56 Penman-Monteith (PM) equation is the recommended equation to estimate potential evapotranspiration. However, when data that satisfy the PM equation is not available or incomplete, the use of PM equation is not an option. In this study, one such method known as Temesgen-Melesse's (TM) method was assessed in relation to the PM equation using data of eight class-I meteorological stations in Ethiopia. In the study, first the problems with this method were identified and the TM equation was modified. The modifications made were replacement of the average maximum temperature at the denominator of the equation varying with time with the average of Tmax for each location (which is a constant for a given location). The Second consideration was calibrating the power of the maximum temperature at the numerator using PM data instead of taking it as a constant 2.5 suggested by the authors in their original equation. Then the three (the original TM, the modified TM with constant power of 2.5 and the modified TM with the power calibrated) methods were fitted against PM equation. Thereafter tests using statistical parameters, model tendency parameters and model performances were carried out. The results indicate the modified TM equation to be better than the original TM equation in terms of percent slope (0.8-12.3 against 1.3-15.1) and the correlation coefficient (R2) and the slope (100% good or satisfactory against 25%). The modified and calibrated equation gave best results in terms of percent error by slope (0.5-2.3), by coefficient of efficiency (100% good or satisfactory), by R2 and slope (100% good or satisfactory) and by mean percent error (5.7-13.6%). Therefore, whenever data that satisfy PM equation are available (even if for limited years), it is better to calibrate the power of the maximum temperature and to consider more decimal places rather than taking 2.5 as suggested by the authors. When data is not available it is better to use the modified TM equation rather than using the original TM equation. The study would benefit those who want to study long-term climate changes and drought patterns, which involve the use of evapotranspiration with limited data that satisfy the PM equation, but have long-term data of temperature.
The use of FAO56-PM is still the preferred method for the estimation of evapotranspiration (ET) regardless of locations. But in places where data that satisfy all the meteorological variables of PM equation are non-existent or missing, the use of either temperature or radiation-based methods is the alternative option, since both radiation and temperature are the main drivers of ET. From the latter two, temperature-based ET estimation methods are still the simplest ones to use. However, there are challenges since some of the parameters used in the temperature-based equations are location dependent. Such location dependence is due to variability in terms of latitude, altitude and other geo-location parameters. Therefore, local calibration of temperature-based methods is necessary to get better estimates of ET. In this study, one temperature-based ET estimation method known as Temesgen-Melesse's (TM) method was assessed in relation to the PM equation using data of ten Class I meteorological stations in Ethiopia. In the study, three different techniques were tested to find location-dependent maximum temperature power ('n') used in TM equation (i.e., to calibrate the method). The first two techniques involve calibration using PM data. In the first case, monthly averaged data that span from 1 to 5 years were used (as five data sets of 12, 24, 36, 48 and 60 months). In the second case, daily values that span from 10 to 30 days were used in three groups of 10-, 20-, and 30-day data sets. In the third technique, an attempt was made to estimate 'n' from the location latitude, altitude and average of the monthly averaged maximum temperature (T̄m x). The results obtained from each technique are given as follows. Calibration from the monthly averaged data gave good 'n' values for all the stations with R 2 values ranging from 0.80 to 0.92. There were no differences in the number of data points (12, 24, 36, 48 and 60 months) used, which means data points of 12 months are sufficient for the calibration. Calibration using the daily data gave satisfactory 'n' results for all the stations tested, though the statistical parameters and performance tests did not give results that are comparable to the monthly averaged values. The results were nearly the same for 10-, 20-, or 20-day data points, which means any one of them can be used for calibration purposes. Estimation of 'n' from latitude, altitude and T̄m x gave results that are comparable to the ones with 'n' calibrated. The percent differences between the 'n' calibrated using data of 131 months and the 'n' values obtained from monthly data and daily data calibrations are less than 0.16% and 0.5%, respectively. The calculated 'n' showed a percent difference of less than 1.1%. Using calculated 'n' is better than performing calibration using daily data. It can also be considered as option when at least 1-year PM data are not available for calibration.
