TDR soil moisture measurements at the Lago Maggiore MAP target area: preliminary results

Menziani, M.; Pugnaghi, Sergio; Pilan, L.; Santangelo, R.; Vincenzi, S.

doi:10.1016/s1464-1909(01)00031-4

Cited by 5 publications

(3 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The above relation is yet to be verified experimentally (Huang et al, 2006), especially using the data of Indian watersheds. Antecedent soil moisture can be one of the most important factors controlling hydrologic processes (Brocca et al, 2008;Menziani et al, 2001;Roberts and Crane, 1997;Stephenson and Freeze, 1974;Weiler et al, 2003). The SCS-CN method has been used worldwide for rainfall runoff modeling, but a common problem encountered is the absence of significant relationship between antecedent soil moisture and measured CN values.…”

Section: Introductionmentioning

confidence: 99%

Physical verification of the effect of land features and antecedent moisture on runoff curve number

Lal

Mishra

Pandey

2015

CATENA

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Physical verification of the effect of land features and antecedent moisture on runoff curve number

Lal

Mishra

Pandey

2015

CATENA

View full text Add to dashboard Cite

“…According to the approach used for simulating the processes, these models can be subdivided into: physically based, i.e. addressing the solution of the Richard's differential equation (Menziani et al, 2001;Tripp and Niemann, 2008;Chen et al, 2012); conceptual that schematize the soil into one (or more) reservoirs (Famiglietti and Wood, 1994;Albertson and Kiely, 2001;Montaldo et al, 2001Montaldo et al, , 2008Baudena et al, 2012) and data-based model, e.g. artificial neural network techniques (Jiang and Cotton, 2004;Elshorbagy et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Improving the representation of soil moisture by using a semi‐analytical infiltration model

Brocca

Melone

Moramarco

et al. 2013

Hydrological Processes

View full text Add to dashboard Cite

Soil moisture is widely recognized as a fundamental variable governing the mass and energy fluxes between the land surface and the atmosphere. In this study, the soil moisture modelling at sub‐daily timescale is addressed by using an accurate representation of the infiltration component. For that, the semi‐analytical infiltration model proposed by Corradini et al. (1997) has been incorporated into a soil water balance model to simulate the evolution in time of surface and profile soil moisture. The performances of this new soil moisture model [soil water balance module‐semi‐analytical (SWBM‐SA)] are compared with those of a precedent version [SWBM‐Green–Ampt (GA)] where the GA approach was employed. Their capability to reproduce in situ soil moisture observations at three sites in Italy, Spain and France is analysed. Hourly observations of quality‐checked rainfall, temperature and soil moisture data for a 2‐year period are used for testing the modelling approaches. Specifically, different configurations for the calibration and validation of the models are adopted by varying a single parameter, that is, the saturated hydraulic conductivity. Results indicate that both SWBMs are able to reproduce satisfactorily the hourly soil moisture temporal pattern for the three sites with root mean square errors lower than 0.024 m3/m3 both in the calibration and validation periods. For all sites, the SWBM‐SA model outperforms the SWBM‐GA with an average reduction of the root mean square error of ~20%. Specifically, the higher improvement is observed for the French site for which in situ observations are measured at 30 cm depth, and this is attributed to the capability of the SA infiltration model to simulate the time evolution of the whole soil moisture profile. The reasonable models performance coupled with the need to calibrate only a single parameter makes them useful tools for soil moisture simulation in different regions worldwide, also in scarcely gauged areas. Copyright © 2013 John Wiley & Sons, Ltd.

show abstract

“…Nondestructive methods used during these experiments were the soil dielectric constant measurements using a probe at L-band in the Cerbaia area, and several TDR probes (Time Domain Reflectometry) in the Toce Valley (Menziani et al, 2001).…”

Section: Ground Truth Methodsmentioning

confidence: 99%

Microwave radiometric measurements of soil moisture in Italy

Macelloni¹,

Paloscia²,

Pampaloni³

et al. 2003

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Within the framework of the MAP and RAPHAEL projects, airborne experimental campaigns were carried out by the IFAC group in 1999 and 2000, using a multifrequency microwave radiometer at L, C and X bands (1.4, 6.8 and 10 GHz). The aim of the experiments was to collect soil moisture and vegetation biomass information on agricultural areas to give reliable inputs to the hydrological models. It is well known that microwave emission from soil, mainly at L-band (1.4 GHz), is very well correlated to its moisture content. Two experimental areas in Italy were selected for this project: one was the Toce Valley, Domodossola, in 1999, and the other, the agricultural area of Cerbaia, close to Florence, where flights were performed in 2000. Measurements were carried out on bare soils, corn and wheat fields at different growth stages and on meadows. Ground data of soil moisture (SMC) were collected by other research teams involved in the experiments. From the analysis of the data sets, it has been confirmed that L-band is well related to the SMC of a rather deep soil layer, whereas C-band is sensitive to the surface SMC and is more affected by the presence of surface roughness and vegetation, especially at high incidence angles. An algorithm for the retrieval of soil moisture, based on the sensitivity to moisture of the brightness temperature at C-band, has been tested using the collected data set. The results of the algorithm, which is able to correct for the effect of vegetation by means of the polarisation index at X-band, have been compared with soil moisture measurements in the ground. Finally, the sensitivity of emission at different frequencies to the soil moisture profile was investigated. Experimental data sets were interpreted by using the Integral Equation Model (IEM) and the outputs of the model were used to train an artificial neural network to reproduce the soil moisture content at different depths.

show abstract

TDR soil moisture measurements at the Lago Maggiore MAP target area: preliminary results

Cited by 5 publications

References 20 publications

Physical verification of the effect of land features and antecedent moisture on runoff curve number

Physical verification of the effect of land features and antecedent moisture on runoff curve number

Improving the representation of soil moisture by using a semi‐analytical infiltration model

Microwave radiometric measurements of soil moisture in Italy

Contact Info

Product

Resources

About