The HPx software for multicomponent reactive transport during variably-saturated flow: Recent developments and applications

Abstract HPx is a multicomponent reactive transport model which uses HYDRUS as the flow and transport solver and PHREEQC-3 as the biogeochemical solver. Some recent adaptations have significantly increased the flexibility of the software for different environmental and engineering applications. This paper gives an overview of the most significant changes of HPx, such as coupling transport properties to geochemical state variables, gas diffusion, and transport in two and three dimensions. OpenMP allows for parallel computing using shared memory. Enhancements for scripting may eventually simplify input definitions and create possibilities for defining templates for generic (sub)problems. We included a discussion of root solute uptake and colloid-affected solute transport to show that most or all of the comprehensive features of HYDRUS can be extended with geochemical information. Finally, an example is used to demonstrate how HPx, and similar reactive transport models, can be helpful in implementing different factors relevant for soil organic matter dynamics in soils. HPx offers a unique framework to couple spatial-temporal variations in water contents, temperatures, and water fluxes, with dissolved organic matter and CO2 transport, as well as bioturbation processes

Can a change in cropping patterns produce water savings and social gains: A case study from the Fergana Valley, Central Asia

Abstract The study examines possible water savings by replacing alfalfa with winter wheat in the Fergana Valley, located upstream of the Syrdarya River in Central Asia. Agricultural reforms since the 1990s have promoted this change in cropping patterns in the Central Asian states to enhance food security and social benefits. The water use of alfalfa, winter wheat/fallow, and winter wheat/green gram (double cropping) systems is compared for high-deficit, low-deficit, and full irrigation scenarios using hydrological modeling with the HYDRUS-1D software package. Modeling results indicate that replacing alfalfa with winter wheat in the Fergana Valley released significant water resources, mainly by reducing productive crop transpiration when abandoning alfalfa in favor of alternative cropping systems. However, the winter wheat/fallow cropping system caused high evaporation losses from fallow land after harvesting of winter wheat. Double cropping (i.e., the cultivation of green gram as a short duration summer crop after winter wheat harvesting) reduced evaporation losses, enhanced crop output and hence food security, while generating water savings that make more water available for other productive uses. Beyond water savings, this paper also discusses the economic and social gains that double cropping produces for the public within a broader developmental context

Modeling Virus Transport and Removal during Storage and Recovery in Heterogeneous Aquifers

A quantitative understanding of virus removal during aquifer storage and recovery (ASR) in physically and geochemically heterogeneous aquifers is needed to accurately assess human health risks from viral infections. A two-dimensional axisymmetric numerical model incorporating processes of virus attachment, detachment, and inactivation in aqueous and solid phases was developed to systematically evaluate the virus removal performance of ASR schemes. Physical heterogeneity was considered as either layered or randomly distributed hydraulic conductivities (with selected variance and horizontal correlation length). Geochemical heterogeneity in the aquifer was accounted for using Colloid Filtration Theory to predict the spatial distribution of attachment rate coefficient. Simulation results demonstrate that the combined effects of aquifer physical heterogeneity and spatial variability of attachment rate resulted in higher virus concentrations in the recovered water at the ASR well (i.e. reduced virus removal). While the sticking efficiency of viruses to aquifer sediments was found to significantly influence virus concentration in the recovered water, the solid phase inactivation under realistic field conditions combined with the duration of storage phase had a predominant influence on the overall virus removal. The relative importance of physical heterogeneity increased under physicochemical conditions that reduced virus removal (e.g. lower value of sticking efficiency or solid phase inactivation rate). This study provides valuable insight on site selection of ASR projects and an approach to optimize ASR operational parameters (e.g. storage time) for virus removal and to minimize costs associated with post-recovery treatment

The effects of preferential flow and soil texture on risk assessments of a NORM waste disposal site

