Soil water management: evaluation of infiltration in furrow irrigarion systems, assessing water and salt content spatially and temporally in the Parc Agrari del Baix Llobregat area.

Sustainability of irrigated agriculture is a growing concern in the Baix Llobregat area. Although irrigated land accounts for a substantial proportion of food supply to the local market, it has been, and still is increasingly degraded by poor agricultural management. This dissertation focuses on ways to evaluate furrow irrigation and to assess soil water content and soil salinity (temporally and spatially) under usual farmers's management practices. This dissertation meets these goals through an extensive study of relevant literature and the implementation of practical research. The latter was carried out with a case study on representative fields of the area. Empirical and stochastic models were applied to evaluate furrow irrigation as well as to monitor water flow and solute transport in the root zone. This research produced a number of key findings: first, evaluating furrow irrigation confirmed that 40-43 % of the applied water would have been saved in the study fields if irrigation was stopped as soon as soil water deficit was fully recharge taking the amount of water needed for salt leaching into account, and that the application efficiency (AE) would increase from 48% to 84% and from 41% to 68% (Field 1 and Field 2, respectively). Second, the predictions of soil water content using ARIMA models were logical, and the next irrigation time and its effect on soil water content at the depth of interest were correctly estimated. Third, considering the linear relationship eb-sb, by transforming the Hilhorst (2000) model, which is based on the deterministic linear relationship eb-sb, into a time- varying Dynamic Linear Model (DLM) enabled us to validate this relationship under field conditions. An offset esb=0 value was derived that would ensure the accurate prediction of sp from measurements of sb. It was shown that the offset esb=0 varied for each depth in the same soil profile. A reason for this might be changes in soil temperature along the soil profile. The sp was then calculated for each depth in the root zone. Fourth, by using a (multiple input--single output) transfer function model, the results showed that soil water content and soil temperature had a significant impact on soil salinity, and soil salinity, predicted as a function of soil water and soil temperature, was correctly estimated. Finally, applying the analysis of variance (ANOVA), the results showed that the irrigation frequency, according to the farmer's usual management practice, had statistically significant effects on soil salinity behaviour, depending on soil depth and position (furrow, ridge). Moreover, it was shown that at the end of the crop's cycle the farmers left the field with less soil salinity, for each depth, than at the beginning of the crop's agricultural cycle

Assessing the relationship between the soil dielectric constant and electrical conductivity using 5TE sensors in the field conditions

Postprint (published version

Estimating Pore Water Electrical Conductivity of Sandy Soil from Time Domain Reflectometry Records Using a Time-Varying Dynamic Linear Model

Despite the importance of computing soil pore water electrical conductivity (σp) from soil bulk electrical conductivity (σb) in ecological and hydrological applications, a good method of doing so remains elusive. The Hilhorst concept offers a theoretical model describing a linear relationship between σb, and relative dielectric permittivity (εb) in moist soil. The reciprocal of pore water electrical conductivity (1/σp) appears as a slope of the Hilhorst model and the ordinary least squares (OLS) of this linear relationship yields a single estimate ( 1/σpˆ ) of the regression parameter vector (σp) for the entire data. This study was carried out on a sandy soil under laboratory conditions. We used a time-varying dynamic linear model (DLM) and the Kalman filter (Kf) to estimate the evolution of σp over time. A time series of the relative dielectric permittivity (εb) and σb of the soil were measured using time domain reflectometry (TDR) at different depths in a soil column to transform the deterministic Hilhorst model into a stochastic model and evaluate the linear relationship between εb and σb in order to capture deterministic changes to (1/σp). Applying the Hilhorst model, strong positive autocorrelations between the residuals could be found. By using and modifying them to DLM, the observed and modeled data of εb obtain a much better match and the estimated evolution of σp converged to its true value. Moreover, the offset of this linear relation varies for each soil depth.DFG, 325093850, Open Access Publizieren 2017 - 2018 / Technische Universität BerlinDFG, GRK 2032, Grenzzonen in urbanen Wassersysteme