The Versilia plain, a well-known and populated tourist area in northwestern Tuscany, is historically subject to floods. The last hydrogeological disaster of 1996 resulted in 13 deaths and in loss worth hundreds of millions of euros. A valid management of the hydraulic and flooding risks of this territory is therefore mandatory. A 7.5 km-long stretch of the Versilia River was simulated in one-dimension using river cross-sections with the FLO-2D Basic model. Simulations of the channel flow and of its maximum flow rate under different input conditions highlight the key role of topography: uncertainties in the topography introduce much larger errors than the uncertainties in roughness. The best digital elevation model (DEM) available for the area, a 1-m light detection and ranging (LiDAR) DEM dating back to 2008-2010, does not reveal all the hydraulic structures (e.g., the 40 cm thick embankment walls), lowering the maximum flow rate to only 150 m 3 /s, much lower than the expected value of 400 m 3 /s. In order to improve the already existing input topography, three different possibilities were considered: (1) to add the embankment walls to the LiDAR data with a targeted Differential GPS (DGPS) survey, (2) to acquire the cross section profiles necessary for simulation with a targeted DGPS survey, and (3) to achieve a very high resolution topography using structure from motion techniques (SfM) from images acquired using an unmanned aerial vehicle (UAV). The simulations based on all these options deliver maximum flow rates in agreement with estimated values. Resampling of the 10 cm cell size SfM-DSM allowed us to investigate the influence of topographic resolution on hydraulic channel flow, demonstrating that a change in the resolution from 30 to 50 cm alone introduced a 10% loss in the maximum flow rate. UAV-SfM-derived DEMs are low cost, relatively fast, very accurate, and they allow for the monitoring of the channel morphology variations in real time and to keep the hydraulic models updated, thus providing an excellent tool for managing hydraulic and flooding risks.
Weather-related disasters represent a major threat to the sustainable development of society. This study focuses directly on the assessment of the state of spatial information quality for the needs of hydrodynamic modeling. Based on the selected procedures and methods designed for the collection and processing of spatial information, the aim of this study was to assess their qualitative level of suitability for 3D flood event modeling in accordance with the Infrastructure for Spatial Information in the European Community (INSPIRE) Directive. In the evaluation process we entered geodetic measurements and the digital relief model 3.5 (DMR 3.5) available for the territory of the Slovak Republic. The result of this study is an assessment of the qualitative analysis on three levels: (i) main channel and surrounding topography data from geodetic measurements; (ii) digital relief model; and (iii) hydrodynamic/hydraulic modeling. The qualitative aspect of the input data shows the sensitivity of a given model to changes in the input data quality condition. The average spatial error in the determination of a point’s position was calculated as 0.017 m of all measured points along a watercourse and its slope foot and slope edge. Although the declared accuracy of DMR 3.5 is assumed to be ±2.50 m, in some of the sections in the selected area there were differences in elevation up to 4.79 m. For this reason, we needed a combination of DMR 3.5 and geodetic measurements to refine the input model for the process of hydrodynamic modeling. The quality of the hydrological data for the monitored N annual flow levels was of fourth-class reliability for the selected area.
On the equator, Indonesia had very complex geographical, geological, hydrological conditions. It was also traversed by three large plates namely the Eurasian plate, the Indo-Australian plate, and the Pacific plate. Because of the colliding meeting of the three plates, the territory of Indonesia had a variety of topography ranging from hills, mountains, plateaus, lowlands, and basins. The basin found in the Juwana watershed caused frequent flooding every year due to the overflow of Juwana River. The river passed through Kudus and Pati. In the last ten years there had been 179 floods in Juwana River. This study aimed to examine the discharge and distribution of floods based on the return period of floods 2, 5, 10, 25, 50 and 100 years. The research method used was frequency analysis, snyder synthetic unit hydrograph analysis, and hydrodynamic modelling using HEC-RAS 5.0.6 2D (two dimention) with unsteady flow. The findings indicated that on the return period of floods 2, 5, 10, 25, 50, and 100 years, the discharge and distribution of floods were 1169.2 m ³ /with the inundated area of 22898.54 Ha, 1401.7 m ³ /with the inundated area of 25558.51 Ha, 1541 m ³ /with the inundated area of 26916.42 Ha, 1704.9 m ³ /with the inundated area of 28411.52 Ha, 1819.9 m ³ /with the inundated area of 29905.85 Ha, and 1930 m ³ /with the inundated area of 30785 Ha respectively.
