Special Issue "Soil Hydrology in Agriculture"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: closed (1 April 2019).

Special Issue Editors

Guest Editor
Dr. Angelo Basile Website E-Mail
Italian National Research Council (CNR) - Institute for Mediterranean Agriculture and Forest Systems (ISAFOM)
Interests: soil hydrology; numerical modelling; soil science; sustainable agriculture; irrigation; decision support systems
Guest Editor
Prof. Antonio Coppola Website E-Mail
School of Agricultural, Forestry, Food and Environmental Sciences (SAFE), Hydraulics Division, University of Basilicata, Potenza, Italy
Interests: soil hydrology; water and solute preferential flow; stochastic approaches; numerical modelling, irrigation at field and district scale; proximal sensing; soil salinity management

Special Issue Information

Dear Colleagues,

Knowing the hydrological behavior of soils is essential for managing and protecting agricultural (and natural) ecosystems. Soil hydrological behavior determines crop responses to water and nutrients provided by irrigation and fertilization. Soil hydrology also controls deep percolation fluxes of water and nutrients, as well as water and nutrient runoff. Thus, it impacts the quality of soil, surface and groundwater resources.

The use of process-based soil-plant-atmosphere models relating soil hydrology to crop growth, combined with advanced techniques (e.g., ICT technologies, proximal and remote sensing, data assimilation) enables the development of Decision Support Systems to be used for quantifying the effect of alternative farm management decisions, as well as crop yield responses to either drought or saline conditions as affected by climatic change. This, in turn, allows a site-specific management of spatially variable soil (Agriculture 4.0.)

It is thus evident that soil hydrology is a key factor in food security and sustainable development goals (i.e., SDG2).

Given these considerations, the objective of this Special Issue is to encourage the submission of manuscripts on the interaction of soil hydrology and agriculture in seeking effective management of water and nutrients. We welcome contributions integrating monitoring and modeling components at applicative scales, from field to district scales.

The Special Issue will deal with the following major topics:

  • Soil hydrology, water uptake and crop response;
  • Soil hydrology and irrigation management from field to district scale;
  • Soil hydrology and nutrient management.

Specific topics will include (not exhaustively):

  • Monitoring and modeling of the interactions between soil hydrological, plant and atmosphere processes, and agricultural management practices;
  • Soil hydrology for irrigation and fertilizer management, including non-conventional water resources;
  • Soil hydrology and soil tillage;
  • Monitoring and modeling root growth and uptake of water and nutrients;
  • The role of soil hydrology in scheduling irrigation at district scale, under conditions of spatially variable soils;
  • Site-specific management related to spatially variable soil hydrological behavior.
  • Carbon, nitrogen and phosphate dynamics in agricultural soils.

Dr. Angelo Basile
Prof. Antonio Coppola
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Soil hydrology
  • Irrigation
  • Soil salinity
  • Nutrients management
  • Numerical modelling
  • Soil-Plant-Atmosphere continuum
  • Proximal and Remote Sensing

Published Papers (16 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Editorial

Jump to: Research, Review

Open AccessEditorial
Special Issue “Soil Hydrology in Agriculture”
Water 2019, 11(7), 1430; https://doi.org/10.3390/w11071430 - 12 Jul 2019
Abstract
Understanding the hydrological behavior of soils is essential for managing and protecting agricultural (and natural) ecosystems [...] Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)