Evaluating the variation of dissolved metals on a highway roadside using a generalized additive mixed model (GAMM)

Assessing metal concentrations in roadside soils requires a better understanding of the extent to which they are affected by different environmental factors such as soil texture, depth, pH, runoff concentration, and precipitation. Monthly data of dissolved Cd, Ni, Cr, Pb, Cu, and Zn concentrations in three different roadside soils (sandy loam, gravel (0–32 mm) and a mixture of sandy loam and gravel) were measured during a 2-year lysimeter field study at different depths. The data was used to assess the variation of trace elements and how they were affected by environmental factors. For data interpretation, generalized additive mixed models (GAMMs) were used to explore the complex behavior of metals in heterogeneous soils by detecting linear and nonlinear trends of metal concentrations in the soil solution. As a result, the modeling approach showed that Cd, Ni, Cr, Pb, Cu, and Zn concentrations are functions of different environmental variables, which have either linear or nonlinear behavior. All investigated metals showed that pH could explain their variation. With exception of precipitation, Ni and Cr variations can nearly be explained by the same environmental factors used in this study (time, pH, infiltration volume, roadside soil type, runoff concentrations, and depth). During the study period, we found that Zn variation can be explained by its nonlinear relationship with all the significant studied environmental factors. As the depth increases from the surface to 30 cm of depth, the metal concentration of Cd, Ni, Cr, Pb, and Zn increases. Surprisingly, the roadside soil consisting of gravel has the lowest organic carbon and showed the lowest median concentration of Cd, Ni, Pb, Cu, and Zn at 30 cm. Moreover, the model showed that the surface runoff volume has no effect on the metal variation in the soil solutionPostprint (published version

Analyzing temporal trends of urban evaporation using generalized additive models

This study aimed to gain new insights into urban hydrological balance (in particular, the evaporation from paved surfaces). Hourly evaporation data were obtained simultaneously from two high-resolution weighable lysimeters. These lysimeters are covered in two pavement sealing types commonly used for sidewalks in Berlin, namely cobble-stones and concrete slabs. A paired experiment in field conditions is designed to determine the mechanism by which these two types of soil sealing affect the evaporation rate under the same climatic conditions. A generalized additive model (GAM) is applied to explain how the climatic conditions interact with soil sealing and to evaluate the variation of evaporation rate according to pavement type. Moreover, taking the advantage of the fact that the experimental design is paired, the study fits a new GAM where the response variable is the difference between the evaporation rate from the two lysimeters and its explanatory variables are the climatic conditions. As a result, under the same climatic conditions, cobble-stones are more prone to increasing the evaporation rate than concrete slabs when the precipitation accumulated over 10 h, solar radiation, and wind speed increases. On the other hand, concrete slabs are more inclined to increase the evaporation rate than cobblestones when the relative humidity increases. GAM represents a robust modeling approach for comparing different sealing types in order to understand how they alter the hydrological balanceFunding: The German Research Foundation DFG (GRK 2032) and the Open Access Publication Fund of TU Berlin.Peer ReviewedPostprint (published version

Transfer function and time series outlier analysis: modelling Soil salinity in loamy sand soil by including the influences of irrigation management and soil temperature

In variable interval irrigation, simply including soil salinity data in the soil salinity model is not valid for making predictions, because changes in irrigation frequency must also be taken into account. This study on variable interval irrigation used capacitance soil sensors simultaneously to obtain hourly measurements of bulk electrical conductivity (sb), soil temperature (t) and soil water content (¿). Observations of sb were converted so that the electrical conductivity of the pore water (sp) could be estimated as an indicator of soil salinity. Values of ¿, t and sp were used to test a mathematical model for studying how sp cross-correlates with t and ¿ to predict soil salinity at a given depth. These predictions were based on measurements of sp, t, and ¿ at a shallow depth. As a result, prediction at shallow depth was successful after integrating intervention analysis and outlier detection into the seasonal autoregressive integrated moving average (ARIMA) model. We then used the (multiple-input/one-output) transfer function models to logically predict soil salinity at the depths of interest. The model could also correctly determine the effect of the irrigation event on soil salinityPeer ReviewedPostprint (author's final draft