Since early 2018 the “Natural Hazards” Section of Geosciences journal has aimed to publish pure, experimental, or applied research that is focused on advancing methodologies, technologies, expertise, and capabilities to detect, characterize, monitor, and model natural hazards and assess their associated risks. This stream of geoscientific research has reached a high degree of specialization and represents a multi-disciplinary research realm. To inaugurate this section, the Special Issue “Key Topics and Future Perspectives in Natural Hazards Research” was launched. After a year and half since the call for papers was initially opened, the special issue is now completed with the editorial introducing the collection of 10 selected papers covering the following hot topics of natural hazards research: (i) trends in publications and research directions at international level; (ii) the role of Big Data in natural disaster management; (iii) assessment of seismic risk through the understanding and quantification of its three components (i.e., hazard, vulnerability and exposure/impact); (iv) climatic/hydro-meteorological hazards (i.e., drought, hurricanes); and (v) scientific analysis of past incidents and disaster forensics (i.e., the Oroville Dam 2017 spillway incident). The present editorial provides a summary of each paper of the collection within the current context of scientific research on natural hazards, pointing out the salient results and key messages.
New mathematical models are developed and corresponding boundary value problems are analytically and numerically solved for Darcian flows in earth (rock)–filled dams, which have a vertical impermeable barrier on the downstream slope. For saturated flow, a 2-D potential model considers a free boundary problem to Laplace’s equation with a traveling-wave phreatic line generated by a linear drawup of a water level in the dam reservoir. The barrier re-directs seepage from purely horizontal (a seepage face outlet) to purely vertical (a no-flow boundary). An alternative model is also used for a hydraulic approximation of a 3-D steady flow when the barrier is only a partial obstruction to seepage. The Poisson equation is solved with respect to Strack’s potential, which predicts the position of the phreatic surface and hydraulic gradient in the dam body. Simulations with HYDRUS, a FEM-code for solving Richards’ PDE, i.e., saturated-unsaturated flows without free boundaries, are carried out for both 2-D and 3-D regimes in rectangular and hexagonal domains. The Barenblatt and Kalashnikov closed-form analytical solutions in non-capillarity soils are compared with the HYDRUS results. Analytical and numerical solutions match well when soil capillarity is minor. The found distributions of the Darcian velocity, the pore pressure, and total hydraulic heads in the vicinity of the barrier corroborate serious concerns about a high risk to the structural stability of the dam due to seepage. The modeling results are related to a “forensic” review of the recent collapse of the spillway of the Oroville Dam, CA, USA.
Recent unprecedented events have highlighted that the existing approach to managing flood risk is inadequate for complex urban systems because of its overreliance on simplistic methods at coarse‐resolution large scales, lack of model physicality using loose hydrologic‐hydraulic coupling, and absence of urban water infrastructure at large scales. Distributed models are a potential alternative as they can capture the complex nature of these events through simultaneous tracking of hydrologic and hydrodynamic processes. However, their application to large‐scale flood mapping and forecasting remains challenging without compromising on spatiotemporal resolution, spatial scale, model accuracy, and local‐scale hydrodynamics. Therefore, it is essential to develop techniques that can address these issues in urban systems while maximizing computational efficiency and maintaining accuracy at large scales. This study presents a physically based but computationally efficient approach for large‐scale (area > 103 km2) flood modeling of extreme events using a distributed model called Interconnected Channel and Pond Routing. The performance of the proposed approach is compared with a hyperresolution‐fixed‐mesh model at 60‐m resolution. Application of the proposed approach reduces the number of computational elements by 80% and the simulation time for Hurricane Harvey by approximately 4.5 times when compared to the fixed‐resolution model. The results show that the proposed approach can simulate the flood stages and depths across multiple gages with a high accuracy (R2 > 0.8). Comparison with Federal Emergency Management Agency building damage assessment data shows a correlation greater than 95% in predicting spatially distributed flooded locations. Finally, the proposed approach can estimate flood stages directly from rainfall for ungaged streams.
Flood risk management strongly relies on inundation models for river basin zoning in flood-prone and risk-free areas. Floodplain zoning is significantly affected by the diverse and concurrent uncertainties that characterize the modelling chain used for producing inundation maps. In order to quantify the relative impact of the uncertainties linked to a lumped hydrological (rainfall–runoff) model and a FLO-2D hydraulic model, a Monte Carlo procedure is proposed in this work. The hydrological uncertainty is associated with the design rainfall estimation method, while the hydraulic model uncertainty is associated with roughness parameterization. This uncertainty analysis is tested on the case study of the Marta coastal catchment in Italy, by comparing the different frequency, extent and depth of inundation simulations associated with varying rainfall forcing and/or hydraulic model roughness realizations. The results suggest a significant predominance of the hydrological uncertainty with respect to the hydraulic one on the overall uncertainty associated with the simulated inundation maps.