Plant Water Consumption Research Articles

Crop coefficient estimated by degree-days for ‘Marandu’ palisadegrass and mixed forage

Considering profitability in pasture-based systems, investigating parameters affecting crop coefficients for irrigation management becomes important. In this experiment, we determined the crop coefficient of ‘Marandu’ palisadegrass based on accumulated degree-days and estimated plant water consumption under single (‘Marandu’ alisadegrass) and mixed (‘Marandu’ palisadegrass + black oats + Italian ryegrass) cropping regimes. The research was conducted at the Luiz de Queiroz College of Agriculture in Piracicaba, São Paulo, Brazil, between 2016 and 2017. Evapotranspiration was assessed using weighing lysimeters while crop evapotranspiration was calculated using mean weight variation. Reference evapotranspiration and degree-days were estimated. Data were obtained from an automated weather station. Equations and regression models relating crop coefficient with accumulated degree-days were generated for two seasons (spring/summer and autumn/winter) and evaluated for two year-cycles, from 2015 to 2018. The results showed better prediction accuracy for the single cropping system in spring/summer 2017–18. Highlights The model for determinating crop coefficient (Kc) by accumulated degree-days showed efficient for use in determination local. The use of the degree days for determination Kc is more vantage because only necessary to measure the air temperature (maximum and minimum). The equations for determining crop coefficient by accumulated degree days for the spring/summer season in Marandu palisade grass cultive show more precision that in mixture forage system.

Selection of Water-Saving Plants and Annual Water Consumption Estimation for Garden Green Spaces in Beijing

Currently, the number of urban garden green spaces (GGSs) being constructed in Beijing is increasing, and their high water resource demands contradict the severe water shortage situation in Beijing that is restricting urban construction and economic development. This has created an urgent need to build water-saving GGSs. This study analyzed and compared the daily/annual water consumption of 79 common plants in Beijing, and low-water-consumption (LWC) trees, shrubs and herbs were selected; additionally, the total annual water consumption (TAWC) of all plants in the built-up areas of all 16 districts in Beijing was calculated according to the result of the eighth general survey of landscaping resources in Beijing. The results are as follows: (1) fifteen LWC tree species were selected from among 25 species, and the average daily water consumption (DWC) was <1.09 kg·m−2; (2) nineteen LWC shrubs were selected from among 35 shrubs, and the average DWC was <1.17 kg·m−2; (3) eleven LWC herbs were selected from among 19 herbs, and the AWC was <460.3 kg·m−2; (4) the TAWC of all trees, shrubs and herb plants in the Beijing GGSs was 1.104 × 109, 0.139 × 109, and 0.16 × 109 m3, respectively. Based on the above results, it was estimated that the TAWC of all plants in the built-up areas of all 16 districts in Beijing is approximately 1.403 × 109 m3. These findings provide a better understanding of the water consumption of GGS plants in cities in semiarid and semihumid climates and can be used to help select LWC greening plants that can reduce water consumption when expanding green areas in cities.

Effect of Four Irrigation Regimes and Different Fertilizers on Vegetative Growth and Fruit Parameters of Eggplant (Solanum melongena L.)

The aim of this study is to determine the effect of four levels of irrigation water and three kinds of fertilizer on components of field-grown eggplant (Solanum melongena) in the years 2017 and 2018. Treatments included four irrigation regimes, which were 100% (I100, control), 80% (I80), 60% (I60), and 40% (I40) of evaporation from Class A pan and three different fertilizers, which were chemical fertilizer (CHF) with 40 kg da-1, organic fertilizer (OF) and developed organic fertilizer (DOF) with 2000 kg da-1. The experiment was designed with a split-plot randomized block with 3 replications. In experimental years, all irrigation treatments were irrigated 12 and 13 times, respectively with a drip irrigation system. Irrigation water amounts applied at I40, I60, I80, I100 in 2017 as 122, 183, 244, 305 mm and in 2018 were 147, 218, 289, 360 mm respectively. Seasonal plant water consumption values are in 2017, 2018 years respectively as follow: I40; 265 mm, 277 mm I60; 326 mm, 342 mm, I80; 386 mm; 382 mm, I100; 447 mm, 423 mm. In both experiment years, the effect of irrigation levels on plant components was statistically significant, the highest value of each component in both seasons was at I100 treatment, it was determined respectively as follow: Plant height PH (67.3 to 89.8 cm), branches number per plant BN (5.1 and 7.0), fruit number per plant FN (5.3 and 7.0), fruit weight FW (190.33 and 198.22 g).