Analyzing Temporal Trends of Urban Evaporation Using Generalized Additive Models

This study aimed to gain new insights into urban hydrological balance (in particular, the evaporation from paved surfaces). Hourly evaporation data were obtained simultaneously from two high-resolution weighable lysimeters. These lysimeters are covered in two pavement sealing types commonly used for sidewalks in Berlin, namely cobble-stones and concrete slabs. A paired experiment in field conditions is designed to determine the mechanism by which these two types of soil sealing affect the evaporation rate under the same climatic conditions. A generalized additive model (GAM) is applied to explain how the climatic conditions interact with soil sealing and to evaluate the variation of evaporation rate according to pavement type. Moreover, taking the advantage of the fact that the experimental design is paired, the study fits a new GAM where the response variable is the difference between the evaporation rate from the two lysimeters and its explanatory variables are the climatic conditions. As a result, under the same climatic conditions, cobble-stones are more prone to increasing the evaporation rate than concrete slabs when the precipitation accumulated over 10 h, solar radiation, and wind speed increases. On the other hand, concrete slabs are more inclined to increase the evaporation rate than cobblestones when the relative humidity increases. GAM represents a robust modeling approach for comparing different sealing types in order to understand how they alter the hydrological balance.DFG, 248198858, GRK 2032: Grenzzonen in urbanen Wassersysteme

Analyzing Temporal Trends of Urban Evaporation Using Generalized Additive Models

This study aimed to gain new insights into urban hydrological balance (in particular, the evaporation from paved surfaces). Hourly evaporation data were obtained simultaneously from two high-resolution weighable lysimeters. These lysimeters are covered in two pavement sealing types commonly used for sidewalks in Berlin, namely cobble-stones and concrete slabs. A paired experiment in field conditions is designed to determine the mechanism by which these two types of soil sealing affect the evaporation rate under the same climatic conditions. A generalized additive model (GAM) is applied to explain how the climatic conditions interact with soil sealing and to evaluate the variation of evaporation rate according to pavement type. Moreover, taking the advantage of the fact that the experimental design is paired, the study fits a new GAM where the response variable is the difference between the evaporation rate from the two lysimeters and its explanatory variables are the climatic conditions. As a result, under the same climatic conditions, cobble-stones are more prone to increasing the evaporation rate than concrete slabs when the precipitation accumulated over 10 h, solar radiation, and wind speed increases. On the other hand, concrete slabs are more inclined to increase the evaporation rate than cobblestones when the relative humidity increases. GAM represents a robust modeling approach for comparing different sealing types in order to understand how they alter the hydrological balance

A stochastic linear model to evaluate the dielectric constant-electrical conductivity relation of a sandy soil using TDR records

Despite the importance of evaluating soil pore water electrical conductivity from soil bulk electrical conductivity in ecological and hydrological applications, it still has not been worked out very well. This study was carried out on a sandy soil under laboratory conditions. We used a Dynamic Linear Model (DLM) and Kaman filter (Kf) to estimate soil pore electrical conductivity. Time series of soil dielectric constant and bulk electrical conductivity were measured by time domain reflectometry (TDR) at different depths in a soil column to modify the deterministic Hilhorst (2000) model into a stochastic model. We analyzed the linear relationship between dielectric constant and bulk electrical conductivity in order to estimate precisely pore water electrical conductivity. As a result, the observed and measured of dielectric constant were reasonably agree well. However, although the linear relation between soil dielectric constant and bulk electrical conductivity which was realized in homogenous soil, the offset of this linear relation varies for each depth. © 2018 IEEE.Postprint (published version