Water Management Applications Research Articles

The Way of Yield Increasing and Cost Reducing in Agriculture: Smart Irrigation and Fertigation

The plants can only use the around 50% of the applied nitrogenous fertilizer. It has been observed that the dynamic fertigation applications help to improve the fertilizer effectiveness. In the dynamic fertigation approach, water and plant nutritional elements are calculated and determined according to the plant dry matter generation rate and root volume. Smart agriculture is an knowledge based decision making approach established upon quantification and observations of the changes in each level of production. With this system, saving can be provided by only supplying the plant‘s daily need of water and fertilizer and preventing the excess irrigation and fertilizing, so yield increase can be achieved by keeping away the plants from the stress conditions. Agricultural production can be increased five times by irrigation but shortening in water sources and decrease in quality reasoned by fast growing are restricted of irrigation which is the main user of freshwater sources. Increasing the water and fertilizer effectiveness with the smart irrigation techniques which can save water and fertilization management applications are the essential strategies to be able to reach the yield increase in order to supply the growing food needs of developing population and help to minimize the environmental damage. In the study, the researches and applications related to smart irrigation and fertilization were tried to be included in a wide scope and tried to keep a light to obtain higher yield with less water and fertilizer use in agriculture.

Hydrological data uncertainty and its implications

Hydrologic data are at the core of our understanding of physical hydrologic processes, our simulation models and forecasts of water resources and hazards, and our monitoring of water quantity and quality. However, hydrologic data are subject to multiple sources of uncertainty that can introduce bias and error into our analyses and decision‐making if not properly accounted for. In this article, we summarize five categories of data uncertainty: measurement uncertainty, derived data uncertainty, interpolation uncertainty, scaling uncertainty, and data management uncertainty. Hydrologic data uncertainty magnitudes are typically in the range 10–40%. To quantify data uncertainty, hydrologists should first construct a perceptual model of uncertainty that itemizes uncertainty sources. The magnitude of each source can then be estimated using replicates (repeated, nested or subsampled measurements), or information from the literature (in‐depth uncertainty results from experimental catchments, colocated gauges or method comparisons). Multiple uncertainty sources can be combined using Monte Carlo methods to determine total uncertainty. Data uncertainty analysis improves hydrologic process understanding by enabling robust hypothesis testing and identification of spatial and temporal patterns that relate to true process differences rather than data uncertainty. By quantifying uncertainty in data used for input or evaluation of hydrologic models, we can prevent parameter bias, exclude disinformative data, and enhance model performance evaluation. In water management applications, quantifying data uncertainty can lead to robust risk analysis, reduced costs, and transparent results that improve the trust of the public and water managers.This article is categorized under: Science of Water > Hydrological Processes Science of Water > Methods Engineering Water > Planning Water

Categorization of trapezoidal open channels based on flow conditions for the choice of simple models

Many applications in water management rely on keeping the water levels of an open water channel within given bounds, e.g. irrigation canals, drainage systems, and hydropower systems. These are all open water channels where the water level is influenced by several known and unknown factors like precipitation, operation of structures, etc. Water levels can be efficiently controlled by model predictive control (MPC). In MPC the optimization algorithms give advice at every time step based on the current state of the system as well as on the expected future state. These algorithms need a model to predict the response of the system to the control inputs. In most cases, the need to guarantee convexity of the optimization problem leads to the requirement that these models should be linear. To date, several such linear models are available in literature, which are suited for control purposes. However, the choice between these models is not straightforward. In this work, we extend a categorization of open channels, based on which the choice of a simple model can be advised.

