Search

Your search keyword '"Tommaso Picciafuoco"' showing total 13 results
Start Over Author "Tommaso Picciafuoco"
13 results on '"Tommaso Picciafuoco"'

1. A Pedotransfer Function for Field-Scale Saturated Hydraulic Conductivity of a Small Watershed

Author

Tommaso Picciafuoco, Renato Morbidelli, Alessia Flammini, Carla Saltalippi, Corrado Corradini, Peter Strauss, and Günter Blöschl

Subjects
Environmental sciences, GE1-350, Geology, QE1-996.5
Abstract

Classical experimental techniques to determine point values of saturated hydraulic conductivity () are complex and time consuming; therefore, the development of pedotransfer functions, PTFs, to derive from easily available soil properties is of great importance. However, PTFs have been generally developed at the local scale, while hydrological modeling requires estimates at larger scales. A small Austrian catchment, where detailed soil characteristics were available, was selected to address this issue. Values of field-scale saturated hydraulic conductivity (<>), observed in a number of catchment areas by double-ring infiltrometers, were used to develop two PTFs, one by multiple linear regression (PTF) and one by ridge regression (PTF). Training and validation of the PTFs in the monitored areas indicate that the PTF provides better outcomes with smaller average errors. This suggests that the ridge regression is a valid alternative to the classical multiple linear regression technique. Predictions of <> by the PTFs in the remaining areas, where infiltration measurements were not performed, were also made to obtain a map of <> for the whole catchment. Two alternative approaches were used: Method A—soil properties were first interpolated and then the PTFs applied; Method B—the PTFs were first applied to sites with available soil properties and then interpolated. The maps of <> obtained by the PTF are not representative of the <> spatial variability. On the other hand, the map generated by the PTF with Method A is consistent with catchment morphology and soil characteristics.

Published
2019
Full Text
View/download PDF

2. Characteristics of the Underestimation Error of Annual Maximum Rainfall Depth Due to Coarse Temporal Aggregation

Author

Renato Morbidelli, Carla Saltalippi, Alessia Flammini, Tommaso Picciafuoco, Jacopo Dari, and Corrado Corradini

Subjects
rainfall data, temporal aggregation, annual maximum rainfall depths, underestimated errors, Meteorology. Climatology, QC851-999
Abstract

This study analyzed all characteristics of the error committed in evaluating annual maximum rainfall depth, Hd, associated with a given duration, d, when data with coarse temporal aggregation, ta, were used. It is well known that when ta = 1 min, this error is practically negligible while coarser temporal aggregations can determine underestimation for a single Hd up to 50% and for the average value of sufficiently numerous series of Hd up to 16.67%. By using a mathematical relation between average underestimation error and the ratio ta/d, each Hd value belonging to a specific series could be corrected through deterministic or stochastic approaches. With a deterministic approach, an average correction was identically applied to all Hd values with the same ta and d while, for a stochastic correction, a thorough knowledge of the statistical characteristics of the underestimation error was required. Accordingly, in this work, rainfall data derived from many stations in central Italy were analyzed and it was assessed that single and average errors, which were both assumed as random variables, followed exponential and normal distributions, respectively. Furthermore, the single underestimation error was also found inversely correlated to the corresponding annual maximum rainfall depth.

Published
2018
Full Text
View/download PDF

3. On the estimation of spatially representative plot scale saturated hydraulic conductivity in an agricultural setting

Author

Peter Strauss, Tommaso Picciafuoco, Alessia Flammini, Corrado Corradini, Günter Blöschl, Carla Saltalippi, and Renato Morbidelli

Subjects
Local measurements, Plot-scale estimate, Saturated hydraulic conductivity, Spatial variability, 010504 meteorology & atmospheric sciences, Coefficient of variation, 0207 environmental engineering, Soil science, 02 engineering and technology, 01 natural sciences, Infiltration (hydrology), Hydraulic conductivity, Environmental science, Infiltrometer, Geometric mean, 020701 environmental engineering, Surface runoff, Uncertainty analysis, 0105 earth and related environmental sciences, Water Science and Technology
Abstract

Spatially representative estimates of saturated hydraulic conductivity, Ks, are needed for simulating catchment scale surface runoff and infiltration. Classical methods for measuring Ks are time-consuming so sampling campaigns need to be designed economically. Important insights can be obtained by experiments directed to understand the controls of Ks in an agricultural setting and identify the minimum number of samples required for estimating representative plot scale Ks. In this study, a total of 131 double-ring infiltrometer measurements were made on 12 plots in a small Austrian catchment. A statistical analysis of Ks across the catchment suggests Ks to be only slightly influenced by physical and topographical soil characteristics while land use is the main control. The highest values of Ks were observed in arable fields, with a median of about 3 times and a coefficient of variation (CV) of about 75% of those in grassland areas. An uncertainty analysis aimed at determining the minimum number of Ks measurements necessary for estimating the geometric mean of Ks over a given area with a specified accuracy suggests that, beyond a specific and plot-size dependent number of measurements, the benefit of any extra measurement is small. The confidence interval of the geometric mean of Ks decreases with the number of measurements and increases with the size of the plot sampled. Applications of these findings for designing field campaigns are discussed.

Published
2019
Full Text
View/download PDF

4. In situ measurements of soil saturated hydraulic conductivity: Assessment of reliability through rainfall-runoff experiments

Author

Rao S. Govindaraju, Tommaso Picciafuoco, Carla Saltalippi, Renato Morbidelli, Alessia Flammini, Marco Cifrodelli, and Corrado Corradini

Subjects
Hydrology, In situ, Measurement method, rainfall–runoff, Rainfall runoff, 0208 environmental biotechnology, Soil science, permeameters, 02 engineering and technology, 020801 environmental engineering, Infiltration (hydrology), infiltration modelling, Hydraulic conductivity, Environmental science, Infiltrometer, Surface runoff, Water Science and Technology, Permeameter
Abstract

The saturated hydraulic conductivity, Ks, is a soil property that has a key role in the partitioning of rainfall into surface runoff and infiltration. The commonly used instruments and methods for in situ measurements of Ks have frequently provided conflicting results. Comparison of Ks estimates obtained by three classical devices—namely, the double ring infiltrometer (DRI), the Guelph version of the constant-head well permeameter (GUELPH-CHP) and the CSIRO version of the tension permeameter (CSIRO-TP) is presented. A distinguishing feature in this study is the use of steady deep flow rates, obtained from controlled rainfall–runoff experiments, as benchmark values of Ks at local and field-plot scales, thereby enabling an assessment of these methods in reliably reproducing repeatable values and in their capability of determining plot-scale variation of Ks. We find that the DRI grossly overestimates Ks, the GUELPH-CHP gives conflicting estimates of Ks with substantial overestimation in laboratory experiments and underestimation at the plot scale, whereas the CSIRO-TP yields average Ks values with significant errors of 24% in the plot scale experiment and 66% in laboratory experiments. Although the DRI would likely yield a better estimate of the nature of variability than the GUELPH-CHP and CSIRO-TP, a separate calibration may be warranted to correct for the overestimation of Ks values. The reasons for such discrepancies within and between the measurement methods are not yet fully understood and serve as motivation for future work to better characterize the uncertainty associated with individual measurements of Ks using these methods and the characterization of field scale variability from multiple local measurements.