This paper investigates the environmental fate of radionuclide decay chains (specially the 238U and 232Th series) being released from a conventional mining installation processing ore containing natural occurring radioactive materials (NORMs). Contaminated waste at the site is being disposed off in an industrial landfill on top of a base of earth material to ensure integrity of the deposit over relatively long geologic times (thousands of years). Brazilian regulations, like those of many other countries, require a performance assessment of the disposal facility using a leaching and off-site transport scenario. We used for this purpose the HYDRUS-1D software package to predict long-term radionuclide transport vertically through both the landfill and the underlying unsaturated zone, and then laterally in groundwater. We assumed that a downgradient well intercepting groundwater was the only source of water for a resident farmer, and that all contaminated water from the well was somehow used in the biosphere. The risk assessment was carried out for both a best-case scenario assuming equilibrium transport in a fine-textured (clay) subsurface, and a worst-case scenario involving preferential flow through a more coarse-textured subsurface. Results show that preferential flow and soil texture both can have a major effect on the results, depending upon the specific radionuclide involved.Indisponível

Transport and fate of viruses in sediment and stormwater from a Managed Aquifer Recharge site

© 2017 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 24 month embargo from date of publication (Oct 2017) in accordance with the publisher’s archiving policyEnteric viruses are one of the major concerns in water reclamation and reuse at Managed Aquifer Recharge (MAR) sites. In this study, the transport and fate of bacteriophages MS2, PRD1, and ΦX174 were studied in sediment and stormwater (SW) collected from a MAR site in Parafield, Australia. Column experiments were conducted using SW, stormwater in equilibrium with the aquifer sediment (EQ-SW), and two pore-water velocities (1 and 5 m day−1) to encompass expected behavior at the MAR site. The aquifer sediment removed >92.3% of these viruses under all of the considered MAR conditions. However, much greater virus removal (4.6 logs) occurred at the lower pore-water velocity and in EQ-SW that had a higher ionic strength and Ca2+ concentration. Virus removal was greatest for MS2, followed by PRD1, and then ΦX174 for a given physicochemical condition. The vast majority of the attached viruses were irreversibly attached or inactivated on the solid phase, and injection of Milli-Q water or beef extract at pH = 10 only mobilized a small fraction of attached viruses ( μs > kdet > μl, and katt was several orders of magnitude greater than μl. Therefore, current microbial risk assessment methods in the MAR guideline may be overly conservative in some instances. Interestingly, virus BTCs exhibited blocking behavior and the calculated solid surface area that contributed to the attachment was very small. Additional research is therefore warranted to study the potential influence of blocking on virus transport and potential implications for MAR guidelines

A comparison of numerical and machine-learning modeling of soil water content with limited input data

Soil water content (SWC) is a key factor in optimizing the usage of water resources in agriculture since it provides information to make an accurate estimation of crop water demand. Methods for predicting SWC that have simple data requirements are needed to achieve an optimal irrigation schedule, especially for various water-saving irrigation strategies that are required to resolve both food and water security issues under conditions of water shortages. Thus, a two-year field investigation was carried out to provide a dataset to compare the effectiveness of HYDRUS-2D, a physically-based numerical model, with various machine-learning models, including Multiple Linear Regressions (MLR), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), and Support Vector Machines (SVM), for simulating time series of SWC data under water stress conditions. SWC was monitored using TDRs during the maize growing seasons of 2010 and 2011. Eight combinations of six, simple, independent parameters, including pan evaporation and average air temperature as atmospheric parameters, cumulative growth degree days (cGDD) and crop coefficient (Kc) as crop factors, and water deficit (WD) and irrigation depth (In) as crop stress factors, were adopted for the estimation of SWCs in the machine-learning models. Having Root Mean Square Errors (RMSE) in the range of 0.54–2.07 mm, HYDRUS-2D ranked first for the SWC estimation, while the ANFIS and SVM models with input datasets of cGDD, Kc, WD and In ranked next with RMSEs ranging from 1.27 to 1.9 mm and mean bias errors of −0.07 to 0.27 mm, respectively. However, the MLR models did not perform well for SWC forecasting, mainly due to non-linear changes of SWCs under the irrigation process. The results demonstrated that despite requiring only simple input data, the ANFIS and SVM models could be favorably used for SWC predictions under water stress conditions, especially when there is a lack of data. However, process-based numerical models are undoubtedly a better choice for predicting SWCs with lower uncertainties when required data are available, and thus for designing water saving strategies for agriculture and for other environmental applications requiring estimates of SWCs