Web based Water Turbidity Monitoring and Automated Filtration System: IoT Application in Water Management

Water supplied to residential areas is prone to contaminants due to pipe residues and silt, and therefore resulted in cloudiness, unfavorable taste, and odor in water. Turbidity, a measure of water cloudiness, is one of the important factors for assessing water quality. This paper proposes a low-cost turbidity system based on a light detection unit to measure the cloudiness in water. The automated system uses Intel Galileo 2 as the microprocessor and a server for a web-based monitoring system. The turbidity detection unit consists of a Light Dependent Resistor (LDR) and a Light Emitting Diode (LED) inside a polyvinyl chloride (PVC) pipe. Turbidity readings were recorded for two different positionings; 90° and 180° between the detector (LDR) and the incident light (LED). Once the turbidity level reached a threshold level, the system will trigger the filtration process to clean the water. The voltage output captured from the designed system versus total suspended solid (TSS) in sample water is graphed and analyzed in two different conditions; in total darkness and in the present of ambient light. This paper also discusses and compares the results from the above-mentioned conditions when the system is submerged in still and flowing water. It was found that the trends of the plotted graph decline when the total suspended solid increased for both 90° and 180° detector turbidimeter in all conditions which imitate the trends of a commercial turbidimeter. By taking the consideration of the above findings, the design can be recommended for a low-cost real-time web-based monitoring system of the water quality in an IOT environment.

Forward Osmosis Application in Manufacturing Industries: A Short Review.

Forward osmosis (FO) is a membrane technology that uses the osmotic pressure difference to treat two fluids at a time giving the opportunity for an energy-efficient water and wastewater treatment. Various applications are possible; one of them is the application in industrial water management. In this review paper, the basic principle of FO is explained and the state-of-the-art regarding FO application in manufacturing industries is described. Examples of FO application were found for food and beverage industry, chemical industry, pharmaceutical industry, coal processing, micro algae cultivation, textile industry, pulp and paper industry, electronic industry, and car manufacturing. FO publications were also found about heavy metal elimination and cooling water treatment. However, so far FO was applied in lab-scale experiments only. The up-scaling on pilot- or full-scale will be the essential next step. Long-term fouling behavior, membrane cleaning methods, and operation procedures are essential points that need to be further investigated. Moreover, energetic and economic evaluations need to be performed before full-scale FO can be implemented in industries.

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

ABSTRACTSpatially distributed high-resolution data of land surface temperature (LST) and evapotranspiration (ET) are important information for crop water management and other applications in the agricultural sector. While satellite data can provide LST high-resolution data of 100 m, the current development of unmanned aerial systems (UAS) and affordable low-weight thermal cameras allows LST and subsequent ET to be derived at resolutions down to centimetre scale.In this study, UAS-based images in the thermal infrared (TIR) and visible spectral range were collected over a managed temperate grassland in July 2016 at the Terrestrial Environmental Observatories Networks TERENO preAlpine observatory site at Fendt, Germany. The UAS set-up included a lightweight thermal camera (Optris Pi Lightweight) and a regular digital camera (Sony α 6000) that allowed for the acquisition of thermal and optical images with a ground resolution of 5 cm and 1 cm, respectively. Three TIR-based ET models of different complexity were applied and the resulting ET estimates were compared to the Eddy covariance (EC) observations of turbulent energy fluxes and also to the evaporative fraction. While the Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature (DATTUTDUT) model and the Triangle Method belong to the group of simpler contextual models, the Two-Source Energy Balance (TSEB) model incorporates a more physically based formulation of the surface energy balance. In addition to the comparison of UAS-based estimates of latent heat fluxes to EC observations, the effect of the spatial resolution of the model imagery input on the modelled results was analysed by running the models with imagery from the native resolution of the acquired images to resolutions that were aggregated up to 30 m.The results show that both contextual models are sensitive to the input image resolution and that the agreement with the EC observations improves with increasing image resolution. The TSEB model assumes that LST pixels represent a mixed signal of the soil and canopy components, thus an image resolution coarse enough to ensure this assumption should be chosen. However, with the exception of the native image resolution of 5 cm, we found no effect of image resolution on the spatially weighted mean TSEB estimates.For the studied grassland, the comparison of model estimates with EC observations indicates that all three models are able to reproduce observed energy fluxes with comparable accuracy with mean absolute errors of ET between 20 and 40 W m−2. The TSEB model showed larger deviations from the reference observations under cloudy conditions with rapid fluctuations of LST within the 30 min averaging period for EC. The two contextual models yielded similar results for most of the flights. The good performance of the DATTUTDUT model, which had the lowest input requirements of the three models, is especially promising in view of the application of UAS for routine near-real-time ET monitoring.