Research

Jump to: Editorial, Review

Open AccessArticle
Simulation of Long-Term Soil Hydrological Conditions at Three Agricultural Experimental Field Plots Compared with Measurements
Water 2019, 11(5), 989; https://doi.org/10.3390/w11050989 - 10 May 2019
Cited by 1
Abstract
Soil hydrological conditions influence crop growth and groundwater recharge and, thus, precise knowledge of such conditions at field scale is important for the investigation of agricultural systems. In our study, we analyzed soil hydrological conditions at three agricultural experimental field plots with sandy [...] Read more.
Soil hydrological conditions influence crop growth and groundwater recharge and, thus, precise knowledge of such conditions at field scale is important for the investigation of agricultural systems. In our study, we analyzed soil hydrological conditions at three agricultural experimental field plots with sandy soils and different crop rotations using a 22-year period from 1993 to 2014 with daily volumetric soil water contents measured by the Time Domain Reflectometry with Intelligent MicroElements (TRIME)-method and pressure heads determined by automatic recording tensiometers. These measured data were compared with soil water contents and pressure heads simulated by a process-based agroecosystem model. Within this 22-year period, time spans with a better model performance and periods with a lower goodness of fit between simulations and observations were observed. The lower goodness of fit in the summer periods was attributed to inadequate calculations of root water uptake. Measurement errors of the TRIME-probes and differences between soil water contents measured by TRIME and pressure heads observed by tensiometers due to different measurement volumes, precision and measuring principles were identified as further reasons for mismatches between simulated and measured model outputs. Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)
Show Figures

Figure 1

Open AccessArticle
Identifying Optimal Irrigation Water Needs at District Scale by Using a Physically Based Agro-Hydrological Model
Water 2019, 11(4), 841; https://doi.org/10.3390/w11040841 - 21 Apr 2019
Cited by 2
Abstract
This paper mainly aims to illustrate an irrigation management tool to simulate scheduling of district-level water needs over the course of an irrigation season. The tool is mostly based on a daily model for simulating flow of water (and solutes) in heterogeneous agri-environmental [...] Read more.
This paper mainly aims to illustrate an irrigation management tool to simulate scheduling of district-level water needs over the course of an irrigation season. The tool is mostly based on a daily model for simulating flow of water (and solutes) in heterogeneous agri-environmental systems (called FLOWS-HAGES). The model produces information on the daily evolution of: soil water contents and pressure potentials in the soil profile; water uptake and actual evapotranspiration; stress periods for each crop; return fluxes to the groundwater and their quality in terms of solute concentrations (e.g., nitrates). FLOWS-HAGES provides a daily list of hydrants to be operated according to water or crop-based criteria. The daily optimal sequence of hydrant use may thus be established by passing the volumes to be delivered on to the model for simulating the hydraulics of the irrigation network, in order to ensure that the discharges flowing inside the network of distribution pipes are delivered under optimal pressure head distribution in the system. All the above evaluations can be carried out in a stochastic framework to account for soil heterogeneity and climate changes. To illustrate the potential of FLOWS-HAGES, a case study was considered for a selected sector of the Irrigation District 10 in the “Sinistra Ofanto” irrigation system (southern Italy, Apulia region). In a 139 ha area (Sector 6 of the Irrigation District), soil profiles were analyzed for characterization of hydraulic properties variability. Hydraulic properties were determined by a combination of field and laboratory measurements. Model simulations were validated by comparing soil water storage simulated and measured by a sensor based on electromagnetic induction technique. Irrigation water volumes and frequency calculated by the model were compared to the volumes actually supplied by the farmers. Compared to the farmers behavior, the model simulates more frequent irrigations with lower irrigation volumes. Finally, some indexes of irrigation performance were calculated for each farm under study. The resulting maps provide useful information on the spatial distribution of farmer behavior, indicating the abuse or underuse of water as well as the fraction of the water lost by drainage following the irrigation method applied. Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)
Show Figures