Published
2017
Full Text
View/download PDF

5. A Pedotransfer Function for Field-Scale Saturated Hydraulic Conductivity of a Small Watershed

Author

Alessia Flammini, Günter Blöschl, Carla Saltalippi, Renato Morbidelli, Peter Strauss, Corrado Corradini, and Tommaso Picciafuoco

Subjects
lcsh:GE1-350, lcsh:Geology, Watershed, Scale (ratio), Hydraulic conductivity, Field (physics), Pedotransfer function, lcsh:QE1-996.5, Soil Science, Soil science, lcsh:Environmental sciences, Mathematics
Abstract

Classical experimental techniques to determine point values of saturated hydraulic conductivity () are complex and time consuming; therefore, the development of pedotransfer functions, PTFs, to derive from easily available soil properties is of great importance. However, PTFs have been generally developed at the local scale, while hydrological modeling requires estimates at larger scales. A small Austrian catchment, where detailed soil characteristics were available, was selected to address this issue. Values of field-scale saturated hydraulic conductivity (<>), observed in a number of catchment areas by double-ring infiltrometers, were used to develop two PTFs, one by multiple linear regression (PTF) and one by ridge regression (PTF). Training and validation of the PTFs in the monitored areas indicate that the PTF provides better outcomes with smaller average errors. This suggests that the ridge regression is a valid alternative to the classical multiple linear regression technique. Predictions of <> by the PTFs in the remaining areas, where infiltration measurements were not performed, were also made to obtain a map of <> for the whole catchment. Two alternative approaches were used: Method A—soil properties were first interpolated and then the PTFs applied; Method B—the PTFs were first applied to sites with available soil properties and then interpolated. The maps of <> obtained by the PTF are not representative of the <> spatial variability. On the other hand, the map generated by the PTF with Method A is consistent with catchment morphology and soil characteristics.

Published
2019

6. Laboratory investigation on the role of slope on infiltration over grassy soils

Author

Tommaso Picciafuoco, Renato Morbidelli, Carla Saltalippi, Rao S. Govindaraju, Marco Cifrodelli, Alessia Flammini, and Corrado Corradini

Subjects
Hillslope hydrology, Infiltration experiments, Infiltration modeling, Surface runoff, 0208 environmental biotechnology, Soil science, 02 engineering and technology, Surface finish, complex mixtures, 020801 environmental engineering, Infiltration (hydrology), Hydraulic conductivity, Soil water, Environmental science, Geotechnical engineering, Subsurface flow, Saturation (chemistry), Vegetation and slope stability, Water Science and Technology
Abstract

Even though natural surfaces are rarely horizontal, infiltration modeling has been primarily confined to horizontal surfaces, and there are not enough studies to clarify the effects of slope on the partition of rainfall into surface and subsurface water. Besides, previous experimental results on the effects of slope provide conflicting conclusions perhaps because of the existence of erosion and crust formation. In this study, new laboratory experiments, performed in the absence of the last two processes, highlight the effect of the slope angle, γ, on infiltration into a grassy soil. The results are compared with those from previous experiments performed on a bare soil and interpreted in terms of an effective soil saturated hydraulic conductivity, Ke (γ). The grassy soil dampens the variation of Ke with γ compared to bare soil. For example, for γ = 10°, the reduction of the gravitational infiltration with respect to the saturation condition was ∼80% for the bare soil, while we find it to be ∼20% for the grassy soil. Finally, we point out that the presence of grass does not affect the results through the development of a two layered soil, but through a substantial variation of roughness.

Published
2016
Full Text
View/download PDF

7. Development and Analysis of Soil Water Infiltration Global Database

Author

Mehdi Rahmati, Lutz Weihermüller, Jan Vanderborght, Yakov A. Pachepsky, Lili Mao, Seyed Hamidreza Sadeghi, Niloofar Moosavi, Hossein Kheirfam, Carsten Montzka, Kris Van Looy, Brigitta Toth, Zeinab Hazbavi, Wafa Al Yamani, Ammar A. Albalasmeh, Ma'in Z. Alghzawi, Rafael Angulo-Jaramillo, Antônio Celso Dantas Antonino, George Arampatzis, Robson André Armindo, Hossein Asadi, Yazidhi Bamutaze, Jordi Batlle-Aguilar, Beatrice Bechet, Fabian Becker, Günter Blöschl, Klaus Bohne, Isabelle Braud, Clara Castellano, Artemi Cerdà, Maha Chalhoub, Rogerio Cichota, Milena Císlerová, Brent Clothier, Yves Coquet, Wim Cornelis, Corrado Corradini, Artur Paiva Coutinho, Muriel Bastista de Oliveira, José Ronaldo de Macedo, Matheus Fonseca Durães, Hojat Emami, Iraj Eskandari, Asghar Farajnia, Alessia Flammini, Nándor Fodor, Mamoun Gharaibeh, Mohamad Hossein Ghavimipanah, Teamrat A. Ghezzehei, Simone Giertz, Evangelos G Hatzigiannakis, Rainer Horn, Juan José Jiménez, Diederik Jacques, Saskia Deborah Keesstra, Hamid Kelishadi, Mahboobeh Kiani-Harchegani, Mehdi Kouselou, Madan Kumar Jha, Laurent Lassabatere, Xiaoyan Li, Mark A. Liebig, Lubomír Lichner, María Victoria López, Deepesh Machiwal, Dirk Mallants, Micael Stolben Mallmann, Jean Dalmo de Oliveira Marques, Miles R. Marshall, Jan Mertens, Félicien Meunier, Mohammad Hossein Mohammadi, Binayak P. Mohanty, Mansonia Pulido Moncada, Suzana Montenegro, Renato Morbidelli, David Moret-Fernández, Ali Akbar Moosavi, Mohammad Reza Mosaddeghi, Seyed Bahman Mousavi, Hasan Mozaffari, Kamal Nabiollahi, Mohammad Reza Neyshabouri, Marta Vasconcelos Ottoni, Theophilo Benedicto Ottoni Filho, Mohammad Reza Pahlavan Rad, Andreas Panagopoulos, Stephan Peth, Pierre-Emmanuel Peyneau, Tommaso Picciafuoco, Jean Poesen, Manuel Pulido, Dalvan José Reinert, Sabine Reinsch, Meisam Rezaei, Francis Parry Roberts, David Robinson, Jesús Rodrigo-Comino, Otto Corrêa Rotunno Filho, Tadaomi Saito, Hideki Suganuma, Carla Saltalippi, Renáta Sándor, Brigitta Schütt, Manuel Seeger, Nasrollah Sepehrnia, Ehsan Sharifi Moghaddam, Manoj Shukla, Shiraki Shutaro, Ricardo Sorando, Ajayi Asishana Stanley, Peter Strauss, Zhongbo Su, Ruhollah Taghizadeh-Mehrjardi, Encarnación Taguas, Wenceslau Geraldes Teixeira, Ali Reza Vaezi, Mehdi Vafakhah, Tomas Vogel, Iris Vogeler, Jana Votrubova, Steffen Werner, Thierry Winarski, Deniz Yilmaz, Michael H. Young, Steffen Zacharias, Yijian Zeng, Ying Zhao, Hong Zhao, and Harry Vereecken