Analytical calculation of electrolyte water content of a Proton Exchange Membrane Fuel Cell for on-board modelling applications

This paper proposes an analytical model of the water content of the electrolyte of a Proton Exchange Membrane Fuel Cell. The model is designed by accounting for several simplifying assumptions, which make the model suitable for on-board/online water management applications, while ensuring a good accuracy of the considered phenomena, with respect to advanced numerical solutions. The achieved analytical solution, expressing electrolyte water content, is compared with that obtained by means of a complex numerical approach, used to solve the same mathematical problem. The achieved results show that the mean error is below 5% for electrodes water content values ranging from 2 to 15 (given as boundary conditions), and it does not overcome 0.26% for electrodes water content above 5. These results prove the capability of the solution to correctly model electrolyte water content at any operating condition, aiming at embodiment into more complex frameworks (e.g., cell or stack models), related to fuel cell simulation, monitoring, control, diagnosis and prognosis.

Low-Density Self-Assembled Poly(N-Isopropyl Acrylamide) Sponges with Ultrahigh and Extremely Fast Water Uptake and Release.

Poly(N-isopropyl acrylamide) (PNIPAM) hydrogels are well known for their temperature-dependent water uptake and release. Hence, they are ideal candidates for water management applications. However, efficiency and rate of water uptake and release, respectively, have to be optimized. Here, highly stable 3D PNIPAM sponges that show a sufficiently low density and high specific pore volume, required for maximizing the amount and rate of water absorption-desorption, are presented. They are prepared by a top-down approach based on freeze-drying a dispersion of short crosslinked PNIPAM fibers coated with crosslinked PNIPAM. The sponges have low densities (4.10-21.04 mg cm-3 ), high porosities >98%, and high specific pore volumes in the range of 47-243 cm3 g-1 depending on the concentration of the dispersions. The sponges absorb high amounts of water (≈7000%) at temperatures below the lower critical solution temperature (LCST) of PNIPAM and can release more than 80% of the absorbed water above the LCST in less than 2 min. Moreover, the water-swollen sponges are reversibly foldable, can be confined to different shapes, and have compressive elastic modulus below 10 Pa. Hence, these spongy materials are of interest not only for water management but also for biomedical applications, smart textiles, and catalysis.

Recent Progress in Self-Cleaning Materials with Different Suitable Applications

Self-cleaning properties have received significant attention for the importance of their potential. Coatings at Nano-scales offer possibilities of using materials for self-cleaning surfaces. Recent efforts have begun to focus on the kinds of materials including metals, semiconductors and polymers. Such materials can have enormous potential in only a few applications. Moreover, the production of these materials requires high costs with low photo activity. In this regard, TiO2 and its derived materials have shown acceptable and effective suggestions for this application. Moreover, the mechanism of self-cleaning has been explained by the effect of hydrophilic and hydrophobic. Hydrophilic and hydrophobic can have many applications in different areas like water purification, microfluidics and photovoltaic. In this review, the application of self-cleaning in solar cells and environment as well as TiO2 derived materials and their applications in water management have been briefly illustrated. In addition, it has been explained that a huge number of self-cleaning materials, applications and improvement in utilities have been essential. In short, we have conducted a comprehensive review of the new approach and to mention numerous materials with hydrophobic and hydrophilic properties would be promising for most environmental concerns. Bio-inspired surface respond in nature through hydrophobic (Cicada Wing, Butterfly Wing, Lotus Leaf, Rice Leaf) and hydrophilic (Fish Scale, Snail Shell, Shark Skin) properties was divided in 4 and 3 respectively. Anti reflective coatings with self-cleaning properties have drowned considerable attention for both their basic appearances and vast applied usages. Antireflective coatings with self-cleaning properties have been considered because of their fascinating features and vast diversity of empirical uses.