Figure 1

Open AccessArticle
Estimates of Tillage and Rainfall Effects on Unsaturated Hydraulic Conductivity in a Small Central European Agricultural Catchment
Water 2019, 11(4), 740; https://doi.org/10.3390/w11040740 - 10 Apr 2019
Cited by 1
Abstract
In arable land, topsoil is exposed to structural changes during each growing season due to agricultural management, climate, the kinetic energy of rainfall, crop and root growth. The shape, size, and spatial distributions of soil aggregates are considerably altered during the season and [...] Read more.
In arable land, topsoil is exposed to structural changes during each growing season due to agricultural management, climate, the kinetic energy of rainfall, crop and root growth. The shape, size, and spatial distributions of soil aggregates are considerably altered during the season and thus affect water infiltration and the soil moisture regime. Agricultural topsoils are prone to soil compaction and surface sealing which result in soil structure degradation and disconnection of preferential pathways. To study topsoil infiltration properties over time, near-saturated hydraulic conductivity of topsoil was repeatedly assessed in a catchment in central Bohemia (Czech Republic) during three consecutive growing seasons, using a recently developed automated tension minidisk infiltrometer (MultiDisk). Seasonal variability of soil bulk density and saturated water content was observed as topsoil consolidated between seedbed preparations. Topsoil unsaturated hydraulic conductivity was lower in spring and increased in the summer months during two seasons, and the opposite trend was observed during one season. Temporal unsaturated hydraulic conductivity variability was higher than spatial variability. Cumulative kinetic energy of rainfall, causing a seasonal decrease in soil macroporosity and unsaturated hydraulic conductivity, was not a statistically significant predictor. Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)
Show Figures

Graphical abstract

Open AccessArticle
Modelling the Impact on Root Water Uptake and Solute Return Flow of Different Drip Irrigation Regimes with Brackish Water
Water 2019, 11(3), 425; https://doi.org/10.3390/w11030425 - 27 Feb 2019
Cited by 1
Abstract
Water scarcity and quality degradation represent real threats to economic, social, and environmental development of arid and semi-arid regions. Drip irrigation associated to Deficit Irrigation (DI) has been investigated as a water saving technique. Yet its environmental impacts on soil and groundwater need [...] Read more.
Water scarcity and quality degradation represent real threats to economic, social, and environmental development of arid and semi-arid regions. Drip irrigation associated to Deficit Irrigation (DI) has been investigated as a water saving technique. Yet its environmental impacts on soil and groundwater need to be gone into in depth especially when using brackish irrigation water. Soil water content and salinity were monitored in a fully drip irrigated potato plot with brackish water (4.45 dSm−1) in semi-arid Tunisia. The HYDRUS-1D model was used to investigate the effects of different irrigation regimes (deficit irrigation (T1R, 70% ETc), full irrigation (T2R, 100% ETc), and farmer’s schedule (T3R, 237% ETc) on root water uptake, root zone salinity, and solute return flows to groundwater. The simulated values of soil water content (θ) and electrical conductivity of soil solution (ECsw) were in good agreement with the observation values, as indicated by mean RMSE values (≤0.008 m3·m−3, and ≤0.28 dSm−1 for soil water content and ECsw respectively). The results of the different simulation treatments showed that relative yield accounted for 54%, 70%, and 85.5% of the potential maximal value when both water and solute stress were considered for deficit, full. and farmer’s irrigation, respectively. Root zone salinity was the lowest and root water uptake was the same with and without solute stress for the treatment corresponding to the farmer’s irrigation schedule (273% ETc). Solute return flows reaching the groundwater were the highest for T3R after two subsequent rainfall seasons. Beyond the water efficiency of DI with brackish water, long term studies need to focus on its impact on soil and groundwater salinization risks under changing climate conditions. Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)
Show Figures