Abstract

In this paper, we present and analyze a global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database, for the first time. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and USA. In addition to its global spatial coverage, the collected infiltration curves cover a time span of research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use were gathered along with the infiltration data, which makes the database valuable for the development of pedo-transfer functions for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements (~76 %) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on the land use is available for 76 % of experimental sites with agricultural land use as the dominant type (~40 %). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for use by public domain only and can be copied freely by referencing it. Supplementary data are available at doi:10.1594/PANGAEA.885492. Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend/update the SWIG by uploading new data to it.

Published
2018
Full Text
View/download PDF

8. Supplementary material to 'Development and Analysis of Soil Water Infiltration Global Database'

Author

Mehdi Rahmati, Lutz Weihermüller, Jan Vanderborght, Yakov A. Pachepsky, Lili Mao, Seyed Hamidreza Sadeghi, Niloofar Moosavi, Hossein Kheirfam, Carsten Montzka, Kris Van Looy, Brigitta Toth, Zeinab Hazbavi, Wafa Al Yamani, Ammar A. Albalasmeh, Ma'in Z. Alghzawi, Rafael Angulo-Jaramillo, Antônio Celso Dantas Antonino, George Arampatzis, Robson André Armindo, Hossein Asadi, Yazidhi Bamutaze, Jordi Batlle-Aguilar, Beatrice Bechet, Fabian Becker, Günter Blöschl, Klaus Bohne, Isabelle Braud, Clara Castellano, Artemi Cerdà, Maha Chalhoub, Rogerio Cichota, Milena Císlerová, Brent Clothier, Yves Coquet, Wim Cornelis, Corrado Corradini, Artur Paiva Coutinho, Muriel Bastista de Oliveira, José Ronaldo de Macedo, Matheus Fonseca Durães, Hojat Emami, Iraj Eskandari, Asghar Farajnia, Alessia Flammini, Nándor Fodor, Mamoun Gharaibeh, Mohamad Hossein Ghavimipanah, Teamrat A. Ghezzehei, Simone Giertz, Evangelos G Hatzigiannakis, Rainer Horn, Juan José Jiménez, Diederik Jacques, Saskia Deborah Keesstra, Hamid Kelishadi, Mahboobeh Kiani-Harchegani, Mehdi Kouselou, Madan Kumar Jha, Laurent Lassabatere, Xiaoyan Li, Mark A. Liebig, Lubomír Lichner, María Victoria López, Deepesh Machiwal, Dirk Mallants, Micael Stolben Mallmann, Jean Dalmo de Oliveira Marques, Miles R. Marshall, Jan Mertens, Félicien Meunier, Mohammad Hossein Mohammadi, Binayak P. Mohanty, Mansonia Pulido Moncada, Suzana Montenegro, Renato Morbidelli, David Moret-Fernández, Ali Akbar Moosavi, Mohammad Reza Mosaddeghi, Seyed Bahman Mousavi, Hasan Mozaffari, Kamal Nabiollahi, Mohammad Reza Neyshabouri, Marta Vasconcelos Ottoni, Theophilo Benedicto Ottoni Filho, Mohammad Reza Pahlavan Rad, Andreas Panagopoulos, Stephan Peth, Pierre-Emmanuel Peyneau, Tommaso Picciafuoco, Jean Poesen, Manuel Pulido, Dalvan José Reinert, Sabine Reinsch, Meisam Rezaei, Francis Parry Roberts, David Robinson, Jesús Rodrigo-Comino, Otto Corrêa Rotunno Filho, Tadaomi Saito, Hideki Suganuma, Carla Saltalippi, Renáta Sándor, Brigitta Schütt, Manuel Seeger, Nasrollah Sepehrnia, Ehsan Sharifi Moghaddam, Manoj Shukla, Shiraki Shutaro, Ricardo Sorando, Ajayi Asishana Stanley, Peter Strauss, Zhongbo Su, Ruhollah Taghizadeh-Mehrjardi, Encarnación Taguas, Wenceslau Geraldes Teixeira, Ali Reza Vaezi, Mehdi Vafakhah, Tomas Vogel, Iris Vogeler, Jana Votrubova, Steffen Werner, Thierry Winarski, Deniz Yilmaz, Michael H. Young, Steffen Zacharias, Yijian Zeng, Ying Zhao, Hong Zhao, and Harry Vereecken

Published
2018
Full Text
View/download PDF

9. Characteristics of the underestimation error of annual maximum rainfall depth due to coarse temporal aggregation

Author

Carla Saltalippi, Renato Morbidelli, Jacopo Dari, Alessia Flammini, Tommaso Picciafuoco, and Corrado Corradini

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, Series (mathematics), Rainfall data, 0208 environmental biotechnology, Annual maximum rainfall depths, Underestimated errors, 02 engineering and technology, Mathematical relation, lcsh:QC851-999, Environmental Science (miscellaneous), 01 natural sciences, 020801 environmental engineering, Exponential function, Normal distribution, Temporal aggregation, Statistics, lcsh:Meteorology. Climatology, Random variable, 0105 earth and related environmental sciences, Mathematics
Abstract

This study analyzed all characteristics of the error committed in evaluating annual maximum rainfall depth, Hd, associated with a given duration, d, when data with coarse temporal aggregation, ta, were used. It is well known that when ta = 1 min, this error is practically negligible while coarser temporal aggregations can determine underestimation for a single Hd up to 50% and for the average value of sufficiently numerous series of Hd up to 16.67%. By using a mathematical relation between average underestimation error and the ratio ta/d, each Hd value belonging to a specific series could be corrected through deterministic or stochastic approaches. With a deterministic approach, an average correction was identically applied to all Hd values with the same ta and d while, for a stochastic correction, a thorough knowledge of the statistical characteristics of the underestimation error was required. Accordingly, in this work, rainfall data derived from many stations in central Italy were analyzed and it was assessed that single and average errors, which were both assumed as random variables, followed exponential and normal distributions, respectively. Furthermore, the single underestimation error was also found inversely correlated to the corresponding annual maximum rainfall depth.