Analysis of Water Consumption in Fruit and Vegetable Processing Plants with the Use of Artificial Intelligence

Fruit and vegetable processing has a significant impact on the environment due to its consumption of a significant amount of water. Water consumption mainly depends on the type of production and the technology used. Water in fruit and vegetable processing plants is used as a raw material, an energy carrier, and in hydro transport, as well as for washing raw materials and maintaining production hygiene. The variety of technological operations carried out in the production process and the seasonality of production make it difficult to objectively assess the use of water in fruit and vegetable processing plants. Few available publications in this field provide numerical values of water unit consumption indices, with none entering into the cause-and-effect relationships of water use in plants in this industry. The aim of this study was to analyze the research to date and to verify the following research hypothesis: the structure of processing and the relationship between the weights of individual products have an impact on water consumption in fruit and vegetable processing plants. For this purpose, neural models of water consumption were developed for the largest agri-food processing plants in Poland that use similar technology. Water consumption was then optimized using genetic algorithms for the processing structure. The results confirmed the hypothesis that production structure has a significant impact on the rationalization of water consumption. The optimization results show that the production of concentrates, juices, and drinks has the greatest impact on water consumption. The lowest water consumption will be achieved when the production of concentrates is at a 2 to 1 ratio to the production of juices and drinks.

Determining the relationship of evapotranspiration with precipitation and temperature over Turkey

Evapotranspiration (ET), which is a combination of the words evaporation and transpiration, is expressed as the sum of water due to water consumption and evaporation in plants. In this study, the NASA Drought Early Warning Systems Network Land Data Assimilation System model (FLDAS NOAH) was used to determine evapotranspiration data for the 2018-2019 water years (October 2017-September 2019) on Turkey. In addition, NASA Global Land Data Assimilation System (GLDAS NOAH) was used for temperature data. Total precipitation data with corrected error rates are taken from MERRA-2 Model M2TMNXFLX. The relationship between the determined monthly total average evapotranspiration values and the monthly average precipitation and monthly average temperature values was determined by ArcGIS. It is important to examine the local evaporation and transpiration conditions in more detail in the regions where water resources planning will be made. The importance of water holding capacity in plants in determining agricultural and hydrological drought can be explained by evapotranspiration.

Dry cooling retrofits at existing fossil fuel-fired power plants in a water-stressed region: Tradeoffs in water savings, cost, and capacity shortfalls

This study investigates the performance, cost, and generating capacity impacts of switching from wet cooling towers to dry cooling systems to reduce the consumptive water use at existing fossil fuel-fired power plants in a water-stressed region. Retrofit analysis of dry cooling is conducted on a unit-by-unit basis for both coal-fired and gas-fired power plants. Unit-level results are then aggregated to the regional level. Based on regional averages, retrofitting dry cooling systems in lieu of wet cooling towers decreases total annual plant water consumption at existing coal- and gas-fired power plants by 93% and 100%, respectively, while increasing the levelized cost of electricity generation by approximately 12% and 18%, respectively. Based on a nominal regional water price, this cost increase corresponds to an average cost of consumptive water savings of $2.5 and $5.9 per cubic meter of water saved at coal and gas plants, respectively, if retrofit difficulty is minimal. Over the course of a year, the change in monthly net regional generating capacity from dry cooling retrofits exhibits a seasonal pattern, with the largest shortfalls occurring in July. The average monthly reduction in net capacity is estimated at 0.7% and 1.2% of the regional nameplate capacity for coal- and gas-based plants, respectively. Dry cooling retrofits thus lead to tradeoffs in water savings, cost, and capacity shortfalls, which vary with power plant characteristics. The tradeoffs identified here can fill existing knowledge gaps to better inform electric power industry water management policies, planning, and decision-making in water-stressed regions.