Two-dimensional modeling of nitrogen and water dynamics for various N-managed water-saving irrigation strategies using HYDRUS

Nitrate losses are the dominant cause of the non-point source pollution under agricultural fields. In this study, the HYDRUS-2D model was first calibrated and validated using data collected during a two-year field investigation in a drip-irrigated maize field and then applied to evaluate the influence of 176 different N-managed water-saving irrigation scenarios on water and N dynamics and maize grain yield. Various scenarios were defined by combining 11 irrigation levels (IL=0–100% with a 10% interval), 8N fertilization rates (NR=0–400kgha−1 with a 50kgha−1 interval) and two water-saving irrigation strategies: deficit irrigation (DI) and partial root-zone drying (PRD). Reliable estimates of soil NO3−-N concentrations (RMSE=0.39–10.9mgl−1 and MBE=−8.9–8.4mgl−1), crop N uptake (RMSE=3.9–8.9kgha−1 and MBE=−5.3–6.25kgha−1), and soil water contents (RMSE=2.3–5.11mm and MBE=1.63–4.93mm) were provided by HYDRUS-2D. Based on the simulated results, the fertigation strategy with NR=200kgha−1 is an optimum strategy. For the higher fertigation rates (NR≥250kgha−1), the NO3−-N leaching out of the surface layers (0–20cm) increased by 0.1–183% while N uptake was enhanced by only 0.3–15%. On the other hand, reducing NR below this level would have resulted in severe economic losses. A 30% reduction in IL at NR=200kgha−1 shows an enormous potential in lowering N leaching below different soil layers (12–99%) while reducing crop N uptake by only 5.4%. In addition, higher crop yield by 0.2–20.2% can be expected under PRD since crop N uptake is enhanced by more water available in the surface layers. While on the one hand, PRD ensures environmentally safer fertilizer applications, on the other hand, the economic objectives are met more easily under PRD than under DI. Additionally, it could be concluded that the HYDRUS-2D model, instead of labor- and time-consuming and expensive field investigations, could be reliably used for determining the optimal scenarios under both the DI and PRD strategies

A field-modeling study for assessing temporal variations of soil-water-crop interactions under water-saving irrigation strategies

Simulation models are useful tools that may help to improve our understanding of soil-water-plant interactions under innovative water-saving irrigation strategies. In this study, the HYDRUS-2D model was applied to evaluate the influence of deficit irrigation (DI) and partial root-zone drying (PRD) on maize water extractions during two cropping cycles of 2010 and 2011. The model was calibrated and validated using measured soil water content data (expressed as equivalent water depths). Reliable estimates of soil water content were provided by HYDRUS-2D, with root mean square error and mean bias error values of 2.3–5.11 and 1.63–4.93mm, respectively. Root water uptake and maize grain yields were reduced by 13.2–28.8% and 13.6–52.8%, respectively, under different water-saving irrigation treatments compared to full irrigation. However, different root and water repartitions in the PRD treatment with a 25% reduction in the irrigation depth (PRD75) improved soil water utilization and consequently, crop growth. Increased root water uptake (2.2–4.4 times higher than in other treatments) from the 60–100cm soil depth in the PRD75 treatment maintained a favorable daily evapotranspiration rate, resulting in no significant reduction in maize grain yield compared to full irrigation. Consequently, a 15.7–85% increase in water use efficiency for maize cultivation under PRD75 ensured 25% water savings without threatening food security in the study area. It can be concluded that HYDRUS-2D can be successfully used to optimize water management under local water-stress conditions

An application of the water footprint assessment to optimize production of crops irrigated with saline water: A scenario assessment with HYDRUS