Published
2018

10. Experimental Analyses of the Evaporation Dynamics in Bare Soils under Natural Conditions

Author

Corrado Corradini, Tommaso Picciafuoco, Alessia Flammini, Renato Morbidelli, Juan Vicente Giráldez, and Carla Saltalippi

Subjects
Hydrogeology, 0208 environmental biotechnology, Evaporation, evaporation dynamics, hydrological balance, soil water content, bare soil, Soil science, soil water content, 02 engineering and technology, 020801 environmental engineering, Field capacity, bare soil, Loam, Soil water, evaporation dynamics, Environmental science, Stage (hydrology), hydrological balance, Water content, Pan evaporation, Water Science and Technology, Civil and Structural Engineering
Abstract

In spite of recent progresses in evaporation estimate through advanced models and laboratory experiments, the drying process of bare soils through its successive stages remains difficult to predict. A study which addresses evaporation modeling in natural bare soils is presented. It relies upon hydro-meteorological measurements performed in a plot with a bare silt loam soil maintained in natural conditions. The following steps are involved: estimate of daily actual evaporation, Ea, through the hydrological balance, scaling with pan evaporation measurements, Epan, and analysis of the relation of Ea/Epan with the soil moisture vertical profile. The results enable us (1) to check the occurrence of the first stage of the evaporation process, characterized by not limited-soil water supply and high evaporative rates, and (2) to identify the transition from the first to the second stage, with decreasing soil water-limited Ea values. The last point requires the introduction of a soil water content threshold at 5 cm depth, that is associated with the soil field capacity. The adopted procedure provides insights on the soil water dynamics at depths differently involved through the successive stages of the evaporative process. Finally, indications on the use of pan evaporation measurements in evaporative rate estimate at least during the first stage of the process are also given.

Published
2018

11. Reassessment of a semi-analytical field-scale infiltration model through experiments under natural rainfall events

Author

Renato Morbidelli, Tommaso Picciafuoco, Carla Saltalippi, Corrado Corradini, Rao S. Govindaraju, and Alessia Flammini

Subjects
Variables, media_common.quotation_subject, 0208 environmental biotechnology, Monte Carlo method, Soil science, 02 engineering and technology, Expected value, Infiltration (HVAC), 020801 environmental engineering, Areal infiltration, Infiltration modelling, Rainfall-runoff experiments, Infiltration modelling, Rainfall-runoff experiments, Areal infiltration, Loam, Soil water, Environmental science, Surface runoff, Water content, Water Science and Technology, media_common
Abstract

Operative distributed/semi-distributed rainfall-runoff formulations need a mathematically tractable component for estimating the expected areal-average infiltration rate, I , while point infiltration models are usually adopted for this purpose. A model for I , suitable for hydrological applications, was proposed by Morbidelli et al. (2006, Hydrological Processes, 20: 1465–1481). The main model tenet is the use of cumulative infiltration as an independent variable and replacement of time by its expected value. While this model - as with many other models for field-scale infiltration - was tested through Monte Carlo methods, it remains untested with experimental observations. In this study, a reassessment of the model’s applicability is conducted through experimental evidence from several rainfall-runoff events observed under natural conditions at the plot scale over a slight slope characterized by a silty loam soil. During each experiment rainfall rate, surface runoff at the plot outlet and soil water content vertical profiles were monitored at short time intervals. An overall analysis of our results suggests that the model reliably simulates I and surface runoff as functions of time and is also suitable for applications under time-dependent rainfall events. The process of redistribution under rainfall hiatus is not addressed by this model.

Published
2018

12. Effect of temporal aggregation on the estimate of annual maximum rainfall depths for the design of hydraulic infrastructure systems

Author

Alessia Flammini, M. Carmen Casas-Castillo, Sean Wilkinson, Marco Cifrodelli, Carla Saltalippi, Renato Morbidelli, Corrado Corradini, Hayley J. Fowler, Tommaso Picciafuoco, and Universitat Politècnica de Catalunya. Departament de Física

Subjects
Hydrology, Series (stratigraphy), Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia [Àrees temàtiques de la UPC], Depth-duration-frequency curves, Física [Àrees temàtiques de la UPC], Rainfall data, 0208 environmental biotechnology, Precipitacions (Meteorologia)--Mesurament, Annual maximum rainfall depths, 02 engineering and technology, Atmospheric sciences, 020801 environmental engineering, Pluja, Rain and rainfall, Temporal aggregation, Rainfall data, Temporal aggregation, Annual maximum rainfall depths, Depth-duration-frequency curves, Environmental science, Precipitation (Meteorology)--Measurement, Water Science and Technology
Abstract

For a few decades the local rainfall measurements are generally obtained by tipping bucket sensors, that allow to record each tipping time corresponding to a well-known rain depth. However, a considerable part of rainfall data to be used in the hydrological practice is available in aggregated form within constant time intervals. This can produce undesirable effects, like the underestimation of the annual maximum rainfall depth, Hd, associated with a given duration, d, that is the basic quantity in the development of rainfall depth-duration-frequency relationships. The errors in the evaluation of Hd from data characterized by a coarse temporal aggregation, ta, and a procedure to reduce the non-homogeneity of the Hd series are here investigated. Our results show that for ta = 1 min the underestimation is practically negligible, whereas for larger temporal aggregations with d = ta the error in a single Hd can reach values up to 50% and in a series of Hd in the average up to 17%. Relationships between the non-dimensional ratio ta/d and the average underestimation of Hd, derived through continuous rainfall data observed in many stations of Central Italy, are presented to overcome this issue. These equations allow to improve the Hd estimates and the associated depth-duration-frequency curves at least in areas with similar climatic conditions. The effect of the correction of the Hd series on the rainfall depth-duration-frequency curves is quantified. Our results indicate that the improvements obtained by the proposed procedure are of the order of 10%.