Optimization, Modeling and Implementation of Plant Water Consumption Control Using Genetic Algorithm and Artificial Neural Network in a Hybrid Structure

Optimization, Modeling and Implementation of Plant Water Consumption Control Using Genetic Algorithm and Artificial Neural Network in a Hybrid Structure

Increased Vegetation in Mountainous Headwaters Amplifies Water Stress During Dry Periods

AbstractThe dynamics of blue and green water partitioning under vegetation and climate change, as well as their different interactions during wet and dry periods, are poorly understood in the literature. We analyzed the impact of vegetation changes on blue water generation in a central Spanish Pyrenees basin undergoing intense afforestation. We found that vegetation change is a key driver of large decreases in blue water availability. The effect of vegetation increase is amplified during dry years, and mainly during the dry season, with streamflow reductions of more than 50%. This pattern can be attributed primarily to increased plant water consumption. Our findings highlight the importance of vegetation changes in reinforcing the decrease in water resource availability. With aridity expected to rise in southern Europe over the next few decades, interactions between climate and land management practices appear to be amplifying future hydrological drought risk in the region.

Water recovery efficiency improvement using the enhanced structure of the mist eliminator

Thermal power plants are users of high water consumption, and the water consumption of cooling towers accounts for more than half of the total water consumption of the whole plant. Therefore, water saving of cooling towers is the key to water saving in thermal power plants. Wave-plate demister as a component of cooling tower influences the performance of entire system. Demister realizes the collection of liquid droplets with the penalty of extra pressure loss. Curved bends and drainage hooks are proposed as enhancing structures of demister to increase separation efficiency and reducing pressure loss simultaneously. Computational result shows that interaction between curved bend and hooks improves the overall performance of demister. Moreover, effect of enhancing parameters on the performance is presented, specifically, Euler number and separation efficiency are correlated as functions of curved bend radius and hook length. Most importantly, an experiment is conducted on a real cooling tower. It shows that the overall thermal capacity is lowered with the presence of demister. Pressure drop, separation efficiency and heat transfer of the entire system are tested with and without demisters, based on which a new criterion is proposed to evaluate the influence of demister on the overall performance of cooling tower in terms of thermal efficiency and droplets collection. Performance indexes as functions of enhancing parameters and droplets dynamic are plotted. Therefore, a quick design of demister can be realized in achieving an optimal performance of cooling tower.

Reduction of water consumption in thermal power plants with radiative sky cooling

Evaporative wet cooling and dry cooling are gradually replacing water-intensive, thermally polluting once-through wet cooling in thermal power plants. Widespread adoption of evaporative wet cooling increases water losses to the atmosphere and still requires uninterrupted makeup water. Dry cooling substantially increases auxiliary power consumption and causes plant efficiency penalty. Therefore, efficient water-saving cooling technologies are of great importance. Here, we explore the water saving potential of day-night radiative sky cooling with and without evaporative wet cooling in thermal power plants. With a radiative cooling system size of 0.0055 km2/MWth normalized by the condenser thermal load at design, we show that a hybrid evaporative-radiative cooling system yields annual water savings of 30–60% in the dry and hot southwestern United States and 50–90% in other parts of the country without causing efficiency penalty. Furthermore, 100% water saving is achievable if the radiative cooling system functions as a stand-alone cooling system, with a much lower efficiency penalty and auxiliary power consumption than that of stand-alone dry cooling systems.

Better irrigation management using the satellite-based adjusted single crop coefficient (aKc) for over sixty crop types in California, USA