Figure 1

Open AccessArticle
How does PTF Interpret Soil Heterogeneity? A Stochastic Approach Applied to a Case Study on Maize in Northern Italy
Water 2019, 11(2), 275; https://doi.org/10.3390/w11020275 - 05 Feb 2019
Cited by 1
Abstract
Soil water balance on a local scale is generally achieved by applying the classical nonlinear Richards equation that requires hydraulic properties, namely, water retention and hydraulic conductivity functions, to be known. Its application in agricultural systems on field or larger scales involves three [...] Read more.
Soil water balance on a local scale is generally achieved by applying the classical nonlinear Richards equation that requires hydraulic properties, namely, water retention and hydraulic conductivity functions, to be known. Its application in agricultural systems on field or larger scales involves three major problems being solved, related to (i) the assessment of spatial variability of soil hydraulic properties, (ii) accounting for this spatial variability in modelling large-scale soil water flow, and (iii) measuring the effects of such variability on real field variables (e.g., soil water storage, biomass, etc.). To deal with the first issue, soil hydraulic characterization is frequently performed by using the so-called pedotransfer functions (PTFs), whose effectiveness in providing the actual information on spatial variability has been questioned. With regard to the second problem, the variability of hydraulic properties at the field scale has often been dealt with using a relatively simple approach of considering soils in the field as an ensemble of parallel and statistically independent tubes, assuming only vertical flow. This approach in dealing with spatial variability has been popular in the framework of a Monte Carlo technique. As for the last issue, remote sensing seems to be the only viable solution to verify the pattern of variability, going by several modelling outputs which have considered the soil spatial variability. Based on these premises, the goals of this work concerning the issues discussed above are the following: (1) analyzing the sensitivity of a Richards-based model to the measured variability of θ(h) and k(θ) parameters; (2) establishing the predictive capability of PTF in terms of a simple comparison with measured data; and (3) establishing the effectiveness of use of PTF by employing as data quality control an independent and spatially distributed estimation of the Above Ground Biomass (AGB). The study area of approximately 2000 hectares mainly devoted to maize forage cultivation is located in the Po plain (Lodi), in northern Italy. Sample sites throughout the study area were identified for hydropedological analysis (texture, bulk density, organic matter content, and other chemical properties on all the samples, and water retention curve and saturated hydraulic conductivity on a sub-set). Several pedotransfer functions were tested; the PTF‒Vereckeen proved to be the best one to derive hydraulic properties of the entire soil database. The Monte Carlo approach was used to analyze model sensitivity to two measured input parameters: the slope of water retention curve (n) and the saturated hydraulic conductivity (k0). The analysis showed sensitivity of the simulated process to the parameter n being significantly higher than to k0, although the former was much less variable. The PTFs showed a smoothing effect of the output variability, even though they were previously validated on a set of measured data. Interesting positive and significant correlations were found between the n parameter, from measured water retention curves, and the NDVI (Normalized Difference Vegetation Index), when using multi-temporal (2004–2018) high resolution remotely sensed data on maize cultivation. No correlation was detected when the n parameter derived from PTF was used. These results from our case study mainly suggest that: (i) despite the good performance of PTFs calculated via error indexes, their use in the simulation of hydrological processes should be carefully evaluated for real field-scale applications; and (ii) the NDVI index may be used successfully as a proxy to evaluate PTF reliability in the field. Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)
Show Figures

Figure 1

Open AccessArticle
Water Infiltration and Surface Runoff in Steep Clayey Soils of Olive Groves under Different Management Practices
Water 2019, 11(2), 240; https://doi.org/10.3390/w11020240 - 31 Jan 2019
Cited by 2
Abstract
When olive groves are cultivated on clayey soils with steep gradients, as in many Mediterranean areas, reducing the runoff and soil erosion rates by adopting proper soil management practices is imperative. A soil cover by pruning residues may represent an alternative to the [...] Read more.
When olive groves are cultivated on clayey soils with steep gradients, as in many Mediterranean areas, reducing the runoff and soil erosion rates by adopting proper soil management practices is imperative. A soil cover by pruning residues may represent an alternative to the commonly adopted mechanical tillage. This study evaluates the water infiltration rates and surface runoff volumes in a steep and clayey olive grove of Southern Italy. These hydrological variables are measured at the plot scale under four soil management practices (mechanical tillage, total artificial protection of soil and soil cover with two different rates of vegetal residues). The measurements have been carried out using a rainfall simulator under dry (undisturbed) and wet (that is, on soils disturbed by intense rainfall) conditions. The mechanical tillage leads to lower water infiltration rates and higher runoff production. The retention of a soil cover by vegetal residues (in the range 3.5–17.5 tons/ha of dry matter) reduces the runoff rate on average by 30%, mainly because of the increased soil infiltration rates (over 100%, compared to mechanical tillage). After soil disturbance due to antecedent rainfall, the runoff generation capacity of a soil disturbed by a heavy precipitation significantly increased compared to undisturbed soils because of the decrease in soil infiltration rates. Overall, the retention of vegetal residues over the soil may be advisable to reduce surface runoff generation rates, particularly for saturated soils. Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)
Show Figures