Sodium silicate gelants for water management in naturally fractured hydrocarbon carbonate formations

Two commercially available, water-soluble, environmentally friendly, sodium silicate gelant systems (Silicate A and Silicate B) are screened and evaluated for water management applications in naturally fractured carbonate (NFC) reservoirs. The gelant impact on oil production and the ability to reverse poorly deployed gel treatments through gel dissolution are also investigated.Several bulk- and core-based tests are engaged, with the two investigated water-soluble silicate gelant chemicals having undergone a thorough and careful investigation of their filterability, injectivity, gelation time, gel strength, and gel shrinkage. The activators used for gel formation are system dependent and included NaCl, HCl, HNO3, HCOOH, and urea. Gelation is mainly controlled by the activator type and concentration, silicate concentration and temperature. Formed gel strength can be improved by increasing the injected silicate concentration but in Silicate B experiments, gelation difficulties are experienced for concentrations exceeding ∼7wt%.Filterability of Silicate B is significantly better than that of Silicate A. Fractured core tests using Silicate A gelant revealed that the average core permeability is reduced by three orders of magnitude from prior- to post-gelation conditions. Silicate B gelants exhibited gelling “difficulties” and formed gels displayed a lower strength compared to Silicate A gels. Unsuccessfully deployed gels may be reversed through dissolution with alkaline fluids (NaOH or KOH); gel dissolution rate is a function of the alkaline fluid concentration and type of process followed.Overall, Silicate A outperforms Silicate B and shows promising properties for its potential utilization in field applications to control injected water in NFC formations.

Lanthanum oxide nanoparticles immobilized reduced graphene oxide polymer brush nanohybrid for environmental vitiation of organic dyes

In the present work, uniformly distributed Lanthanum Oxide nanoparticles on poly (tetrahydrofurfuryl methacrylate) brushes spread over the surface of reduced graphene oxide (La2O3/PTHF/rGO) are synthesized. La2O3/PTHF/rGO is used as catalyst for the degradation of Rhodamine B (RhB), Methyl Orange (MO) and Eosine Y (ESY) dyes. Catalyst has shown excellent catalytic activity as evident by the apparent Rate constant (kapp), which is found to be 26.8, 28.6, and 20.5 (×10−3 s−1), for RhB, MO and ESY respectively, much higher than the reported in literature. The catalyst is recycled for five times without any significant loss in its activity, which makes it suitable for the applications in catalysis and waste water management.

Evaluation of Sensible Heat Flux and Evapotranspiration Estimates Using a Surface Layer Scintillometer and a Large Weighing Lysimeter.

Accurate estimates of actual crop evapotranspiration (ET) are important for optimal irrigation water management, especially in arid and semi-arid regions. Common ET sensing methods include Bowen Ratio, Eddy Covariance (EC), and scintillometers. Large weighing lysimeters are considered the ultimate standard for measurement of ET, however, they are expensive to install and maintain. Although EC and scintillometers are less costly and relatively portable, EC has known energy balance closure discrepancies. Previous scintillometer studies used EC for ground-truthing, but no studies considered weighing lysimeters. In this study, a Surface Layer Scintillometer (SLS) was evaluated for accuracy in determining ET as well as sensible and latent heat fluxes, as compared to a large weighing lysimeter in Bushland, TX. The SLS was installed over irrigated grain sorghum (Sorghum bicolor (L.) Moench) for the period 29 July–17 August 2015 and over grain corn (Zea mays L.) for the period 23 June–2 October 2016. Results showed poor correlation for sensible heat flux, but much better correlation with ET, with r2 values of 0.83 and 0.87 for hourly and daily ET, respectively. The accuracy of the SLS was comparable to other ET sensing instruments with an RMSE of 0.13 mm·h−1 (31%) for hourly ET; however, summing hourly values to a daily time step reduced the ET error to 14% (0.75 mm·d−1). This level of accuracy indicates that potential exists for the SLS to be used in some water management applications. As few studies have been conducted to evaluate the SLS for ET estimation, or in combination with lysimetric data, further evaluations would be beneficial to investigate the applicability of the SLS in water resources management.