Published
2017

13. Development and analysis of the Soil Water Infiltration Global database

Author

M. Rahmati, L. Weihermüller, J. Vanderborght, Y. A. Pachepsky, L. Mao, S. H. Sadeghi, N. Moosavi, H. Kheirfam, C. Montzka, K. Van Looy, B. Toth, Z. Hazbavi, W. Al Yamani, A. A. Albalasmeh, M. Z. Alghzawi, R. Angulo-Jaramillo, A. C. D. Antonino, G. Arampatzis, R. A. Armindo, H. Asadi, Y. Bamutaze, J. Batlle-Aguilar, B. Béchet, F. Becker, G. Blöschl, K. Bohne, I. Braud, C. Castellano, A. Cerdà, M. Chalhoub, R. Cichota, M. Císlerová, B. Clothier, Y. Coquet, W. Cornelis, C. Corradini, A. P. Coutinho, M. B. de Oliveira, J. R. de Macedo, M. F. Durães, H. Emami, I. Eskandari, A. Farajnia, A. Flammini, N. Fodor, M. Gharaibeh, M. H. Ghavimipanah, T. A. Ghezzehei, S. Giertz, E. G. Hatzigiannakis, R. Horn, J. J. Jiménez, D. Jacques, S. D. Keesstra, H. Kelishadi, M. Kiani-Harchegani, M. Kouselou, M. Kumar Jha, L. Lassabatere, X. Li, M. A. Liebig, L. Lichner, M. V. López, D. Machiwal, D. Mallants, M. S. Mallmann, J. D. de Oliveira Marques, M. R. Marshall, J. Mertens, F. Meunier, M. H. Mohammadi, B. P. Mohanty, M. Pulido-Moncada, S. Montenegro, R. Morbidelli, D. Moret-Fernández, A. A. Moosavi, M. R. Mosaddeghi, S. B. Mousavi, H. Mozaffari, K. Nabiollahi, M. R. Neyshabouri, M. V. Ottoni, T. B. Ottoni Filho, M. R. Pahlavan-Rad, A. Panagopoulos, S. Peth, P.-E. Peyneau, T. Picciafuoco, J. Poesen, M. Pulido, D. J. Reinert, S. Reinsch, M. Rezaei, F. P. Roberts, D. Robinson, J. Rodrigo-Comino, O. C. Rotunno Filho, T. Saito, H. Suganuma, C. Saltalippi, R. Sándor, B. Schütt, M. Seeger, N. Sepehrnia, E. Sharifi Moghaddam, M. Shukla, S. Shutaro, R. Sorando, A. A. Stanley, P. Strauss, Z. Su, R. Taghizadeh-Mehrjardi, E. Taguas, W. G. Teixeira, A. R. Vaezi, M. Vafakhah, T. Vogel, I. Vogeler, J. Votrubova, S. Werner, T. Winarski, D. Yilmaz, M. H. Young, S. Zacharias, Y. Zeng, Y. Zhao, H. Zhao, H. Vereecken, Institute of Bio- and Geosciences [Jülich] (IBG), Forschungszentrum Jülich GmbH, Department of Soil Science and Engineering, Faculty of Agriculture, University of Maragheh, ISMC International Soil Modeling Consortium, Institute of Bio and Geosciences Forschungszentrum Jülich, USDA-ARS : Agricultural Research Service, Chinese Academy of Agricultural Sciences (CAAS), Tarbiat Modares University [Tehran], Urmia University, Hungarian Academy of Sciences (MTA), University of Pannonia, UAE University, Jordan University of Science and Technology [Irbid, Jordan], Laboratoire d'Ecologie des Hydrosystèmes Naturels et Anthropisés (LEHNA), Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Centre National de la Recherche Scientifique (CNRS), Centro Acadêmico do Agreste (CAA), Universidade Federal de Pernambuco [Recife] (UFPE), Hellenic Agricultural Organization, Soil and Water Resources Institute, Department of Physics (DFI), Federal University of Lavras (UFLA), University of Tehran, Makerere University (MAK), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Innovative Groundwater Solutions, Interactions et dynamique des environnements de surface (IDES), Université Paris-Sud - Paris 11 (UP11)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay, Eau et Environnement (IFSTTAR/GERS/EE), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-PRES Université Nantes Angers Le Mans (UNAM), Department of Earth Sciences, Institute of Geographical Sciences, Freie Universität Berlin, Centre for Water Resource Systems, Institute of Hydraulic Engineering and Water Resources Management, University of Technology, University of Rostock [Germany], Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Pyrenean Institute of Ecology (CSIC), Universitat de València (UV), Mount Albert Research Station, New Zealand Institute for Plant and Food Research Limited, Czech Technical University in Prague (CTU), The New Zealand Institute for Plant & Food Research (NEW ZEALAND), Institut des Sciences de la Terre d'Orléans - UMR7327 (ISTO), Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS), Biogéosystèmes Continentaux - UMR7327, PSL Research University (PSL)-PSL Research University (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Ghent University [Belgium] (UGENT), Department of Civil and Environmental Engineering of the University of Perugia, Italy, Università degli Studi di Perugia (UNIPG), UniRedentor University Center, Embrapa Solos, Ministério da Agricultura, Department of Soil Science, Faculty of Agriculture, Ferdowsi University of Mashhad, Agricultural Research, Education and Extension Organization Maragheh, Dryland Agricultural Research Institute, East Azerbaijan Agricultural and Natural Resources Research and Education center, Scientific Member of Soil and Water Research Department, Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, Centre for Agricultural Research [Budapest] (ATK), Department of Natural Resources and Environment, Faculty of Agriculture, Jordan University of Science and Technology, Department of Watershed Management Engineering, Faculty of Natural Resources, Life and Environmental Sciences, University of California, Geographisches Institut, Rheinische Friedrich-Wilhelms-Universität Bonn, Institute of Plant Nutrition and Soil Science, Christian-Albrechts-Universität zu Kiel (CAU), ARAID Researcher, Spanish National Research Council (IPE-CSIC), Instituto Pirenaico de Ecología-CSIC (IPE-CSIC), Enginereed and Geosystems Analysis Unit, Belgian Nuclear Research Centre, Soil, Water and Land Use Team, Wageningen Environmental Researc, Civil, Surveying and Environmental Engineering, University of Newcastle [Australia] (UoN), Department of Soil Science, College of Agriculture, Isfahan University of Technology, Agricultural and Food Engineering Department, Indian Institute of Technology Kharagpur (IIT Kharagpur), State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Research Soil Scientist, United States Department of Agriculture - Agricultural Research Service, Slovak Academy of Sciences, Slovak Academy of Science [Bratislava] (SAS), Departamento de Suelo y Agua, Consejo Superior de Investigaciones Científicas (CSIC), Pomology Department, Estación Experimental de Aula Dei, Regional Research Station, ICAR-Central Arid Zone Research Institute, CSIRO Land and Water, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Soil Science Graduate Program (ufsm.br/ppgcs), Federal University of Santa Maria, Science and Technology of the Amazonas – IFAM, Federal Institute of Education, Environment Centre Wales, Bangor University, ENGIE, Earth and Life Institute - Environmental Sciences (ELIE), Université Catholique de Louvain (UCL), Department of Environmental Sciences, Urmia Lake Research Institute, Department of Biological and Agricultural Engineering, 2117 TAMU, College Station, Texas A&M University System, Department of Agroecology, Research Centre Foulum, Aarhus University, Shiraz University (Shiraz University ), University of Kurdistan, University of Tabriz, Department of Hydrology, Geological Survey of Brazil (CPRM), Department of Water Resources and Environment, Soil and Water Research Department, Agricultural Research, Education and Extension Organization (AREEO), Sistan Agricultural and Natural Resources Research and Education Center, Department of Soil Science, University of Saskatchewan, Department of Earth and