Graphical abstract

Open AccessFeature PaperArticle
Physics-Informed Data-Driven Models to Predict Surface Runoff Water Quantity and Quality in Agricultural Fields
Water 2019, 11(2), 200; https://doi.org/10.3390/w11020200 - 24 Jan 2019
Cited by 2
Abstract
Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models (PBMs), which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with PBMs, data-driven models are [...] Read more.
Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models (PBMs), which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with PBMs, data-driven models are becoming increasingly popular for describing the behavior of hydrological and water resources systems since these models can be used to complement or even replace physically based-models. Here we propose a new data-driven model as an alternative to a physically-based overland flow and transport model. First, we have developed a physically-based numerical model to simulate overland flow and contaminant transport. A large number of numerical simulations was then carried out to develop a database containing information about the impact of various relevant factors on surface runoff quantity and quality, such as different weather patterns, surface topography, vegetation, soil conditions, contaminants, and best management practices. Finally, the resulting database was used to train data-driven models. Several Machine Learning techniques were explored to find input-output functional relations. The results indicate that the Neural Network model with two hidden layers performed the best among selected data-driven models, accurately predicting runoff water quantity and quality over a wide range of parameters. Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)
Show Figures

Graphical abstract

Open AccessArticle
Field Water Balance Closure with Actively Heated Fiber-Optics and Point-Based Soil Water Sensors
Water 2019, 11(1), 135; https://doi.org/10.3390/w11010135 - 13 Jan 2019
Cited by 2
Abstract
While traditional soil water sensors measure soil water content (SWC) at point scale, the actively heated fiber-optics (AHFO) sensor measures the SWC at field scale. This study compared the performance of a distributed (e.g., AHFO) and a point-based sensor on closing the field [...] Read more.
While traditional soil water sensors measure soil water content (SWC) at point scale, the actively heated fiber-optics (AHFO) sensor measures the SWC at field scale. This study compared the performance of a distributed (e.g., AHFO) and a point-based sensor on closing the field water balance and estimating the evapotranspiration (ET). Both sensors failed to close the water balance and produced larger errors in estimated ET (ETε), particularly for longer time periods with >60 mm change in soil water storage (ΔSWS), and this was attributed to a lack of SWC measurements from deeper layers (>0.24 m). Performance of the two sensors was different when only the periods of ˂60 mm ΔSWS were considered; significantly lower residual of the water balance (Re) and ETε of the distributed sensor showed that it could capture the small-scale spatial variability of SWC that the point-based sensor missed during wet (70–104 mm SWS) periods of ˂60 mm ΔSWS. Overall, this study showed the potential of the distributed sensor to provide a more accurate value of SWS at field scale and to reduce the errors in water balance for shorter wet periods. It is suggested to include SWC measurements from deeper layers to better evaluate the performance of the distributed sensor, especially for longer time periods of >60 mm ΔSWS, in future studies. Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)
Show Figures