Several Surface Energy Balance (SEB) models are currently used to unleash the boundless potential of Geographic Information System (GIS) and Remote Sensing (RS) techniques. Their main output, namely the actual evapotranspiration (ETa), is required for the assessment of water budget at basin, regional and national levels. Still, the lack of the required expertise coupled with sometimes missing input data limits their usage by researchers, policy makers, water managers and farmers. In this study, a novel comprehensive monthly adjusted crop coefficients (aKc) list was produced, in which these coefficients are usually used to retrieve the much-needed ETa using the climate-sensitive reference crop evapotranspiration (ET0). More particularly, the ETa is calculated for more than sixty different crop types present in the Mediterranean-climate California, United States. It is based on the two consecutive years of 2018 and 2019, which were wet and dry, respectively. The Google Earth Engine (GEE) version of the Surface Energy Balance Algorithm for Land-Improved (SEBALI), surnamed SEBALIGEE, with an Absolute Mean Error (AME) of 9.56 mm/month in the study area was used along the annual crop map from the United States Department of Agriculture (USDA). The main results showed that the average monthly aKc values ranged between 0.45 and 1.53. More specifically, October and November presented the lowest aKc values averaged among all crop types with aKc values around 0.76. On the other hand, March, April and June had the largest average aKc values at nearly 1.17. The monthly aKc values of the 60 crops studied in the plain of California, would potentially assist authorities and hydrologists to better calculate the actual monthly plant water consumption, in a simpler way over the upcoming years.

Correction to: The relationship between plant growth and water consumption: a history from the classical four elements to modern stable isotopes

Correction to: The relationship between plant growth and water consumption: a history from the classical four elements to modern stable isotopes

Adenosine 5′ phosphosulfate reductase and sulfite oxidase regulate sulfite-induced water loss in Arabidopsis

Chloroplast-localized adenosine-5'-phosphosulphate reductase (APR) generates sulfite and plays a pivotal role in reduction of sulfate to cysteine. The peroxisome-localized sulfite oxidase (SO) oxidizes excess sulfite to sulfate. Arabidopsis wild type, SO RNA-interference (SO Ri) and SO overexpression (SO OE) transgenic lines infiltrated with sulfite showed increased water loss in SO Ri plants, and smaller stomatal apertures in SO OE plants compared with wild-type plants. Sulfite application also limited sulfate and abscisic acid-induced stomatal closure in wild type and SO Ri. The increases in APR activity in response to sulfite infiltration into wild type and SO Ri leaves resulted in an increase in endogenous sulfite, indicating that APR has an important role in sulfite-induced increases in stomatal aperture. Sulfite-induced H2O2 generation by NADPH oxidase led to enhanced APR expression and sulfite production. Suppression of APR by inhibiting NADPH oxidase and glutathione reductase2 (GR2), or mutation in APR2 or GR2, resulted in a decrease in sulfite production and stomatal apertures. The importance of APR and SO and the significance of sulfite concentrations in water loss were further demonstrated during rapid, harsh drought stress in root-detached wild-type, gr2 and SO transgenic plants. Our results demonstrate the role of SO in sulfite homeostasis in relation to water consumption in well-watered plants.

Assessing of evapotranspiration models using limited climatic data in Southeast Anatolian Project Region of Turkey.

Evapotranspiration carries vital importance in areas with arid and semi-arid climate properties for many issues, including the planning of irrigation water as a scarce resource, the establishment of irrigation programs and conducting project design for drainage. The empirical equations used for determining plant water consumption are classified subject to the diversity of the utilized data. The Penman–Monteith method used frequently in many parts of the world as a standard method needs more climate data. Models that yield results that are similar to those of the standard method with less climate parameters are preferred due to their ease of use and wide impact. Temperature, relative humidity and radiation data for the years 2008–2017 were utilized to analyze the usability of the Hargreaves–Samani and Turc-1961 equations with regard to the estimation of reference evapotranspiration in four provinces located in Southeastern Anatolia Region. Results obtained via models were compared in pairs by way of the standard method in order to define the performance of the models. While the best performances were obtained from the comparison with the standard method and Hargreaves–Samani value pair, the comparison of the standard model with Turc displayed the lowest performance. Based on the study data, ETo-Turc values were higher in the provinces analyzed, thus displaying a lower performance. While maximum long term annual monthly average ETo-HS value was identified as 7.6 mm at Diyarbakır in July, whereas the lowest value was determined at Kilis with 5.8 mm; the highest and lowest ETo-Turc values were obtained in the same month at Diyarbakır and Kilis with 13.3 and 10.3 mm respectively. It was calculated based on the long term average annual total ETo values that while highest ETo-HS was calculated at Diyarbakır with 1,500 mm, whereas the lowest value was calculated at Batman with 1,183 mm. The highest value for ETo-Turc was obtained at Diyarbakır with 2,365 mm while Mardin had the lowest ETo value with 1,920 mm. Accordingly, based on the ETo values calculated at both cities studies based on both models, Diyarbakır had the highest values, whereas Kilis had the lowest ETo values. According to the standard method known as PM, lowest daily ETo values were calculated in all provinces, which displayed the highest performance among the models. As a result of this study, it is possible to use the Hargreaves-Samani model instead of the standard model in the absence of reliable climatic data.