Agriculture, due to a growing scarcity of fresh water resources, often uses low-quality waters for irrigation, such as saline waters. However, unmanaged applications of such waters may have negative environmental and economic consequences. Based on the concept of the water footprint (WF), a measure of the consumptive and degradative water use, the field-calibrated and validated HYDRUS (2D/3D) model was applied to find optimal management scenarios (from 1980 different evaluated scenarios). These scenarios were defined as a combination of different salinity rates (SR), irrigation levels (IL, the ratio of an actual irrigation water deth and a full irrigation water depth), nitrogen fertilization rates (NR), and two water-saving irrigation strategies, deficit irrigation (DI) and partial root-zone drying (PRD). The consumptive WF was defined as the crop water consumption divided by the crop yield. The grey WF was calculated for the N fertilizer and defined as the volume of freshwater required to dilute nitrogen (N) in recharge so as to meet ambient water quality standards. Simulated components of water and solute dynamics were used to calculate criteria indices, which were divided into two groups: (a) environmental indices, including the degradative grey water footprint (GWF) and the apparent N recovery rate efficiency (ARE), and (b) economic indices, including economic water (EWP) and land (ELP) productivities. While significant improvements of 3.9–59.2%, 0.1–165.8%, and 0.01–166.5% in ARE, EWP, and ELP, respectively, were obtained when NR varied within the range of 0–200 kg ha−1, changes in these indices were relatively minor when NR was higher than 200 kg ha−1. At a given NR, GWF tends to increase considerably by up to 180% when DI-crops are subject to low-intermediate salt (SR < 7 dS m−1) and water (IL > 70%) stresses. This is at the expense of up to a 55% reduction in ELP and up to a 120% increase in EWP. With N uptake 0.2–17.3% higher, PRD seems to be a more viable agro-hydrological option than DI in reducing a pollutant load into regional aquifers as well as in sustaining farm economics. The entire analysis reveals that the PRD strategy with N-fertilization rates of 100-200 kg ha−1, a moderate salinity stress (SR < 5 dS m−1), and irrigation levels of 60–90% represents the best management scenario. It can be concluded that, while there is a substantial need for rescheduling irrigation and fertilization managements when crops are irrigated with saline waters, HYDRUS modeling may be a reliable alternative to extensive field investigations when determining the optimal agricultural management practices

A comprehensive numerical analysis of the hydraulic behavior of a permeable pavement

The increasing frequency of flooding events in urban catchments related to an increase in impervious surfaces highlights the inadequacy of traditional urban drainage systems. Low Impact Development (LID) techniques have proven to be a viable and effective alternative by reducing stormwater runoff and increasing the infiltration and evapotranspiration capacity of urban areas. However, the lack of adequate modeling tools represents a barrier in designing and constructing such systems. This paper investigates the suitability of a mechanistic model, HYDRUS-1D, to correctly describe the hydraulic behavior of permeable pavement installed at the University of Calabria. Two different scenarios of describing the hydraulic behavior of the permeable pavement system were analyzed: the first one uses a single-porosity model for all layers of the permeable pavement; the second one uses a dual-porosity model for the base and sub-base layers. Measured and modeled month-long hydrographs were compared using the Nash-Sutcliffe efficiency (NSE) index. A Global Sensitivity Analysis (GSA) followed by a Monte Carlo filtering highlighted the influence of the wear layer on the hydraulic behavior of the pavement and identified the ranges of parameters generating behavioral solutions. Reduced ranges were then used in the calibration procedure conducted with the metaheuristic Particle swarm optimization (PSO) algorithm for the estimation of hydraulic parameters. The best fit value for the first scenario was NSE = 0.43; for the second scenario, it was NSE = 0.81, indicating that the dual-porosity approach is more appropriate for describing the variably-saturated flow in the base and sub-base layers. Estimated parameters were validated using an independent, month-long set of measurements, resulting in NSE values of 0.43 and 0.86 for the first and second scenarios, respectively. The improvement in correspondence between measured and modeled hydrographs confirmed the reliability of the combination of GSA and PSO in dealing with highly dimensional optimization problems. Obtained results have demonstrated that PSO, due to its easiness of implementation and effectiveness, can represent a new and viable alternative to traditional optimization algorithms for the inverse estimation of unsaturated hydraulic properties. Finally, the results confirmed the suitability and the accuracy of HYDRUS-1D in correctly describing the hydraulic behavior of permeable pavements