Figure 1

Open AccessArticle
A Simple Method for Estimating Field Crop Evapotranspiration from Pot Experiments
Water 2018, 10(12), 1823; https://doi.org/10.3390/w10121823 - 11 Dec 2018
Cited by 2
Abstract
Pot experiments are a low-cost and easy-to-use technique for studies of soil evaporation and plant transpiration in controlled environments. However, little attention has been paid to the applicability of evapotranspiration (ET) measured in pot experiments to the field. The objective of this study [...] Read more.
Pot experiments are a low-cost and easy-to-use technique for studies of soil evaporation and plant transpiration in controlled environments. However, little attention has been paid to the applicability of evapotranspiration (ET) measured in pot experiments to the field. The objective of this study was to determine whether a pot experiment can be used for measuring field ET. Evapotranspiration experiments with winter wheat and summer maize were conducted in pots and lysimeters under various water-deficit conditions. The measured ET values in the pot experiments under different water conditions were considerably different from those of the lysimeters. Causes of such differences in ET were analyzed, and a series of corrections were proposed to eliminate the effects of different crop densities, representative areas per plant, and soil moisture conditions on pot experiment results. After these corrections, the discrepancy in the total ET of wheat-maize seasons between pots and lysimeters was greatly reduced from a maximum of 117% to only approximately 10%. The relative mean square errors (RMSEs) for daily ET values also decreased from a maximum value of 4.56 mm to less than 1.5 mm for the wheat season and from a maximum value of 6.02 mm to approximately 2 mm for the maize season. Possible measures were proposed to further improve the accuracy of the corrected ET obtained from pot experiments. In sum, pot experiments can serve as a feasible tool for estimating ET in the field just with a few routine measurements at regions where large-scale weighing lysimeters, an eddy covariance device, and even meteorological data are not available. The proposed corrections can also be used for upscaling small-scale ET measurements to a large scale. Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)
Show Figures

Figure 1

Open AccessArticle
Effects of Mulched Drip Irrigation on Soil Moisture and Groundwater Recharge in the Xiliao River Plain, China
Water 2018, 10(12), 1755; https://doi.org/10.3390/w10121755 - 29 Nov 2018
Cited by 3
Abstract
Mulched drip irrigation for maize cultivation has been widely implemented in the Xiliao River Plain in Northeast China in recent years. However, the effects of the change in irrigation method on soil water content and groundwater recharge in this area still remains uncertain. [...] Read more.
Mulched drip irrigation for maize cultivation has been widely implemented in the Xiliao River Plain in Northeast China in recent years. However, the effects of the change in irrigation method on soil water content and groundwater recharge in this area still remains uncertain. In this study, soil water content under mulched drip irrigation and flood irrigation was measured through field experiments. Soil water movement in the entire growing season under the two irrigation methods was simulated for the quantitative analysis of groundwater recharge by the Hydrus-2D model. Results showed that soil water content under mulched drip irrigation was generally larger than that of flood irrigation in the initial growth stage. However, an opposite trend was observed in the main growth stage. The simulated results indicated that the cumulative water fluxes of flood irrigation were greater than the values of mulched drip irrigation. Moreover, while infiltration depth under flood irrigation reached the maximum simulated depth (400 cm), infiltration depth under mulched drip irrigation was only 325 cm. The results of this study showed that mulched drip irrigation reduced the infiltration depth and groundwater recharge to some extent in the Xiliao River Plain. Such results are helpful in determining the influence of mulched drip irrigation on groundwater and can be a reference for the maintenance of the sustainability of regional groundwater in the large-scale promotion of mulched drip irrigation. Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)
Show Figures