Water yield and consumption of cauliflower plants grown in a hydroponic system using brackish waters and different flow rates

HIGHLIGHTS Raising the flow rate of the nutrient solution with brackish water results in less water consumption in cauliflower. The water yield in cultivation of cauliflower depends on the chemical composition of the water used in the nutrient solution. The cauliflower production is viable in hydroponics using waters with electrical conductivities of up to 5.88 dS m-1.

Elevated CO2 Modulates Plant Hydraulic Conductance Through Regulation of PIPs Under Progressive Soil Drying in Tomato Plants.

Increasing atmospheric CO2 concentrations accompanied by abiotic stresses challenge food production worldwide. Elevated CO2 (e[CO2]) affects plant water relations via multiple mechanisms involving abscisic acid (ABA). Here, two tomato (Solanum lycopersicum) genotypes, Ailsa Craig (AC) and its ABA-deficient mutant (flacca), were used to investigate the responses of plant hydraulic conductance to e[CO2] and drought stress. Results showed that e[CO2] decreased transpiration rate (E) increased plant water use efficiency only in AC, whereas it increased daily plant water consumption and osmotic adjustment in both genotypes. Compared to growth at ambient [CO2], AC leaf and root hydraulic conductance (Kleaf and Kroot) decreased at e[CO2], which coincided with the transcriptional regulations of genes of plasma membrane intrinsic proteins (PIPs) and OPEN STOMATA 1 (OST1), and these effects were attenuated in flacca during soil drying. Severe drought stress could override the effects of e[CO2] on plant water relation characteristics. In both genotypes, drought stress resulted in decreased E, Kleaf, and Kroot accompanied by transcriptional responses of PIPs and OST1. However, under conditions combining e[CO2] and drought, some PIPs were not responsive to drought in AC, indicating that e[CO2] might disturb ABA-mediated drought responses. These results provide some new insights into mechanisms of plant hydraulic response to drought stress in a future CO2-enriched environment.

The impact of land use on future water balance - A simple approach for analysing climate change effects

Regional climate change projections for Europe agree in predicting a statistically significant warming in all seasons. The most significant climate change effect is its impact on water cycle through altering precipitation patterns and evapotranspiration processes at multiple scales. The anticipated changes in the distribution and precipitation amounts together with continuously increasing temperatures may induce a higher rate of water consumption in plants, which can generate changes in soil moisture, groundwater, and the water cycle. Thus, climate change can cause changes in the water balance equations structure. A Thornthwaite-type monthly step water balance model was established to compare the water balance in three different surface land cover types: (i) a natural forested area; (ii) a parcel with mixed surface cover; (iii) an agricultural area. The key parameter of the model is the water storage capacity of the soil. Maximal rooting depth of the given area is also determinable during the calibration process using actual evapotranspiration (AET) and soil physical data. The locally calibrated model was employed for assessing future AET and soil moisture of selected land cover types using data from four bias-corrected regional climate models. The projections demonstrate increasing actual evapotranspiration values in each surface cover type at the end of the 21st century. Regarding the 10th percentile minimum soil moisture values, the forested area displayed an increasing trend, while the agricultural field and mixed parcel showed a strong decrease. The 30-year monthly means of evapotranspiration shows the maximum values in June and July, while the minimum soil moisture in September. Water stress analysis indicates water stress is expected to occur only in the agricultural field during the 21st century. The comparison of the three surface covers reveals that forest has the greatest soil water storage capacity due to the highest rooting depth. Thus, according to the projections for 21st century, less water stress is predicted to occur at the forested area compared to the other two surface covers which shows shallow rooting depth.