Environmental Sciences [Leuven-Heverlee], Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), GeoEnvironmental Research Group, Faculty of Philosophy and Letters, University of Extremadura, Soil Science Department, University of Panonia, Department of Soil Management, UNESCO Chair on Eremology, Ghent University, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran, Soil and Water Research Institute, Instituto de Geomorfología y Suelos, Department of Geography, Universidad de Málaga [Málaga], Department of Physical Geography, Trier University, Civil Engineering Program, Alberto Luiz Coimbra Institute for Postgraduate Studies and Research in Engineering (COPPE), Federal University of Rio de Janeiro, Faculty of Agriculture, United Graduate School of Agricultural Science, Department of Materials and Life Science, Seikei University, Plant and Environmental Sciences, University of Gothenburg (GU), Rural Development Division, Japan International Research Center for Agricultural Sciences (JIRCAS), RiverLy (UR Riverly), Department of Agricultural and Bio-Resources Engineering, Faculty of Engineering, Ahmadu Bello University Zaria, Federal Agency for Water Management, Institute for land and water management research, Department of Water Resources, ITC Faculty of Geo-Information Science and Earth Observation, Twente University, Faculty of Agriculture and Natural Resources, Ardakan University, Department of Rural Engineering, University of Córdoba, Soil Physics, Embrapa Soils, Department of Soil Science, Agriculture Faculty, University of Zanja, Faculty of Civil Engineering, Department of Geography, Escuela Militar de Ingeniería (EMI), Engineering Faculty, Civil Engineering Department, Munzur University, Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, University Station, University of Texas at Austin [Austin], Monitoring and Exploration Technologies, Helmholtz Centre for Environmental Research (UFZ), College of Resources and Environmental Engineering, Ludong University, ANR-11-BS56-0027,FLOODSCALE,Observation et modélisation multi-échelles pour la compréhension et la simulation des crues éclair(2011), ANR-07-VULN-0001,AVUPUR,Assessing the Vulnerability of Peri-Urban-Rivers.(2007), MEHDI RAHMATI, University of Maragheh, Maragheh, Iran/Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, Germany, LUTZ WEIHERMÜLLER, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, Germany, SEYED HAMIDREZA SADEGHI, Tarbiat Modares University, Iran, LILI MAO, Chinese Academy of Agricultural Sciences, Beijing, YAKOV A. PACHEPSKY, USDA-ARS Environmental Microbial and Food Safety Laboratory, Beltsville, MD, JAN VANDERBORGHT, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, Germany, NILOOFAR MOOSAVI, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, Germany, HOSSEIN KHEIRFAM, Urmia University, Urmia, Iran, CARSTEN MONTZKA, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, Germany, KRIS VAN LOOY, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, Germany, ZEINAB HAZBAVI, Tarbiat Modares University, Iran, BRIGITTA TOTH, Hungarian Academy of Sciences, Budapest, Hungary/University of Pannonia, Keszthely, Hungary, WAFA AL YAMANI, Environment Agency, Abu Dhabi, UAE, AMMAR A. ALBALASMEH, Jordan University of Science and Technology, RAFAEL ANGULO-JARAMILLO, Univ Lyon, Université Claude Bernard Lyon, ANTÔNIO CELSO DANTAS ANTONINO, UFPE, GEORGE ARAMPATZIS, Hellenic Agricultural Organization, Soil and Water Resources Institute, Greece, ROBSON ANDRÉ ARMINDO, UFLA, HOSSEIN ASADI, University of Tehran, Karaj, Iran, YAZIDHI BAMUTAZE, Makerere University, Kampala, Uganda, JORDI BATLLE-AGUILAR, INRA, AgroParisTech Thiverval-Grignon, France/IDES CNRS/Université Paris-Sud, Orsay CEDEX/Innovative Groundwater Solutions (IGS), South Australia, Australia, BÉATRICE BÉCHET, IFSTTAR, GERS, France, MA'IN Z. ALGHZAWI, Jordan University of Science and Technology, FABIAN BECKER, Freie Universität Berlin, BRENT CLOTHIER, Plant and Food Research, Palmerston North, New Zealand, WIM CORNELIS, Ghent University, Ghent, Belgium, CORRADO CORRADINI, University of Perugia, Perugia, Italy, ARTUR PAIVA COUTINHO, UFPE, MURIEL BASTISTA DE OLIVEIRA, UniRedentor, Itaperuna, JOSE RONALDO DE MACEDO, CNPS, MATHEUS FONSECA DURÃES, UFLA, NÁNDOR FODOR, Agricultural Institute, Centre for Agricultural Research, Hungarian Academy of Sciences, GÜNTER BLÖSCHL, Centre for Water Resource Systems, TU Wien, Karlsplatz/Institute of Hydraulic Engineering and Water Resources Management, ALESSIA FLAMMINI, Ghent University, Ghent, Belgium, ASGHAR FARAJNIA, East Azerbaijan Agricultural and Natural Resources Research and Education Center, Iran, IRAJ ESKANDARI, Dryland Agricultural Research Institute, Agricultural Research, Education and Extension Organization Maragheh, East Azerbaijan, Iran, HOJAT EMAMI, Ferdowsi University of Mashhad, Mashhad, Iran, KLAUS BOHNE, University of Rostock, Germany, ISABELLE BRAUD, Irstea, UE RiverLy, Lyon-Villeurbanne Center, France, CLARA CASTELLANO, Pyrenean Institute of Ecology-CSIC, ARTEMI CERDÀ, University of Valencia, Spain, MAHA CHALHOUB, INRA AgroParisTech Functional Ecology and Ecotoxicology of Agroecosystems, ROGERIO CICHOTA, Plant and Food Research, Mount Albert Research Station, Auckland, New Zealand, MILENA CÍSLEROVÁ, Czech Technical University in Prague, Faculty of Civil Engineering, YVES COQUET, INRA AgroParisTech Functional Ecology and Ecotoxicology of Agroecosystems/Université d'Orléans, CNRS, Orléans, France, HAMID KELISHADI, Isfahan University of Technology, Iran, RAINER HORN, Christian-Albrechts-Universität zu Kiel, Germany, EVANGELOS G. HATZIGIANNAKIS, Hellenic Agricultural Organization, Soil and Water Resources Institute, Greece, SIMONE GIERTZ, Universität Bonn, Bonn, Germany, TEAMRAT A. GHEZZEHEI, University of California, Merced, USA, MOHAMAD HOSSEIN GHAVIMIPANAH, Tarbiat Modares University, Iran, MAMOUN GHARAIBEH, Jordan University of Science and Technology, JUAN JOSÉ JIMÉNEZ, ARAID Researcher, Instituto Pirenaico de Ecología, Spanish National Research Council, SASKIA DEBORAH KEESSTRA, Soil, Water and Land Use Team, Wageningen Environmental Research/the University of Newcastle, Australia, DIEDERIK JACQUES, Enginereed and Geosystems Analysis Unit, Belgian Nuclear Research Centre, Mol, Belgium, MAHBOOBEH KIANI-HARCHEGANI, Faculty of Natural Resources, Tarbiat Modares University, Iran, MEHDI KOUSELOU, Faculty of Agriculture, University of Maragheh, Maragheh, Iran, MADAN KUMAR JHA, Indian Institute of Technology Kharagpur, India, LAURENT LASSABATERE, Univ Lyon, Université Claude Bernard Lyon 1, CNRS, ENTPE, Vaulx-en-Velin, France, XIAOYAN LI, Beijing Normal University, Beijing, China, MARK A. LIEBIG, USDA Agricultural Research Service, Mandan, ND, USA, DENIZ YILMAZ, Munzur University, Tunceli, Turkey, MICHAEL H. YOUNG, University of Texas at Austin, University Station, USA, HONG ZHAO, University of Twente, Enschede, the Netherlands, HARRY VEREECKEN, Forschungszentrum Jülich GmbH, Institute of Bio- and Geosciences: Agrosphere (IBG-3), Jülich, Germany/ISMC International Soil Modeling Consortium, Institute of Bio and Geosciences Forschungszentrum, Germany., MARÍA VICTORIA LÓPEZ, Departamento de Suelo y Agua, Estación Experimental de Aula Dei (EEAD), Consejo Superior de Investigaciones Científicas, Spain, DEEPESH