Figure 1

Open AccessArticle
Artificial Neural Networks for Predicting the Water Retention Curve of Sicilian Agricultural Soils
Water 2018, 10(10), 1431; https://doi.org/10.3390/w10101431 - 12 Oct 2018
Cited by 3
Abstract
Modeling soil-water regime and solute transport in the vadose zone is strategic for estimating agricultural productivity and optimizing irrigation water management. Direct measurements of soil hydraulic properties, i.e., the water retention curve and the hydraulic conductivity function, are often expensive and time-consuming, and [...] Read more.
Modeling soil-water regime and solute transport in the vadose zone is strategic for estimating agricultural productivity and optimizing irrigation water management. Direct measurements of soil hydraulic properties, i.e., the water retention curve and the hydraulic conductivity function, are often expensive and time-consuming, and represent a major obstacle to the application of simulation models. As a result, there is a great interest in developing pedotransfer functions (PTFs) that predict the soil hydraulic properties from more easily measured and/or routinely surveyed soil data, such as particle size distribution, bulk density (ρb), and soil organic carbon content (OC). In this study, application of PTFs was carried out for 359 Sicilian soils by implementing five different artificial neural networks (ANNs) to estimate the parameter of the van Genuchten (vG) model for water retention curves. The raw data used to train the ANNs were soil texture, ρb, OC, and porosity. The ANNs were evaluated in their ability to predict both the vG parameters, on the basis of the normalized root-mean-square errors (NRMSE) and normalized mean absolute errors (NMAE), and the water retention data. The Akaike’s information criterion (AIC) test was also used to assess the most efficient network. Results confirmed the high predictive performance of ANNs with four input parameters (clay, sand, and silt fractions, and OC) in simulating soil water retention data, with a prediction accuracy characterized by MAE = 0.026 and RMSE = 0.069. The AIC efficiency criterion indicated that the most efficient ANN model was trained with a relatively low number of input nodes. Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)
Show Figures

Figure 1

Open AccessArticle
Comparison of the Roles of Optimizing Root Distribution and the Water Uptake Function in Simulating Water and Heat Fluxes within a Maize Agroecosystem
Water 2018, 10(8), 1090; https://doi.org/10.3390/w10081090 - 17 Aug 2018
Cited by 1
Abstract
Roots are an important water transport pathway between soil and plant. Root water uptake (RWU) plays a key role in water and heat exchange between plants and the atmosphere. Inaccurate RWU schemes in land surface models are one crucial reason for decreased model [...] Read more.
Roots are an important water transport pathway between soil and plant. Root water uptake (RWU) plays a key role in water and heat exchange between plants and the atmosphere. Inaccurate RWU schemes in land surface models are one crucial reason for decreased model performance. Despite some types of RWU functions being adopted in land surface models, none have been certified as suitable for maize farmland ecosystems. Based on 2007–2009 data observed at the maize agroecosystem field station in Jinzhou, China, the RWU function and root distribution (RD) in the Common Land Model (CoLM) were optimized and the effects of the optimizations on model performance were compared. Results showed that RD parameters calculated with root length density were more practical relative to root biomass in reflecting soil water availability, and they improved the simulation accuracy for water and heat fluxes. The modified RWU function also played a significant role in optimizing the simulation of water and heat fluxes. Similarly, the respective and integrated roles of two optimization schemes in improving CoLM performance were significant during continuous non-precipitation days, especially during the key water requirement period of maize. Notably, the improvements were restrained within a threshold of soil water content, and the optimizations were inoperative outside this threshold. Thus, the optimized RWU function and the revised RD introduced into the CoLM model are applicable for simulation of water and heat fluxes for maize farmland ecosystems in arid areas. Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)
Show Figures

Figure 1

Open AccessFeature PaperArticle
Impact of Infiltration Process Modeling on Soil Water Content Simulations for Irrigation Management
Water 2018, 10(7), 850; https://doi.org/10.3390/w10070850 - 26 Jun 2018
Cited by 5
Abstract
The uncertainty in a hydrological model, due to its structure or implemented input parameters, affects the accuracy of simulations that are usually used for important applications such as drought predictions, flood risk assessment, irrigation scheduling, ground water recharge and contamination. Several models describing [...] Read more.
The uncertainty in a hydrological model, due to its structure or implemented input parameters, affects the accuracy of simulations that are usually used for important applications such as drought predictions, flood risk assessment, irrigation scheduling, ground water recharge and contamination. Several models describing soil infiltration processes have been developed. Some are analytical, while others implement numerical solutions of the Richards’ equation. The objective of this work was to assess the impact of infiltration process modeling on soil water content simulations. For this study, different infiltration models were included within FEST-WB (Flash Flood Event-based Spatially-distributed rainfall-runoff Transformations-Water Balance) distributed hydrological model (SCS-CN, Green and Ampt, Philip and Ross solution). Performances of implemented infiltration models in simulating soil water content were evaluated against observations acquired in the experimental site located in a maize field in northern Italy. Soil water content was monitored together with continuous measurements of meteorological data. A sensitivity analysis was performed to assess the most important parameters governing infiltration process in the different models tested. A comparison of soil water content simulations show that Ross solution allowed the description of soil moisture variation along the vertical, but simpler lumped models provide sufficient accuracy when properly calibrated. Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)
Show Figures