Study of Two-Dimensional, all – Time Dispersion of a Solute in a Fluid – Saturated Porous Medium

The paper presents the mathematical formulation which describes the dispersion of solute in a laminar flow in a sparsely packed porous medium. The effect of interphase mass transfer on dispersion in a unidirectional flow through a horizontally extent of infinite porous channel is examined using the generalized dispersion model of Sankarasubramanian and Gill. The model brings into focus three important coefficients namely the exchange coefficient, the convection coefficient and the dispersion coefficient. The time-dependent dispersion coefficient and mean concentration distribution are computed and results are represented graphically. The problem finds many applications in waste water management, in chromatography and in biomechanical problems.

Studies on catalytic degradation of organic pollutants and anti-bacterial property using biosynthesized CuO nanostructures

Metal oxide nanostructures have become an inevitable class of materials explored for the environmental and biomedical applications. Thus there is a budding demand to develop a method that purge the need of toxic chemicals. It is a report on a novel and eco-friendly method for the rapid synthesis of copper oxide (CuO) nanostructures using Psidium guajava leaf extract. The synthesis route follows green protocols and exploits the phytochemicals present in the leaves. These nanostructures have been characterized by XRD, UV–vis spectroscopy, FTIR spectroscopy and TEM. BET specific surface area analysis reveals the information of availability of active surface sites in CuO nanostructures. Particle size obtained from XRD, TEM and BET studies are found to be ~17–20nm. The XRD pattern, UV absorption at 270nm and the characteristic IR bands in the region from 400 to 600cm−1 confirms the formation of nanostructured CuO. The catalytic activity of the synthesized CuO nanostructures has been evaluated by monitoring the degradation of the dyes methylene blue, methyl orange, methyl red and eosin yellow. The synthesized CuO nanostructures could also very effectively catalyze the reduction of the pollutants 2-NP, 3-NP and 4-NP to the corresponding amino compounds. The degradations are observed to be complete within 4–12min. Anti-microbial activity of CuO nanocrystals against E. coli and S. aureus has also been assessed by agar well diffusion method. This study provides a promising route for the facile and cost-effective synthesis of bio-active CuO nanocatalysts which could find applications in biomedical field and waste water management.

How uncertainty analysis of streamflow data can reduce costs and promote robust decisions in water management applications

AbstractStreamflow data are used for important environmental and economic decisions, such as specifying and regulating minimum flows, managing water supplies, and planning for flood hazards. Despite significant uncertainty in most flow data, the flow series for these applications are often communicated and used without uncertainty information. In this commentary, we argue that proper analysis of uncertainty in river flow data can reduce costs and promote robust conclusions in water management applications. We substantiate our argument by providing case studies from Norway and New Zealand where streamflow uncertainty analysis has uncovered economic costs in the hydropower industry, improved public acceptance of a controversial water management policy, and tested the accuracy of water quality trends. We discuss the need for practical uncertainty assessment tools that generate multiple flow series realizations rather than simple error bounds. Although examples of such tools are in development, considerable barriers for uncertainty analysis and communication still exist for practitioners, and future research must aim to provide easier access and usability of uncertainty estimates. We conclude that flow uncertainty analysis is critical for good water management decisions.

Estimation of spatial mean soil water storage using temporal stability at the hillslope scale in black locust (Robinia pseudoacacia) stands