MACHIWAL, ICAR-Central Arid Zone Research Institute, Regional Research Station, Gujarat, India, DIRK MALLANTS, CSIRO Land and Water, Glen Osmond, South Australia, Australia, MICAEL STOLBEN MALLMANN, UFSM, JEAN DALMO DE OLIVEIRA MARQUES, IFAM, MILES R. MARSHALL, Centre for Ecology & Hydrology, Environment Centre Wales, Deiniol Road, Bangor, UK, JAN MERTENS, ENGIE Research and Technologies, Brussels, Belgium, FÉLICIEN MEUNIER, Université catholique de Louvain, Earth and Life Institute-Environmental Sciences, Louvain-la Neuve, Belgium, MOHAMMAD HOSSEIN MOHAMMADI, University of Tehran, Karaj, Iran, BINAYAK P. MOHANTY, Department of Biological and Agricultural Engineering, Texas A&M Univ., College Station, USA, MANSONIA PULIDO-MONCADA, Aarhus University, Department of Agroecology, Research Centre Foulum, Tjele, Denmark, SUZANA MONTENEGRO, UFPE, RENATO MORBIDELLI, University of Perugia, Perugia, Italy, DAVID MORET-FERNÁNDEZ, Departamento de Suelo y Agua, Estación Experimental de Aula Dei (EEAD), Consejo Superior de Investigaciones Científicas (CSIC), Spain, ALI AKBAR MOOSAVI, Department of Soil Science, College of Agriculture, Shiraz University, Shiraz, Iran, MOHAMMAD REZA MOSADDEGHI, Department of Soil Science, College of Agriculture, Isfahan University of Technology, Iran, SEYED BAHMAN MOUSAVI, Department of Soil Science and Engineering, Faculty of Agriculture, University of Maragheh, Maragheh, Iran, HASAN MOZAFFARI, Department of Soil Science, College of Agriculture, Shiraz University, Shiraz, Iran, KAMAL NABIOLLAHI, Department of Soil Science and Engineering, Faculty of Agriculture, University of Kurdistan, Iran, MOHAMMAD REZA NEYSHABOURI, Department of Soil Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran, MARTA VASCONCELOS OTTONI, CPRM, THEOPHILO BENEDICTO OTTONI FILHO, UFRJ, MOHAMMAD REZA PAHLAVAN-RAD, Soil and Water Research Department, Sistan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Zabol, Iran, ANDREAS PANAGOPOULOS, Hellenic Agricultural Organization, Soil and Water Resources Institute, Greece, STEPHAN PETH, Department of Soil Science, University of Kassel, Germany, PIERRE-EMMANUEL PEYNEAU, IFSTTAR, Bouguenais, France, TOMMASO PICCIAFUOCO, Centre for Water Resource Systems, Vienna, Austria/University of Perugia, Perugia, Italy, JEAN POESEN, Catholic University of Leuven, Geo-Institute, Belgium, MANUEL PULIDO, GeoEnvironmental Research Group, University of Extremadura, Cáceres, Spain, DALVAN JOSÉ REINERT, UFSM, SABINE REINSCH, Centre for Ecology & Hydrology, Environment Centre Wales, UK, MEISAM REZAEI, Department of Soil Management, UNESCO Chair on Eremology, Ghent University, Ghent, Belgium/Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran, FRANCIS PARRY ROBERTS, Centre for Ecology & Hydrology, Environment Centre Wales, UK, DAVID ROBINSON, Centre for Ecology & Hydrology, Environment Centre Wales, Deiniol Road, UK, JESÚS RODRIGO-COMINO, University of Málaga, Spain/Trier University, Trier, Germany, OTTO CORRÊA ROTUNNO FILHO, UFRJ, TADAOMI SAITO, Faculty of Agriculture, Tottori University, Japan, HIDEKI SUGANUMA, Seikei University, Tokyo, Japan, CARLA SALTALIPPI, Department of Civil and Environmental Engineering, University of Perugia, Perugia, Italy, RENÁTA SÁNDOR, Agricultural Institute, Centre for Agricultural Research, Hungarian Academy of Sciences, Hungary, BRIGITTA SCHÜTT, Freie Universität Berlin, Department of Earth Sciences, Institute of Geographical Sciences, Berlin, Germany, MANUEL SEEGER, Department of Physical Geography, Trier University, Germany, NASROLLAH SEPEHRNIA, Department of Soil Science, College of Agriculture, Isfahan University of Technology, Isfahan, Iran, EHSAN SHARIFI MOGHADDAM, Department of Watershed Management Engineering, Faculty of Natural Resources, Tarbiat Modares University, Iran, MANOJ SHUKLA, Plant and Environmental Sciences, New Mexico State University, Las Cruces, New Mexico, USA, SHIRAKI SHUTARO, Japan International Research Center for Agricultural Science, Rural Development Division, Tsukuba, Japan, RICARDO SORANDO, Irstea, UE RiverLy, Lyon-Villeurbanne Center, France, AJAYI ASISHANA STANLEY, Ahmadu Bello University Zaria, Nigeria, PETER STRAUSS, Institute for Land and Water Management Research, Federal Agency for Water Management, Austria, ZHONGBO SU, University of Twente, Enschede, the Netherlands, RUHOLLAH TAGHIZADEH-MEHRJARDI, Ardakan University, Ardakan, Yazd Province, Iran, ENCARNACIÓN TAGUAS, University of Córdoba, Spain, WENCESLAU GERALDES TEIXEIRA, CNPS, ALI REZA VAEZI, University of Zanjan, Zanjan, Iran, MEHDI VAFAKHAH, Tarbiat Modares University, Iran, YING ZHAO, Ludong University, China, YIJIAN ZENG, University of Twente, Enschede, the Netherlands, STEFFEN ZACHARIAS, UFZ Helmholtz Centre for Environment Research, Monitoring and Exploration Technologies, Leipzig, Germany, LUBOMÍR LICHNER, Institute of Hydrology, Slovak Academy of Sciences, Bratislava, Slovakia, TOMAS VOGEL, Czech Technical University in Prague, Faculty of Civil Engineering, Czech Republic, IRIS VOGELER, Plant and Food Research, Mount Albert Research Station, Auckland, New Zealand, JANA VOTRUBOVA, Czech Technical University in Prague, Faculty of Civil Engineering, Czech Republic, STEFFEN WERNER, Department of Geography, Ruhr University Bochum, Germany, THIERRY WINARSKI, Univ Lyon, Université Claude Bernard Lyon 1, CNRS, ENTPE, Vaulx-en-Velin, France, Jülich Research Centre, European Commission, Ministerio de Economía y Competitividad (España), Czech Science Foundation, Slovak Research and Development Agency, Rahmati, Mehdi, López Sánchez, María Victoria, Moret-Fernández, David, Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS), PSL Research University (PSL)-PSL Research University (PSL)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Rahmati, Mehdi [0000-0001-5547-6442], López Sánchez, María Victoria [0000-0003-4113-0381], Moret-Fernández, David [0000-0002-6674-0453], Forschungszentrum Jülich GmbH | Centre de recherche de Juliers, Helmholtz-Gemeinschaft = Helmholtz Association-Helmholtz-Gemeinschaft = Helmholtz Association, Université Claude Bernard Lyon 1 (UCBL), Hellenic Agricultural Organization Demeter (HAO Demeter), Makerere University [Kampala, Ouganda] (MAK), University of Rostock, Plant & Food Research, Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-Centre National de la Recherche Scientifique (CNRS)-Université d'Orléans (UO)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers en région Centre (OSUC), Universiteit Gent = Ghent University [Belgium] (UGENT), Virginia Polytechnic Institute and State University [Blacksburg], Beijing Normal University (BNU), Slovak Academy of Sciences (SAS), Université Catholique de Louvain = Catholic University of Louvain (UCL), Aarhus University [Aarhus], Universidad de Málaga [Málaga] = University of Málaga [Málaga], Programa de Engenharia Civil (COC/COPPE-UFRJ), Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia (COPPE-UFRJ), Universidade Federal do Rio de Janeiro (UFRJ)-Universidade Federal do Rio de Janeiro (UFRJ), Ahmadu Bello University, Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), College of Resources and Environmental Engineering [Yantai], Department of Water Resources, UT-I-ITC-WCC, and Faculty of Geo-Information Science and Earth Observation