Water requirement of gerberas and their behavior under a water-saving strategy, in northern Bahia

Gerbera crop evapotranspiration was defined, as well as its relationship with meteorological elements and the influence of different irrigation rates on its biometric characteristics, under a shaded mesh environment in Juazeiro-BA. The experiment was performed in randomized 4x2 blocks, with irrigation rates (60; 80; 100; and 120% of water consumption per plant) and gerbera hybrids (‘Essandre’ and DTCS), in five replicates. Gerbera water consumption was determined using total mass variation (vase+substrate+plant) on consecutive days. Total water volume required was 68.19 and 66.9 L plant-1, in DTCS and ‘Essandre’, respectively, in a 240-day cycle after acclimatization, with no significant difference between them. Mean values of the relationship between plant water consumption and reference crop evapotranspiration outside the shaded environment were 0.042 and 0.025L plant-1 mm-1day-1 during the vegetative phase and 0.055 and 0.029 mmL plant-1 mm-1day-1 during the reproductive phase of ‘Essandre’ and DTCS, respectively. The equation (Y=0.1176 *+ 0.0159*x ETo+ 0.0008** x DAA) estimated the water volume required by gerberas. Water stress negatively affected leaf area, number of gerbera leaves, and gerbera leaf temperature, with quadratic behavior.

Physio-Morphological and Biochemical Trait-Based Evaluation of Ethiopian and Chinese Wheat Germplasm for Drought Tolerance at the Seedling Stage

For Ethiopia’s wheat production, drought is a major natural disaster. Exploration of drought-resistant varieties from a bulk of wheat germplasm conserved in the gene bank is of paramount importance for breeding climate change-resilient modern cultivars. The present study was aimed at identifying the best performing drought-resistant genotypes under non-stress and polyethylene glycol simulated (PEG) stress conditions in a growth chamber. Forty diverse Ethiopian bread and durum wheat cultivars along with three Chinese bread wheat cultivars possessing strong drought resistance and susceptibility were evaluated. After acclimation with the natural environment, the seedlings were imposed to severe drought stress (20% PEG6000), and 15 seedling traits including photosynthetic and free proline were investigated. Our findings indicated that drought stress caused a profound decline in plant water consumption (83.0%), shoot fresh weight (64.9%), stomatal conductance (61.6%), root dry weight (55.2%), and other investigated traits except root to shoot length ratio and proline content which showed a significant increase under drought stress. A significant and positive correlation was found between photosynthetic pigments in both growth conditions. Proline exhibited a negative correlation with most of the investigated traits except root to shoot length ratio and all photosynthetic pigments which showed a positive and non-significant association. Our result also showed a wide range of genetic variation (CV) ranging from 3.23% to 47.3%; the highest in shoot dry weight (SDW) (47.3%) followed by proline content (44.63%) and root dry weight (36.03%). Based on multivariate principal component biplot analysis and average sum of ranks (ASR), G12, G16 and G25 were identified as the best drought tolerant and G6, G42, G4, G11, and G9 as bottom five sensitive. The potential of these genotypes offers further investigation at a molecular and cellular level to identify the novel gene associated with the stress response.

Ability of stochastic modelling to forecast crop reference evapotranspiration*

AbstractThe main objective of this study is to evaluate the ability to forecast seasonal and non‐seasonal monthly reference plant water consumption (ET0) with the Box–Jenkins approach (autoregressive integrated moving average), the abbreviation of which is ARIMA (indicated as SARIMA for seasonal series). This target was achieved by using the necessary climate parameters obtained from the Ankara meteorology station to calculate the monthly ET0 data sequences by using the Penman–Monteith relationship. Of the 12 months’ non‐seasonal ET0 data, only 4 months achieved all the conditions expected in simulation after satisfying the stationary condition. The ARIMA (SARIMA) (1,0,1) (3,1,0) model produced the best results among all models providing the necessary conditions for the seasonal series. When comparing the results of ET0 estimation from this model to that of the non‐seasonal series, it was determined that using the seasonal series rather than making an estimate based on the non‐seasonal series provided more successful results, and the model giving the most successful forecast for the study is the SARIMA model above.