Figure 1

Review

Jump to: Editorial, Research

Open AccessFeature PaperReview
Why We Should Include Soil Structural Dynamics of Agricultural Soils in Hydrological Models
Water 2018, 10(12), 1862; https://doi.org/10.3390/w10121862 - 15 Dec 2018
Cited by 6
Abstract
Surface soil structure is sensitive to natural and anthropogenic impacts that alter soil hydraulic properties (SHP). These alterations have distinct consequences on the water cycle. In this review, we summarized published findings on the quantitative effects of different agricultural management practices on SHP [...] Read more.
Surface soil structure is sensitive to natural and anthropogenic impacts that alter soil hydraulic properties (SHP). These alterations have distinct consequences on the water cycle. In this review, we summarized published findings on the quantitative effects of different agricultural management practices on SHP and the subsequent response of the water balance components. Generally, immediately after tillage, soils show a high abundance of large pores, which are temporally unstable and collapse due to environmental factors like rainfall. Nevertheless, most hydrological modeling studies consider SHP as temporally constant when predicting the flow of water and solutes in the atmosphere-plant-soil system. There have been some developments in mathematical approaches to capture the temporal dynamics of soil pore space. We applied one such pore evolution model to two datasets to evaluate its suitability to predict soil pore space dynamics after disturbance. Lack of knowledge on how dispersion of pore size distribution behaves after tillage may have led to over-estimation of some values predicted by the model. Nevertheless, we found that the model predicted the evolution of soil pore space reasonably well (r2 > 0.80 in most cases). The limiting factor to efficiently calibrate and apply such modeling tools is not in the theoretical part but rather the lack of adequate soil structural and hydrologic data. Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)
Show Figures

Figure 1

Open AccessReview
Cropland Soil Salinization and Associated Hydrology: Trends, Processes and Examples
Water 2018, 10(8), 1030; https://doi.org/10.3390/w10081030 - 03 Aug 2018
Cited by 5
Abstract
While global food demand and world population are rapidly growing, land potential for cropping is steadily declining due to various soil degradation processes, a major one of them being soil salinization. Currently, approximately 20% of total cropland and 33% of irrigated agricultural land [...] Read more.
While global food demand and world population are rapidly growing, land potential for cropping is steadily declining due to various soil degradation processes, a major one of them being soil salinization. Currently, approximately 20% of total cropland and 33% of irrigated agricultural land are salinized as a result of poor agricultural practices and it is expected that by 2050, half of the croplands worldwide will become salinized. Thus, there is a real need to better understand soil salinization processes and to develop agricultural practices that will enable production of the needed amount of food to feed humanity, while minimizing soil salinization and other degradation processes. The major sources of solutes in agricultural environments are: (i) the soil itself, and the parent geological material; (ii) shallow and salt rich groundwater; and (iii) salt rich irrigation water. The salinization of soil is a combination of transport of solutes towards the root zone to replenish evaporation and transpiration and limited washing of the soil by rain or irrigation. Therefore, most salinized soils are present in arid and semi-arid environments where precipitation is low and evaporation is high. In this manuscript, examples of soil salinization processes from croplands around the world will be presented and discussed to bring attention to this important topic, to present the latest scientific insights and to highlight the gaps that should be filled, from both scientific and practical perspectives. Full article
(This article belongs to the Special Issue Soil Hydrology in Agriculture)
Show Figures

Figure 1

Water, EISSN 2073-4441, Published by MDPI AG
Back to TopTop