Subjects
Condutividade Hidráulica, [SDV]Life Sciences [q-bio], 0208 environmental biotechnology, 02 engineering and technology, Silt, computer.software_genre, Soil, RING INFILTROMETERS, 900 Geschichte und Geografie::910 Geografie, Reisen::910 Geografie, Reisen, Hydraulic conductivity, ELECTRICAL-CONDUCTIVITY, Agricultural land, ddc:550, Meteorology & Atmospheric Sciences, SATURATED HYDRAULIC CONDUCTIVITY, Geosciences, Multidisciplinary, database, lcsh:Environmental sciences, 2. Zero hunger, lcsh:GE1-350, Database, IN-SITU, lcsh:QE1-996.5, Geology, 04 agricultural and veterinary sciences, PE&RC, Pedo-transfer functions, 6. Clean water, Infiltration (hydrology), HYDROPHYSICAL PARAMETERS, [SDE]Environmental Sciences, Physical Sciences, INFILTRATION GLOBAL DATABASE, Hidrologia, PHYSICAL-PROPERTIES, SANDY SOIL, TENSION INFILTROMETER, Ecology and Environment, Pedotransfer function, PEDOTRANSFER FUNCTIONS, Life Science, SOIL INFILTRATION MEASUREMENTS, Land surface models, Soil Water Infiltration Global database, ANALYSIS OF THE SOIL WATER, Science & Technology, Land use, Infiltration, 15. Life on land, 020801 environmental engineering, Infiltração, lcsh:Geology, Solo, Infiltration, Land surface models, Land use, Pedo-transfer functions, SWIG, Agriculture and Soil Science, Data quality, ITC-ISI-JOURNAL-ARTICLE, Earth and Environmental Sciences, INFILTROMETER MEASUREMENTS, Soil water, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, General Earth and Planetary Sciences, Environmental science, Hydrology, ITC-GOLD, computer
Abstract

27 Pags.- 11 Tabls.- 8 Figs. © Author(s) 2018. This work is distributed under the Creative Commons Attribution 4.0 License., In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements ( ∼ 76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76 % of the experimental sites with agricultural land use as the dominant type (∼ 40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it., First author thanks the International and Scientific Cooperation Office of the University of Maragheh, Iran, as well as the research committee and board members of the university for their assistance in conducting the current work. The financial support received from the Forschungszentrum Jülich GmbH is gratefully acknowledged by the first author. Parts of the database were made available through research work carried out in the framework of LIFE+ projects funded by the EC. The support of the Spanish Ministry of Economy through project CGL2014-53017-C2-1-R is acknowledged. The support of the Czech Science Foundation through project no. 16-05665S is acknowledged. The support of the Slovak Research and Development Agency through project no. APVV-15-0160 is acknowledged.

Published
2018
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results