Black locust (Robinia pseudoacacia) has been extensively planted on the Loess Plateau for soil and water conservation, but afforestation with this non-native tree has produced some negative effects such as soil desiccation. Knowledge of the soil water storage (SWS) within soil profiles in black locust stands is thus critical for optimization of forest management for sustainable production. The objectives of this study were to evaluate the temporal stability of SWS to identify the most time-stable locations (MTSLs) for reliably estimating the mean SWS and to further investigate the factors influencing its temporal stability. The SWS values of various soil layers (0–1, 1–2, and 2–3m) were measured from May 2014 to October 2015 at 70 locations along two 187-m long transects on a hillslope covered with black locust in the Loess Plateau, China. A total of 18 SWS datasets were collected over the period of measurement. Results indicated that the temporal variation of spatial mean SWS decreased and the spatial variation of SWS increased with increasing soil depth. A strong temporal persistence in all soil layers was demonstrated by high Spearman's rank correlation coefficients (P<0.01), with the temporal stability in deep soil layers relatively more stable than in shallow layer. Among four methods (MRD, mean relative difference; SDRD, standard deviation of relative difference; ITS, index of temporal stability; and MABE, mean absolute bias error) used to identify the MTSLs for the estimation of the mean SWS, the ITS provided the best results. The MTSLs identified in diverse layers of the first transect were then used to successfully predict the mean SWS along the second transect (R2>0.91). Elevation, soil saturated hydraulic conductivity, leaf area index, and fine root area density were the major factors influencing the temporal stability of SWS. The results of this study were useful for estimating mean SWS and could improve soil water management and hydrological applications in sloping black locust forested areas of the Loess Plateau.

A Coupled Level Set and Volume of Fluid method for automotive exterior water management applications

Motivated by the need for practical, high fidelity, simulation of water over surface features of road vehicles a Coupled Level Set Volume of Fluid (CLSVOF) method has been implemented into a general purpose CFD code. It has been implemented such that it can be used with unstructured and non-orthogonal meshes. The interface reconstruction step needed for CLSVOF has been implemented using an iterative ‘clipping and capping’ algorithm for arbitrary cell shapes and a re-initialisation algorithm suitable for unstructured meshes is also presented. Successful verification tests of interface capturing on orthogonal and tetrahedral meshes are presented. Two macroscopic contact angle models have been implemented and the method is seen to give very good agreement with experimental data for a droplet impinging on a flat plate for both orthogonal and non-orthogonal meshes. Finally the flow of a droplet over a round edged channel is simulated in order to demonstrate the ability of the method developed to simulate surface flows over the sort of curved geometry that makes the use of a non-orthogonal grid desirable.

Cross‐scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.

Crop Modeling Applications in Agricultural Water Management

Abstract. This article introduces the fourteen articles that comprise the “Crop Modeling and Decision Support for Optimizing Use of Limited Water” collection. This collection was developed from a special session on crop modeling applications in agricultural water management held at the 2016 ASABE Annual International Meeting (AIM) in Orlando, Florida. In addition, other authors who were not able to attend the 2016 ASABE AIM were also invited to submit papers. The articles summarized in this introductory article demonstrate a wide array of applications in which crop models can be used to optimize agricultural water management. The following section titles indicate the topics covered in this collection: (1) evapotranspiration modeling (one article), (2) model development and parameterization (two articles), (3) application of crop models for irrigation scheduling (five articles), (4) coordinated water and nutrient management (one article), (5) soil water management (two articles), (6) risk assessment of water-limited irrigation management (one article), and (7) regional assessments of climate impact (two articles). Changing weather and climate, increasing population, and groundwater depletion will continue to stimulate innovations in agricultural water management, and crop models will play an important role in helping to optimize water use in agriculture. Keywords: Agricultural water management, Crop modeling, Evapotranspiration, Irrigation, Irrigation scheduling.

Gold nanoworms immobilized graphene oxide polymer brush nanohybrid for catalytic degradation studies of organic dyes

In the present work, we report gold nanoparticles (AuNPs) on poly (dimethylaminoethyl methacrylate) (PDMAEMA) brushes immobilized reduced graphene oxide (Au/PDMAEMA/RGO) as catalyst for degradation kinetic studies of Rhodamine B (RB), Methyl Orange (MO) and Eosine Y (EY) dyes, having an excellent catalytic activity, as evident by the apparent rate constant (kapp), which is found to be 21.8, 26.2, and 8.7 (×10−3s−1), for RB, MO and EY respectively. Au/PDMAEMA/RGO catalyst is easy to use, highly efficient, recyclable, which make it suitable for applications in waste water management. Foremost, synthesis of PDMAEMA brushes on graphene oxide is accomplished by Atom transfer radical polymerization method (ATRP), whereas AuNPs are synthesized by simple chemical reduction method.